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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/26/2023 was filed before the mailing date of the first office action. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101. Claims 1-18 are directed to a method, claim 19 is directed to a non-transitory computer-readable medium, and claim 20 is directed to a system; therefore, claims 1-20 fall within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter). However, claims 1-20 fall within the judicial exception of an abstract idea, specifically the abstract ideas of “Mental Processes” (including observation, evaluation, and opinion) and “Mathematical Concepts (including mathematical calculations and relationships)”.
Claim 1:
Claim 1 is directed to a method; therefore, the claim does fall within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter).
Claim 1 recites the following abstract ideas:
determining. . . a proposed network compute cloud configuration for a hybrid quantum-classical telecommunications network supported by a plurality of cloud environments (mental step directed to observation, evaluation – a person could determine a proposed network cloud configuration in their mind for an observed hybrid quantum classical telecommunications network comprising a plurality of cloud environments);
determining . . . a protocol that is required to implement the proposed network compute cloud configuration, based on a topology of the hybrid quantum-classical telecommunications network (mental step directed to observation, evaluation – a person could determine a protocol in their mind to implement an observed or mentally determined proposed network configuration based on observed network topology data).
Claim 1 recites the following additional elements:
a processing system including at least one processor and delegating, by the processing system, a quantum function of the proposed network compute cloud configuration among the plurality of cloud environments, using the protocol. These limitations are interpreted as generic computer components used to merely apply the claimed abstract ideas and transmitting information comprising a command over a network, which does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea (see MPEP 2106.05(d)(II) and MPEP 2106.05(f)).
Claim 19 is a non-transitory computer-readable medium claim and its limitation is included in claim 1. The only difference is that claim 19 requires a non-transitory computer-readable medium, which is interpreted as a generic computer component used to merely apply the abstract ideas as described in the rejection of claim 1 (see MPEP 2106.05(f)). Therefore, claim 19 is rejected for the same reasons as claim 1.
Claim 20 is a system claim and its limitation is included in claim 1. The only difference is that claim 20 requires a system, which is interpreted as a generic computer component used to merely apply the abstract ideas as described in the rejection of claim 1 (see MPEP 2106.05(f)). Therefore, claim 20 is rejected for the same reasons as claim 1.
The independent claims are not patent eligible.
Dependent claims 2-18 when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea, as they recite further embellishment of the judicial exception.
Claim 2 recites wherein the processing system is part of a quantum-classical compute cloud network optimizer. This limitation is interpreted as an additional element further describing the technological environment comprising the computer components used to merely apply the claimed abstract ideas, which does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea (see MPEP 2106.05(d) and MPEP 2106.05(h)).
Claim 3 recites wherein the quantum-classical compute cloud network optimizer includes a distributed quantum-classical blockchain database and a quantum federated reinforcement learning agent. This limitation is interpreted as an additional element further describing the technological environment comprising the computer components used to merely apply the claimed abstract ideas, which does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea (see MPEP 2106.05(d) and MPEP 2106.05(h)).
Claim 4 recites wherein the distributed quantum-classical blockchain database stores network data for the hybrid quantum-classical telecommunications network. This limitation is interpreted as an additional element further describing the technological environment in which the claimed abstract ideas are performed and as storing data in memory, which do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea (see MPEP 2106.05(d)(II) and MPEP 2106.05(h)).
Claim 5 recites wherein the quantum federated reinforcement learning agent takes as an input at least one of: a traffic demand in the hybrid quantum-classical telecommunications network, locations of the plurality of cloud environments, a latency requirement of the hybrid quantum-classical telecommunications network, or a cost of the proposed network compute cloud configuration and generates as an output a delegation of the quantum function. Taking at least a traffic demand as input and outputting a delegation are interpreted as additional elements further describing the technological environment in which the claimed abstract ideas are performed and as receiving and transmitting data over a network, which do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea (see MPEP 2106.05(d)(II) and MPEP 2106.05(h)).
