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 .
Claim Objections
Claims 2-3 are objected to because of the following informalities:
In Claim 2, line 1, “the correlation function” was probably meant to be the correlation function value; and in lines 3-4, “n first measurement results” was probably meant to be the n first measurement results; and in line 4, “the n the second measurement results” was probably meant to be: the n second measurement results; and in line 5, “a correlation function value” was probably meant to be the correlation function value.
In Claim 3, line 5, “a correlation function value” was probably meant to be the correlation function value.
Appropriate correction is required.
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 1-14 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.
The term “approximately” in Claims 1, 10 and 14 is a relative term which renders the claim indefinite. The term is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Dependent claims are subsequently rejected.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) are: “a measurement result acquisition module configured to: acquire a transformation process”; and “a weight parameter acquisition module configured to process the second measurement results”; and “a correlation function computation module configured to compute a correlation function value”; and “an objective function computation module configured to compute an expected value”; and “a variational parameter adjustment module configured to adjust variational parameters”; and “a thermalized state acquisition module configured to acquire, under a condition that the expected value of the objective function satisfies a convergence condition, the mixed state of the target quantum system” in Claim 10.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
All claims are directed towards either a method or an apparatus or system and thus satisfies Step 1 as falling into one of the statutory categories.
Step 2A, Prong One:
Independent Claim 1 recites (the same analysis applies to similar independent Claims 10 and 14):
and then measuring an output quantum state of the parameterized quantum circuit for n times to obtain n sets of measurement results,
wherein the combined qubits include auxiliary qubits and system qubits of a target quantum system,
each set of measurement results includes: first measurement results corresponding to the system qubits, and second measurement results corresponding to the auxiliary qubits, wherein n is a positive integer;
computing a correlation function value of a mixed state of the target quantum system based on the weight parameters and the first measurement results;
computing an expected value of an objective function based on the correlation function value of the mixed state;
adjusting variational parameters by taking an expected value convergence of the objective function as a goal,
these limitations, under their broadest reasonable interpretation, are considered to be directed towards the “Mathematical Concepts” grouping of abstract ideas. These limitations are all mathematical functions and do not really disclose performing any specific quantum computation, but rather gathering measurement data and performing mathematical function on the received or gathered data as pointed out in the specification as filed (see for example paragraphs 53-61, 102-107, 117-120).
Step 2A, Prong Two:
Claim 1 recites the additional elements of (the same analysis applies to similar independent Claims 10 and 14):
acquiring a transformation process performed by a parameterized quantum circuit on an input quantum state of combined qubits,
this limitation is considered as adding insignificant extra-solution activity (acquiring data) to the judicial exception - see MPEP 2106.05(g).
processing the second measurement results through a neural network to obtain weight parameters;
this limitation is considered as using a neural network as a tool to perform the abstract idea - see MPEP 2106.05(f).
wherein the variational parameters comprise at least one of: parameters of the parameterized quantum circuit, or parameters of the neural network;
and acquiring, under a condition that the expected value of the objective function satisfies a convergence condition, the mixed state of the target quantum system to approximately characterize a thermalized state of the target quantum system.
these limitations are considered as adding insignificant extra-solution activity (acquiring data) to the judicial exception - see MPEP 2106.05(g).
The additional element(s) of a “computer device” as recited in independent Claims 1 and 14 is recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are considered as appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (acquiring data) - see MPEP 2106.05(d), and using a neural network as a tool to perform the abstract idea - see MPEP 2106.05(f). The additional element(s) of a “computer device” as recited in independent Claims 1 and 14 amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are therefore not patent eligible.
Dependent Claim 2 is also considered as directed towards the “Mathematical Concepts” grouping of abstract ideas.
Dependent Claims 3, 5, 7 are also considered as appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (acquiring/processing data) - see MPEP 2106.05(d).
Dependent Claim 4 is also considered as directed towards the “Mathematical Concepts” grouping of abstract ideas. The first limitation considered as appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (acquiring data) - see MPEP 2106.05(d).
Dependent Claims 6, 8-9 are considered as appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (setting thermalized states or value ranges and arranging the qubits) - see MPEP 2106.05(d).
