DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This office action is in response to submission of application on 3/29/23.
Claims 1-20 are presented for examination.
Claim Objections
Claims 10 and 20 are objected to because of the following informalities:
Claim 10: “The method of claim 19, ...” Claim 19 appears after claim 10. Therefore, claim 10 cannot be a dependent of claim 19.
Claim 20: “The non-transitory computer readable storage medium of claim of claim 19,” There is a typo in repeating “of claim” twice.
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.
Claim 7 is objected to because of the following informalities:
Claim 7 recites the limitation, “multiplying a cost vector by -iγj and then exponentiating element-by-element…” without defining the variables “-iγj”.
Appropriate correction is required.
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 11-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Claims 11-20 are directed to a non-transitory computer readable storage medium; therefore, the claims are directed to one of the four statutory categories.
Step 2A Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Claim 11 recites limitations of:
precomputing a diagonal vector comprising diagonal elements of a phase Hamiltonian; - mathematical concept (relationships, formulas or equations, calculations) of computing a diagonal vector
initializing a state vector; - mathematical concept (relationships, formulas or equations, calculations) establishing the initial mathematical vector
applying a phase operator to the state vector with the first circuit parameter; - mental process (observation, evaluation, judgement) as a human mind is able to apply the operator to a state vector
applying a mixing operator to the state vector with the second circuit parameter; - mental process (observation, evaluation, judgement) as a human mind is able apply a mixing operator to a state vector
reading the state vector; - mental process (observation, evaluation, judgement) as a human mind is able read the state vector
computing a quality of the state vector based on the objective; - mathematical concept (relationships, formulas or equations, calculations) computing a quality of the state vector
Step 2A Prong Two: Does the claim recite additional elements that integrate the judicial
exception into a practical application?
Claim 11 recites limitations of:
A non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising: - A non-transitory computer readable storage medium invokes a generic computer component. See MPEP § 2106.05(f).
receiving, from a client application, a compact description of a problem and an objective to evaluate, a first circuit parameter, and a second circuit parameter; - receiving a compact description of a problem and an objective merely amounts to data gathering which is insignificant extra-solution activity. See MPEP § 2106.05(g), item (3), which identifies necessary data gathering and outputting as an example of extra-solution activity.
and updating the first circuit parameter and the second circuit parameter based on the quality. – updating the parameters merely amounts to readjusting which is insignificant extra-solution activity. See MPEP § 2106.05(g), item (3), which identifies necessary readjusting as an example of extra-solution activity
Step 2B: Does the claim recite additional elements that amounts to significantly more than the
judicial exception?
The additional elements are:
A non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising: - A non-transitory computer readable storage medium invokes a generic computer component. See MPEP § 2106.05(f).
receiving, from a client application, a compact description of a problem and an objective to evaluate, a first circuit parameter, and a second circuit parameter; - receiving a compact description of a problem and an objective merely amounts to data gathering which is insignificant extra-solution activity. See MPEP § 2106.05(g). Data gathering is well-understood, routine, and conventional. See MPEP 2106.05(d)(II)(iv).
and updating the first circuit parameter and the second circuit parameter based on the quality. – updating the parameters merely amounts to readjusting which is insignificant extra-solution activity. See MPEP § 2106.05(g). Readjusting is well-understood, routine, and conventional. See MPEP 2106.05(d)(II)(ii).
The additional elements do not amount to significantly more than the abstract idea. Therefore,
the claim is not patent eligible.
The above analysis similarly applies to the dependent claims.
Dependent claim 12 recites,
wherein the compact description of the problem comprises a computer program that computes a cost function to be optimized. - mathematical concept (relationships, formulas or equations, calculations) computing a cost function to be optimized
Dependent claim 13 recites,
wherein the objective to evaluate comprises an expectation value that is an inner product between the phase operator and the state vector. - mathematical concept (relationships, formulas or equations, calculations) an inner product calculation
Dependent claim 14 recites,
wherein the objective to evaluate comprises an expectation value that is a sum of selected square absolute values of state vector entries. - mathematical concept (relationships, formulas or equations, calculations) a sum of squared absolute values calculation
Dependent claim 15 recites,
receiving an initial vector, wherein the initial vector comprises a vector having a length of 2n and elements equal to 12n2, wherein n is a number of qubits in the state vector - receiving an initial vector merely amounts to data gathering which is insignificant extra-solution activity. See MPEP § 2106.05(g). Data gathering is well-understood, routine, and conventional. See MPEP 2106.05(d)(II)(iv).
