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 .
DETAILED ACTION
This action is responsive to the Application filed on 10/29/2024
Claims 1-10 are pending in this case. Claims 1 and 7 are independent claims.
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.
Claim(s) 1-10 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an
abstract idea without significantly more.
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (Step 1). If the claim does fall within one of the statutory categories, the second step in the analysis is to determine whether the claim is directed to a judicial exception (Step 2A). The Step 2A analysis is broken into two prongs. In the first prong (Step 2A, Prong 1), it is determined whether or not the claims recite a judicial exception (e.g., mathematical concepts, mental processes, certain methods of organizing human activity). If it is determined in Step 2A, Prong 1 that the claims recite a judicial exception, the analysis proceeds to the second prong (Step 2A, Prong 2), where it is determined whether or not the claims integrate the judicial exception into a practical application. If it is determined at step 2A, Prong 2 that the claims do not integrate the judicial exception into a practical application, the analysis proceeds to determining whether the claim is a patent-eligible application of the exception (Step 2B). If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim integrates the judicial exception into a practical application, or else amounts to significantly more than the abstract idea itself. Applicant is advised to consult the 2019 PEG for more details of the analysis.
Step 1 Analysis: Is the claim to a process, machine, manufacture or composition of matter? See MPEP § 2106.03.
Claims 1-6 are drawn to a apparatus and claims 7-10 are drawn to a method, therefore each of these claim groups falls under one of four categories of statutory subject matter (machine/products/apparatus, process/method, manufactures and compositions of matter; Step 1). Nonetheless, the claims are directed to a judicially recognized exception of an abstract idea without significant more (Step 2A, see below). Independent claims 1 and 7 are nonverbatim but similar in claim construction, hence share the same rationale that the claimed inventions are directed to non-statutory subject matter as follows:
Regarding claim 1:
Claim 1 recites: An electronic apparatus comprising:
an input interface; and
at least one processor configured to receive bit-format input data using the input interface,
convert input bits included in the input data to obtain input qubits,
encode the input qubits to obtain encoded qubits,
estimate quantum amplitude values of a predetermined number of the input qubits using a quantum neural network (QNN) based on the encoded qubits,
determine a probability value corresponding to the data based on the estimated quantum amplitude values, and
authenticate the input data by comparing the determined probability value with a predetermined authentication radius value
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Claim 1 is directed to an abstract idea, specifically a mental process performed in the human mind (including an observation, evaluation, judgment, opinion) and mathematical concept, a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number”. See MPEP § 2106.04(a)(2)(III) & MPEP § 2106.04(a)(2)(I)(C).
Independent claim 1 recites in part:
estimate quantum amplitude values of a predetermined number of the input qubits […]
The limitation above is broadly and reasonably interpreted as a mental process and mathematical concept. For example, a person (e.g., engineer , etc.) can manually apply matrices to the state vector through matrix multiplication and determine the resulting quantum state, whose coefficients represent the resulting quantum amplitude values. See MPEP § 2106.04(a)(2)(III) & MPEP § 2106.04(a)(2)(I)(C).
determine a probability value corresponding to the data based on the estimated quantum amplitude values
The limitation above is broadly and reasonably interpreted as a mental process and mathematical concept. Assessing or processes those values to arrive at another value , namely the probability. The limitation involves evaluating existing numerical information to determine a resulting probability value. See MPEP § 2106.04(a)(2)(III) & MPEP § 2106.04(a)(2)(I)(C).
authenticate the input data by comparing the determined probability value with a predetermined authentication radius value
The limitation above is broadly and reasonably interpreted as a mental process and mathematical concept. Such comparison and evaluation of information constitutes an observation, evaluation, judgement, or opinion that can practically be performed in the human mind. See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
Independent claim 1 recites in part:
“An electronic apparatus comprising:
an input interface”, an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP §§ 2106.04(d), 2106.05(f)(2).
“at least one processor configured to receive bit-format input data using the input interface”, recited at a high-level of generality (i.e., as a generic processor performing data gathering and mathematical calculations) such that they amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
“convert input bits included in the input data to obtain input qubits, encode the input qubits to obtain encoded qubits,” an additional element that amounts to adding insignificant extra-solution activity to the judicial exception (includes both pre-solution and post-solution activity). See MPEP §§ 2106.04(d), 2106.05(g).
