DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is in responsive to communication(s): original application filed on 12/20/2023, said application claims a priority filing date of 12/21/202. Claims pending. Claims 1, 3, an independent.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: 400 in FIG. 4. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 6-12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 6 recites the limitation "… quantum sensors configured to measure electric fields at the grid nodes, the quantum sensors being coupled to respective quantum network interfaces so that electric-field data generated by the quantum sensors …" in lines 1-3, which rendering the claim indefinite because "… the grid nodes including respective quantum network interfaces coupling respective atomic clocks to the quantum network" is also recited in its based claim and it is unclear whether two instances of "respective quantum network interfaces" are the same or different. Clarification is required.
Claims 7-12 are rejected for fully incorporating the deficiency of their respective base claims.
Claim 8 recites the limitation "… quantum computer systems included in respective power grid nodes …" in lines 1-2, which rendering the claim indefinite because "A power grid comprising: grid nodes …" is also recited in its based claim and it is unclear whether "respective power grid nodes" recited here is related to "grid nodes" recited in its based claim. Clarification is required. .
Claim 8 recites the limitation "… the quantum computer systems being coupled with the respective quantum network interfaces …" in lines 2-3, which rendering the claim indefinite because "… the grid nodes including respective quantum network interfaces coupling respective atomic clocks to the quantum network" is also recited in its based Claim 4 and "… quantum sensors configured to measure electric fields at the grid nodes, the quantum sensors being coupled to respective quantum network interfaces so that electric-field data generated by the quantum sensors …" is also recited in its based Claim 6, and it is unclear which instance of "respective quantum network interfaces" is referred by "the respective quantum network interfaces" recited here if two instances of "respective quantum network interfaces" recited in its based Claims 4 and 6 are different. clarification is required.
Claims 9-12 are rejected for fully incorporating the deficiency of their respective base claims.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 3-8, 13-18, and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by BUSH et al. (WO 2024/055044 A2, priority date: 09/09/2022), hereinafter BUSH.
Independent Claim 1
BUSH discloses a power grid node (BUSH, ¶ [0005]: power grid sensing using quantum technologies including quantum sensing; power grid protection intelligent electric devices such as PMUs or entanglement-based PMUs (ePMUs) or quantum PMUs (qPMUs) (generating synchrophasor information) and relays are quantum entangled with one another over a quantum network to implement a secure power protection scheme; ¶¶ [0045] and [0050]-[0051] with FIG. 2: the power grid may include generator stations, transmission lines and tower, and individual consumer distribution lines; the one or more qPMUs 110 are placed at different locations or substations within an electrical grid system; the one or more qPMUs 110 may be connected in a quantum network (or a quantum communication network) and each qPMU may be represented as a node; the connections between the nodes denote that, in general, the initial state in which the quantum network is prepared can be entangled between the one or more qPMUs 110; ¶ [0102] with FIG. 9: the quantum network may include equipment hubs connected in a ring topology with a plurality of quantum nodes connected to each Equipment Hub) comprising: an atomic clock (BUSH, ¶¶ [0007]-[0010]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation; the processor may use an atomic clock as a reference clock; ¶ [0054] with FIG. 2: the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability);
a quantum network interface configured to: connect the atomic clock to a quantum network (BUSH, ¶¶ [0007]-[0008]: the power grid sensing system includes: one or more qPMUs (quantum Phasor Measurement Units) configured to measure quantum signals representing quantum states of entangled electrical devices in the quantum network, and a PDC (Phasor Data Concentrator) configured to process the quantum signals into measurement data based on quantum synchronization protocols; the quantum network is a fiber optic network existing in parallel with a power network in where qPMUs and PDC are located; qPMUs communicate with each other over the quantum network; each qPMU includes: a network interface configured to transmit the quantum signal; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; ¶¶ [0032]-[0037] with FIG. 1: in the quantum data plane, entanglement sources such as entangled Qubits (photons) are distributed via a quantum network; the quantum network provides entanglement distribution for quantum power protection coordination (or power protection coordination) in the power network system; in the quantum network, electrical devices (e.g., relays 1100, ePMU 110, etc.) are entangled; the quantum network may include an attack detection capability; in the quantum network, a quantum network entanglement source 1110 is provided to distribute entangled photons; the quantum network entanglement source 1110 may be referred to an entanglement source; in a quantum power protection coordination process or system, intelligent electrical devices (such as qPMUs 110, PMUs, and relays 1100) used for protection of the power grid are quantum-entangled with one another over a quantum network to implement a secure power protection scheme; pairs of mutually entangled devices may form a connected chain; a chain of such entangled devices, one end of which entangles with a trusted device, may extend the trust for each electrical device entangled in the chain; this is referred to as an entanglement chain of trust; in the quantum network, the communicated information remains in quantum state until they are processed or read; the quantum communication is provided via the quantum network which is a fiber optic network existing in parallel with the power network system (or the power grid); ¶¶ [0046]-[0050] with FIG. 2: the power grid sensing system 100 is provided to perform phasor measurement in a quantum format using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, quantum time transport, etc.), and may be referred to as a quantum power grid sensing system or a power grid sensing system; the power grid sensing system 100 includes one or more quantum phasor measurement units (qPMUs) 110, one or more phasor measurement units (PMUs) 115, one or more phasor data concentrators (PDCs) including a local PDC 120, a PDC 130, a data storage 140, a monitoring module 150, an off-line Dynamic analysis module 160, an external source 170; the quantum network is assumed to be a fiber optic network existing in parallel with the power network system; the one or more qPMUs 110 may be connected in a quantum network (or a quantum communication network) and each qPMU may be represented as a node; ¶¶ [0075]-[0078] with FIGS. 3-4: the quantum signal may be transmitted to PDC (e.g., PDC 130) via the network interface 240; the PDC (e.g., PDC 130) may configured to communicate with multiple qPMUs (e.g., qPMUs 110), concentrate data, align data by time, identify missing data, archive the data for post event analysis, aggregate and re-transmit data; the receiver 310 is configured to receive the quantum signals from qPMUs (or a network interface 240) or other PDCs (e.g., a local PDC 120, a PDC 130); ¶ [0083]: qPMU s 110 communicate each other over the quantum network);
receive quantum synchronization input; the atomic clock configured to synchronize itself with other atomic clocks based on the received quantum synchronization input (BUSH, ¶¶ [0007]-[0012]: a PDC (Phasor Data Concentrator) configured to process the quantum signals into measurement data based on quantum synchronization protocols; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using an atomic clock as a reference clock; synchronize the quantum signals based on quantum synchronization protocols to generate output signal including the measurement data; quantum signals representing quantum states of entangled electrical devices in a quantum network and modifying a voltage angle of the entangled electrical devices to an optimal voltage value based on a universal reference frame or a GPS-enabled time synchronized information; the synchronized quantum signals are measured by: computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; the universal reference frame is based on a global synchronously rotating dq0 reference frame transformation; ¶ [0038]: the quantum system may be packaged into a photonic integrated circuit that could reside within the power protection intelligent electronic devices such as synchronized phasors and relays; ¶ [0053]-[0064] with FIG. 2: the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signal can be a complex amplitude or a quantum wave function which is a complex-valued function of space; the complex-valued function of space can be referred to as a phasor-valued function of space; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; thus, the power grid sensing system 100 can detect more subtle anomalies in current variation and phase angles; the one or more PMUs 115 are placed at different locations or substations in the power grid sensing system 100; a PMU 115 may provide synchronized phasor measurement data of voltage, current and frequency according to the present disclosure; the synchronized phasor measurement data may be provided in real time; the qPMU 110 and the PMU 115 may upload its quantum signals with time information such as time stamp, using communication medium; the PDC 130 may process the measured quantum signals into measurement data based on quantum clock synchronization protocols; the PDC 130 may synchronize the quantum signals by using time signal from an external source 170, such as Global Positioning System (GPS), or an atomic clock; the PDC 130 may correlate the data by time information (e.g., timetag) to create a system-wide measurement; the PDC 130 provides system management by monitoring all the input data for loss, errors and synchronization; the PDC 130 may monitor qPMU time synchronization status and/or PMU time synchronization status and applies appropriate filters to eliminate spurious alarms; the synchronized quantum signals and/or the synchronized phasor measurement data may be additionally stored in the data storage 140 coupled to the PDC 130 for the purpose of post-disturbance analysis or for tracking the state of a power network system; ¶¶ [0072]-[0073] and [0083]-[0086] with FIGS. 3 and 5: the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using a reference clock such as an atomic clock or GPS (Global positioning System) based clock; receive the quantum signals and synchronize the quantum signals based on the quantum synchronization protocols to generate output signal including the measurement data; provide improved time synchronization resolution and reduce unnecessary time for monitoring and settling electrical devices; ¶¶ [0079]-[0081] with FIGS. 2: process the quantum signals into measurement data based on quantum clock synchronization protocols; synchronize the quantum signals based on the quantum synchronization protocols; the quantum clock synchronization protocols are provided to tackle synchronizing distant clocks in multipartite network settings and with quantum enhancement; the quantum time synchronization in the quantum network can be part of a higher stratum and is provided as a master clock for classical network such as conventional power network; therefore, the quantum time synchronization may interface to the power grid sensing system 100 including PMUs (e.g., PMUs 115) via a boundary clock as IEEE 1588; it enables time synchronization to remain accessible to classical phasor measurement and quantum phasor measurement; the PDC 130 may be configured to concentrate and/or time align the measurements based on the internal clock); and
