DETAILED ACTION
Notice of 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 .
Priority
Regarding Provisional Patent App. Nos. 63/106,423 (filed 10/28/2020) and 63/222,546 (filed 7/16/2021) and PCT Application No. PCT/CA2021/051467 (filed 10/19/2021), Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Preliminary Amendment
The Preliminary Amendment submitted on 6/15/2024 has been considered. Claims 4, 14-19, 24-27, 29-32, 34-35, 37-40, and 42-76 are cancelled. Claims 1-3, 5-13, 20-23, 28, 33, 36, and 41 are pending.
Information Disclosure Statement
Except as set forth below, the information disclosure statements submitted on 5/28/2024 and 5/28/2024 have both been considered.
The information disclosure statement filed 5/28/2024 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. Foreign application CA 2021051467 has not been provided.
Both IDSs have been placed in the application file, but the information referred to therein with respect to Foreign application CA 2021051467 has not been considered.
Drawings
The drawings are objected to because Figs. 3A, 4A-B, 5A-B, and 6 should be corrected to comply with the applicable sections of 37 CFR 1.84 set forth below. In particular, such figures should be drawings using India ink or its equivalent.
(a) Drawings. There are two acceptable categories for presenting drawings in utility and design patent applications.
(1) Black ink. Black and white drawings are normally required. India ink, or its equivalent that secures solid black lines, must be used for drawings; or
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claim 28 is objected to because of the following informalities:
In claim 28, line 2, “operatorGpq” should “operator Gpq” to add a space.
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.
Claims 7-13, 21-23, 28, 33, and 36 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 7 recites the limitation "wherein the generator decomposition provides" in line 1. There is insufficient antecedent basis for this limitation in the claim. The examiner suggests considering whether claim 7 should depend from claim 3, which would provide sufficient antecedent basis. For purposes of compact prosecution, claim 7 will be interpreted as reciting “wherein a generator of the unitary transformation is decomposed to provide”.
Claim 8 recites the limitation "the analytical gradients" in line 2. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “the gradients are analytical gradients”.
Claim 8 recites the limitation “the fermionic shift gates” in lines 5. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “the fermionic shift operations”.
Claim 8 recites the limitation “the n-fold excitation operator G” in lines 11-12. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “the n-fold excitation operator Gpq”.
Claim 8 recites the limitation “the fermionic shift gates” in lines 16. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “the fermionic shift operations”.
Claim 8 recites the limitation “the n-fold excitation operator G” in line 17. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “the n-fold excitation operator Gpq”.
Claims 9-13 depend from claim 8, do not remedy the deficiencies of claim 8, and are therefore rejected for the same reasons explained above with respect to claim 8.
Claim 9 recites the limitation “the generator G” in line 1. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “a generator G.”
Claim 10 recites the limitation “the generator G” in line 1. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “a generator G.”
Claim 21 is rejected because while it recites a “system”, the claim specifically recites “perform a method for implementing, on the quantum computer, a n-fold fermionic excitation operator, the method comprising,” so it is unclear whether infringement will occur when (1) the system is made, sold, offered for sale, or imported, or (2) the recited method is actually performed. MPEP 2173 explains that “primary purpose of this requirement of definiteness of claim language is to ensure that the scope of the claims is clear so the public is informed of the boundaries of what constitutes infringement of the patent.” Here, because it is not clear to the public when infringement will actually occur, claim 21 is indefinite. The examiner suggests amending claim 21 to recite “are capable of performing operations, on the quantum computer, of a n-fold fermionic excitation operator, the operations comprising,” or something similar, if that is indeed what Applicant intends.
Claims 22-23 depend from claim 21, do not remedy the deficiencies of claim 21, and are therefore rejected for the same reasons explained above with respect to claim 21.
Claim 28 recites the limitation “the fermionic shift gates” in lines 7. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “[[the]] fermionic shift gates”.
Claim 28 recites the limitation “the n-fold excitation operator G” in line 8. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “the n-fold excitation operator Gpq”.
Claim 28 recites the limitation “the fermionic shift gates” in lines 12. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “[[the]] fermionic shift gates”.
Claim 28 recites the limitation “the n-fold excitation operator G” in line 13. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “the n-fold excitation operator Gpq”.
