8DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The amendment filed 01/02/2026 has been received and considered. Claims 2 and 10 are cancelled. Claims 1, 3-9, and 11-20 are presented for examination.
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, 3-9, and 11-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claim 1, Step 1: a method (process = 2019 PEG Step 1 = yes)
Independent claim 1, Step 2A, Prong One: claim recites:
determining a quadratic form corresponding to the optimization problem; identifying a plurality of vectors that represents the quadratic form; (mathematical concepts)
setting a dimensionality of each vector included in the plurality of vectors, the dimensionality indicating a number of terms included in each vector, the setting of the dimensionality including: (mental concepts)
computing a square of each term included in the vector; summing the square of each term; and computing a square root of the sum of the square of each term; generating a first set of unit vectors based on the dimensionality of one or more vectors from the plurality of vectors and based on a coefficient corresponding to each of the vectors; performing one or more unitary operations to quantize each respective unit vector included in the first set as a respective indexed quantum state; and setting a respective final quantum state corresponding to each respective indexed quantum state (mathematical concepts)
These limitations are substantially drawn to mathematical concepts: mathematical relationships, formulas or equations, and calculations and mental concepts: observation, evaluation, judgment, opinion. Information and/or data also fall within the realm of abstract ideas because information and data are intangible. See Electric Power Group1 (Electric Power hereinafter): “Information… is an intangible”.
As to the limitations "determining a quadratic form corresponding to the optimization problem”, the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. See for example in the Specification:
"[0035]… the quadratic form may be represented by a matrix of coefficients and one or more vectors that correspond to the matrix of coefficients as described above in relation to Equations (1)-(3)".
As to the limitations "identifying a plurality of vectors that represents the quadratic form”, the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. See for example in the Specification (underline emphasis added):
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As to the limitations "generating a first set of unit vectors based on the dimensionality of one or more vectors from the plurality of vectors and based on a coefficient corresponding to each of the vectors”, the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. See for example in the Specification (underline emphasis added):
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As to the limitations "performing one or more unitary operations to quantize each respective unit vector included in the first set as a respective indexed quantum state", the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. See for example in the Specification:
[0023]… Unitary operations, Ui and/or Vj, corresponding to each row and/or each column of a vector coefficient matrix, A, may be applied to the quantum registers according to the following relationships:
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As to the limitations "setting a respective final quantum state corresponding to each respective indexed quantum state", the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. See for example in the Specification:
[0039]… setting the final quantum state may be facilitated by a quantum rounding process as described above and in relation to method 400 of Figure 4.
[0026]… Based on the measurement of the resulting qubit and the related probability of the dot product being positive or negative, a final quantum state corresponding to the quadratic form may be set
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As to the limitations "setting a dimensionality of each vector included in the plurality of vectors, the dimensionality indicating a number of terms included in each vector", the term "setting" is not elaborated but merely repeated in the Application description. "Setting" a value of a mathematical term is mental in nature (mental processes including a judgment, opinion).
If a claim limitation, under its broadest reasonable interpretation, covers abstract ideas, then it falls within groupings of abstract ideas (2019 PEG Step 2A, Prong One: Abstract Idea Grouping? = Yes).
Independent claim 1, Step 2A, Prong Two: As to the limitations “obtaining an optimization problem that includes a plurality of discrete variable choices", these limitations describe the concept of “mere data gathering”, which corresponds to the concepts identified as abstract ideas by the courts. As to these limitations, they are not elaborated but merely repeated in the Application description. Data gathering, including when limited to particular content does not change its character as information, is also within the realm of abstract ideas. Data gathering has not been held by the courts to be enough to qualify as “significantly more”. They are considered insignificant extra-solution activity. See Electric Power.
As to the limitations "performing one or more operations to configure the optimization problem in a manner that allows for the optimization problem to be solved using a quantum computing system" and "determining, using the quantum computing system, one or more solutions to the optimization problem based on the final quantum state corresponding to each respective indexed quantum state", they represent no more than just “apply it” limitations, because they recite only the idea of a solution or outcome, i.e., they fail to recite details of how a solution to a problem is accomplished.
This judicial exception is not integrated into a practical application (2019 PEG Step 2A, Prong Two: Additional elements that integrate the Judicial exception/Abstract idea into a practical application? = NO).
Independent claim 1, Step 2B: As discussed with respect to Step 2A, Prong two, claim 1 recites data gathering, these limitations are recited at a high level of generality; and therefore, remain insignificant extra-solution activity even upon reconsideration.