Dependent Claims 11-13 are considered as merely using a processor/computer as a tool to perform the abstract idea - see MPEP 2106.05(f).
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.
Claims 1-5, 7-14 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang, “Variational Quantum-Neural Hybrid Eigensolver”, June 2021, in applicants’ IDS, in view of Verdon, US 20210097422 A1.
Regarding Claim 1, Zhang teaches:
acquiring a transformation process performed by a parameterized quantum circuit on an input quantum state of combined qubits (Fig. 1: “parameters in both PQC and neural network are optimized with gradient based optimizer from the expectation result”, the PQC being the parameterized quantum circuit and the figure caption further pointing out the input quantum state of the qubits; And p. 4: “the gradients with respect to the PQC and the neural network can be efficiently obtained via parameter shift … and backpropagation, respectively, which facilitate gradient-based classical optimizers to update parameters”, the classical optimizer representing the transformation process),
and then measuring an output quantum state of the parameterized quantum circuit for n times to obtain n sets of measurement results (p. 8: “we have to measure the system at least N…times”),
wherein the combined qubits include auxiliary qubits and system qubits of a target quantum system (Fig. 1: caption discusses the qubits of the quantum system),
each set of measurement results includes: first measurement results corresponding to the system qubits, and second measurement results corresponding to the auxiliary qubits, wherein n is a positive integer (Fig. 1: caption discusses the “small measurement circuit” for the qubits);
processing the second measurement results through a neural network to obtain weight parameters (Fig. 1: “the zeroth qubit as the star qubit… are fed into the classical neural network f with trainable weights… parameters in both PQC and neural network are optimized with gradient based optimizer from the expectation result”);
computing a correlation function value of a mixed state of the target quantum system based on the weight parameters and the first measurement results (Fig. 1: “The expectation of H can then be estimated according to Eq. (9)”; And p. 3: wherein the expectation of H as described by equation 9 is “the expectation value from the quantum-neural hybrid state”, the expectation representing the correlation. See also Verdon, US 20210097422 A1, for example paragraph 61: “The parameterized mixed state model 104 is a quantum computing device that processes classical and quantum information to perform hybrid quantum-probabilistic inference and, once trained, outputs a quantum state 154 that features the quantum correlations and classical correlations of a target quantum mixed state”);
computing an expected value of an objective function based on the correlation function value of the mixed state (Fig. 1: “The expectation of H can then be estimated according to Eq. (9). Finally parameters in both PQC and neural network are optimized with gradient based optimizer from the expectation result”; And, p. 2: wherein “The aim is to minimize the energy expectation” that is the objective function. See also Verdon, US 20210097422 A1, for example paragraph 35: “In some implementations determining the partial derivative of the loss function with respect to the first set of variational parameters comprises computing a set of expectation values that are dependent on a classical energy function”);
adjusting variational parameters by taking an expected value convergence of the objective function as a goal, wherein the variational parameters comprise at least one of: parameters of the parameterized quantum circuit, or parameters of the neural network (Fig. 1: “Finally parameters in both PQC and neural network are optimized with gradient based optimizer from the expectation result”. The optimizing of the parameters equivalent to its adjusting);
and acquiring, under a condition that the expected value of the objective function satisfies a convergence condition (Fig. 1 and caption and p. 2: wherein “The aim is to minimize the energy expectation” that is the objective function).
Zhang may not have explicitly taught the following, however, Verdon shows:
A thermalized state preparation method under a quantum system performed by a computer device, comprising:
the mixed state of the target quantum system to approximately characterize a thermalized state of the target quantum system (paragraphs 6, 23: “This specification describes technologies for generating target quantum states of quantum systems. In particular, methods and systems for the generative tasks of preparing a thermal state of a quantum system and learning an approximate reconstruction of a mixed state of a quantum system”). (Emphasis added).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to use the teachings of Verdon with that of Zhang for having a thermalized state preparation method under a quantum system.
The ordinary artisan would have been motivated to modify Zhang in the manner set forth above for the purposes of learning an approximate reconstruction of a mixed state of a quantum system [Verdon: paragraph 6].