a quantum sensor configured to measure an electric field as electric-field data, wherein the electric-field data is transferred over the quantum network to other power grid nodes (BUSH, ¶ [0006]: the quantum sensing can be used to realize combinations of range, resolution and sensitivity for measurements of critical parameters so that the quantum sensor can be deployed to monitor the performance and integrity of the power network system and to analyze parameters in overhead power lines; the quantum sensor may increase time precision and capture higher-harmonic content (e.g., harmonics caused by semiconductor switching, inverter control dynamics, nonlinear loads, and transformer saturation); ¶¶ [0033]-[0034] with FIG. 1: Sensors such as Phasor Measurement Units (PMU) monitor power within power lines and buses and associated power transport mechanisms; when a fault condition is detected, data measured by the PMU will show anomalous changes in physical quantities like voltage, current, and phase angle; this information is used to determine whether electrical devise such as relays, located in spatially remote locations from the PMU, should be triggered, with the goal of isolating the faulty portion of the system; the quantum power protection coordination is implemented by placing a quantum entangled phasor measurement unit (entanglement-based PMU, ePMU) in the quantum plane; ¶¶ [0047]-[0053] with FIG. 1: the PMUs 115 (phasor measurement units 115) may be able to measure parameters such as frequency, voltage, current, or power. Certain measurements, such as a phasor, may then be communicated to a Phasor Data Concentrator (e.g., a PDC 130); the PDC 130 is to concentrate data from various PMUs, and to distribute the data; the PDC 130 may be able to initiate communication with multiple PMUs, archive data for post event analysis, aggregate and re-transmit data, and filter/structure output datasets; the PDC 130 may then output datasets to upstream devices such as a monitoring module (e.g., a monitoring module 150); power grid applications may be used to process the data transmitted by the PDC 130; e.g., the PDC 130 may output the datasets for analysis of power transmissions; the measurement of the one or more qPMUs (to determine the electrical parameters) may project onto a state that is entangled between qPMUs; a qPMU 110 (quantum phasor measurement unit 110) may be a physical equipment and referred to as a quantum sensor or a quantum sensing device; the quantum sensor may be one of an atom/ion sensor, a carbon nanodiamonds sensor, a silicon carbide sensor, a Rare earth ion-doped solids sensor, a Perovskites sensor and a quantum dots sensor; the qPMU 110 may be an alternative to a conventional PMU (e.g., PMU 115) measuring phasor data defined in IEEE C3 7 .118 protocol; ¶¶ [0069]-[0075] with FIGS. 2-3: the qPMU 110 may detect the pair of entangled photons and measure quantum signal (or quantum measurement data) by using quantum sensing; the quantum sensing is broadly defined as the use of quantum material, quantum coherence, and/or quantum entanglement to measure physical quantities (i.e., temperature, electromagnetic fields, etc.) and/or to enhance the sensitivity of classical measurements; the quantum sensing such as photonic quantum sensing, non-photonic quantum sensing to enhance performance of a conventional sensing with the promise of reduced noise; the sensing module 200 is configured to measure the quantum signal; the quantum signal is computed based on spin Qubits or entangled photons according to the quantum sensing; the detector 210 may detect or receive spin Qubits or entangled photons from the sources distributed via the quantum network; the quantum computing phase estimation may be used to measure the quantum signal, such as phase, power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using use a reference clock such as an atomic clock or GPS (Global positioning System) based clock; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the quantum signal may be transmitted to PDC (e.g., PDC 130) via the network interface 240).
Independent Claim 3
BUSH discloses a power grid comprising: grid nodes, each of the grid nodes being a member of a set including power plants, renewable power sources, and substations (BUSH, ¶¶ [0004]-[0005] and [0042]: a power network system (or power grid protection system) typically relies upon high fault currents (up to 6 per-unit) provided by synchronous generators at conventional thermal power plants to isolate and clear faults; new inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and battery energy storage continue to displace synchronous machine-based resources, new paradigms for power network system are required, as IBRs can only provide a modest amount of fault current; power grid sensing using quantum technologies including quantum sensing; power grid protection intelligent electric devices such as PMUs or entanglement-based PMUs (ePMUs) or quantum PMUs (qPMUs) (generating synchrophasor information) and relays are quantum entangled with one another over a quantum network to implement a secure power protection scheme; ¶ [0050] with FIG. 2: the one or more qPMUs 110 are placed at different locations or substations within an electrical grid system; the one or more qPMUs 110 may be connected in a quantum network (or a quantum communication network) and each qPMU may be represented as a node), the grid nodes including respective atomic clocks (BUSH, ¶¶ [0007]-[0010]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation; the processor may use an atomic clock as a reference clock; ¶ [0054] with FIG. 2: the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability); and power transmission lines electrically coupling each of the grid nodes to at least one other of the grid nodes (BUSH, ¶¶ [0006]-[0007]: the quantum sensing can be used to realize combinations of range, resolution and sensitivity for measurements of critical parameters so that the quantum sensor can be deployed to monitor the performance and integrity of the power network system and to analyze parameters in overhead power lines; the quantum network is a fiber optic network existing in parallel with a power network in where qPMUs and PDC are located; qPMUs communicate with each other over the quantum network; ¶¶ [0033]-[0034] with FIGS. 1-2: the power system protection is one of the primary goals for utility companies; sensors such as Phasor Measurement Units (PMU) monitor power within power lines and buses and associated power transport mechanisms; when a fault condition is detected, data measured by the PMU will show anomalous changes in physical quantities like voltage, current, and phase angle; this information is used to determine whether electrical devise such as relays, located in spatially remote locations from the PMU, should be triggered, with the goal of isolating the faulty portion of the system; in a quantum power protection coordination process or system, intelligent electrical devices (such as qPMUs 110, PMUs, and relays 1100) used for protection of the power grid are quantum-entangled with one another over a quantum network to implement a secure power protection scheme; pairs of mutually entangled devices may form a connected chain; a chain of such entangled devices, one end of which entangles with a trusted device, may extend the trust for each electrical device entangled in the chain; this is referred to as an entanglement chain of trust; ¶ [0037]-[0039]: the quantum communication is provided via the quantum network which is a fiber optic network existing in parallel with the power network system ( or the power grid); since there are unavoidable losses in fiber optic transmission lines, distance limitations on quantum communication are being overcome with quantum repeaters; entangled state is conveyed to power protection equipment (power grid protection intelligent electric devices such as relays) over the quantum network; the optimal placement including determination of where to deploy a mix of classical and entanglement-based PMUs (ePMU) and which ePMUs should be entangled with one another to maximize effectiveness while minimizing load on the quantum network may be provided using quantum computing; ¶ [0045]: the power grid may include generator stations, transmission lines and tower, and individual consumer distribution lines; ¶ [0051] with FIG. 2: the connections between the nodes denote that, in general, the initial state in which the quantum network is prepared can be entangled between the one or more qPMUs 110; ¶¶ [0054]-[0062] with FIG. 2: the qPMU 110 can be deployed to monitor the performance and integrity of the power network and to analyze parameters in overhead power lines in a power network system; the quantum state outputs from qPMU s 110 are interconnected in the quantum network and the quantum network helps implement entanglement-based algorithms that fuse the outputs from qPMUs 110 into a global result; the quantum signals from the one or more qPMUs 110 may be communicated to the PDC 130 or a dedicated local PDC 120 at the control center in the power system; the phasor measurement data from the one or more PMUs 115 may be communicated to the PDC 130 or a dedicated local PDC 120 at the control center; the local PDC 120 may be connected to other surrounding substations including qPMUs 110 and/or PMUs 115 then transmit data (or data sets) to the PDC 130; ¶ [0077] with FIG. 2: the PDC (e.g., PDC 130) may configured to communicate with multiple qPMUs (e.g., qPMUsl 10), concentrate data, align data by time, identify missing data, archive the data for post event analysis, aggregate and re-transmit data; ¶ [0083] with FIG. 2: qPMU s 110 communicate each other over the quantum network; ¶ [0088]: support quantum communication using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, etc.); the system may include a plurality of electrical devices, where an electrical device is operationally connected with another electrical device and coordinated in the power grid for coordinated power protection; ¶ [0102] with FIG. 9: the quantum network may include equipment hubs connected in a ring topology with a plurality of quantum nodes connected to each Equipment Hub).