Claims 33 and 36 depend from claim 28, do not remedy the deficiencies of claim 28, and are therefore rejected for the same reasons explained above with respect to claim 28.
Claim 36 recites the limitation “the generator G” in line 1. There is insufficient antecedent basis for this limitation in the claim. For purposes of compact prosecution, this limitation will be interpreted as “a generator G.”
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 and 41 rejected under 35 U.S.C. 103 as being unpatentable over US 20200134107 A1, hereinafter referenced as LOW, in view of US 20210097422 A1, hereinafter referenced as VERDON-AKZAM.
Regarding Claim 1
LOW teaches:
A method performed by a classical computer for implementing, on a quantum computer, an operator, wherein: (LOW, para. 0004: “In certain embodiments, a quantum algorithm description is input (e.g., into a classical computer). The quantum algorithm description is synthesized into a synthesized quantum circuit representation (e.g., using the classical computer and using an appropriate compilation/synthesis tool for quantum computing). In the illustrated embodiment, the quantum circuit representation is implementable on a quantum computing device, and the synthesizing comprises assigning one or more ancilla qubits to be used for at least one non-Clifford operation. The synthesized quantum circuit representation is output (e.g., the synthesized quantum circuit representation is a set of low-level machine instructions for implementation on a quantum device).”;
LOW, para. 0061: “At 716, a quantum computing device is controlled to implement the quantum circuit representations (e.g., by a classical computer in communication with a quantum computing device, such as in a configuration as shown in FIG. 5).”;
Examiner’s Note: LOW teaches techniques for using a classical computer to synthesize a quantum circuit to run on a quantum computing device)
the quantum computer having a plurality of qubits and configurable to implement a universal set of gates; (LOW, para. 0003: “Efficient synthesis of arbitrary quantum states and unitaries from a universal fault-tolerant gate-set (e.g., Clifford+T) is a goal in quantum computation. As physical quantum computers are fixed in size, all available qubits should be used if it minimizes overall gate counts, especially that of the expensive T-gates.”;
LOW, para. 0016: “In any scalable approach to quantum computation, unitaries are desirably expressed in terms of a universal fault-tolerant quantum gate set, such as Clifford gates {H, S, C.sub.NOT} and T gates.”
LOW, para. 0018: “However, not all fault-tolerant quantum gates are equal. It is now understood that fault-tolerant Clifford gates {H, S, CNOT} are generally cheap. In contrast, fault-tolerant non-Clifford T gates are incredibly expensive but very useful for universal quantum computing”
the classical computer including a processor, a non-transitory computer-readable medium, and computer program instructions stored in the non-transitory computer-readable medium, the computer program instructions being executable by the processor to perform the method, the method comprising: (LOW, para. 0063: “Any of the disclosed embodiments can be implemented by one or more computer-readable media storing computer-executable instructions, which when executed by a computer cause the computer to perform any of the disclosed methods. Also disclosed herein are systems for performing embodiments of the disclosed embodiments comprising a classical computer configured to program, control, and/or measure a quantum computing device.”
LOW, para. 0065: “FIG. 2 illustrates a generalized example of a suitable classical computing environment 200 in which several of the described embodiments can be implemented”
LOW, para. 0066: “With reference to FIG. 2, the computing environment 200 includes at least one processing device 210 and memory 220. In FIG. 2, this most basic configuration 230 is included within a dashed line. The processing device 210 (e.g., a CPU or microprocessor) executes computer-executable instructions.”)
generating and storing, in the non-transitory computer-readable medium, computer-readable data that, when executed on the quantum computer, causes a quantum circuit of the quantum computer to execute repeatedly to perform a sequence of operations that (LOW, para. 0004: “In certain embodiments, a quantum algorithm description is input (e.g., into a classical computer). The quantum algorithm description is synthesized into a synthesized quantum circuit representation (e.g., using the classical computer and using an appropriate compilation/synthesis tool for quantum computing). In the illustrated embodiment, the quantum circuit representation is implementable on a quantum computing device, and the synthesizing comprises assigning one or more ancilla qubits to be used for at least one non-Clifford operation. The synthesized quantum circuit representation is output (e.g., the synthesized quantum circuit representation is a set of low-level machine instructions for implementation on a quantum device).”;
LOW, para. 0061: “At 716, a quantum computing device is controlled to implement the quantum circuit representations (e.g., by a classical computer in communication with a quantum computing device, such as in a configuration as shown in FIG. 5).”;
Examiner’s Note: LOW teaches techniques for using a classical computer to synthesize instructions (corresponding to recited “sequence of operations”) to be run on a quantum computer)
However, LOW fails to explicitly teach:
implements a unitary transformation for reducing the evaluation of a gradient to measurement of one or more expectation values.