“… using a quantum neural network (QNN) based on the encoded qubits”, amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “QNN” is used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
First, the additional elements directed to generally linking the use of a judicial exception to a particular technological environment or field of use are deemed insufficient to transform the judicial exception to a patentable invention because the claimed limitations generally link the judicial exception to the technology environment, see MPEP 2106.05(h). However, they are included below for the sake of completeness.
Second, the additional elements mere application of the abstract idea or mere instructions to implement an abstract idea on a computer are deemed insufficient to transform the judicial exception to a patentable invention because the limitations generally apply the use of a generic computer and/or process with the judicial exception. See MPEP 2106.05(f). However, they are included below for the sake of completeness.
Independent claim 1 recites in part:
“An electronic apparatus comprising:
an input interface”, an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP §§ 2106.04(d), 2106.05(f)(2).
“at least one processor configured to receive bit-format input data using the input interface”, recited at a high-level of generality (i.e., as a generic processor performing data gathering and mathematical calculations) such that they amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
“convert input bits included in the input data to obtain input qubits, encode the input qubits to obtain encoded qubits” an additional element that amounts to adding insignificant extra-solution activity to the judicial exception (includes both pre-solution and post-solution activity). See MPEP §§ 2106.04(d), 2106.05(g).
“… using a quantum neural network (QNN) based on the encoded qubits”, amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “QNN” is used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d).
Thus, considering the additional elements individually and in combination and the claims as a whole, the additional elements do not provide significantly more than the abstract idea. The claims are not eligible subject matter.
Therefore, in examining elements as recited by the limitations individually and as an ordered combination, as a whole the independent claim limitations do not recite what have the courts have identified as “significantly more”.
Regarding claim 7
Claim 7 recites: A method for controlling an electronic apparatus, the method comprising: receiving bit-format input data;
converting input bits included in the input data to obtain input qubits;
encoding the input qubits to obtain encoded qubits;
estimating quantum amplitude values of a predetermined number of the input qubits using a quantum neural network (QNN) based on the encoded qubits;
determining a probability value corresponding to the data based on the estimated quantum amplitude values; and
authenticating the input data by comparing the determined probability value with a predetermined authentication radius value
Step 2A Prong One Analysis: Does the claim recite an abstract idea, law of nature, or natural phenomenon? See MPEP § 2106.04(II)(A)(1).
Claim 7 is directed to an abstract idea, specifically a mental process performed in the human mind (including an observation, evaluation, judgment, opinion) and mathematical concept, a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number”. See MPEP § 2106.04(a)(2)(III) & MPEP § 2106.04(a)(2)(I)(C).
Independent claim 7 recites in part:
estimate quantum amplitude values of a predetermined number of the input qubits […]
The limitation above is broadly and reasonably interpreted as a mental process and mathematical concept. For example, a person (e.g., engineer , etc.) can manually apply matrices to the state vector through matrix multiplication and determine the resulting quantum state, whose coefficients represent the resulting quantum amplitude values. See MPEP § 2106.04(a)(2)(III) & MPEP § 2106.04(a)(2)(I)(C).
determine a probability value corresponding to the data based on the estimated quantum amplitude values
The limitation above is broadly and reasonably interpreted as a mental process and mathematical concept. Assessing or processes those values to arrive at another value , namely the probability. The limitation involves evaluating existing numerical information to determine a resulting probability value. See MPEP § 2106.04(a)(2)(III) & MPEP § 2106.04(a)(2)(I)(C).
authenticate the input data by comparing the determined probability value with a predetermined authentication radius value
The limitation above is broadly and reasonably interpreted as a mental process and mathematical concept. Such comparison and evaluation of information constitutes an observation, evaluation, judgement, or opinion that can practically be performed in the human mind. See MPEP § 2106.04(a)(2)(III).
Step 2A Prong Two Analysis: Does the claim recite additional elements that integrate the judicial exception into a practical application? See MPEP § 2106.04(d).
Independent claim 7 recites in part:
“A method for controlling an electronic apparatus, the method comprising: receiving bit-format input data”, an additional element that amounts to adding insignificant extra-solution activity to the judicial exception (includes pre-solution). See MPEP §§ 2106.04(d), 2106.05(g).
“converting input bits included in the input data to obtain input qubits;
encoding the input qubits to obtain encoded qubits,” an additional element that amounts to adding insignificant extra-solution activity to the judicial exception (includes both pre-solution and post-solution activity). See MPEP §§ 2106.04(d), 2106.05(g).