Dependent claim 16 recites,
wherein the first circuit parameter corresponds to a time for which evolution is performed in the phase operator, and the second circuit parameter corresponds to a time for which evolution is performed in the mixing operator. - this element constitutes “mere instructions to apply an exception.” (MPEP § 2106.05(f)).
Dependent claim 17 recites,
wherein the phase operator is applied to the state vector with the first circuit parameter by: multiplying a cost vector by -iγj and then exponentiating element-by-element, resulting in a phase vector; - mathematical concept (relationships, formulas or equations, calculations) multiplying a cost vector and exponentiating element-by-element
and calculating an element-by-element product between the state vector and the phase vector. - mathematical concept (relationships, formulas or equations, calculations) calculating an element-by-element product
Dependent claim 18 recites,
wherein the mixing operator is applied to the state vector with the second circuit parameter by: performing a Fast Uniform SU(2) Transform on the state vector; - mathematical concept (relationships, formulas or equations, calculations) transform on the state vector
and applying the phase operator to the state vector. - mental process (observation, evaluation, judgement) as a human mind is able to apply the phase operator to the state vector
Dependent claim 19 recites,
repeating the application of the phase operator to the state vector with the updated first circuit parameter, the application of the mixing operator to the state vector with the updated second circuit parameter, the reading of the state vector, and the computation of the quality of the state vector based on the objective until a stopping criteria is met. - this element constitutes “mere instructions to apply an exception.” (MPEP § 2106.05(f)).
Dependent claim 20 recites,wherein the stopping criteria comprises the quality between iterations changing by less than a
certain amount. - this element constitutes “mere instructions to apply an exception.” (MPEP § 2106.05(f)).
The dependent claims do no integrate the abstract idea into a practical application, nor do they amount to significantly more than the abstract idea.
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.
The following are the references used:
McKiernan et al. (Automated Quantum Programming Via Reinforcement Learning for Combinatorial Optimization, herein McKiernan)
Crooks et al. (Performance of the Quantum Approximate Optimization Algorithm on the Maximum Cut Problem, herein Crooks)
Farhi et al. (A Quantum Approximate Optimization Algorithm, herein Farhi)
Niu et al. (Optimizing QAOA: Success Probability and Runtime Dependence on Circuit Depth, herein Niu)
Boixo et al. (Characterizing Quantum Supremacy in Near-Term Devices, herein Boixo)
Zhuang et al. (Efficient Classical Computation of Quantum Mean Values for Shallow QAOA Circuits, herein Zhuang)
Claim(s) 1, 2, 9, 11, 12, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over McKiernan, in view of Crooks.
Regarding claim 1,
McKiernan teaches,
receiving, at a quantum computer simulator computer program executed by a classical computer and from a client application, a compact description of a problem and an objective to evaluate, a first circuit parameter, and a second circuit parameter; (McKiernan, page 2, section 2, “executing on a classical computing resource… the problem may be described by the specification of a ‘problem instance’ (e.g. a weighted graph) and a ‘reward function’” and page 14, section 4, “optimizing two classical parameters, conventionally denoted γ and β,”, note: a quantum computer simulator computer program executed by a classical computer maps to executing on a classical computing resource. A compact description of a problem maps to a problem instance. An objective to evaluate maps to a reward function. A first circuit parameter, and a second circuit parameter, maps to two classical parameters… γ and β)
initializing, by the quantum computer simulator computer program, a state vector; (McKiernan, page 14, section 4, “QAOA with p=1 consists of optimizing two classical parameters, conventionally denoted γ and β, such that the expectation value of the problem Hamiltonian is maximized by the quantum state defined by |γ,β⟩=e−ıβBe−ıγHC|+⟩⊗n (2) where n denotes the number of qubits (10 in our case), |+⟩⊗n=H⊗n|0⟩ n is the equal-superposition state of all bitstrings,”, note: a state vector maps to the quantum state |γ,β⟩ that the simulator builds. Initializing… a state vector maps to preparing |+⟩⊗n… the equal-superposition state of all bitstrings because the state |γ,β⟩ is built by applying the two operator. Preparing the starting state is initializing the state vector because a state cannot be evolved, read, or scored before it has been set up.)