However, in a related field of endeavor (quantum computing, see para. 0002), VERDON-AKZAM teaches and makes obvious:
implements a unitary transformation for reducing the evaluation of a gradient to measurement of one or more expectation values. (VERDON-AKZAM, para. 0019: “In some implementations determining the partial derivative of the loss function with respect to the first set of variational parameters comprises determining a difference between i) an expected value of the gradient of an energy function with respect to a first pulled back data state, wherein the first pulled back data state is generated by applying a quantum circuit to the target mixed state, the quantum circuit representing an inverse of a unitary operator used to prepare the parameterized ansatz quantum state, and ii) an expected value of the gradient of a distribution that can be classically sampled.”;
VERDON-AKZAM, para. 0102: “Therefore, in these implementations, to determine the partial derivative of the loss function ... with respect to the first set θ of variational parameters, the system computes expectation values of the gradient (with respect to θ) of the energy eigenvalues R.sub.θ(x) of the initial Hamiltonian ... (step 308). For each eigenstate ...the system determines the gradient (with respect to θ) of the corresponding eigenvalue R.sub.θ(x) multiplied by an probability of the first pulled back state ... producing the eigenstate (step 308). The system can compute this expected value of the gradient using quantum and classical computations. For example, for each eigenstate in the eigenbasis and according to a finite difference method or parameter-shift gradient estimator, ...”;
VERDON-AKZAM, para. 0104: “back propagate the prepared target mixed state through the quantum neural network”
Examiner’s Note: the LOW-VERDON-AKZAM combination now modifies the quantum computer of LOW, which implements quantum unitaries, to calculate a partial derivative of a loss function (corresponding to a gradient that is back-propagated through a quantum neural network), where such calculation is based on different computed expectation values)
Before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of LOW and VERDON-AKZAM as described herein. As disclosed by VERDON-AKZAM, one of ordinary skill would have been motivated to do so in order to because VERDON-AKZAM teaches techniques that “enable mixed quantum states and thermal quantum states to be learned and reproduced with high fidelity. Unlike known techniques for learning mixed quantum states that are typically tailored specifically for low-rank density matrices, the presently described techniques are generic and can be applied to mixed and thermal states of any rank. In addition, the presently described techniques enable estimates of mixed state entropy, free energy, and the diagonalizing transformation of the target system, the last of which enables modular time evolution and facilitates full quantum simulation of a previously unknown system. This provides the possibility of using quantum machine learning to compute state entropies of analytically intractable syste” (para. 0042).