“… using a quantum neural network (QNN) based on the encoded qubits”, amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “QNN” is used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole.
Step 2B Analysis: Does the claim recite additional elements that amount to significantly more than the judicial exception? See MPEP § 2106.05.
First, the additional elements directed to generally linking the use of a judicial exception to a particular technological environment or field of use are deemed insufficient to transform the judicial exception to a patentable invention because the claimed limitations generally link the judicial exception to the technology environment, see MPEP 2106.05(h). However, they are included below for the sake of completeness.
Second, the additional elements mere application of the abstract idea or mere instructions to implement an abstract idea on a computer are deemed insufficient to transform the judicial exception to a patentable invention because the limitations generally apply the use of a generic computer and/or process with the judicial exception. See MPEP 2106.05(f). However, they are included below for the sake of completeness.
Independent claim 7 recites in part:
“A method for controlling an electronic apparatus, the method comprising: receiving bit-format input data”, an additional element that amounts to adding insignificant extra-solution activity to the judicial exception (includes pre-solution). See MPEP §§ 2106.04(d), 2106.05(g).
“converting input bits included in the input data to obtain input qubits;
encoding the input qubits to obtain encoded qubits,” an additional element that amounts to adding insignificant extra-solution activity to the judicial exception (includes both pre-solution and post-solution activity). See MPEP §§ 2106.04(d), 2106.05(g).
“… using a quantum neural network (QNN) based on the encoded qubits”, amounts to adding the words “apply it” (or an equivalent) with the judicial exception and reciting only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is unclear how the “QNN” is used nor the specification makes it clear how these actions are performed. Thus, these additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d).
Thus, considering the additional elements individually and in combination and the claims as a whole, the additional elements do not provide significantly more than the abstract idea. The claims are not eligible subject matter.
Therefore, in examining elements as recited by the limitations individually and as an ordered combination, as a whole the independent claim limitations do not recite what have the courts have identified as “significantly more”.
Furthermore, regarding dependent claims 2-6 which are dependent on claim 1 and claims 8-10 which are dependent on claim 7, the claims are directed to a judicial exception without significantly more as highlighted below in the claim limitations by evaluating the claim limitations under Step 2A and 2B:
Claim 2 is dependent on claim 1, and incorporates an additional element that generally links the use of the judicial exception to a particular technological environment or field of use. See MPEP §§ 2106.04(d), 2106.05(h).
Claim 3 is dependent on claim 2, and incorporates additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP §§ 2106.04(d), 2106.05(g).
Claims 4 and 9 are dependent on claims 2 and 7, and incorporates additional element that amounts to adding insignificant extra-solution activity to the judicial exception (e.g., post-solution activity). See MPEP §§ 2106.04(d), 2106.05(g).
Claim 5 is dependent on claim 4, and incorporates an additional element that generally links the use of the judicial exception to a particular technological environment or field of use. See MPEP §§ 2106.04(d), 2106.05(h).
Claim 6 and 10 are dependent on claim 2 and 7, and incorporates additional elements are recited in a manner that represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP § 2106.05(f) and § 2106.04(d).
Claim 8 is dependent on claim 7, and include additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP §§ 2106.04(d), 2106.05(g).
The dependent claims as analyzed above, do not recite limitations that integrated the judicial exception into a practical application. In addition, the claim limitations do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B).
Therefore, the claims do not recite any limitations, when considered individually or as a whole, that recite what the courts have identified as “significantly more”, see MPEP 2106.05; and therefore, as a whole the claims are not patent eligible.
As shown above, the dependent claims do not provide any additional elements that when considered individually or as an ordered combination, amount to significantly more than the abstract idea identified. Therefore, as a whole the dependent claims do not recite what the courts have identified as “significantly more” than the recited judicial exception.
Therefore, claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception and does not recite, when claim elements are examined individually and as a whole, elements that the courts have identified as “significantly more” than the recited judicial exception.
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 1-2 are rejected under 35 U.S.C. 103 as being unpatentable over Neven et al. (Pub No.: 20200169396 A1), hereinafter referred to as Neven, in view of Boothby et al. (Pub No.: 20200371974 A1), hereinafter referred to as Boothby and further in view of Sarkar et al. (Pub No.: 20160253486 A1), hereinafter referred to as Sarkar.