Claim 4
BUSH discloses all the elements as stated in Claim 3 and further discloses a quantum network, the grid nodes including respective quantum network interfaces coupling respective atomic clocks to the quantum network (BUSH, ¶¶ [0007]-[0008]: the power grid sensing system includes: one or more qPMUs (quantum Phasor Measurement Units) configured to measure quantum signals representing quantum states of entangled electrical devices in the quantum network, and a PDC (Phasor Data Concentrator) configured to process the quantum signals into measurement data based on quantum synchronization protocols; the quantum network is a fiber optic network existing in parallel with a power network in where qPMUs and PDC are located; qPMUs communicate with each other over the quantum network; each qPMU includes: a network interface configured to transmit the quantum signal; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; ¶¶ [0032]-[0037] with FIG. 1: in the quantum data plane, entanglement sources such as entangled Qubits (photons) are distributed via a quantum network; the quantum network provides entanglement distribution for quantum power protection coordination (or power protection coordination) in the power network system; in the quantum network, electrical devices (e.g., relays 1100, ePMU 110, etc.) are entangled; the quantum network may include an attack detection capability; in the quantum network, a quantum network entanglement source 1110 is provided to distribute entangled photons; the quantum network entanglement source 1110 may be referred to an entanglement source; in a quantum power protection coordination process or system, intelligent electrical devices (such as qPMUs 110, PMUs, and relays 1100) used for protection of the power grid are quantum-entangled with one another over a quantum network to implement a secure power protection scheme; pairs of mutually entangled devices may form a connected chain; a chain of such entangled devices, one end of which entangles with a trusted device, may extend the trust for each electrical device entangled in the chain; this is referred to as an entanglement chain of trust; in the quantum network, the communicated information remains in quantum state until they are processed or read; the quantum communication is provided via the quantum network which is a fiber optic network existing in parallel with the power network system (or the power grid); ¶¶ [0046]-[0050] with FIG. 2: the power grid sensing system 100 is provided to perform phasor measurement in a quantum format using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, quantum time transport, etc.), and may be referred to as a quantum power grid sensing system or a power grid sensing system; the power grid sensing system 100 includes one or more quantum phasor measurement units (qPMUs) 110, one or more phasor measurement units (PMUs) 115, one or more phasor data concentrators (PDCs) including a local PDC 120, a PDC 130, a data storage 140, a monitoring module 150, an off-line Dynamic analysis module 160, an external source 170; the quantum network is assumed to be a fiber optic network existing in parallel with the power network system; the one or more qPMUs 110 may be connected in a quantum network (or a quantum communication network) and each qPMU may be represented as a node; ¶¶ [0075]-[0078] with FIGS. 3-4: the quantum signal may be transmitted to PDC (e.g., PDC 130) via the network interface 240; the PDC (e.g., PDC 130) may configured to communicate with multiple qPMUs (e.g., qPMUs 110), concentrate data, align data by time, identify missing data, archive the data for post event analysis, aggregate and re-transmit data; the receiver 310 is configured to receive the quantum signals from qPMUs (or a network interface 240) or other PDCs (e.g., a local PDC 120, a PDC 130); ¶ [0083]: qPMU s 110 communicate each other over the quantum network).
Claim 5
BUSH discloses all the elements as stated in Claim 4 and further discloses wherein the quantum network interfaces are configured to synchronize the atomic clocks across the quantum network (BUSH, ¶¶ [0007]-[0012]: a PDC (Phasor Data Concentrator) configured to process the quantum signals into measurement data based on quantum synchronization protocols; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using an atomic clock as a reference clock; synchronize the quantum signals based on quantum synchronization protocols to generate output signal including the measurement data; quantum signals representing quantum states of entangled electrical devices in a quantum network and modifying a voltage angle of the entangled electrical devices to an optimal voltage value based on a universal reference frame or a GPS-enabled time synchronized information; the synchronized quantum signals are measured by: computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; the universal reference frame is based on a global synchronously rotating dq0 reference frame transformation; ¶ [0038]: the quantum system may be packaged into a photonic integrated circuit that could reside within the power protection intelligent electronic devices such as synchronized phasors and relays; ¶ [0053]-[0064] with FIG. 2: the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signal can be a complex amplitude or a quantum wave function which is a complex-valued function of space; the complex-valued function of space can be referred to as a phasor-valued function of space; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; thus, the power grid sensing system 100 can detect more subtle anomalies in current variation and phase angles; the one or more PMUs 115 are placed at different locations or substations in the power grid sensing system 100; a PMU 115 may provide synchronized phasor measurement data of voltage, current and frequency according to the present disclosure; the synchronized phasor measurement data may be provided in real time; the qPMU 110 and the PMU 115 may upload its quantum signals with time information such as time stamp, using communication medium; the PDC 130 may process the measured quantum signals into measurement data based on quantum clock synchronization protocols; the PDC 130 may synchronize the quantum signals by using time signal from an external source 170, such as Global Positioning System (GPS), or an atomic clock; the PDC 130 may correlate the data by time information (e.g., timetag) to create a system-wide measurement; the PDC 130 provides system management by monitoring all the input data for loss, errors and synchronization; the PDC 130 may monitor qPMU time synchronization status and/or PMU time synchronization status and applies appropriate filters to eliminate spurious alarms; the synchronized quantum signals and/or the synchronized phasor measurement data may be additionally stored in the data storage 140 coupled to the PDC 130 for the purpose of post-disturbance analysis or for tracking the state of a power network system; ¶¶ [0072]-[0073] and [0083]-[0086] with FIGS. 3 and 5: the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using a reference clock such as an atomic clock or GPS (Global positioning System) based clock; receive the quantum signals and synchronize the quantum signals based on the quantum synchronization protocols to generate output signal including the measurement data; provide improved time synchronization resolution and reduce unnecessary time for monitoring and settling electrical devices; ¶¶ [0079]-[0081] with FIGS. 2: process the quantum signals into measurement data based on quantum clock synchronization protocols; synchronize the quantum signals based on the quantum synchronization protocols; the quantum clock synchronization protocols are provided to tackle synchronizing distant clocks in multipartite network settings and with quantum enhancement; the quantum time synchronization in the quantum network can be part of a higher stratum and is provided as a master clock for classical network such as conventional power network; therefore, the quantum time synchronization may interface to the power grid sensing system 100 including PMUs (e.g., PMUs 115) via a boundary clock as IEEE 1588; it enables time synchronization to remain accessible to classical phasor measurement and quantum phasor measurement; the PDC 130 may be configured to concentrate and/or time align the measurements based on the internal clock).
Claim 6
BUSH discloses all the elements as stated in Claim 5 and further discloses quantum sensors configured to measure electric fields at the grid nodes, the quantum sensors being coupled to respective quantum network interfaces so that electric-field data generated by the quantum sensors can be transferred to grid nodes other than their respective grid nodes (BUSH, ¶ [0006]: the quantum sensing can be used to realize combinations of range, resolution and sensitivity for measurements of critical parameters so that the quantum sensor can be deployed to monitor the performance and integrity of the power network system and to analyze parameters in overhead power lines; the quantum sensor may increase time precision and capture higher-harmonic content (e.g., harmonics caused by semiconductor switching, inverter control dynamics, nonlinear loads, and transformer saturation); ¶¶ [0033]-[0034] with FIG. 1: Sensors such as Phasor Measurement Units (PMU) monitor power within power lines and buses and associated power transport mechanisms; when a fault condition is detected, data measured by the PMU will show anomalous changes in physical quantities like voltage, current, and phase angle; this information is used to determine whether electrical devise such as relays, located in spatially remote locations from the PMU, should be triggered, with the goal of isolating the faulty portion of the system; the quantum power protection coordination is implemented by placing a quantum entangled phasor measurement unit (entanglement-based PMU, ePMU) in the quantum plane; ¶¶ [0047]-[0053] with FIG. 1: the PMUs 115 (phasor measurement units 115) may be able to measure parameters such as frequency, voltage, current, or power. Certain measurements, such as a phasor, may then be communicated to a Phasor Data Concentrator (e.g., a PDC 130); the PDC 130 is to concentrate data from various PMUs, and to distribute the data; the PDC 130 may be able to initiate communication with multiple PMUs, archive data for post event analysis, aggregate and re-transmit data, and filter/structure output datasets; the PDC 130 may then output datasets to upstream devices such as a monitoring module (e.g., a monitoring module 150); power grid applications may be used to process the data transmitted by the PDC 130; e.g., the PDC 130 may output the datasets for analysis of power transmissions; the measurement of the one or more qPMUs (to determine the electrical parameters) may project onto a state that is entangled between qPMUs; a qPMU 110 (quantum phasor measurement unit 110) may be a physical equipment and referred to as a quantum sensor or a quantum sensing device; the quantum sensor may be one of an atom/ion sensor, a carbon nanodiamonds sensor, a silicon carbide sensor, a Rare earth ion-doped solids sensor, a Perovskites sensor and a quantum dots sensor; the qPMU 110 may be an alternative to a conventional PMU (e.g., PMU 115) measuring phasor data defined in IEEE C3 7 .118 protocol; ¶¶ [0069]-[0075] with FIGS. 2-3: the qPMU 110 may detect the pair of entangled photons and measure quantum signal (or quantum measurement data) by using quantum sensing; the quantum sensing is broadly defined as the use of quantum material, quantum coherence, and/or quantum entanglement to measure physical quantities (i.e., temperature, electromagnetic fields, etc.) and/or to enhance the sensitivity of classical measurements; the quantum sensing such as photonic quantum sensing, non-photonic quantum sensing to enhance performance of a conventional sensing with the promise of reduced noise; the sensing module 200 is configured to measure the quantum signal; the quantum signal is computed based on spin Qubits or entangled photons according to the quantum sensing; the detector 210 may detect or receive spin Qubits or entangled photons from the sources distributed via the quantum network; the quantum computing phase estimation may be used to measure the quantum signal, such as phase, power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using use a reference clock such as an atomic clock or GPS (Global positioning System) based clock; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the quantum signal may be transmitted to PDC (e.g., PDC 130) via the network interface 240).