Regarding Claim 41
LOW teaches:
A computer product with non-transitory computer-readable media storing program instructions, (LOW, para. 0063: “Any of the disclosed embodiments can be implemented by one or more computer-readable media storing computer-executable instructions, which when executed by a computer cause the computer to perform any of the disclosed methods. Also disclosed herein are systems for performing embodiments of the disclosed embodiments comprising a classical computer configured to program, control, and/or measure a quantum computing device.”) the computer program instructions being executable on a quantum computer to: (LOW, para. 0004: “In certain embodiments, a quantum algorithm description is input (e.g., into a classical computer). The quantum algorithm description is synthesized into a synthesized quantum circuit representation (e.g., using the classical computer and using an appropriate compilation/synthesis tool for quantum computing). In the illustrated embodiment, the quantum circuit representation is implementable on a quantum computing device, and the synthesizing comprises assigning one or more ancilla qubits to be used for at least one non-Clifford operation. The synthesized quantum circuit representation is output (e.g., the synthesized quantum circuit representation is a set of low-level machine instructions for implementation on a quantum device).”;
LOW, para. 0061: “At 716, a quantum computing device is controlled to implement the quantum circuit representations (e.g., by a classical computer in communication with a quantum computing device, such as in a configuration as shown in FIG. 5).”;
cause a quantum circuit of the quantum computer to execute repeatedly to perform a sequence of operations that (LOW, para. 0004: “In certain embodiments, a quantum algorithm description is input (e.g., into a classical computer). The quantum algorithm description is synthesized into a synthesized quantum circuit representation (e.g., using the classical computer and using an appropriate compilation/synthesis tool for quantum computing). In the illustrated embodiment, the quantum circuit representation is implementable on a quantum computing device, and the synthesizing comprises assigning one or more ancilla qubits to be used for at least one non-Clifford operation. The synthesized quantum circuit representation is output (e.g., the synthesized quantum circuit representation is a set of low-level machine instructions for implementation on a quantum device).”;
LOW, para. 0061: “At 716, a quantum computing device is controlled to implement the quantum circuit representations (e.g., by a classical computer in communication with a quantum computing device, such as in a configuration as shown in FIG. 5).”;
Examiner’s Note: LOW teaches techniques for using a classical computer to synthesize instructions (corresponding to recited “sequence of operations”) to be run on a quantum computer)
However, LOW fails to explicitly teach:
implements a unitary transformation for reducing the evaluation of a gradient to measurement of one or more expectation values.
However, in a related field of endeavor (quantum computing, see para. 0002), VERDON-AKZAM teaches and makes obvious:
implements a unitary transformation for reducing the evaluation of a gradient to measurement of one or more expectation values. (VERDON-AKZAM, para. 0019: “In some implementations determining the partial derivative of the loss function with respect to the first set of variational parameters comprises determining a difference between i) an expected value of the gradient of an energy function with respect to a first pulled back data state, wherein the first pulled back data state is generated by applying a quantum circuit to the target mixed state, the quantum circuit representing an inverse of a unitary operator used to prepare the parameterized ansatz quantum state, and ii) an expected value of the gradient of a distribution that can be classically sampled.”;
VERDON-AKZAM, para. 0102: “Therefore, in these implementations, to determine the partial derivative of the loss function ... with respect to the first set θ of variational parameters, the system computes expectation values of the gradient (with respect to θ) of the energy eigenvalues R.sub.θ(x) of the initial Hamiltonian ... (step 308). For each eigenstate ...the system determines the gradient (with respect to θ) of the corresponding eigenvalue R.sub.θ(x) multiplied by an probability of the first pulled back state ... producing the eigenstate (step 308). The system can compute this expected value of the gradient using quantum and classical computations. For example, for each eigenstate in the eigenbasis and according to a finite difference method or parameter-shift gradient estimator, ...”;
VERDON-AKZAM, para. 0104: “back propagate the prepared target mixed state through the quantum neural network”
Examiner’s Note: the LOW-VERDON-AKZAM combination now modifies the quantum computer of LOW, which implements quantum unitaries, to calculate a partial derivative of a loss function (corresponding to a gradient that is back-propagated through a quantum neural network), where such calculation is based on different computed expectation values)
Before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of LOW and VERDON-AKZAM as described herein. As disclosed by VERDON-AKZAM, one of ordinary skill would have been motivated to do so in order to because VERDON-AKZAM teaches techniques that “enable mixed quantum states and thermal quantum states to be learned and reproduced with high fidelity. Unlike known techniques for learning mixed quantum states that are typically tailored specifically for low-rank density matrices, the presently described techniques are generic and can be applied to mixed and thermal states of any rank. In addition, the presently described techniques enable estimates of mixed state entropy, free energy, and the diagonalizing transformation of the target system, the last of which enables modular time evolution and facilitates full quantum simulation of a previously unknown system. This provides the possibility of using quantum machine learning to compute state entropies of analytically intractable syste” (para. 0042).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over LOW in view of VERDON-AKZAM and further in view of US 20170364796 A1, hereinafter referenced as WIEBE.
Regarding Claim 7
LOW and VERDON-AKZAM teach the method of claim 1 as explained above. However, LOW and VERDON-AKZAM fail to explicitly teach:
wherein the generator decomposition provides an implementation that reduces the evaluation of the gradient to evaluation of a linear combinations of expectation values that can be measured on the quantum computer.