Claim 6 recites wherein the plurality of cloud environments includes at least one external cloud network and at least one internal cloud network. This limitation is interpreted as an additional element further describing the technological environment comprising the computer components used to merely apply the claimed abstract ideas, which does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea (see MPEP 2106.05(d) and MPEP 2106.05(h)).
Claim 7 recites wherein the protocol is determined based on an end-to-end connectivity between nodes of the hybrid quantum-classical telecommunications network. Determining a protocol based on an end-to-end connectivity is interpreted as a mental step directed to observation, evaluation – a person could determine a protocol in their mind based on observed end-to-end connectivity data between nodes of a network.
Claim 8 recites wherein the end-to-end connectivity comprises classical online communication-quantum offline communication. This limitation is interpreted as a further description of the kind of data observed in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 9 recites wherein the protocol comprises a prepare and send universal blind quantum computation protocol. This limitation is interpreted as a further description of the kind of protocol determined in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 10 recites wherein the end-to-end connectivity comprises classical online communication-quantum online communication. This limitation is interpreted as a further description of the kind of data observed in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 11 recites wherein the protocol comprises a measurement only-universal blind quantum computation protocol. This limitation is interpreted as a further description of the kind of protocol determined in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 12 recites wherein the end-to-end connectivity comprises classical offline communication-quantum offline communication. This limitation is interpreted as a further description of the kind of data observed in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 13 recites wherein the protocol comprises a pseudo-secret random qubit generator protocol. This limitation is interpreted as a further description of the kind of protocol determined in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 14 recites wherein the end-to-end connectivity comprises classical online communication-no quantum communication. This limitation is interpreted as a further description of the kind of data observed in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 15 recites wherein the protocol comprises a prepare and send fully homomorphic encryption protocol. This limitation is interpreted as a further description of the kind of protocol determined in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 16 recites wherein the end-to-end connectivity comprises classical offline communication-no quantum communication. This limitation is interpreted as a further description of the kind of data observed in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 17 recites wherein the protocol comprises a classical fully homomorphic encryption for quantum circuits protocol. This limitation is interpreted as a further description of the kind of protocol determined in the mental step as described in the rejection of claim 7 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Claim 18 recites wherein the quantum function comprises at least one of: a quantum computation, quantum federated reinforcement learning, a quantum virtualized network function, or a quantum containerized network function. This limitation is interpreted as a further description of the information delegated, or transmitted over a network as described in the rejection of claim 1 and does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
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.
Claims 1-6 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al (“Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet”, herein Xu) in view of Smith et al (US 11477015 B1, herein Smith).
Regarding claim 1, Xu teaches a method comprising: determining, by a processing system including at least one processor, a proposed network compute cloud configuration for a hybrid quantum-classical telecommunications network [supported by a plurality of cloud environments] (pg. 143 left column para. 2 recites “we propose a stochastic QKD resource (i.e., wavelength) allocation model to optimize the QKD deployment cost of the Quantum Internet. To protect FEL models and public keys from eavesdropping attacks, we propose a hierarchical architecture for quantum-secured FEL systems that includes the FEL layer, the control and management layer, and the QKD infrastructure layer. To handle the dynamics of security demands from the FEL layer, we model the QKD resource allocation of QKD managers and QKD controllers in the control and management layer as a stochastic programming model that allocates QKD resources from the QKD infrastructure layer to cluster heads in the FEL layer” (i.e., a method of determining a network cloud configuration for a hybrid quantum-classical system));