Claim 7
BUSH discloses all the elements as stated in Claim 6 and further discloses wherein the quantum sensors are coupled to the atomic clocks so that the quantum sensors can be activated and deactivated at certain times (BUSH, ¶¶ [0067]-[0068] with FIG. 2: the power grid sensing system 100 may provide a quantum network-enabled wide area monitoring and control (qWAMPAC) function via the monitoring module 150, which can achieve heightened degrees of stability and optimality through communication of a universal reference frame for the power network system voltage based on principles of quantum entanglement and the resulting ability to securely communicate real-time, near-instantaneous time-synchronized phasor measurements over the quantum network; the monitoring module 150 may selectively modify a voltage angle of one or more electrical devices of the entangled electrical devices to an optimal voltage value based on the universal reference frame; the power grid sensing system 100 can utilize the quantum entanglement and classical electromagnetic machines and drives so that the power grid sensing system 100 uses a global synchronously rotating dq0 (direct quantum zero) reference frame transformation to provide the universal reference frame; therefore, the power grid sensing system 100 can achieve more precise current and/or voltage regulation, vastly improving dynamic response time and settling time while accommodating not only for network swing dynamics, but also network electromagnetic dynamics; the monitoring module 150 may send control signals to cause the electrical device to inject current in the universal reference frame rotating synchronously with the global dq0 reference frame; since the electrical devices are entangled in the quantum network, the power grid sensing system 100 can perform quantum network-enabled control actions and reduce or nearly eliminate unnecessary time for settling grid-forming inverter resources; the power grid sensing system 100 can perform control actions using GPS-enabled time synchronized information and other control signals besides the voltage angle can be modified in this fashion, including active and reactive power references and frequency and voltage droop parameters; ¶¶ [0079]-[0081] with FIG. 2: the quantum clock synchronization protocols are provided to tackle synchronizing distant clocks in multipartite network settings and with quantum enhancement; the quantum time synchronization in the quantum network can be part of a higher stratum and is provided as a master clock for classical network such as conventional power network; therefore, the quantum time synchronization may interface to the power grid sensing system 100 including PMUs (e.g., PMUs 115) via a boundary clock as IEEE 1588; it enables time synchronization to remain accessible to classical phasor measurement and quantum phasor measurement; the PDC 130 may then be configured to concentrate and/or time align the measurements based on the internal clock; ¶¶ [0083]-[0086] with FIGS. 2 and 5: measure quantum signals representing quantum states of entangled electrical devices in a quantum network (410); computes a quantum signal based on quantum computing phase estimation (411); the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use an atomic clock as the reference clock; process the quantum signals into measurement data based on quantum clock synchronization protocols (420); receive the quantum signals and synchronize the quantum signals based on the quantum synchronization protocols to generate output signal including the measurement data; provide improved time synchronization resolution and reduce unnecessary time for monitoring and settling electrical devices).
Claim 8
BUSH discloses all the elements as stated in Claim 7 and further discloses quantum computer systems included in respective power grid nodes, the quantum computer systems being coupled with the respective quantum network interfaces, the atomic clocks and the quantum sensors, the quantum computer systems being configured to estimate or determine grid states of the power grid based on information obtained from the quantum sensors (BUSH, ¶¶ [0007]-[0011]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation and a network interface configured to transmit the quantum signal; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; ¶¶ [0039]-[0041]: the optimal placement including determination of where to deploy a mix of classical and entanglement-based PMUs (ePMU) and which ePMUs should be entangled with one another to maximize effectiveness while minimizing load on the quantum network may be provided using quantum computing; the placement and coordination of ePMUs placement are optimized by a quantum computing or a quantum annealing hardware to minimize the number of PMUs required (assuming a mix of classical and quantum PMUs), overhead of the quantum network (minimizes the amount of entanglement, and the number of multipartite entanglements), and maximize the cybersecurity of the power grid; ¶¶ [0046]-[0055] with FIG. 2: perform phasor measurement in a quantum format using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, quantum time transport, etc.); the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; the quantum signals may be provided in real time; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the quantum state outputs from qPMU s 110 are interconnected in the quantum network and the quantum network helps implement entanglement-based algorithms that fuse the outputs from qPMUs 110 into a global result; therefore, quantum computing would not suffer from delay in measurement at each qPMU 110, classical transport, and aggregation over the network and loading into the quantum network; ¶ [0068] with FIG. 2: the optimal voltage value is calculated using optimal power flow calculation or by other means, such as a decentralized control algorithm; or the optimal voltage may be sent to a quantum computer (not shown in FIG. 2) then processed by a quantum computer which communicates with the monitoring module 150 to get the result faster; ¶¶ [0071]-[0075] with FIG. 3: the qPMU 110 includes a sensing module 200, a detector 210, a processor(s) 220, a memory 230, and a network interface 240; the processor(s) 210 may compute the quantum signal based on quantum computing phase estimation; the quantum signal is computed based on spin Qubits or entangled photons according to the quantum sensing; the quantum computing phase estimation is, but not limited to, being performed by executing a quantum Fourier transformation (QFT) algorithm; perform the quantum computing phase estimation to measure the quantum signal, such as phase, power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use a reference clock such as an atomic clock or GPS (Global positioning System) based clock; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; ¶¶ [0083]-[0088] with FIG. 5: compute a quantum signal based on quantum computing phase estimation (411); the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use an atomic clock as the reference clock; the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; support quantum communication using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, etc.)).
Independent Claim 13
BUSH discloses a power-grid process comprising: operating a power grid having plural grid nodes that are members of a set including power plants, renewable power sources, and substations (BUSH, ¶¶ [0004]-[0005] and [0042]: a power network system (or power grid protection system) typically relies upon high fault currents (up to 6 per-unit) provided by synchronous generators at conventional thermal power plants to isolate and clear faults; new inverter-based resources (IBRs) such as solar photovoltaics, wind turbines, and battery energy storage continue to displace synchronous machine-based resources, new paradigms for power network system are required, as IBRs can only provide a modest amount of fault current; power grid sensing using quantum technologies including quantum sensing; power grid protection intelligent electric devices such as PMUs or entanglement-based PMUs (ePMUs) or quantum PMUs (qPMUs) (generating synchrophasor information) and relays are quantum entangled with one another over a quantum network to implement a secure power protection scheme; ¶¶ [0045] and [0050] with FIG. 2: the power grid may include generator stations, transmission lines and tower, and individual consumer distribution lines; the one or more qPMUs 110 are placed at different locations or substations within an electrical grid system; the one or more qPMUs 110 may be connected in a quantum network (or a quantum communication network) and each qPMU may be represented as a node), the grid nodes including respective atomic clocks, and regulating power transmission frequencies of power transmissions between the grid nodes using the atomic clocks (BUSH, ¶¶ [0006]-[0010]: the quantum sensing can be used to realize combinations of range, resolution and sensitivity for measurements of critical parameters so that the quantum sensor can be deployed to monitor the performance and integrity of the power network system and to analyze parameters in overhead power lines; the quantum sensor may increase time precision and capture higher-harmonic content (e.g., harmonics caused by semiconductor switching, inverter control dynamics, nonlinear loads, and transformer saturation); therefore, the power grid sensing system can provide ubiquitous, high-resolution, and time-synchronized measurements that would help provide further insight into addressing these possible dynamic interactions; also, multiple-harmonic sliding window discrete Fourier transforms can be calculated at arbitrarily high multiples of the SiC-based IBR switching frequency to generate a set of synchrophasor results that would be instrumental in an online rigorous investigation of high-order, coupled dynamics, as well as mitigation of hard-to-address dynamic interactions; the power grid sensing system includes: one or more qPMUs (quantum Phasor Measurement Units) configured to measure quantum signals representing quantum states of entangled electrical devices in the quantum network, and a PDC (Phasor Data Concentrator) configured to process the quantum signals into measurement data based on quantum synchronization protocols; each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation and a network interface configured to transmit the quantum signal; the processor may use an atomic clock as a reference clock; ¶[0033]: the power network must support rapid data transfer within the frequency of sampling of the phasor data; ¶ [0048] with FIG. 2: the PMUs (e.g., PMUs 115) may be able to measure parameters such as frequency, voltage, current, or power. Certain measurements, such as a phasor, may then be communicated to a Phasor Data Concentrator (e.g., a PDC 130); ¶ [0054] with FIG. 2: the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; ¶ [0057] with FIG. 2: a PMU 115 may provide synchronized phasor measurement data of voltage, current and frequency, wherein the synchronized phasor measurement data may be provided in real time; ¶ [0063] with FIG. 2: the PDC 130 may process the measured quantum signals into measurement data based on quantum clock synchronization protocols; the PDC 130 may synchronize the quantum signals by using time signal from an external source 170, such as Global Positioning System (GPS), or an atomic clock; ¶¶ [0067]-[0068] with FIG. 2: the power grid sensing system 100 may provide a quantum network-enabled wide area monitoring and control (qWAMPAC) function via the monitoring module 150, which achieve heightened degrees of stability and optimality through communication of a universal reference frame for the power network system voltage based on principles of quantum entanglement and the resulting ability to securely communicate real-time, near-instantaneous time-synchronized phasor measurements over the quantum network; the monitoring module 150 may selectively modify a voltage angle of one or more electrical devices of the entangled electrical devices to an optimal voltage value based on the universal reference frame; the power grid sensing system 100 can utilize the quantum entanglement and classical electromagnetic machines and drives so that the power grid sensing system 100 uses a global synchronously rotating dq0 ( direct quantum zero) reference frame transformation to provide the universal reference frame; therefore, the power grid sensing system 100 can achieve more precise current and/or voltage regulation, vastly improving dynamic response time and settling time while accommodating not only for network swing dynamics, but also network electromagnetic dynamics; the monitoring module 150 may send control signals to cause the electrical device to inject current in the universal reference frame rotating synchronously with the global dq0 reference frame; since the electrical devices are entangled in the quantum network, the power grid sensing system 100 can perform quantum network-enabled control actions and reduce or nearly eliminate unnecessary time for settling grid-forming inverter resources; the power grid sensing system 100 can perform control actions using GPS-enabled time synchronized information and other control signals besides the voltage angle can be modified in this fashion, including active and reactive power references and frequency and voltage droop parameters; in this case, unentangled devices (resources) that lose their connection to the quantum network may be controlled by a conventional grid-forming control method to synchronize with the power network system by regulating voltage and frequency locally based on local active power and reactive power feedback; ¶ [0081] with FIG. 2: the PDC 130 may receive a time signal from an external source (e.g., the external source 170), such as a GPS clock, an atomic clock, and/or or a high resolution time clock; the PDC 130 may then be configured to concentrate and/or time align the measurements based on the internal clock; ¶ [0093] with FIG. 2: a pair of the entangled electrical devices (e.g., power relay device 1100, qPMU 110) are configured to check (e.g., periodically check with a certain frequency) their respective entangled quantum states by measuring states of the entangled photons to ensure that the pre-configured correlation state of the pair is maintained).