applying, by the quantum computer simulator computer program, a phase operator to the state vector with the first circuit parameter; (McKiernan, page 14, section 4, “the quantum state defined by |γ,β⟩=e−ıβBe−ıγHC|+⟩⊗n… C denotes the problem Hamiltonian”, note: a phase operate maps to e−ıβBe−ıγHC… where C denotes the problem Hamiltonian. With the first circuit parameter maps to γ because γ is the angle, one of the two optimized parameters, that sets how the phase operator acts.)
applying, by the quantum computer simulator computer program, a mixing operator to the state vector with the second circuit parameter; (McKiernan, page 14, section 4, “the quantum state defined by |γ,β⟩=e−ıβBe−ıγHC|+⟩⊗n… B denotes the ‘mixer’ which is conventionally taken to be B= n j=1Xj.”, note: a mixing operate maps to B denotes the mixer. With the second circuit parameter maps to β.)
reading, by the quantum computer simulator computer program, the state vector; (McKiernan, page 14, section 4, “These expectation values are calculated exactly via matrix multiplication, and not estimated through sampling.”, note: computing the results from the full stored state means the program accesses, reads, the state-vector entries.)
computing, by the quantum computer simulator computer program, a quality of the state vector based on the objective; (McKiernan, page 14, section 4, “compute the solution quality as the expectation value of the cost Hamiltonian”, note: computing a quality maps to compute the solution quality. Based on the objective maps to as the expectation value of the cost Hamiltonian, which is the objective. McKiernan has two vectors that could be called a state vector, the reinforcement-learning observation and the quantum state built by the simulator. The claim refers to the quantum state. The quality is the cost of the Hamiltonian’s expectation value. B is just the bitstring obtained by measuring the quantum state and the quality score. So the state vector is |ψ⟩ and the quality is the cost Hamiltonian’s expectation value taken from |ψ⟩)
and updating, by the quantum computer simulator computer program, the first circuit parameter and the second circuit parameter based on the quality. (McKiernan, page 14, section 4, “optimizing two classical parameters, conventionally denoted γ and β, such that the expectation value of the problem Hamiltonian is maximized”, note: updating the first circuit parameter and the second circuit parameter maps to optimizing two classical parameters. Based on the quality maps to such that the expectation value… is maximized.)
McKiernan does not teach,
A method for low-cost simulation of quantum algorithms, comprising:
precomputing, by the quantum computer simulator computer program, a diagonal vector comprising diagonal elements of a phase Hamiltonian;
Crooks teaches,
A method for low-cost simulation of quantum algorithms, comprising: (Crooks, abstract, “find good approximate solutions of hard combinatorial problems… a quantum circuit simulator implemented with TensorFlow.”)
precomputing, by the quantum computer simulator computer program, a diagonal vector comprising diagonal elements of a phase Hamiltonian; (Crooks, page 1, “a cost Hamiltonian which is diagonal in the computational basis… for which any bit string gives an energy”, note: a phase Hamiltonian maps to a cost Hamiltonian. Diagonal elements maps to diagonal in the computational basis. A diagonal vector maps to the per-bit string energy values.)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of McKiernan and Crooks because Crooks encodes the costs as a Hamiltonian that’s diagonal in the computational basis. Each answer’s cost becomes one number that is worked out once and reused every time the state is scores, so the simulation stays cheap. This allows for efficiency.
Regarding claim 2,
The combination of McKiernan and Crooks teaches,
The method of claim 1, wherein the compact description of the problem comprises a computer program that computes a cost function to be optimized. (Crooks, abstract, “a quantum circuit simulator implemented with TensorFlow.” And page 1, “we encode the graph structure into a cost Hamiltonian”, note: a computer program maps to a quantum circuit simulator implemented with TensorFlow. Computes a cost function maps to encode the graph structure into a cost Hamiltonian.)
Regarding claim 9,
The combination of McKiernan and Crooks teaches,
The method of claim 1, further comprising: repeating, by the quantum computer simulator computer program, the steps of applying the phase operator to the state vector with the updated first circuit parameter, applying the mixing operator to the state vector with the updated second circuit parameter, reading the state vector, and computing the quality of the state vector based on the objective until a stopping criteria is met. (McKiernan, page 2, section 2, “repeated until the agent ‘wins’, wherein the reward exceeds some threshold”)
Claims 11, 12, and 19 is a non-transitory computer readable storage medium claim, A non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising: (Crooks, page 3, “we implemented a simple quantum virtual machine (a simulation of a gate based quantum computer) on top of TensorFlow”), that corresponds to method claims 1, 2, and 9, respectively. Otherwise, they are not patentably distinguishable. Therefore, 11, 12, and 19 are rejected for the same reasons as claims 1, 2, and 9, respectively.