determining, by the processing system, a protocol that is required to implement the proposed network compute cloud configuration, based on a topology of the hybrid quantum-classical telecommunications network (pg. 145 left column para. 2 recites “each QKD manager first queries the secret-key status and then sends configurations to QKD controllers via the simple network management protocol (SNMP). According to the received instructions, QKD controllers handshake with QKD nodes for detailed configurations. In the QKD infrastructure layer, there are three types of nodes (i.e., QKD nodes, trusted relays, and untrusted relays) and two types of links (i.e., key management (KM) and QKD links). We consider that the FEL nodes are co-located with the QKD nodes and that different types of links can be multiplexed within a single fiber. Therefore, the topology of the QKD layer follows that of the FEL layer, which can be denoted by G(V, E). Here, V represents the set of FEL/QKD nodes, and E denotes the collection of fiber connections” (i.e., determining a protocol to implement the network configuration based on a network topology));
and delegating, by the processing system, a quantum function of the proposed network compute cloud configuration [among the plurality of cloud environments], using the protocol (pg. 143 right column para. 3 recites “we propose a learning-based QKD resource allocation scheme for quantum-secured FEL systems, which is strengthened by federated reinforcement learning. In particular, we use the model-free off-policy soft actor-critic (SAC) structure to learn the optimal QKD resource allocation strategy. For each QKD manager and each controller, a policy network is adopted to configure the QKD nodes by learning the allocation strategy during the interaction with quantum-secured FEL systems. Moreover, a Q-network is adopted as a critic of each QKD manager and controller to evaluate the state-action values of its local policy, i.e., the performance of the local policy” (i.e., delegating a quantum function based on the network protocol)).
However, while Xu teaches delegating quantum functions in a network cloud configuration, Xu does not explicitly teach a plurality of cloud environments.
Smith teaches a plurality of cloud environments (col. 3 lines 29-36 recite “an account node may have access to a cloud-based QPU system or other quantum computing resource that can run quantum algorithms remotely from the access node. Accordingly, the example account nodes 11A, 11B can be implemented using entirely "classical" computing hardware, or the example account nodes 11A, 11B may include some quantum computing hardware”. Col. 7 line 59 – col. 8 line 10 recite “The example computing environment 101 can provide services to the access nodes 110, for example, as a cloud-based or remote-accessed computer, as a distributed computing resource, as a supercomputer or another type of high-performance computing resource, or in another manner. As shown in FIG. 2, to access computing resources of the computing environment 101, the access nodes 110 send programs 112 to the server 108 and in response, the access nodes 110 receive data 114 from the server 108. The access nodes 110 may access services of the computing environment 101 in another manner, and the server 108 or other components of the computing environment 101 may expose computing resources in another manner. Any of the access nodes 110 can operate local to, or remote from, the server 108 or other components of the computing environment 101. In the example shown in FIG. 2, the access node 110A has a local data connection to the server 108 and communicates directly with the server 108 through the local data connection” (i.e., a plurality of cloud environment configurations)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine these teachings by adapting the cloud network configuration optimization and delegation method from Xu to operate across the distributed cloud configurations in Smith. Smith and Xu are both directed to methods of operating hybrid quantum-classical systems in a cloud environment. One of ordinary skill in the art would recognize that the network configuration optimization methods from Xu could be extended to distributed cloud environment nodes like those taught by Smith.
Regarding claim 2, the combination of Xu and Smith teaches the method of claim 1, wherein the processing system is part of a quantum-classical compute cloud network optimizer (Xu pg. 148 left column para. 4 recites “we first formulate the QKD resource allocation problem as a deterministic linear programming model. Furthermore, considering the uncertainty, i.e., the required secret-key rates, in quantum-secured FEL systems, we develop a stochastic programming model for QKD resource allocation. In the resource allocation model, the management signals are usually brief and can be encoded as quantum information and transmitted in QKD links, and thus the data transmission is secured by quantum cryptography” (i.e., a quantum-classical network optimization system)).