Regarding Claim 2, with Zhang teaching those limitations of the claim as previously pointed out, Verdon further teaches:
The method according to claim 1, wherein the computing of the correlation function comprises: performing weighted averaging on operation results corresponding to n first measurement results based on the weight parameters corresponding to the n the second measurement results to obtain a correlation function value of the mixed state of the target quantum system (paragraph 120: “The system can then determine an average value… using the obtained measurement results, and use these computed averages..”).
Regarding Claim 3, Zhang further teaches:
The method according to claim 2, further comprising: operating and processing the n first measurement results respectively using an objective correlation function to obtain operation results corresponding to the n first measurement results respectively, wherein the objective correlation function is used for acquiring a correlation function value of the mixed state of the target quantum system under a target Pauli string (p. 3: “Since H can be decomposed to a summation of Pauli strings, it suffices to to compute the expectation for each Pauli string and then add them up. For this reason, we will assume without loss of generality that H is a Pauli string”).
Regarding Claim 4, Zhang further teaches:
The method according to claim 3, wherein the computing of the expected value comprises: acquiring correlation function values of the mixed state under a plurality of different Pauli strings, wherein the correlation function values of the mixed state under the plurality of different Pauli strings are acquired by using different correlation functions; computing an expected value of Hamiltonian corresponding to the mixed state based on the correlation function values of the mixed state under the plurality of different Pauli strings (p. 3: “Since H can be decomposed to a summation of Pauli strings, it suffices to to compute the expectation for each Pauli string and then add them up. For this reason, we will assume without loss of generality that H is a Pauli string”);
And with Zhang teaching those limitations of the claim as previously pointed out, Verdon further teaches:
and computing the expected value of the objective function based on the expected value of Hamiltonian corresponding to the mixed state and an entropy corresponding to the mixed state (paragraph 23: “determining, by classical and quantum computation, values of the first set of variational parameters and second set of variational parameters that minimize a quantum relative entropy of the parameterized ansatz quantum state with respect to the target thermal state; and preparing the parameterized ansatz quantum state with the determined values of the first set of variational parameters and second set of variational parameters as a final approximation to the target thermal state”. And, paragraph 57: “The approximation is characterized by the target Hamiltonian and target inverse temperature and is obtained by minimizing the free energy of a mixed quantum state whose entropy is known analytically”). (Emphasis added).
Regarding Claim 5, with Zhang teaching those limitations of the claim as previously pointed out, Verdon further teaches:
The method according to claim 1, wherein when a thermalized state in a first form of the target quantum system needs to be acquired, the objective function is free energy corresponding to a thermalized state in a second form, and the thermalized state in the first form and the thermalized state in the second form are two thermalized states in different forms and have a local approximation characteristic therebetween (paragraph 32: “In some implementations determining values of the first set of variational parameters and second set of variational parameters that minimize a quantum relative entropy of the parameterized ansatz quantum state with respect to the target thermal state comprises determining values of the first set of variational parameters and second set of variational parameters that minimize a loss function based on the quantum relative entropy of the parameterized ansatz quantum state with respect to the target thermal state”. And, paragraph 57: “The approximation is characterized by the target Hamiltonian and target inverse temperature and is obtained by minimizing the free energy of a mixed quantum state whose entropy is known analytically”).
Regarding Claim 7, Zhang further teaches:
The method according to claim 1, wherein the processing the second measurement results through the neural network comprises: processing the second measurement results through the neural network, and limiting output results of the neural network within a value range to obtain weight parameters within the value range (p. 11: “The final scalar output is activated…where … is a trainable weight that regulates the output range of f and, in turn, controls the magnitude of fluctuations for VQNHE estimation. By restricting the range or the maximum value of f, we can keep the measurement overhead for VQNHE estimation as low as possible while witnessing just a slightly worse performance. This is a classic trade-off. Nonetheless, we report the result for a Heisenberg model with… f ϵ [1/e, e] is guaranteed”).