However, in a related field of endeavor (quantum computers, see para. 0001), WIEBE teaches and makes obvious:
wherein the generator decomposition provides an implementation that reduces the evaluation of the gradient to evaluation of a linear combinations of expectation values that can be measured on the quantum computer. (WIEBE, para. 0045: “One method for estimating the gradients ... involves preparing the Gibbs state from the mean-field state and then drawing samples from the resultant distribution in order to estimate the expectation values required in Eqns. (1a)-(1c) above. This approach can be improved using the quantum method known as amplitude amplification, a generalization of Grover's search algorithm that quadratically reduces the mean number of repetitions needed to draw a sample from the Gibbs distribution using the methods discussed above.”;
Examiner’s Note: the LOW-VERDON-AKZAM-WIEBE combination now estimates the gradient using expectation values (and combinations thereof) in view of WIEBE, wherein the broadest reasonable interpretation of “a generator decomposition” includes decomposing a gradient by generating expectation values and combining them)
Before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of LOW, VERDON-AKZAM, and WIEBE as described herein. One of ordinary skill would have been motivated to do so because using expectation values will save computing resources as opposed to calculating the gradient itself.
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over LOW in view of VERDON-AKZAM and further in view of US 20180232652 A1, hereinafter referenced as CURTIS.
Regarding Claim 21
LOW teaches:
A system comprising: (LOW, para. 0005: “Also disclosed herein are systems for performing embodiments of the disclosed embodiments comprising a classical computer configured to program, control, and/or measure a quantum computing device.”)
a classical computer, the classical computer comprising a processor, a non-transitory computer-readable medium, and computer program instructions stored in the non- transitory computer-readable medium; (LOW, para. 0063: “Any of the disclosed embodiments can be implemented by one or more computer-readable media storing computer-executable instructions, which when executed by a computer cause the computer to perform any of the disclosed methods. Also disclosed herein are systems for performing embodiments of the disclosed embodiments comprising a classical computer configured to program, control, and/or measure a quantum computing device.”
LOW, para. 0065: “FIG. 2 illustrates a generalized example of a suitable classical computing environment 200 in which several of the described embodiments can be implemented”
LOW, para. 0066: “With reference to FIG. 2, the computing environment 200 includes at least one processing device 210 and memory 220. In FIG. 2, this most basic configuration 230 is included within a dashed line. The processing device 210 (e.g., a CPU or microprocessor) executes computer-executable instructions.”)
a quantum computer comprising a plurality of qubits and configurable to implement a universal set of gates, (LOW, para. 0003: “Efficient synthesis of arbitrary quantum states and unitaries from a universal fault-tolerant gate-set (e.g., Clifford+T) is a goal in quantum computation. As physical quantum computers are fixed in size, all available qubits should be used if it minimizes overall gate counts, especially that of the expensive T-gates.”;
LOW, para. 0016: “In any scalable approach to quantum computation, unitaries are desirably expressed in terms of a universal fault-tolerant quantum gate set, such as Clifford gates {H, S, C.sub.NOT} and T gates.”
LOW, para. 0018: “However, not all fault-tolerant quantum gates are equal. It is now understood that fault-tolerant Clifford gates {H, S, CNOT} are generally cheap. In contrast, fault-tolerant non-Clifford T gates are incredibly expensive but very useful for universal quantum computing”)
wherein the computer program instructions, when executed by the processor, perform a method for ... , the method comprising: (LOW, para. 0063: “Any of the disclosed embodiments can be implemented by one or more computer-readable media storing computer-executable instructions, which when executed by a computer cause the computer to perform any of the disclosed methods. Also disclosed herein are systems for performing embodiments of the disclosed embodiments comprising a classical computer configured to program, control, and/or measure a quantum computing device.”