Regarding claim 3, the combination of Xu and Smith teaches the method of claim 2, wherein the quantum-classical compute cloud network optimizer includes a distributed quantum-classical blockchain database (Smith col. 2 lines 60-65 recite “Blockchains maintained by the example blockchain system shown in FIG. 1 encode information in quantum states. For example, a blockchain may include a quantum state (e.g., a Quantum Rotation Ledger, QRL), and perform operations on the quantum state according to the techniques and rules described herein”. Smith col. 8 lines 36-39 recite “the server 108 includes a personal computing device, a computer cluster, one or more servers, databases, networks, or other types of classical or quantum computing equipment” (i.e., a quantum-classical blockchain database)) and a quantum federated reinforcement learning agent (Xu pg. 143 right column para. 3 recites “we propose a learning-based QKD resource allocation scheme for quantum-secured FEL (i.e., federated edge learning) systems, which is strengthened by federated reinforcement learning. Q-network is adopted as a critic of each QKD manager and controller to evaluate the state-action values of its local policy, i.e., the performance of the local policy. To avoid direct reward sharing, QKD managers encrypt the Q-networks and then share them with QKD controllers for their local policy evaluation and improvement. In this way, the incomplete experience issues of QKD controllers can be addressed, thus improving the training efficiency of agents in the control and management layer. In addition, to further improve convergence efficiency, the local policy of QKD controllers is aggregated as the global QKD resource allocation policy for QKD managers after improving the local policies of QKD controllers” (i.e., a quantum federated reinforcement learning agent)).
Regarding claim 4, the combination of Xu and Smith teaches the method of claim 3, wherein the distributed quantum-classical blockchain database stores network data for the hybrid quantum-classical telecommunications network (Smith col. 2 lines 60-65 recite “Blockchains maintained by the example blockchain system shown in FIG. 1 encode information in quantum states. For example, a blockchain may include a quantum state (e.g., a Quantum Rotation Ledger, QRL), and perform operations on the quantum state according to the techniques and rules described herein”. Smith col. 8 lines 36-39 recite “the server 108 includes a personal computing device, a computer cluster, one or more servers, databases, networks, or other types of classical or quantum computing equipment” (i.e., a quantum-classical blockchain database storing data related to the hybrid quantum-classical network)).
Regarding claim 5, the combination of Xu and Smith teaches the method of claim 3, wherein the quantum federated reinforcement learning agent takes as an input at least one of: a traffic demand in the hybrid quantum-classical telecommunications network, locations of the plurality of cloud environments, a latency requirement of the hybrid quantum-classical telecommunications network, or a cost of the proposed network compute cloud configuration and generates as an output a delegation of the quantum function (Xu pg. 143 left column para. 2 recites “we propose a stochastic QKD resource (i.e., wavelength) allocation model to optimize the QKD deployment cost of the Quantum Internet. To protect FEL models and public keys from eavesdropping attacks, we propose a hierarchical architecture for quantum-secured FEL systems that includes the FEL layer, the control and management layer, and the QKD infrastructure layer. To handle the dynamics of security demands from the FEL layer, we model the QKD resource allocation of QKD managers and QKD controllers in the control and management layer as a stochastic programming model that allocates QKD resources from the QKD infrastructure layer to cluster heads in the FEL layer” (i.e., using the potential cost of the network configuration to determine how to delegate the quantum functions)).
Regarding claim 6, the combination of Xu and Smith teaches the method of claim 1, wherein the plurality of cloud environments includes at least one external cloud network and at least one internal cloud network (Smith col. 3 lines 29-32 recite “an account node may have access to a cloud-based QPU system or other quantum computing resource that can run quantum algorithms remotely from the access node”. Smith col. 9 lines 59-63 recite “The example computing environment 101 can provide services to the access nodes 110, for example, as a cloud-based or remote-accessed computer, as a distributed computing resource, as a supercomputer or another type of high-performance computing resource, or in another manner” (i.e., at least one internal and one external aspect of a cloud network)).