Claim(s) 3, 5, 13, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over McKiernan, in view of Crooks, and in further view of Farhi.
Regarding claim 3,
Farhi teaches,
The method of claim 1, wherein the objective to evaluate comprises an expectation value that is an inner product between the phase operator and the state vector. (Farhi, page 3, “Let Fp be the expectation of C in this state Fp(γ,β) = ⟨γ,β|C |γ,β⟩.”, note: an expectation value maps to the expectation of C in this state. An inner product between the phase operator and the state vector maps to the equation.)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of McKiernan, Crooks, and Farhi because Farhi shows that scoring a state with the expectation value is the standard QAOA objective. On a classical simulator it can be worked out directly and from the state’s amplitudes, instead of being estimated by running the circuit many times and sampling which makes it cheap and precise.
Regrading claim 5,
Farhi teaches,
The method of claim 1, further comprising: receiving, by the quantum computer simulator computer program, an initial vector, wherein the initial vector comprises a vector having a length of 2n and elements equal to 12n2, wherein n is a number of qubits in the state vector. (Farhi, page 2, equation 5, “The initial state |s⟩ will be the uniform superposition over computational basis states: |s⟩ = 1 √ 2n X z |z⟩”, note: a length of 2n… wherein n is a number of qubits in the state vector maps to the sum of z over the 2n basis states of n qubits. Elements equal to 12n2 maps to the coefficient 1 √ 2n.)
Claims 13 and 15 is a non-transitory computer readable storage medium claim, A non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising: (Crooks, page 3, “we implemented a simple quantum virtual machine (a simulation of a gate based quantum computer) on top of TensorFlow”), that corresponds to method claims 3 and 5, respectively. Otherwise, they are not patentably distinguishable. Therefore, 13 and 15 are rejected for the same reasons as claims 3 and 5, respectively.
Claim(s) 4, 6, 14, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over McKiernan, in view of Crooks, and in further view of Niu.
Regarding claim 4,
Niu teaches,
The method of claim 1, wherein the objective to evaluate comprises an expectation value that is a sum of selected square absolute values of state vector entries. (Niu, page 3, section 2, ˆ HC =|N N|= 1 2 (σz N +IN) … “F =|N|Up|1 |2 = 1|U† p ˆHCUp|1. This is equivalent to the success probability, so we will use them interchangeably henceforth. We can then treat 3 state transfer as a special kind of maximization satisfaction problem, except that the cost function F”, note: the objective to evaluate maps to the cost function F (F is the thing Niu maximizes). An expectation value maps to 1|U† p ˆHCUp|1 (F is the expectation value). A sum of selected square absolute values of state vector entries maps to |N|Up|1 |2 and HC =|N N| (HC just picks out the chosen answers, so this values adds up the squared sizes of exactly those picked entries of the state))
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of McKiernan, Crooks, with Niu because Niu scores by success probability, the weight sitting on the desired answers, and treats each setting as the amount of time the state evolves under each operator. Success probability directly measures the chance of getting the right answer, the thing being maximized, and the time view gives each setting a concrete physical meaning.
Regarding claim 6,
Niu teaches,
The method of claim 1, wherein the first circuit parameter corresponds to a time for which evolution is performed in the phase operator, and the second circuit parameter corresponds to a time for which evolution is performed in the mixing operator. (Niu, page 2, section 2, “each kth QAOA iteration consists of a unitary evolution under ˆ HB for time δB k then followed by a unitary evolution under ˆ HC for time δC k.” note: a first circuit parameter… a time for which evolution is performed in the phase operator maps to a unitary evolution under HC for time δC k (HC is the phase operator and δC k is how long it runs). Second circuit parameter… in the mixing operator maps to a unitary evolution under ˆ HB for time δB k (HB is the mixer and δB k is how long it runs))
Claims 14 and 16 is a non-transitory computer readable storage medium claim, The non-transitory computer readable storage medium of claim 11, (Crooks, page 3, “we implemented a simple quantum virtual machine (a simulation of a gate based quantum computer) on top of TensorFlow”), that corresponds to method claims 4 and 6, respectively. Otherwise, they are not patentably distinguishable. Therefore, claims 14 and 16 are rejected for the same reasons as claims 4 and 6, respectively.