Claim 14
BUSH discloses all the elements as stated in Claim 13 and further discloses operating the power grid without synchronizing the atomic clocks to an external time reference (BUSH, ¶¶ [0007]-[0010]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation and a network interface configured to transmit the quantum signal; the processor may use an atomic clock as a reference clock; ¶ [0054] with FIG. 2: the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; ¶ [0081] with FIG. 2: the PDC 130 may receive a time signal from an external source (e.g., the external source 170), such as a GPS clock, an atomic clock, and/or or a high resolution time clock; the PDC 130 may then be configured to concentrate and/or time align the measurements based on the internal clock; ).
Claim 15
BUSH discloses all the elements as stated in Claim 13 and further discloses synchronizing the atomic clocks to each other using a quantum network of the power grid (BUSH, ¶¶ [0007]-[0012]: a PDC (Phasor Data Concentrator) configured to process the quantum signals into measurement data based on quantum synchronization protocols; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using an atomic clock as a reference clock; synchronize the quantum signals based on quantum synchronization protocols to generate output signal including the measurement data; quantum signals representing quantum states of entangled electrical devices in a quantum network and modifying a voltage angle of the entangled electrical devices to an optimal voltage value based on a universal reference frame or a GPS-enabled time synchronized information; the synchronized quantum signals are measured by: computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; the universal reference frame is based on a global synchronously rotating dq0 reference frame transformation; ¶ [0038]: the quantum system may be packaged into a photonic integrated circuit that could reside within the power protection intelligent electronic devices such as synchronized phasors and relays; ¶ [0053]-[0064] with FIG. 2: the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signal can be a complex amplitude or a quantum wave function which is a complex-valued function of space; the complex-valued function of space can be referred to as a phasor-valued function of space; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; thus, the power grid sensing system 100 can detect more subtle anomalies in current variation and phase angles; the one or more PMUs 115 are placed at different locations or substations in the power grid sensing system 100; a PMU 115 may provide synchronized phasor measurement data of voltage, current and frequency according to the present disclosure; the synchronized phasor measurement data may be provided in real time; the qPMU 110 and the PMU 115 may upload its quantum signals with time information such as time stamp, using communication medium; the PDC 130 may process the measured quantum signals into measurement data based on quantum clock synchronization protocols; the PDC 130 may synchronize the quantum signals by using time signal from an external source 170, such as Global Positioning System (GPS), or an atomic clock; the PDC 130 may correlate the data by time information (e.g., timetag) to create a system-wide measurement; the PDC 130 provides system management by monitoring all the input data for loss, errors and synchronization; the PDC 130 may monitor qPMU time synchronization status and/or PMU time synchronization status and applies appropriate filters to eliminate spurious alarms; the synchronized quantum signals and/or the synchronized phasor measurement data may be additionally stored in the data storage 140 coupled to the PDC 130 for the purpose of post-disturbance analysis or for tracking the state of a power network system; ¶¶ [0072]-[0073] and [0083]-[0086] with FIGS. 3 and 5: the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using a reference clock such as an atomic clock or GPS (Global positioning System) based clock; receive the quantum signals and synchronize the quantum signals based on the quantum synchronization protocols to generate output signal including the measurement data; provide improved time synchronization resolution and reduce unnecessary time for monitoring and settling electrical devices; ¶¶ [0079]-[0081] with FIGS. 2: process the quantum signals into measurement data based on quantum clock synchronization protocols; synchronize the quantum signals based on the quantum synchronization protocols; the quantum clock synchronization protocols are provided to tackle synchronizing distant clocks in multipartite network settings and with quantum enhancement; the quantum time synchronization in the quantum network can be part of a higher stratum and is provided as a master clock for classical network such as conventional power network; therefore, the quantum time synchronization may interface to the power grid sensing system 100 including PMUs (e.g., PMUs 115) via a boundary clock as IEEE 1588; it enables time synchronization to remain accessible to classical phasor measurement and quantum phasor measurement; the PDC 130 may be configured to concentrate and/or time align the measurements based on the internal clock).
Claim 16
BUSH discloses all the elements as stated in Claim 13 and further discloses synchronizing the atomic clocks to an external time reference (BUSH, ¶¶ [0007]-[0010]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation and a network interface configured to transmit the quantum signal; the processor may use an atomic clock as a reference clock; ¶ [0054] with FIG. 2: the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; ¶ [0063] with FIG. 2: the PDC 130 may synchronize the quantum signals by using time signal from an external source 170, such as Global Positioning System (GPS), or an atomic clock).
Claim 17
BUSH discloses all the elements as stated in Claim 13 and further discloses using quantum sensors of the grid nodes to characterize electric fields at the grid nodes to yield electric-field data (BUSH, ¶ [0006]: the quantum sensing can be used to realize combinations of range, resolution and sensitivity for measurements of critical parameters so that the quantum sensor can be deployed to monitor the performance and integrity of the power network system and to analyze parameters in overhead power lines; the quantum sensor may increase time precision and capture higher-harmonic content (e.g., harmonics caused by semiconductor switching, inverter control dynamics, nonlinear loads, and transformer saturation); ¶¶ [0033]-[0034] with FIG. 1: Sensors such as Phasor Measurement Units (PMU) monitor power within power lines and buses and associated power transport mechanisms; when a fault condition is detected, data measured by the PMU will show anomalous changes in physical quantities like voltage, current, and phase angle; this information is used to determine whether electrical devise such as relays, located in spatially remote locations from the PMU, should be triggered, with the goal of isolating the faulty portion of the system; the quantum power protection coordination is implemented by placing a quantum entangled phasor measurement unit (entanglement-based PMU, ePMU) in the quantum plane; ¶¶ [0047]-[0053] with FIG. 1: the PMUs 115 (phasor measurement units 115) may be able to measure parameters such as frequency, voltage, current, or power. Certain measurements, such as a phasor, may then be communicated to a Phasor Data Concentrator (e.g., a PDC 130); the PDC 130 is to concentrate data from various PMUs, and to distribute the data; the PDC 130 may be able to initiate communication with multiple PMUs, archive data for post event analysis, aggregate and re-transmit data, and filter/structure output datasets; the PDC 130 may then output datasets to upstream devices such as a monitoring module (e.g., a monitoring module 150); power grid applications may be used to process the data transmitted by the PDC 130; e.g., the PDC 130 may output the datasets for analysis of power transmissions; the measurement of the one or more qPMUs (to determine the electrical parameters) may project onto a state that is entangled between qPMUs; a qPMU 110 (quantum phasor measurement unit 110) may be a physical equipment and referred to as a quantum sensor or a quantum sensing device; the quantum sensor may be one of an atom/ion sensor, a carbon nanodiamonds sensor, a silicon carbide sensor, a Rare earth ion-doped solids sensor, a Perovskites sensor and a quantum dots sensor; the qPMU 110 may be an alternative to a conventional PMU (e.g., PMU 115) measuring phasor data defined in IEEE C3 7 .118 protocol; ¶¶ [0069]-[0075] with FIGS. 2-3: the qPMU 110 may detect the pair of entangled photons and measure quantum signal (or quantum measurement data) by using quantum sensing; the quantum sensing is broadly defined as the use of quantum material, quantum coherence, and/or quantum entanglement to measure physical quantities (i.e., temperature, electromagnetic fields, etc.) and/or to enhance the sensitivity of classical measurements; the quantum sensing such as photonic quantum sensing, non-photonic quantum sensing to enhance performance of a conventional sensing with the promise of reduced noise; the sensing module 200 is configured to measure the quantum signal; the quantum signal is computed based on spin Qubits or entangled photons according to the quantum sensing; the detector 210 may detect or receive spin Qubits or entangled photons from the sources distributed via the quantum network; the quantum computing phase estimation may be used to measure the quantum signal, such as phase, power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network using use a reference clock such as an atomic clock or GPS (Global positioning System) based clock; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the quantum signal may be transmitted to PDC (e.g., PDC 130) via the network interface 240).
Claim 18
BUSH discloses all the elements as stated in Claim 17 and further discloses using quantum computer systems of the grid nodes to provide state estimates of states of the power grid based on the electric-field data (BUSH, ¶¶ [0007]-[0011]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation and a network interface configured to transmit the quantum signal; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; ¶¶ [0039]-[0041]: the optimal placement including determination of where to deploy a mix of classical and entanglement-based PMUs (ePMU) and which ePMUs should be entangled with one another to maximize effectiveness while minimizing load on the quantum network may be provided using quantum computing; the placement and coordination of ePMUs placement are optimized by a quantum computing or a quantum annealing hardware to minimize the number of PMUs required (assuming a mix of classical and quantum PMUs), overhead of the quantum network (minimizes the amount of entanglement, and the number of multipartite entanglements), and maximize the cybersecurity of the power grid; ¶¶ [0046]-[0055] with FIG. 2: perform phasor measurement in a quantum format using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, quantum time transport, etc.); the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; the quantum signals may be provided in real time; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the quantum state outputs from qPMU s 110 are interconnected in the quantum network and the quantum network helps implement entanglement-based algorithms that fuse the outputs from qPMUs 110 into a global result; therefore, quantum computing would not suffer from delay in measurement at each qPMU 110, classical transport, and aggregation over the network and loading into the quantum network; ¶ [0068] with FIG. 2: the optimal voltage value is calculated using optimal power flow calculation or by other means, such as a decentralized control algorithm; or the optimal voltage may be sent to a quantum computer (not shown in FIG. 2) then processed by a quantum computer which communicates with the monitoring module 150 to get the result faster; ¶¶ [0071]-[0075] with FIG. 3: the qPMU 110 includes a sensing module 200, a detector 210, a processor(s) 220, a memory 230, and a network interface 240; the processor(s) 210 may compute the quantum signal based on quantum computing phase estimation; the quantum signal is computed based on spin Qubits or entangled photons according to the quantum sensing; the quantum computing phase estimation is, but not limited to, being performed by executing a quantum Fourier transformation (QFT) algorithm; perform the quantum computing phase estimation to measure the quantum signal, such as phase, power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use a reference clock such as an atomic clock or GPS (Global positioning System) based clock; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; ¶¶ [0083]-[0088] with FIG. 5: compute a quantum signal based on quantum computing phase estimation (411); the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use an atomic clock as the reference clock; the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; support quantum communication using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, etc.)).