With respect to claim 1. Neven disclose:
Convert input bits included in the input data to obtain input qubits (In paragraph [0064], Neven suggests converting input bits included in input data to obtain input qubits by disclosing machine learning task data comprising a Boolean input {0,1} and preparing corresponding qubits such that each respective binary digit is represented by a corresponding qubit having a 0 or 1 computational basis state.)
Encode the input qubits to obtain encoded qubits (In paragraph [0064-0065], Neven discloses encoding the input qubits to obtain encoded qubits by preparing multiple input qubits in an initial quantum state that encodes the machine learning task data input. In particular, Neven teaches that one or more control devices encode the machine learning task data input into the initial quantum state of the multiple qubits by setting the z-direction of the respective qubits, wherein, for binary input data, the qubits corresponding to the binary digits are to respective 0 or 1 computational states.)
Estimate quantum amplitude values of a predetermined number of the input qubits using a quantum neural network (QNN) based on the encoded qubits (In paragraph [0055], Neven disclose encoding machine learning input into an initial quantum state of multiple qubits and subsequently processing the encoded quantum state using intermediate quantum neural network layers comprising quantum logic gates. In paragraph [0065], Neven discloses that the quantum neural network evolves the quantum state of the plurality of qubits, and calculations performed by the system depend upon the evolved quantum state of the multiple qubits and target qubit. Accordingly, under the broadest reasonable interpretation, and absent a more restrictive definition or particular amplitude-estimation procedure in the Specification, Nevens Qin processing of the encoded qubits to obtain and evaluate the resulting quantum-state information reasonably teaches estimating values representative of quantum amplitudes associated with the processed qubits.)
Determine a probability value corresponding to the data based on the estimated quantum amplitude values (In paragraph [0065], Neven discloses that the quantum neural network evolves the quantum state of the qubits, and the resulting calculations depend upon the evolved quantum state. In paragraph [0073], Neven discloses a target measure of a qubit evolved quantum state to generate an output corresponding to the machine learning task. )
With respect to claim 1, Boothby do not explicitly disclose:
An electronic apparatus comprising: an input interface
At least one processor configured to receive bit-format input data using the input interface
Authenticate the input data by comparing the determined probability value with a predetermined authentication radius value
However, it is known by Boothby to disclose:
An electronic apparatus comprising: an input interface (In paragraph [0050], Boothby discloses operating quantum processors 120 whereby input and output are performed (e.g., substantially simultaneously) by an I/O system comprising one or more input interfaces and one or more output interfaces.)
At least one processor configured to receive bit-format input data using the input interface (In paragraph [0047], Boothby discloses that the quantum processor includes multiple qubits and couplers connecting pairs of qubits. A quit control system controls the individual qubits through interfaces, while the coupler control system controls the coupling between qubits.)
Neven in view of Boothby analogous pieces of art both are directed to quantum computing systems that receive input data, represent or provide the input using qubit, process the qubits using a quantum processor, and generate an output resulting from the quantum processing. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Neven, with multiple qubits prepared in an initial quantum state encoding a machine learning task data input as taught by Neven, with a quantum processor executing a problem to generate a classical output state as taught by Boothby.
The motivation for doing so would have been to improve the accuracy and time in which the neural network can be trained and used at inference (See [0044] of Neven.)
With respect to claim 1, Neven and Boothby do not explicitly disclose:
Authenticate the input data by comparing the determined probability value with a predetermined authentication radius value
However, it is known by Sarkar to disclose:
Authenticate the input data by comparing the determined probability value with a predetermined authentication radius value (In paragraph [0038], Sarkar discloses authenticating input data by comparing a determined probability value with a predetermined authentication value. In particular, Sarkar determines a user probability value indicative of the likelihood that a requestor is an authorized user and compares the determined user probability value with a predefined application threshold value to determine whether the requestor is authenticated. In paragraph [0166], Sarkar discloses a determined probability value of 0.50 compared against a predefined threshold value of 0.40, resulting in successful authentication. )
Neven in view of Boothby and Sarkar analogous pieces of art both are directed to quantum computing systems that receive input data, represent or provide the input using qubit, process the qubits using a quantum processor, and generate an output resulting from the quantum processing. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Sarkar, to authenticate probability evaluation module as taught by Sarkar. The motivation for doing so would have been to improved authentication of a requestor (See [0014] of Sarkar.)