Claim(s) 7, 10, 17, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over McKiernan, in view of Crooks, and in further view of Zhuang.
Regarding 7,
Zhuang teaches,
The method of claim 1, wherein the step of applying, by the quantum computer simulator computer program, the phase operator to the state vector with the first circuit parameter comprises: multiplying a cost vector by -iγj and then exponentiating element-by-element, resulting in a phase vector; and calculating an element-by-element product between the state vector and the phase vector. (Zhuang, page 2, “the ˆ C is diagonal in the computational basis vector |z such that z| ˆC|z = C(z)… ˆUC(γ) = e−iγˆ”, note: a cost vector maps to z| ˆC|z = C(z) because this is the list of costs, one per answer. Multiplying a cost vector by – iγj… exponentiating… to obtain a phase vector maps to ˆUC(γ) = e−iγˆ because that’s the same math, applied to the diagonal, gives the list of phases. An element-by-element product between the state vector and the phase vector maps to applying the diagonal e−iγˆ because a diagonal operator multiples each state number by its matching value, one for one.)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of McKiernan, Crooks with Zhuang because Zhuang writes the phase operator as a diagonal one and ends the loop once the optimizer converges. A diagonal operator is cheap to apply, each state number just gets multiplied by its own matching value, and stopping at convergence ends the run once the score stops changing much, so no extra rounds are wasted.
Regarding claim 10,
Zhuang teaches,
The method of claim 19, wherein the stopping criteria comprises the quality between iterations changing by less than a certain amount. (Zhuang, page 1, “calls for classical optimizer to find iterative parameters until con vergence condition is reached”, note: the stopping criteria is met when the quality… between iterations changes by less than a certain amount maps to until convergence condition is reached because convergence means the score has stopped changing much from one round to the next.)
Claims 17 and 20 is a non-transitory computer readable storage medium claim, The non-transitory computer readable storage medium of claim 11, (Crooks, page 3, “we implemented a simple quantum virtual machine (a simulation of a gate based quantum computer) on top of TensorFlow”), that corresponds to method claims 7 and 10, respectively. Otherwise, they are not patentably distinguishable. Therefore, claims 17 and 20 are rejected for the same reasons as claims 7 and 10, respectively.
Claim(s) 8 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over McKiernan, in view of Crooks, and in further view of Boixo.
Regrading claim 8,
Boixo teaches,
The method of claim 1, wherein the step of applying the mixing operator to the state vector with the second circuit parameter comprises: performing, by the quantum computer simulator computer program, a Fast Uniform SU(2) Transform on the state vector; (Boixo, page 14, “we apply Usq to the pairs of amplitudes whose indices differ in the k-th bits of their binary index… applying Usq to every pair of amplitudes thatare2k elements apart.”. note: SU(2) Transform on the state vector maps to apply Usq to the pairs of amplitudes because it’s applying one little single qubit spin to the state. Fast maps to ever pair of amplitudes that are 2^k elements apart because it is handled in tiny 2x2 pieces instead of one giant multiple.)
Boixo does not teach,
and applying, by the quantum computer simulator computer program, the phase operator to the state vector.
McKiernan teaches,
and applying, by the quantum computer simulator computer program, the phase operator to the state vector. (McKiernan, page 14, section 4, “the quantum state defined by |γ,β⟩=e−ıβBe−ıγHC|+⟩⊗n… C denotes the problem Hamiltonian”)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of McKiernan, Crooks, and Boixo because Boixo applies the mixer in tiny pieces, updating the state’s numbers two at a time, instead of one big multiply. Doing it in small pieces keeps the step cheap to run on a normal computer as the state gets bigger.
Claim 18 is a non-transitory computer readable storage medium claim, The non-transitory computer readable storage medium of claim 11, (Crooks, page 3, “we implemented a simple quantum virtual machine (a simulation of a gate based quantum computer) on top of TensorFlow”), that corresponds to method claim 8 respectively. Otherwise, they are not patentably distinguishable. Therefore, claim 18 is rejected for the same reasons as claim 8, respectively.
Conclusion
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/U.P.T./Examiner, Art Unit 2124
/MIRANDA M HUANG/Supervisory Patent Examiner, Art Unit 2124
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