Claim 20
BUSH discloses all the elements as stated in Claim 18 and further discloses importing at least some of the electric-field data in the quantum computer systems by transferring atomic sensor elements of the quantum sensors into quantum registers of the quantum computer systems (BUSH, ¶ [0005]: the quantum network has quantum repeaters capable of relaying single photon-encoded signals over long distances which is in the middle of sources; ¶¶ [0008], [0010], [0072], and [0084] with FIG. 3: the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; the detector 210 may detect or receive spin Qubits or entangled photons from the sources distributed via the quantum network; ¶ [0014]: the entangled photons may be referred to as entangled quantum information; the entangled photons are represented by Qubits; ¶ [0032]: in the quantum data plane, entanglement sources such as entangled Qubits (photons) are distributed via a quantum network; ¶ [0038]: entangled state is conveyed to power protection equipment (power grid protection intelligent electric devices such as relays) over the quantum network including, e.g., bulk optical components including mirrors, beam splitters, phase modulators, and single photon detectors; a quantum memory may be utilized as well; the quantum system may be packaged into a photonic integrated circuit that could reside within the power protection intelligent electronic devices such as synchronized phasors and relays; ¶ [0040]: in this secure direct entanglement approach, there is no cybersecurity key or cryptography applied to the transmitted data. Instead, entangled Qubits (photons) are distributed to endpoints and quantum operations applied to the Qubits to signal power protection coordination actions; any attempt to attack the entangled pairs will be detected via quantum bit error rate during entanglement; ¶ [0052]: the quantum sensor may be, but not limited to, one of an atom/ion sensor, a carbon nanodiamonds sensor, a silicon carbide sensor, a Rare earth ion-doped solids sensor, a Perovskites sensor and a quantum dots sensor; ¶ [0053] with FIGS. 1-2: the entanglement sources as depicted in FIG. 1 may send a pair of entangled photons or spin Qubits to qPMUs 110 in different locations; the qPMU 110 may detect the pair of entangled photons or Qubits by using quantum sensing; ¶ [0054]: the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; ¶ [0087]: the power gird sensing system may leverage quantum memories near the at least two entangled electrical devices, if possible; ¶¶ [0090]-[0093] with FIG. 2: the power grid sensing system may set up pre-configuration of a respective electrical device of the plurality of electrical devices which is configured to be entangled with other electrical devices in the quantum network; the pre-configuration represents which electrical device (e.g., power relay 1100) in the quantum network should trip or not trip, and when should that happen; the pre-configuration is represented by a Qubit and determined by the respective electrical device or the power grid sensing system; the power grid sensing system includes an entanglement source 1110 (e.g., implemented using a processor) which is configured to provide or distribute photons over the quantum network to the electrical devices to initiate or implement quantum entanglement of those devices; the entangled photons are based on, but not limited to, at least one of polarization entanglement and time-energy entanglement; the entangled photons are represented by Qubits (e.g., Qubit A and Qubit B) but are not limited thereto; the quantum state of the respective electrical device may be represented by, but is not limited to, various properties of the quantum state, such as an integer variable (e.g., 0, 1 ), phase, photon polarization angle, timing, energy, or momentum; such properties of the quantum state may be used to represent the power grid phasor (e.g., magnitude and phase angle for the voltage or current at a specific location on the power grid) measured by the qPMU 110; ¶ [0102] with FIG. 9: the power gird sensing system may leverage quantum memories near the first electrical device (Alice) and the second electrical device (Bob), if possible; ¶ [0104] with FIG. 2: the quantum phase information represents a phase angle which is an angular displacement between a current and voltage waveform measured in degrees or radians; the quantum phase information may be measure by qPMU in the power grid (e.g., qPMU 110) and encoded in single photon transmissions; ¶ [0111]: a respective electrical device ( e.g., a first electrical device 1100-1, a second electrical device 1100-2) may measure the quantum information (e.g., quantum properties, such as phase, photon polarization angle, timing, energy, or momentum of a respective photon) to determine its quantum state).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over BUSH in view of Giovannetti et al. ("Quantum enhanced positioning and clock synchronization", arXiv:quant-ph/0103006v3, Jun 1, 2001, pp. 1-4 or NATURE, VOL 412, JULY 26, 2001, pp. 417-419), hereinafter Giovannetti.
Claim 2
BUSH discloses all the elements as stated in Claim 1 and further discloses wherein the received quantum synchronization input comprises a first number of entangled signals, wherein each entangled signal comprises a second number of (BUSH, ¶¶ [0007]-[0014]: the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; synchronize the quantum signals based on quantum synchronization protocols to generate output signal including the measurement data; quantum signals representing quantum states of entangled electrical devices in a quantum network and modifying a voltage angle of the entangled electrical devices to an optimal voltage value based on a universal reference frame or a GPS-enabled time synchronized information; the synchronized quantum signals are measured by: computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; the universal reference frame is based on a global synchronously rotating dq0 reference frame transformation; the entangled photons may be referred to as entangled quantum information; the entangled photons are represented by Qubits; ¶¶ [0053]-[0064], [0069]-[0073], and [0083]-[0086] with FIGS 1-3 and 5: the entanglement sources as depicted in FIG. 1 may send a pair of entangled photons or spin Qubits to qPMUs 110 in different locations; the qPMU 110 may detect the pair of entangled photons or Qubits by using quantum sensing; the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signal can be a complex amplitude or a quantum wave function which is a complex-valued function of space; the complex-valued function of space can be referred to as a phasor-valued function of space; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability. Thus, the power grid sensing system 100 can detect more subtle anomalies in current variation and phase angles; the quantum signals may be provided in real time; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the PDC 130 may process the measured quantum signals into measurement data based on quantum clock synchronization protocols; the PDC 130 may synchronize the quantum signals by using time signal from an external source 170, such as Global Positioning System (GPS), or an atomic clock; ¶¶ [0079]-[0081] with FIGS. 2: process the quantum signals into measurement data based on quantum clock synchronization protocols; synchronize the quantum signals based on the quantum synchronization protocols; the quantum clock synchronization protocols are provided to tackle synchronizing distant clocks in multipartite network settings and with quantum enhancement; the quantum time synchronization in the quantum network can be part of a higher stratum and is provided as a master clock for classical network such as conventional power network; therefore, the quantum time synchronization may interface to the power grid sensing system 100 including PMUs (e.g., PMUs 115) via a boundary clock as IEEE 1588; it enables time synchronization to remain accessible to classical phasor measurement and quantum phasor measurement; the PDC 130 may be configured to concentrate and/or time align the measurements based on the internal clock).
BUSH fails to explicitly disclose wherein the received quantum synchronization input comprises a first number of entangled pulses, wherein each entangled pulse comprises a second number of squeezed particles.
Giovannetti teaches a system and a method using quantum techniques (Giovannetti, 1st paragraph in Page 1), wherein the received quantum synchronization input comprises a first number of entangled pulses, wherein each entangled pulse comprises a second number of squeezed particles (Giovannetti, 1st paragraph in Page 1: quantum entanglement and squeezing can be employed to overcome the classical power/bandwidth limits on these procedures, enhancing their accuracy; frequency entangled pulses could be used to construct quantum positioning systems (QPS), to perform clock synchronization, or to do ranging (quantum radar): all of these techniques exhibit a similar enhancement compared with analogous protocols that use classical light; 2nd-3rd paragraphs in Page 1: the accuracy of such a procedure depends on the number of pulses, their bandwidth and the number of photons per pulse; this paper shows that by measuring the correlations between the times of arrival of M pulses which are frequency-entangled, one can in principle increase the accuracy of such a positioning procedure by a factor √M as compared to positioning using unentangled pulses with the same bandwidth; moreover, if number-squeezed pulses can be produced, it is possible to obtain a further increase in accuracy of √N by employing squeezed pulses of N quanta, vs. employing “classical” coherent states with N mean number of quanta; combining entanglement with squeezing gives an overall enhancement of √MN; in addition, the procedure exhibits improved security: because the timing information resides in the entanglement between pulses, it is possible to implement quantum cryptographic schemes that do not allow an eavesdropper to obtain information on the position of Alice; the clock synchronization problem can be treated using the same method; quantum features such as entanglement and squeezing can in principle be used to supply a significant enhancement of the accuracy of clock synchronization as compared to classical protocols using light of the same frequency and power; in fact, the clock synchronization can be accomplished by sending pulses back and forth between the parties whose clocks are to be synchronized and measuring the times of arrival of the pulses (Einstein’s protocol); in this way synchronization may be treated on the same basis as positioning and the same accuracy enhancements may be achieved through entanglement and squeezing).