Regarding claim 18, the combination of Xu and Smith teaches the method of claim 1, wherein the quantum function comprises at least one of: a quantum computation, quantum federated reinforcement learning, a quantum virtualized network function, or a quantum containerized network function (Xu pg. 143 right column para. 3 recites “we propose a learning-based QKD resource allocation scheme for quantum-secured FEL (i.e., federated edge learning) systems, which is strengthened by federated reinforcement learning. Q-network is adopted as a critic of each QKD manager and controller to evaluate the state-action values of its local policy, i.e., the performance of the local policy. To avoid direct reward sharing, QKD managers encrypt the Q-networks and then share them with QKD controllers for their local policy evaluation and improvement. In this way, the incomplete experience issues of QKD controllers can be addressed, thus improving the training efficiency of agents in the control and management layer. In addition, to further improve convergence efficiency, the local policy of QKD controllers is aggregated as the global QKD resource allocation policy for QKD managers after improving the local policies of QKD controllers” (i.e., a quantum federated reinforcement learning function)).
Claim 19 is a non-transitory computer-readable medium claim and its limitation is included in claim 1. The only difference is that claim 19 requires a non-transitory computer-readable medium (Smith col. 20 lines 64-67 recite “Some of the operations described in this specification can 65 be implemented as operations performed by a data processing apparatus on data stored on one or more computer-readable storage devices or received from other sources”). Therefore, claim 19 is rejected for the same reasons as claim 1.
Claim 20 is a system claim and its limitation is included in claim 1. The only difference is that claim 20 requires a system (Smith col. 20 lines 64-67 recite “Some of the operations described in this specification can 65 be implemented as operations performed by a data processing apparatus on data stored on one or more computer-readable storage devices or received from other sources”). Therefore, claim 20 is rejected for the same reasons as claim 1.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Xu et al (“Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet”, herein Xu) in view of Smith et al (US 11477015 B1, herein Smith), in further view of Randriamasy (US 20140254382 A1, herein Randriamasy).
Regarding claim 7, the combination of Xu and Smith teaches the method of claim 1, wherein the protocol is determined based on [an end-to-end connectivity between] nodes of the hybrid quantum-classical telecommunications network (Smith col. 2 lines 20-29 recite “FIG. 1 is a schematic diagram of an example blockchain system 10. The example blockchain system 10 includes account nodes 11A, 11B ( open circles), miner nodes 13 (filled circles) and an administrator node 15 (square). The blockchain system 10 includes a peer-to-peer network 12 formed by peer-to-peer connections 14 between respective pairs of the miner nodes 13. The account nodes 11A, 11B and the administrator node 15 may also be part of the peer-to-peer network 12, or they may communicate with the miner nodes 13 using another communication protocol”. Smith col. 9 lines 32-39 recite “all or part of the computing environment 101 operates as a hybrid computing environment, and the server 108 operates as a host system for the hybrid environment. For example, the programs 112 can be formatted as hybrid computing programs, which include instructions for execution by one or more quantum processor units and instructions that can be executed by another type of computing resource” (i.e., a communication protocol determined for nodes of a hybrid classical-quantum network)).
However, the combination of Smith and Xu does not explicitly teach a protocol based on an end-to-end connectivity of a telecommunications network.
Randriamasy teaches a protocol based on an end-to-end connectivity of a telecommunications network (para. [0007] recites “a method for optimization of IP traffic between a User Equipment having access to an IP network via an IP Connectivity Access Network, and an IP connection endpoint in said IP network, for an application allowing a choice in said IP connection endpoint, said method comprising at least one step based on a selection of an IP connection endpoint according to end-to-end IP traffic optimization criteria” (i.e., a method for optimizing a network protocol based on end-to-end connectivity between endpoints, or nodes)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine these teachings by modifying the communication protocol from Xu (as modified by Smith) with the end-to-end connectivity network traffic optimization method from Randriamasy. Xu and Randriamasy are both directed to network configuration systems, and one of ordinary skill in the art would be motivated to include the end-to-end optimization method from Randriamasy in Xu’s network configuration optimization method to optimize the connection between nodes in the hybrid quantum-classical network configuration.