generating and storing, in the non-transitory computer-readable medium, computer-readable data that, when executed on the quantum computer, causes a quantum circuit of the quantum computer to execute repeatedly to perform a sequence of operations that (LOW, para. 0004: “In certain embodiments, a quantum algorithm description is input (e.g., into a classical computer). The quantum algorithm description is synthesized into a synthesized quantum circuit representation (e.g., using the classical computer and using an appropriate compilation/synthesis tool for quantum computing). In the illustrated embodiment, the quantum circuit representation is implementable on a quantum computing device, and the synthesizing comprises assigning one or more ancilla qubits to be used for at least one non-Clifford operation. The synthesized quantum circuit representation is output (e.g., the synthesized quantum circuit representation is a set of low-level machine instructions for implementation on a quantum device).”;
LOW, para. 0061: “At 716, a quantum computing device is controlled to implement the quantum circuit representations (e.g., by a classical computer in communication with a quantum computing device, such as in a configuration as shown in FIG. 5).”;
Examiner’s Note: LOW teaches techniques for using a classical computer to synthesize instructions (corresponding to recited “sequence of operations”) to be run on a quantum computer)
However, LOW fails to explicitly teach:
implementing, on the quantum computer, a n-fold fermionic excitation operator
implements a unitary transformation for reducing the evaluation of a gradient to measurement of one or more expectation values.
However, in a related field of endeavor (quantum computing, see para. 0002), VERDON-AKZAM teaches and makes obvious:
implements a unitary transformation for reducing the evaluation of a gradient to measurement of one or more expectation values. (VERDON-AKZAM, para. 0019: “In some implementations determining the partial derivative of the loss function with respect to the first set of variational parameters comprises determining a difference between i) an expected value of the gradient of an energy function with respect to a first pulled back data state, wherein the first pulled back data state is generated by applying a quantum circuit to the target mixed state, the quantum circuit representing an inverse of a unitary operator used to prepare the parameterized ansatz quantum state, and ii) an expected value of the gradient of a distribution that can be classically sampled.”;
VERDON-AKZAM, para. 0102: “Therefore, in these implementations, to determine the partial derivative of the loss function ... with respect to the first set θ of variational parameters, the system computes expectation values of the gradient (with respect to θ) of the energy eigenvalues R.sub.θ(x) of the initial Hamiltonian ... (step 308). For each eigenstate ...the system determines the gradient (with respect to θ) of the corresponding eigenvalue R.sub.θ(x) multiplied by an probability of the first pulled back state ... producing the eigenstate (step 308). The system can compute this expected value of the gradient using quantum and classical computations. For example, for each eigenstate in the eigenbasis and according to a finite difference method or parameter-shift gradient estimator, ...”;
VERDON-AKZAM, para. 0104: “back propagate the prepared target mixed state through the quantum neural network”
Examiner’s Note: the LOW-VERDON-AKZAM combination now modifies the quantum computer of LOW, which implements quantum unitaries, to calculate a partial derivative of a loss function (corresponding to a gradient that is back-propagated through a quantum neural network), where such calculation is based on different computed expectation values)
Before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of LOW and VERDON-AKZAM as described herein. As disclosed by VERDON-AKZAM, one of ordinary skill would have been motivated to do so in order to because VERDON-AKZAM teaches techniques that “enable mixed quantum states and thermal quantum states to be learned and reproduced with high fidelity. Unlike known techniques for learning mixed quantum states that are typically tailored specifically for low-rank density matrices, the presently described techniques are generic and can be applied to mixed and thermal states of any rank. In addition, the presently described techniques enable estimates of mixed state entropy, free energy, and the diagonalizing transformation of the target system, the last of which enables modular time evolution and facilitates full quantum simulation of a previously unknown system. This provides the possibility of using quantum machine learning to compute state entropies of analytically intractable syste” (para. 0042).
However, LOW and VERDON-AKZAM fail to explicitly teach:
implementing, on the quantum computer, a n-fold fermionic excitation operator
However, in a related field of endeavor (quantum information processing hardware, see para. 0001), CURTIS teaches and makes obvious:
implementing, on the quantum computer, a n-fold fermionic excitation operator (CURTIS, para. 0074: “FIG. 5B is another plot 500B showing gate counts for example quantum logic circuits configured to simulate an “excitation” quantum logic operator in a fermionic Hamiltonian.”;
Examiner’s Note: the LOW-VERDON-AKZAM-CURTIS combination now implements an excitation operator, using a fermionic Hamiltonian, where n=1, using the quantum computer of LOW)
Before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of LOW, VERDON-AKZAM, and CURTIS as described herein. As disclosed by CURTIS, one of ordinary skill would have been motivated to do so in order to simulate “fermions on a gate-based quantum information processor.” (para. 0014). Further, as disclosed by CURTIS, one of ordinary skill would have been motivated to do so because CURTIS teaches techniques so that “with fewer quantum logic gates can provide practical advantages; for example, the quantum logic circuit may be executed in less time, with less error correction, with greater accuracy or a combination of these and other advantages. For instance, a quantum information processor may have a limited per-gate fidelity, so fewer gates may translate to more accurate calculations and potentially unlock larger problems.” (para. 0015).