Regarding claim 2, Neven in view of Boothby and Sarkar disclose the elements of claim 1. In addition, Neven disclose:
The electronic apparatus as claimed in claim 1, wherein the at least one processor comprises: a state preparation module configured to superpose the input qubits to obtain superposed qubits, a diffusion module group configured to estimate the quantum amplitude values using the QNN based on the superposed qubits, and a measurement module configured to determine the probability value based on the estimated quantum amplitude values (In paragraph [0065], Neven discloses that the quantum neural network evolves the quantum state of the qubits, and the resulting calculations depend upon the evolved quantum state. In paragraph [0073], Neven discloses a target measure of a qubit evolved quantum state to generate an output corresponding to the machine learning task. )
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Neven in view of Boothby, Sarkar and further in view of Mckay et al. (Pub No.: 20200272929 A1), hereinafter referred to as Mckay.
Regarding claim 3, Neven in view of Boothby and Sarkar disclose elements of claim 2. Neven in view of Boothby and Sarkar do not explicitly disclose:
The electronic apparatus as claimed in claim 2, wherein the state preparation module is further configured to: receive a first plurality of qubits from among the input qubits, and distribute the received first plurality of qubits and a second plurality of qubits to have a predetermined distribution centered on an average of the first plurality of qubits and the second plurality of qubits
However, Mckay disclose the limitation (In paragraph [0038], Mackay discloses that the quantum computing device 10 further includes a first tunable frequency bus 18 configured to couple at least one of the first plurality of qubits 12 to a second qubit. In paragraph [0050], Mackay discloses that the quantum computing device further includes a first tunable frequency bus 36 configured to couple the first plurality of qubits 32 to the second qubit 34.)
Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, having the teaching of Neven in view of Boothby and Sarkar to include Mckay, with a first plurality of qubits having a first resonance frequency and a second qubit having a second resonance frequency as taught by Mckay. The motivation for doing so would have been to substantially reduce or eliminate frequency collision and crosstalk between the plurality of qubits (See [0046] of Mckay.)
Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Neven in view of Boothby, Sarkar and further in view of Burkot et al. (Pub No.: 20210287127 A1), hereinafter referred to as Burkot.
Regarding claim 4, Neven in view of Boothby and Sarkar disclose elements of claim 2. Neven in view of Boothby and Sarkar do not explicitly disclose:
The electronic apparatus as claimed in claim 2, wherein the diffusion module group comprises a predetermined number of diffusion modules, and wherein each diffusion module included in the predetermined number of diffusion modules is configured to output an estimated quantum amplitude value
However, Burkot disclose the limitation (In paragraph [0020], Burkot discloses conventional Grover operations: the qubits are initialized, Hadamard gates put them into superposition, an oracle operates on the qubits, and a Grover diffusion gate applies the Grover diffusion operator. In paragraph [0021], Burkot disclose providing a quantum circuit containing a plurality of Grover diffusion gates. Those gates can implement different diffusion operators, and selected diffusion operators can be applied after respective oracle calls. A diffusion operator can also be applied to more than one. The circuit then, measures the bits to generate the quantum-computing result.)
Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, having the teaching of Neven in view of Boothby and Sarkar to include Burkot, with a plurality of diffusion gates of the quantum circuit, a plurality of diffusion operators as taught by Burkot. The motivation for doing so would have been to optimize a measurement, such as a measurement of an ancillary qubit or other qubit (See [0043]] of Burkot.)
Regarding claim 5, Neven in view of Boothby, Sarkar and Burkot disclose elements of claim 4. In addition, Neven disclose:
The electronic apparatus as claimed in claim 4, wherein the diffusion module comprises at least one of a QNN module, an inverse state preparation module, a search operator module, and the state preparation module (In paragraph [0072], Neven discloses that one or more intermediate quantum neural network layers in this manner map the encoded data input to an evolved state of the target qubit.)
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Neven in view of Boothby, Sarkar and further in view of Woerner et al. (US Patent No. 10,810,665 B2), hereinafter referred to as Woerner.
Regarding claim 6, Neven in view of Boothby and Sarkar disclose elements of claim 2. Neven in view of Boothby and Sarkar do not explicitly disclose:
The electronic apparatus as claimed in claim 2, wherein the measurement module comprises an inverse quantum Fourier transform (IQFT) module configured to identify the probability value corresponding to the data by superposing the quantum amplitude values
However, Woerner disclose the limitation (In Cols. 6–7, lines 46-10, Woerner discloses determining a probability value by performing an inverse quantum Fourier transform as part of a quantum amplitude-estimation process. In particular, Woerner discloses placing a plurality of qubits into superposition, applying controlled powers of an amplitude-estimator Q, and subsequently applying an inverse quantum Fourier transform to the qubits. The resulting quantum state is measured to obtain a value y, which is mapped to an estimated amplitude/probability value ã=sin.sup.2 (yπ/M).
Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, having the teaching of Neven in view of Boothby and Sarkar to include Woerner, with probability value represents a probability of measuring a one state in the ancilla qubit as taught by Woerner. The motivation for doing so would have been to increase the quantum estimated value at risk approaches the classical value indicated by the vertical solid line (See (Col.15, lines 62-64) of Woerner. )
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Neven et al. (Pub No.: 20200169396 A1), hereinafter referred to as Neven, in view of Sarkar et al. (Pub No.: 20160253486 A1), hereinafter referred to as Sarkar.
With respect to claim 7. Neven disclose:
A method for controlling an electronic apparatus, the method comprising: receiving bit-format input data (In paragraph [0056], Neven disclose receiving bit-format input data, wherein receiving machine-learning task input data comprising a Boolean function {0,1}, and further discloses that the data input may comprise a binary string of length n having respective binary digits of zero or one. )
Converting input bits included in the input data to obtain input qubits (In paragraph [0064], Neven suggests converting input bits included in input data to obtain input qubits by disclosing machine learning task data comprising a Boolean input {0,1} and preparing corresponding qubits such that each respective binary digit is represented by a corresponding qubit having a 0 or 1 computational basis state.)
Encoding the input qubits to obtain encoded qubits (In paragraph [0064-0065], Neven discloses encoding the input qubits to obtain encoded qubits by preparing multiple input qubits in an initial quantum state that encodes the machine learning task data input. In particular, Neven teaches that one or more control devices encode the machine learning task data input into the initial quantum state of the multiple qubits by setting the z-direction of the respective qubits, wherein, for binary input data, the qubits corresponding to the binary digits are to respective 0 or 1 computational states.)
Estimating quantum amplitude values of a predetermined number of the input qubits using a quantum neural network (QNN) based on the encoded qubits (In paragraph [0055], Neven disclose encoding machine learning input into an initial quantum state of multiple qubits and subsequently processing the encoded quantum state using intermediate quantum neural network layers comprising quantum logic gates. In paragraph [0065], Neven discloses that the quantum neural network evolves the quantum state of the plurality of qubits, and calculations performed by the system depend upon the evolved quantum state of the multiple qubits and target qubit. Accordingly, under the broadest reasonable interpretation, and absent a more restrictive definition or particular amplitude-estimation procedure in the Specification, Nevens Qin processing of the encoded qubits to obtain and evaluate the resulting quantum-state information reasonably teaches estimating values representative of quantum amplitudes associated with the processed qubits.)
Determining a probability value corresponding to the data based on the estimated quantum amplitude values (In paragraph [0065], Neven discloses that the quantum neural network evolves the quantum state of the qubits, and the resulting calculations depend upon the evolved quantum state. In paragraph [0073], Neven discloses a target measure of a qubit evolved quantum state to generate an output corresponding to the machine learning task. )
With respect to claim 7, Neven do not explicitly disclose:
Authenticate the input data by comparing the determined probability value with a predetermined authentication radius value
However, it is known by Sarkar to disclose:
Authenticate the input data by comparing the determined probability value with a predetermined authentication radius value (In paragraph [0038], Sarkar discloses authenticating input data by comparing a determined probability value with a predetermined authentication value. In particular, Sarkar determines a user probability value indicative of the likelihood that a requestor is an authorized user and compares the determined user probability value with a predefined application threshold value to determine whether the requestor is authenticated. In paragraph [0166], Sarkar discloses a determined probability value of 0.50 compared against a predefined threshold value of 0.40, resulting in successful authentication. )
Neven in view of Sarkar analogous pieces of art both are directed to quantum computing systems that receive input data, represent or provide the input using qubit, process the qubits using a quantum processor, and generate an output resulting from the quantum processing. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Neven, with multiple qubits prepared in an initial quantum state encoding a machine learning task data input as taught by Neven, to authenticate probability evaluation module as taught by Sarkar. The motivation for doing so would have been to improve the accuracy and time in which the neural network can be trained and used at inference (See [0044] of Neven.)