Claims 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al (“Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet”, herein Xu) in view of Smith et al (US 11477015 B1, herein Smith), in further view of Randriamasy (US 20140254382 A1, herein Randriamasy), in further view of Quantum Protocol Zoo (“Prepare-and-Send Universal Blind Quantum Computation”, herein QPZ Prepare-and-Send).
Regarding claim 8, the combination of Xu, Smith, and Randriamasy teaches the method of claim 7.
However, the combination of Xu, Smith, and Randriamasy does not explicitly teach wherein the end-to-end connectivity comprises classical online communication-quantum offline communication.
QPZ Prepare and Send teaches wherein the end-to-end connectivity comprises classical online communication-quantum offline communication (QPZ Prepare-and-Send para. 1 recites “The example protocol achieves the functionality of Secure Client-Server Delegated Quantum Computation by assigning quantum computation to an untrusted device while maintaining privacy of the input, output and computation of the client. The client requires to be able to prepare and send quantum states while the server requires to possess a device with quantum memory, measurement and entanglement generation technology. Following description deals with a method which involves quantum offline and classical online communication, called Blind Quantum Computation. It means the protocol needs one-time quantum communication at the end or starting of the protocol while continuous classical communication between the parties, throughout the execution” (i.e., classical online-quantum offline communication connectivity))
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine these teachings by modifying the network configuration protocol from Xu (as modified by Smith and Randriamasy) with the prepare-and-send protocol from QPZ Prepare-and-Send. Xu and QPZ Prepare-and-Send teach methods of network node communication in a hybrid quantum-classical environment. One of ordinary skill in the art would be motivated to adapt the protocol from Xu to include the quantum offline and classical online communication protocol from QPZ Prepare-and-Send to further secure the communication between potentially untrusted network nodes.
Regarding claim 9, the combination of Xu, Smith, Randriamasy, and QPZ Prepare-and-Send teaches the method of claim 8, wherein the protocol comprises a prepare and send universal blind quantum computation protocol (QPZ Prepare-and-Send para. 1 recites “The example protocol achieves the functionality of Secure Client-Server Delegated Quantum Computation by assigning quantum computation to an untrusted device while maintaining privacy of the input, output and computation of the client. The client requires to be able to prepare and send quantum states while the server requires to possess a device with quantum memory, measurement and entanglement generation technology. Following description deals with a method which involves quantum offline and classical online communication, called Blind Quantum Computation. It means the protocol needs one-time quantum communication at the end or starting of the protocol while continuous classical communication between the parties, throughout the execution” (i.e., a prepare and send universal blind quantum computation protocol)).
Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al (“Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet”, herein Xu) in view of Smith et al (US 11477015 B1, herein Smith), in further view of Randriamasy (US 20140254382 A1, herein Randriamasy), in further view of Quantum Protocol Zoo (“Measurement-Only Universal Blind Quantum Computation”, herein QPZ Measurement Only).
Regarding claim 10, the combination of Xu, Smith, and Randriamasy teaches the method of claim 7.
However, the combination of Xu, Smith, and Randriamasy does not explicitly teach wherein the end-to-end connectivity comprises classical online communication-quantum online communication.
QPZ Measurement Only teaches wherein the end-to-end connectivity comprises classical online communication-quantum online communication (QPZ Measurement Only pg. para. 1 recites “The example protocol achieves the functionality of Secure Client-Server Delegated Computation by assigning quantum computation to an untrusted device while maintaining privacy of the input, output and computation of the client. The client requires to be able to prepare and send quantum states while the server requires to possess a device with quantum memory, measurement and entanglement generation technology. Following description deals with a method which involves quantum online and classical online communication, called Blind Quantum Computation” (i.e., classical online-quantum online communication connectivity)).