Allowable Subject Matter
Claims 2-3, 5-6, 8-13, 20, 22-23, 28, 33, 36 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims (and with respect to claims 8-13, 22-23, 28, 33, and 36, if the rejections under 35 U.S.C. 112(b) are overcome).
The following is a statement of reasons for the indication of allowable subject matter:
Claim 2 would be considered allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims because none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specified in claim 2, including at least:
wherein the unitary transformation is implemented by implementing:
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The closest prior art of record discloses:
US 20200134107 A1, hereinafter referenced as LOW, teaches using a classical computer to synthesize a quantum circuit representation that is loaded onto a quantum device. (para. 0004).
US 20210097422 A1, hereinafter referenced as VERDON-AKZAM, teaches determining a partial derivative of a loss function by computing different expected values. (para. 0019).
Arzani, Francesco, et al. "Polynomial approximation of non-Gaussian unitaries by counting one photon at a time." Physical Review A 95.5 (2017): 052352, hereinafter referenced as ARZANI, teaches using a Taylor series for polynomial expansion of a quantum unitary operator. (p. 052352-1, section I). However, ARZANI does not teach performing the polynomial expansion specifically as a function of amplitudes and number of distinct eigenvalues in the generator of the unitary transform as specifically claimed herein.
US 20200143280 A1, hereinafter referenced as HAAH, teaches decomposing a unitary operator into overlapping smaller blocks of unitary operators, where such blacks are based in part on a Taylor series expansion. (para. 0067). However, HAAH does not teach performing the polynomial expansion specifically as a function of amplitudes and number of distinct eigenvalues in the generator of the unitary transform as specifically claimed herein.
However, the examiner has found that the distinct feature of the Applicant's claimed invention over the prior art is the explicit claiming of the aforementioned limitations in combination with all the other limitations as specified in claim 2. Moreover, the examiner finds that one of ordinary skill would not have been motivated to use the precise formulation as recited in claim 2, requiring knowledge of gradient amplitudes and number of distinct eigenvalues present in the generator of the unitary transformation as recited herein. Therefore, because the prior art of record does not anticipate nor make obvious the limitations of claim 2, claim 2 would be allowed if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim 3 would be considered allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims because none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specified in claim 3, including at least:
wherein the unitary transformation is implemented by implementing:
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The closest prior art of record discloses:
US 20200134107 A1, hereinafter referenced as LOW, teaches using a classical computer to synthesize a quantum circuit representation that is loaded onto a quantum device. (para. 0004).
US 20210097422 A1, hereinafter referenced as VERDON-AKZAM, teaches determining a partial derivative of a loss function by computing different expected values. (para. 0019).
US 20220221647 A1, hereinafter referenced as PEREZ LOPEZ, teaches the general concept of breaking down a complex circuit into smaller units with respect to an optical network, where smaller 2-dimensional waveguides are used. (para. 0005). But PEREZ LOPEZ does not teach the precise decomposition of a generator of a unitary transformation using operators having 2 or 3 distinct eigenvalues (e.g., 2- or 3-dimensional operators).
Reck, Michael, et al. "Experimental realization of any discrete unitary operator." Physical review letters 73.1 (1994): 58, hereinafter referenced as RECK, teaches that a unitary matrix of N dimensions can be deconstructed to a product of successive 2-D beam splitter matrices with appropriate phase shifts. (see p. 59, left column). However, RECK does not teach the precise decomposition of a generator of a unitary transformation.