Regarding Claim 8, Zhang further teaches:
The method according to claim 7, wherein the value range is [1/r, r], and r is a value greater than 1 (p. 11: “The final scalar output is activated…where … is a trainable weight that regulates the output range of f and, in turn, controls the magnitude of fluctuations for VQNHE estimation. By restricting the range or the maximum value of f, we can keep the measurement overhead for VQNHE estimation as low as possible while witnessing just a slightly worse performance. This is a classic trade-off. Nonetheless, we report the result for a Heisenberg model with… f ϵ [1/e, e] is guaranteed”. Wherein e is approximately 2.71 that is greater than 1).
Regarding Claim 9, with Zhang teaching those limitations of the claim as previously pointed out, Verdon further teaches:
The method according to claim 1, wherein the system qubits and the auxiliary qubits are arranged in an overlapped manner (paragraph 66: “The qubit assembly 118 also includes adjustable coupling elements, e.g., coupler 126, that allow for interactions between coupled qubits. In the schematic depiction of FIG. 1, each qubit is adjustably coupled to each of its four adjacent qubits by means of respective coupling elements. However, this is an example arrangement of qubits and couplers and other arrangements are possible, including arrangements that are non-rectangular, arrangements that allow for coupling between non-adjacent qubits, and arrangements that include adjustable coupling between more than two qubits”. The coupling enabling overlap of the qubits. See also Martinis, US 20210035007 A1, paragraph 117, “In some cases, e.g., those where the system pairs multiple data qubits with respective neighboring measurement qubits into overlapping pairs, the parallel couplers may have different directions”).
Regarding Claim 11, with Zhang teaching those limitations of the claim as previously pointed out, Verdon further teaches:
A computer device comprising a processor; and a memory storing instructions executable by the processor to configure the processor to implement the method according to claim 1 (paragraph 73).
Regarding Claim 12, with Zhang teaching those limitations of the claim as previously pointed out, Verdon further teaches:
A non-transitory computer-readable storage medium storing instructions executable by a processor to implement the method according to claim 1 (paragraph 73).
Regarding Claim 13, with Zhang teaching those limitations of the claim as previously pointed out, Verdon further teaches:
A computer program product comprising a computer program stored in a non-transitory computer-readable storage medium, wherein the computer program is executable by a processor to configure the processor to implement the method according to claim 1 (paragraphs 72-73).
Claims 10 and 14 are similar to Claim 1 and are rejected under the same rationale as stated above for that claim.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang, “Variational Quantum-Neural Hybrid Eigensolver”, June 2021, in applicants’ IDS, in view of Verdon, US 20210097422 A1, and further in view of Giudice, “Rényi free energy and variational approximations to thermal states”, May 2021.
Regarding Claim 6, with Zhang and Verdon teaching those limitations of the claim as previously pointed out, neither Zhang nor Verdon may have taught all of the following, however, Giudice shows:
The method according to claim 5, wherein the thermalized state in the first form is a Gibbs thermalized state, and the thermalized state in the second form is a Renyi thermalized state (Abstract: wherein it is discussed both the Gibbs and Renyi thermal states). (Emphasis added).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to use the teachings of Giudice with that of Zhang and Verdon for having a Gibbs and Renyi thermalized state.
The ordinary artisan would have been motivated to modify Zhang and Verdon in the manner set forth above for the purposes of having thermal states that describe the equilibrium properties of a system [Giudice: Introduction].
Examiner's Note:
The Examiner cites particular pages, sections, columns, line numbers, and/or paragraphs in the references as applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in its entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner and the additional related prior arts made of record that are considered pertinent to applicant's disclosure to further show the general state of the art. The Examiner's interpretations in parenthesis are provided with the cited references to assist the applicants to better understand how the examiner interprets the prior art to read on the claims. Such comments are entirely consistent with the intent and spirit of compact prosecution.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO-892 and applicants’ provided IDS prior art where for example the NPL of Verdon provided by applicants teaches a Variational Quantum Thermalizer for generating the thermal state of a given Hamiltonian and target temperature.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVE MISIR whose telephone number is (571)272-5243. The examiner can normally be reached M-R 8-5 pm, F some hours.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abdullah Al Kawsar can be reached at 5712703169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAVE MISIR/Primary Examiner, Art Unit 2127