Regarding claim 11, the combination of Xu, Smith, Randriamasy, and QPZ Measurement Only teaches the method of claim 10, wherein the protocol comprises a measurement only-universal blind quantum computation protocol (QPZ Measurement Only pg. 2 para. 1 recites “The following Universal Blind Quantum Computation (UBQC) protocol uses the unique feature of Measurement Based Quantum Computation (MBQC) that separates the classical and quantum parts of a computation” (i.e., a measurement only universal blind quantum computation protocol)).
Claims 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al (“Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet”, herein Xu) in view of Smith et al (US 11477015 B1, herein Smith), in further view of Randriamasy (US 20140254382 A1, herein Randriamasy), in further view of Quantum Protocol Zoo (“Pseudo-Secret Random Qubit Generator”, herein QPZ PSQRG).
Regarding claim 12, the combination of Xu, Smith, and Randriamasy teaches the method of claim 7.
However, the combination of Xu, Smith, and Randriamasy does not explicitly wherein the end-to-end connectivity comprises classical offline communication-quantum offline communication.
QPZ PSQRG teaches wherein the end-to-end connectivity comprises classical offline communication-no quantum communication (QPZ PSQRG para. 1 recites “The example protocol enables fully-classical parties to generate secret single qubit states using only public classical channels and a single quantum Server. An application of this functionality could be to carry out Delegated Quantum Computation by just classical online communication (classical communication throughout the protocol) and no quantum communication. This functionality could be used to replace a quantum channel completely such that a classical Client can perform various quantum applications over classical network connected to a quantum Server” (i.e., classical offline-no quantum communication connectivity)).
See claim 8 for motivation to combine.
Regarding claim 13, the combination of Xu, Smith, Randriamasy, and QPZ PSQRG teaches the method of claim 12, wherein the protocol comprises a pseudo-secret random qubit generator protocol (QPZ PSQRG para. 1 recites “The example protocol enables fully-classical parties to generate secret single qubit states using only public classical channels and a single quantum Server. This functionality could be used to replace a quantum channel completely such that a classical Client can perform various quantum applications over classical network connected to a quantum Server. It allows a fully classical Client to instructs Server to generate random single qubit states such that Client has complete knowledge of the state of qubit prepared but Server does not” (i.e., a pseudo-secret random qubit generator protocol)).
Claims 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al (“Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet”, herein Xu) in view of Smith et al (US 11477015 B1, herein Smith), in further view of Randriamasy (US 20140254382 A1, herein Randriamasy), in further view of Quantum Protocol Zoo (“Prepare-and-Send Quantum Fully Homomorphic Encryption”, herein QPZ Prepare-and-Send FHE).
Regarding claim 14, the combination of Xu, Smith, and Randriamasy teaches the method of claim 7.
However, the combination of Xu, Smith, and Randriamasy does not explicitly teach wherein the end-to-end connectivity comprises classical online communication-quantum offline communication.
QPZ Prepare-and-Send FHE teaches wherein the end-to-end connectivity comprises classical offline communication-quantum offline communication (QPZ Prepare-and-Send FHE para. 1 recites “This example protocol achieves the functionality of Secure Client-Server Delegated Computation by a method which involves quantum offline and classical offline communication, called Quantum Fully Homomorphic Encryption (QFHE). Offline communication means there is exchange of information is not required throughout the protocol but only once at the start or end of the protocol. It allows the Client to encrypt quantum data in such a way that Server can carry out any arbitrary quantum computations on the encrypted data without having to interact with the encrypting party. It hides the output and input of the computation while Server is allowed to choose the unitary operation for required computation. Thus, the circuit is known to the Server while efforts can be made to hide it from the encrypting party i.e. Client. Based on the existence of classical Homomorphic Encryption (HE) scheme, it comes with properties of correctness, compactness and full homomorphism . QFHE can be used to keep the circuit private to the Server and hidden from the Client unlike UBQC where the circuit is private to the Client and hidden from the Server” (i.e., classical offline-quantum offline communication connectivity)).
See claim 8 for motivation to combine.