However, the examiner has found that the distinct feature of the Applicant's claimed invention over the prior art is the explicit claiming of the aforementioned limitations in combination with all the other limitations as specified in claim 3. Moreover, the examiner finds that one of ordinary skill would not have been motivated to use the precise formulation as recited in claim 3, requiring decomposition using “operators with two or three distinct eigenvalues,” without the hindsight aid of Applicant’s disclosure. Therefore, because the prior art of record does not anticipate nor make obvious the limitations of claim 3, claim 3 would be allowed if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claims 5-6 depend from claim 3 and would be allowed for the same reasons explained above with respect to claim 3 if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim 8 would be considered allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome, because none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specified in claim 8, including at least:
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The closest prior art of record discloses:
US 20200134107 A1, hereinafter referenced as LOW, teaches using a classical computer to synthesize a quantum circuit representation that is loaded onto a quantum device. (para. 0004).
US 20210097422 A1, hereinafter referenced as VERDON-AKZAM, teaches determining a partial derivative of a loss function by computing different expected values. (para. 0019).
US 20220019931 A1, hereinafter referenced as JIANG, teaches “expansion operators in the set of expansion operators approximate fermionic excitations in an active space spanned by the active set of orbitals and a virtual space spanned by the virtual set of orbitals.” (para. 0004).
Schuld, Maria, et al. "Evaluating analytic gradients on quantum hardware." Physical Review A 99.3 (2019): 032331, hereinafter referenced as SCHULD, teaches techniques for evaluating analytic gradients on quantum hardware.
However, the examiner has found that the distinct feature of the Applicant's claimed invention over the prior art is the explicit claiming of the aforementioned limitations in combination with all the other limitations as specified in claim 8. Moreover, the examiner finds that one of ordinary skill would not have been motivated to use the precise mathematical equations as recited in claim 8 without the hindsight aid of Applicant’s disclosure. Therefore, because the prior art of record does not anticipate nor make obvious the limitations of claim 8, claim 8 would be allowed if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome.
Claims 9-13 and 20 depend from claim 8 and would be allowed for the same reasons explained above with respect to claim 8 if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome.
Claim 22 claims a system that corresponds to the method of claim 2, and would therefore be allowed for the same reasons explained above with respect to claim 2, if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome.
Claim 23 claims a system that corresponds to the method of claim 3, and would therefore be allowed for the same reasons explained above with respect to claim 3, if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome.
Claim 28 would be considered allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome, because none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specified in claim 28, including at least:
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The closest prior art of record discloses:
US 20200134107 A1, hereinafter referenced as LOW, teaches using a classical computer to synthesize a quantum circuit representation that is loaded onto a quantum device. (para. 0004).
US 20210097422 A1, hereinafter referenced as VERDON-AKZAM, teaches determining a partial derivative of a loss function by computing different expected values. (para. 0019).
US 20220019931 A1, hereinafter referenced as JIANG, teaches “expansion operators in the set of expansion operators approximate fermionic excitations in an active space spanned by the active set of orbitals and a virtual space spanned by the virtual set of orbitals.” (para. 0004).
Schuld, Maria, et al. "Evaluating analytic gradients on quantum hardware." Physical Review A 99.3 (2019): 032331, hereinafter referenced as SCHULD, teaches techniques for evaluating analytic gradients on quantum hardware.
However, the examiner has found that the distinct feature of the Applicant's claimed invention over the prior art is the explicit claiming of the aforementioned limitations in combination with all the other limitations as specified in claim 28. Moreover, the examiner finds that one of ordinary skill would not have been motivated to use the precise mathematical equations as recited in claim 28 without the hindsight aid of Applicant’s disclosure. Therefore, because the prior art of record does not anticipate nor make obvious the limitations of claim 28, claim 28 would be allowed if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome.
Claims 33 and 36 depend from claim 28 and would be allowed for the same reasons explained above with respect to claim 28 if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and provided that the rejections under 35 U.S.C. 112(b) are overcome.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20180137422 A1 (Wiebe). “At 220, gradients are computed using expectation values of accepted samples based on Eqns. 1a-1c.” (para. 0035).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL C LEE whose telephone number is (571)272-4933. The examiner can normally be reached M-F 12:00 pm - 8:00 pm ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Omar Fernandez Rivas can be reached at 571-272-2589. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL C. LEE/Examiner, Art Unit 2128
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