BUSH and Giovannetti are analogous art because they are from the same field of endeavor, a system and a method using quantum techniques. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to apply the teaching of Giovannetti to BUSH. Motivation for doing so would enhance accuracy (Giovannetti, 1st-3rd paragraphs in Page 1).
Claims 9-12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over BUSH in view of Dong et al. ("Several recent developments in estimation and robust control of quantum systems", 2017 Australian and New Zealand Control Conference (ANZCC), December 17-20, 2017. Gold Coast Convention Centre, Australia, pp. 190-195), hereinafter Dong.
Claim 9
BUSH discloses all the elements as stated in Claim 8 and further discloses wherein the quantum computer systems are configured to estimate the grid states (BUSH, BUSH, ¶¶ [0007]-[0011]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation and a network interface configured to transmit the quantum signal; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; ¶¶ [0039]-[0041]: the optimal placement including determination of where to deploy a mix of classical and entanglement-based PMUs (ePMU) and which ePMUs should be entangled with one another to maximize effectiveness while minimizing load on the quantum network may be provided using quantum computing; the placement and coordination of ePMUs placement are optimized by a quantum computing or a quantum annealing hardware to minimize the number of PMUs required (assuming a mix of classical and quantum PMUs), overhead of the quantum network (minimizes the amount of entanglement, and the number of multipartite entanglements), and maximize the cybersecurity of the power grid; ¶¶ [0046]-[0055] with FIG. 2: perform phasor measurement in a quantum format using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, quantum time transport, etc.); the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; the quantum signals may be provided in real time; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the quantum state outputs from qPMU s 110 are interconnected in the quantum network and the quantum network helps implement entanglement-based algorithms that fuse the outputs from qPMUs 110 into a global result; therefore, quantum computing would not suffer from delay in measurement at each qPMU 110, classical transport, and aggregation over the network and loading into the quantum network; ¶ [0068] with FIG. 2: the optimal voltage value is calculated using optimal power flow calculation or by other means, such as a decentralized control algorithm; or the optimal voltage may be sent to a quantum computer (not shown in FIG. 2) then processed by a quantum computer which communicates with the monitoring module 150 to get the result faster; ¶¶ [0071]-[0075] with FIG. 3: the qPMU 110 includes a sensing module 200, a detector 210, a processor(s) 220, a memory 230, and a network interface 240; the processor(s) 210 may compute the quantum signal based on quantum computing phase estimation; the quantum signal is computed based on spin Qubits or entangled photons according to the quantum sensing; the quantum computing phase estimation is, but not limited to, being performed by executing a quantum Fourier transformation (QFT) algorithm; perform the quantum computing phase estimation to measure the quantum signal, such as phase, power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use a reference clock such as an atomic clock or GPS (Global positioning System) based clock; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; ¶¶ [0083]-[0088] with FIG. 5: compute a quantum signal based on quantum computing phase estimation (411); the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use an atomic clock as the reference clock; the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; support quantum communication using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, etc.)).
BUSH fails to explicitly disclose estimate the states using quantum tomography.
Dong teaches a system and a method using quantum technology (Dong, Section I in Page 190), wherein estimate the states using quantum tomography (Dong, Abstract in Page 190: quantum state tomography via linear regression estimation and adaptive quantum state estimation are introduced and a Hamiltonian identification algorithm is outlined; two quantum robust control approaches including sliding mode control and sampling-based learning control are illustrated; Section I in Page 190: a fundamental task in quantum technology is to characterize the state of a quantum system and identify the parameters in the system; the estimation procedure of a static quantum state is often referred as quantum state tomography; for estimating a dynamical state, quantum filtering theory has been developed, which is especially useful for addressing the measurement-based quantum feedback control problem; the area of identifying key parameters in quantum systems can be referred as quantum system identification; another important problem is robustness of quantum systems in developing practical quantum technology since real quantum systems are often subject to noises, incomplete knowledge or uncertainties; in this paper, we introduce some recent developments in the areas of estimation and robust control of quantum systems; we present several examples and methods that were recently developed by the authors and their collaborators, and aim to illustrate; several classes of significant quantum estimation and control problems as well as outline open questions for future research; Section II with FIG. 1 in Pages 190-192: quantum state tomography provides a framework to reconstruct quantum states; to estimate a quantum state, we usually need to make measurements on many copies of the state; for a given unknown quantum state, we need to design POVM measurement and develop an estimation algorithm to reconstruct the quantum state from measurement data; various quantum state tomography methods have been developed such as maximum likelihood estimation (MLE) method, Bayesian mean estimation approach and linear regression estimation (LRE); an advantage of LRE for quantum state tomography is that its computational complexity can be characterized and the theoretical error upper bound may be obtained; another advantage of LRE is that it is suitable for developing adaptive quantum state estimation method; adaptive protocols have been proven to have the capability to improve the quantum estimation precision; in adaptive state estimation as shown in Figure 1, we first make measurements on part of copies and get a rough estimate of the quantum state; then we find optimal measurement bases to make measurements on some other copies; using (6) and (7), one can recursively incorporate new measurement data into historical measurement data, which provides a convenient way for adaptive estimation of ρ; in this sense, the LRE method is more suitable for adaptive reconstruction of quantum states due to its recursive procedure than traditional MLE or Bayesian mean method; in the LRE framework, instead of repeatedly calculating all the historical data when new data arrive, we only need to add the new data into historical information matrix and vector, which significantly reduces the calculation cost; based on the observation, an adaptive quantum state tomography protocol has been developed in [14]; in the first stage, one performs a standard LRE on N1 copies with the standard cube measurement bases to obtain a preliminary
Θ
^
and Q; in the second stage, the initial values of Q in (6) and
Θ
^
in (7) are set as Q0 = Q and
Θ
^
0
=
Θ
^
, and then the remaining N −N1 copies are utilized for multi-step adaptive estimation; the adaptive quantum state tomography can improve the estimation precision; the efficiency of the estimation algorithms may be further enhanced if there is prior knowledge on the quantum state to be reconstructed; various variants of LRE could be developed for quantum state tomography and different adaptivity criteria can be explored for adaptive estimation of quantum states; Section III in Pages 192-193: a quantum process ε maps an input state ρin to an output state ρout; we can obtain the full characterization of ε by reconstructing X; a central issue in quantum process tomography is to design an algorithm to find a physical estimation
X
^
such that Bvec(
X
^
) is close enough to vec(
Λ
^
); for a closed quantum system, its evolution can be described by (11) and H is the system Hamiltonian; a Hamiltonian identification method using measurement time traces has been proposed based on classical system identification theory and it has also been used to experimentally identify the Hamiltonian in spin systems; dynamical decoupling was employed for identifying parameters in the Hamiltonian; adaptive approaches were only applied to the identification problems of several simple quantum systems such as estimating the Hamiltonian parameter of a two-level system and more adaptive algorithms could be developed to enhance the identification precision for quantum systems).
BUSH and Dong are analogous art because they are from the same field of endeavor, a system and a method using quantum technology. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to apply the teaching of Dong to BUSH. Motivation for doing so would improve.
Claim 10
BUSH in view of Dong discloses all the elements as stated in Claim 9 and further discloses wherein the quantum computer systems have respective quantum registers populated at least in part by compute atoms having a first atomic number and a first atomic weight (BUSH, ¶¶ [0008], [0010], [0072], and [0084] with FIG. 3: the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; the detector 210 may detect or receive spin Qubits or entangled photons from the sources distributed via the quantum network; ¶ [0014]: the entangled photons may be referred to as entangled quantum information; the entangled photons are represented by Qubits; ¶ [0032]: in the quantum data plane, entanglement sources such as entangled Qubits (photons) are distributed via a quantum network; ¶ [0038]: entangled state is conveyed to power protection equipment (power grid protection intelligent electric devices such as relays) over the quantum network including, e.g., bulk optical components including mirrors, beam splitters, phase modulators, and single photon detectors; a quantum memory may be utilized as well; the quantum system may be packaged into a photonic integrated circuit that could reside within the power protection intelligent electronic devices such as synchronized phasors and relays; ¶ [0040]: in this secure direct entanglement approach, there is no cybersecurity key or cryptography applied to the transmitted data. Instead, entangled Qubits (photons) are distributed to endpoints and quantum operations applied to the Qubits to signal power protection coordination actions; any attempt to attack the entangled pairs will be detected via quantum bit error rate during entanglement; ¶ [0052]: the quantum sensor may be, but not limited to, one of an atom/ion sensor, a carbon nanodiamonds sensor, a silicon carbide sensor, a Rare earth ion-doped solids sensor, a Perovskites sensor and a quantum dots sensor; ¶ [0053] with FIGS. 1-2: the entanglement sources as depicted in FIG. 1 may send a pair of entangled photons or spin Qubits to qPMUs 110 in different locations; the qPMU 110 may detect the pair of entangled photons or Qubits by using quantum sensing; ¶ [0087]: the power gird sensing system may leverage quantum memories near the at least two entangled electrical devices, if possible; ¶¶ [0090]-[0092]: the power grid sensing system may set up pre-configuration of a respective electrical device of the plurality of electrical devices which is configured to be entangled with other electrical devices in the quantum network; the pre-configuration represents which electrical device (e.g., power relay 1100) in the quantum network should trip or not trip, and when should that happen; the pre-configuration is represented by a Qubit and determined by the respective electrical device or the power grid sensing system; the power grid sensing system includes an entanglement source 1110 (e.g., implemented using a processor) which is configured to provide or distribute photons over the quantum network to the electrical devices to initiate or implement quantum entanglement of those devices; the entangled photons are based on, but not limited to, at least one of polarization entanglement and time-energy entanglement; the entangled photons are represented by Qubits (e.g., Qubit A and Qubit B) but are not limited thereto; ¶ [0102] with FIG. 9: the power gird sensing system may leverage quantum memories near the first electrical device (Alice) and the second electrical device (Bob), if possible).