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Neven in view of Sarkar and further in view of Mckay et al. (Pub No.: 20200272929 A1), hereinafter referred to as Mckay.
Regarding claim 8, Neven and Sarkar disclose the elements of claim 7. Neven and Sarkar do not disclose:
The method as claimed in claim 7, wherein the encoding comprises: receiving a first plurality of qubits from among the input qubits
Distributing the first plurality of qubits and a second plurality of qubits to have a predetermined distribution centered on an average of the first plurality of qubits and the second plurality of qubits, and wherein each qubit of the first plurality of qubits and the second plurality of qubits is superposed
However, Mckay disclose the limitation:
The method as claimed in claim 7, wherein the encoding comprises: receiving a first plurality of qubits from among the input qubits (In paragraph [0038], Mackay discloses that the quantum computing device 10 further includes a first tunable frequency bus 18 configured to couple at least one of the first plurality of qubits 12 to a second qubit. )
Distributing the first plurality of qubits and a second plurality of qubits to have a predetermined distribution centered on an average of the first plurality of qubits and the second plurality of qubits, and wherein each qubit of the first plurality of qubits and the second plurality of qubits is superposed (In paragraph [0050], Mckay discloses that the quantum computing device further includes a first tunable frequency bus 36 configured to couple the first plurality of qubits 32 to the second qubit 34.)
Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, having the teaching of Neven in view of Boothby and Sarkar to include Mckay, with a first plurality of qubits having a first resonance frequency and a second qubit having a second resonance frequency as taught by Mckay. The motivation for doing so would have been to substantially reduce or eliminate frequency collision and crosstalk between the plurality of qubits (See [0046] of Mckay.)
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Neven in view of Sarkar and further in view of Burkot et al. (Pub No.: 20210287127 A1), hereinafter referred to as Burkot.
Regarding claim 9, Neven and Sarkar disclose elements of claim 7. Neven and Sarkar do not explicitly disclose:
The method as claimed in claim 7, further comprising outputting the estimated quantum amplitude values, wherein a number of the estimated quantum amplitude values corresponds to a predetermined number of diffusion modules included in the electronic apparatus
However, Burkot disclose the limitation (In paragraph [0020], Burkot discloses conventional Grover operations: the qubits are initialized, Hadamard gates put them into superposition, an oracle operates on the qubits, and a Grover diffusion gate applies the Grover diffusion operator. In paragraph [0021], Burkot disclose providing a quantum circuit containing a plurality of Grover diffusion gates. Those gates can implement different diffusion operators, and selected diffusion operators can be applied after respective oracle calls. A diffusion operator can also be applied to more than one. The circuit then, ensures the bits to generate the quantum-computing result.)
Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, having the teaching of Neven in view of Sarkar to include Burkot, with a plurality of diffusion gates of the quantum circuit, a plurality of diffusion operators as taught by Burkot. The motivation for doing so would have been to optimize a measurement, such as a measurement of an ancillary qubit or other qubit (See [0043]] of Burkot.)
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Neven in view of Sarkar and further in view of Woerner et al. (US Patent No. 10,810,665 B2), hereinafter referred to as Woerner.
Regarding claim 10, Neven and Sarkar disclose the elements of claim 7. Neven and Sarkar do not explicitly disclose:
The method as claimed in claim 7, wherein the determining of the probability value comprises performing an inverse quantum Fourier transform (IQFT) process determine the probability value by superposing the quantum amplitude values
However, Woerner disclose the limitation (In Cols. 6–7, lines 46-10, Woerner discloses determining a probability value by performing an inverse quantum Fourier transform as part of a quantum amplitude-estimation process. In particular, Woerner discloses placing a plurality of qubits into superposition, applying controlled powers of an amplitude-estimator Q, and subsequently applying an inverse quantum Fourier transform to the qubits. The resulting quantum state is measured to obtain a value y, which is mapped to an estimated amplitude/probability value ã=sin.sup.2 (yπ/M).)
Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, having the teaching of Neven in view of Sarkar to include Woerner, with probability value represents a probability of measuring a one state in the ancilla qubit as taught by Woerner. The motivation for doing so would have been to increase the quantum estimated value at risk approaches the classical value indicated by the vertical solid line (See (Col.15, lines 62-64) of Woerner. )
Conclusion
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EVEL HONORE
Examiner
Art Unit 2142
/Mariela Reyes/Supervisory Patent Examiner, Art Unit 2142