Regarding claim 15, the combination of Xu, Smith, Randriamasy, and QPZ FHE teaches the method of claim 14, wherein the protocol comprises a prepare and send fully homomorphic encryption protocol (QPZ Prepare-and-Send FHE pg. 1 para. 1 recites “This example protocol achieves the functionality of Secure Client-Server Delegated Computation by a method which involves quantum offline and classical offline communication, called Quantum Fully Homomorphic Encryption (QFHE). QPZ Prepare-and-Send FHE pg. 2 para. 1 recites “Homomorphic Encryption (HE) schemes can be divided into four stages: Key Generation generates keys for encryption, decryption, and evaluation of the circuit, Encryption encodes the input into a ciphertext using encryption key, Homomorphic Evaluation performs operations (implements the circuit) on the encrypted input using evaluation key and Decryption transforms result of the ciphertext to actual outcome of the circuit using decryption key. This protocol requires Client to prepare and send the quantum states to Server, hence the name, Prepare and Send QFHE” (i.e., a prepare-and-send fully homomorphic encryption protocol)).
Claims 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Xu et al (“Privacy-Preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet”, herein Xu) in view of Smith et al (US 11477015 B1, herein Smith), in further view of Randriamasy (US 20140254382 A1, herein Randriamasy), in further view of Quantum Protocol Zoo (“Classical Fully Homomorphic Encryption for Quantum Circuits” , herein QPZ FHE).
Regarding claim 16, the combination of Xu, Smith, and Randriamasy teaches the method of claim 7.
However, the combination of Xu, Smith, and Randriamasy does not explicitly teach wherein the end-to-end connectivity comprises classical offline communication-no quantum communication.
QPZ FHE teaches wherein the end-to-end connectivity comprises classical offline communication-no quantum communication (QPZ FHE para. 1 recites “The example protocol achieves the functionality of Delegated Quantum Computation by a method which involves fully classical offline and no quantum communication. It uses only classical Homomorphic Encryption (HE) scheme to evaluate quantum circuits for classical input/output. It allows a fully classical Client to hide her data such that Server can carry out any arbitrary quantum computation on the encrypted data without having any knowledge about Client’s inputs. It hides the output and input of the computation while Server is allowed to choose the unitary operation (any quantum gate) for required computation” (i.e., classical offline-no quantum communication connectivity)).
See claim 8 for motivation to combine.
Regarding claim 17, the combination of Xu, Smith, Randriamasy, and QPZ FHE teaches the method of claim 16, wherein the protocol comprises a classical fully homomorphic encryption for quantum circuits protocol (QPZ FHE para. 1 recites “The example protocol achieves the functionality of Delegated Quantum Computation by a method which involves fully classical offline and no quantum communication. It uses only classical Homomorphic Encryption (HE) scheme to evaluate quantum circuits for classical input/output. It allows a fully classical Client to hide her data such that Server can carry out any arbitrary quantum computation on the encrypted data without having any knowledge about Client’s inputs. It hides the output and input of the computation while Server is allowed to choose the unitary operation (any quantum gate) for required computation” (i.e., a classical fully homomorphic encryption protocol)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20220188686 A1 (Richardson et al) teaches a method for managing quantum computing resources, selecting a quantum computing resource for implementation of a task, and causing the quantum computing resource to run a quantum algorithm associated with the task.
US 20230229514 A1 (Pinho et al) teaches a method for optimizing a computation workflow by selecting, for each of a plurality of quantum computing nodes, a resource from the candidate resource allocation associated with that quantum computing node, and executing a respective quantum algorithm associated with that quantum computing node.
US 20220084085 A1 (Rigetti et al) teaches a method for dynamically partitioning and virtualizing a monolithic quantum-classical hybrid computing resource into multiple different and independently-saleable parcels of configurations of qubits and qubit-qubit links on one or more quantum processor units.
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/L.M.F./ Examiner, Art Unit 2147
/VIKER A LAMARDO/Supervisory Patent Examiner, Art Unit 2147