Claim 11
BUSH in view of Dong discloses all the elements as stated in Claim 10 and further discloses wherein at least some of the compute atoms are sensor atoms of the quantum sensors and are included in the quantum sensors (BUSH, ¶ [0052]: the quantum sensor may be, but not limited to, one of an atom/ion sensor, a carbon nanodiamonds sensor, a silicon carbide sensor, a Rare earth ion-doped solids sensor, a Perovskites sensor and a quantum dots sensor).
Claim 12
BUSH in view of Dong discloses all the elements as stated in Claim 10 and further discloses wherein at least some of the compute atoms are sensor atoms of the quantum sensors and encode sense data captured before they were transported into the quantum registers (BUSH, ¶ [0005]: the quantum network has quantum repeaters capable of relaying single photon-encoded signals over long distances which is in the middle of sources; ¶ [0052]: the quantum sensor may be, but not limited to, one of an atom/ion sensor, a carbon nanodiamonds sensor, a silicon carbide sensor, a Rare earth ion-doped solids sensor, a Perovskites sensor and a quantum dots sensor; ¶ [0054]: the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; ¶ [0104] with FIG. 2: the quantum phase information represents a phase angle which is an angular displacement between a current and voltage waveform measured in degrees or radians; the quantum phase information may be measure by qPMU in the power grid (e.g., qPMU 110) and encoded in single photon transmissions).
Claim 19
BUSH discloses all the elements as stated in Claim 18 and further discloses wherein the quantum computer systems are configured to compute the state estimates (BUSH, BUSH, ¶¶ [0007]-[0011]: each qPMU includes: a processor configured to compute a quantum signal based on quantum computing phase estimation and a network interface configured to transmit the quantum signal; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; computing a quantum signal based on quantum computing phase estimation, and processing the measured quantum signals into measurement data based on quantum clock synchronization protocols; ¶¶ [0039]-[0041]: the optimal placement including determination of where to deploy a mix of classical and entanglement-based PMUs (ePMU) and which ePMUs should be entangled with one another to maximize effectiveness while minimizing load on the quantum network may be provided using quantum computing; the placement and coordination of ePMUs placement are optimized by a quantum computing or a quantum annealing hardware to minimize the number of PMUs required (assuming a mix of classical and quantum PMUs), overhead of the quantum network (minimizes the amount of entanglement, and the number of multipartite entanglements), and maximize the cybersecurity of the power grid; ¶¶ [0046]-[0055] with FIG. 2: perform phasor measurement in a quantum format using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, quantum time transport, etc.); the qPMU 110 may compute a quantum signal based on quantum computing phase estimation; the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when phases are not synchronized over the quantum network; the quantum signals may represent quantum states which electrical power current and voltage phasor information are encoded; the qPMU 110 may use a reference clock such as an atomic clock so that it can provide more accuracy, precision, resolution, and stability; the quantum signals may be provided in real time; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; the quantum state outputs from qPMU s 110 are interconnected in the quantum network and the quantum network helps implement entanglement-based algorithms that fuse the outputs from qPMUs 110 into a global result; therefore, quantum computing would not suffer from delay in measurement at each qPMU 110, classical transport, and aggregation over the network and loading into the quantum network; ¶ [0068] with FIG. 2: the optimal voltage value is calculated using optimal power flow calculation or by other means, such as a decentralized control algorithm; or the optimal voltage may be sent to a quantum computer (not shown in FIG. 2) then processed by a quantum computer which communicates with the monitoring module 150 to get the result faster; ¶¶ [0071]-[0075] with FIG. 3: the qPMU 110 includes a sensing module 200, a detector 210, a processor(s) 220, a memory 230, and a network interface 240; the processor(s) 210 may compute the quantum signal based on quantum computing phase estimation; the quantum signal is computed based on spin Qubits or entangled photons according to the quantum sensing; the quantum computing phase estimation is, but not limited to, being performed by executing a quantum Fourier transformation (QFT) algorithm; perform the quantum computing phase estimation to measure the quantum signal, such as phase, power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use a reference clock such as an atomic clock or GPS (Global positioning System) based clock; the quantum signals may represent quantum states of entangled electrical devices in a quantum network; ¶¶ [0083]-[0088] with FIG. 5: compute a quantum signal based on quantum computing phase estimation (411); the quantum computing phase estimation may be used to measure phase or power phase angle; the quantum computing phase estimation may be used to align clock phases when the clock phases are not synchronized over the quantum network; use an atomic clock as the reference clock; the quantum signal is computed based on spin Qubits or entangled photons transmitted via the quantum network; support quantum communication using quantum technologies (e.g., quantum sensing, quantum network, quantum computing, etc.)).
BUSH fails to explicitly disclose to compute the state estimates using quantum tomography.
Dong teaches a system and a method using quantum technology (Dong, Section I in Page 190), wherein compute the state estimates using quantum tomography (Dong, Abstract in Page 190: quantum state tomography via linear regression estimation and adaptive quantum state estimation are introduced and a Hamiltonian identification algorithm is outlined; two quantum robust control approaches including sliding mode control and sampling-based learning control are illustrated; Section I in Page 190: a fundamental task in quantum technology is to characterize the state of a quantum system and identify the parameters in the system; the estimation procedure of a static quantum state is often referred as quantum state tomography; for estimating a dynamical state, quantum filtering theory has been developed, which is especially useful for addressing the measurement-based quantum feedback control problem; the area of identifying key parameters in quantum systems can be referred as quantum system identification; another important problem is robustness of quantum systems in developing practical quantum technology since real quantum systems are often subject to noises, incomplete knowledge or uncertainties; in this paper, we introduce some recent developments in the areas of estimation and robust control of quantum systems; we present several examples and methods that were recently developed by the authors and their collaborators, and aim to illustrate; several classes of significant quantum estimation and control problems as well as outline open questions for future research; Section II with FIG. 1 in Pages 190-192: quantum state tomography provides a framework to reconstruct quantum states; to estimate a quantum state, we usually need to make measurements on many copies of the state; for a given unknown quantum state, we need to design POVM measurement and develop an estimation algorithm to reconstruct the quantum state from measurement data; various quantum state tomography methods have been developed such as maximum likelihood estimation (MLE) method, Bayesian mean estimation approach and linear regression estimation (LRE); an advantage of LRE for quantum state tomography is that its computational complexity can be characterized and the theoretical error upper bound may be obtained; another advantage of LRE is that it is suitable for developing adaptive quantum state estimation method; adaptive protocols have been proven to have the capability to improve the quantum estimation precision; in adaptive state estimation as shown in Figure 1, we first make measurements on part of copies and get a rough estimate of the quantum state; then we find optimal measurement bases to make measurements on some other copies; using (6) and (7), one can recursively incorporate new measurement data into historical measurement data, which provides a convenient way for adaptive estimation of ρ; in this sense, the LRE method is more suitable for adaptive reconstruction of quantum states due to its recursive procedure than traditional MLE or Bayesian mean method; in the LRE framework, instead of repeatedly calculating all the historical data when new data arrive, we only need to add the new data into historical information matrix and vector, which significantly reduces the calculation cost; based on the observation, an adaptive quantum state tomography protocol has been developed in [14]; in the first stage, one performs a standard LRE on N1 copies with the standard cube measurement bases to obtain a preliminary
Θ
^
and Q; in the second stage, the initial values of Q in (6) and
Θ
^
in (7) are set as Q0 = Q and
Θ
^
0
=
Θ
^
, and then the remaining N −N1 copies are utilized for multi-step adaptive estimation; the adaptive quantum state tomography can improve the estimation precision; the efficiency of the estimation algorithms may be further enhanced if there is prior knowledge on the quantum state to be reconstructed; various variants of LRE could be developed for quantum state tomography and different adaptivity criteria can be explored for adaptive estimation of quantum states; Section III in Pages 192-193: a quantum process ε maps an input state ρin to an output state ρout; we can obtain the full characterization of ε by reconstructing X; a central issue in quantum process tomography is to design an algorithm to find a physical estimation
X
^
such that Bvec(
X
^
) is close enough to vec(
Λ
^
); for a closed quantum system, its evolution can be described by (11) and H is the system Hamiltonian; a Hamiltonian identification method using measurement time traces has been proposed based on classical system identification theory and it has also been used to experimentally identify the Hamiltonian in spin systems; dynamical decoupling was employed for identifying parameters in the Hamiltonian; adaptive approaches were only applied to the identification problems of several simple quantum systems such as estimating the Hamiltonian parameter of a two-level system and more adaptive algorithms could be developed to enhance the identification precision for quantum systems).
BUSH and Dong are analogous art because they are from the same field of endeavor, a system and a method using quantum technology. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to apply the teaching of Dong to BUSH. Motivation for doing so would improve.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bordow et al. (US 2025/0035676 A1, filed on 12/14/2022) discloses in ABSTARCT that (1) detecting a level of current in a conductor such as a power line can be accomplished using sensing devices that are coupled to the line; (2) such devices can have a clamshell or briefcase-style shape and close about the line; (3) the line passes through a channel between the sides of the device; (4) a quantum substance made of a material having a phonon decay sideband is arranged nearby the channel, and a light source and a scanning source work in tandem to cause the
substance to emit light that can be analyzed to determine a magnitude of a magnetic field on the substance; and (5) by distributing such sensing devices about a grid or other electrical distribution network, current throughout the network can be collected and analyzed to ascertain the presence and location of interferences with the grid.
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/HWEI-MIN LU/Primary Examiner, Art Unit 2142
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