As discussed with respect to Step 2A, Prong two, limitations reciting only the idea of a solution or outcome are just “apply it” limitations, because they fail to recite details of how a solution to a problem is accomplished. See MPEP 2106.05(f)(1). The limitations are so broad that little is known about how the claimed "configure the optimization problem in a manner that allows for the optimization problem to be solved using a quantum computing system" and "determining, using the quantum computing system, one or more solutions to the optimization problem" are performed. There is no elaboration of any special meanings for these amended limitations in the claims and Specification. The specification merely reads (underline emphasis added):
"[0017]… a system and a method of quantizing quadratic forms such that the vectors corresponding to the quadratic forms may be represented by quantum states associated with a quantum computing system, and one or more feasible solutions to the optimization problems with which the quadratic forms are associated may be determined by the quantum computing system…
[0049]… Because quantum computer systems operate probabilistically, multiple copies of each indexed quantum state may facilitate more accurate determination of whether a resulting qubit is likely to be positive or negative".
Thus, taken alone the individual additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the additional elements as an ordered combination adds nothing that is not already present when looking at the additional elements taken individually. There is no indication that their combination improves the functioning of a computer itself or improves any other technology (underline emphasis added). Therefore, the claim does not amount to significantly more than the abstract idea itself (2019 PEG Step 2B: NO).
Claims 9 and 17 recite substantially the same elements as claim 1 and are rejected for the same reasons above.
Independent claims 9 and 17, Step 2A Prong two and 2B: As to the further additional
elements computer-readable storage media and a system comprising processors, they are recited at a high level of generality and as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Their collective functions merely provide conventional computer implementation. The use of a computer to implement the abstract idea of a mathematical or mental algorithm has not been held by the courts to be enough to qualify as “significantly more”. The implementation on a computing system is described in the specification (underline emphasis added):
"[0056] Generally, the processor 510 may include any suitable special-purpose or general purpose computer, computing entity, or processing device".
Dependent claims, Step 2A, Prong One: The claim limitations further the abstract ideas concepts of their independent claims. (See Independent claim 1, Step 2A, Prong One above).
As to the limitations "3/11/18… the coefficient corresponding to each of the vectors is determined from a coefficient matrix, a particular coefficient representing an intersection between a matrix row and a matrix column”, the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. See for example in the Specification (underline emphasis added):
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As to the unitary operations limitations, the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. (See Independent claim 1, Step 2A, Prong One above).
As to the limitations "4/12/19… determining a final coefficient based on a first value of the first quantum register and a second value of the second quantum register after the threshold amplitude is exceeded", the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. See for example in the Specification (underline emphasis added): "[0046]… determining the final coefficient may be facilitated according to Equation (10)".
As to the limitations "4/12/19… setting a first quantum register and a second quantum register as zeroes, the first quantum register representing a quantum state index and the second quantum register representing the unit vectors; setting a threshold amplitude for the first quantum register and the second quantum register", "7/15… wherein the optimization problem is a correlation clustering problem involving a plurality of data points and wherein each of the one or more solutions to the optimization problem includes partitioning one or more of the data points of the plurality into one or more groups", and "8/16… wherein the optimization problem is a maximum cut problem involving a graph dataset including a plurality of nodes and a plurality of edges connecting each node of the plurality of nodes wherein each of the one or more solutions to the optimization problem includes a division of the graph dataset into a first set of nodes and a second set of nodes that maximizes a number of edges between nodes included in the first set of nodes and nodes included in the second set of nodes", these limitations are substantially drawn to mental concepts. As to the setting quantum registers and setting a threshold amplitude for quantum registers limitations, the setting terms are not elaborated but merely repeated in the Application description. As to the limitations partitioning data points into groups, they are mental in nature. These limitations can be characterized as entailing a user judging, i.e. processing, information and/or data, that can be performed in the human mind or by a human using a pen and paper. As to the graphs and divisions of graph dataset into nodes limitations, they are mental in nature. These activities can be characterized as entailing a user performing graph operations that can be performed in the human mind or by a human using a pen and paper.
As to the limitations "5/13/20… wherein setting a respective final quantum state corresponding to each respective indexed quantum state and determining the one or more solutions to the optimization problem comprises: generating one or more copies of each respective indexed quantum state; setting a random quantum state corresponding to each of the generated copies; applying a Hadamard transformation to the random quantum state corresponding to each of the generated copies… determining whether a probability of the resulting qubit is more likely to be positive or more likely to be negative based on the measuring; and setting the respective final quantum state corresponding to each respective indexed quantum state as -1 responsive to the probability of the resulting qubit being more likely to be negative", the limitations, as drafted and under their broadest reasonable interpretation, are mathematical concepts. (See Independent claim 1, Step 2A, Prong One above).
If a claim limitation, under its broadest reasonable interpretation, covers abstract ideas, then it falls within groupings of abstract ideas (2019 PEG Step 2A, Prong One: Abstract Idea Grouping? = Yes).
Dependent claims, Step 2A Prong two: The claims recite the additional elements quantum registers and qubits.
As to the limitations “5/13/20… measuring a resulting qubit based on the Hadamard transformation applied to the random quantum state", these limitations describe the concept of “mere data gathering”. (See Independent claim 1, Step 2A Prong two above).
As to the limitations "6/14… wherein the optimization problem is a community detection problem relating to users on a social media network and wherein each of the one or more solutions to the optimization problem includes one or more groups of users on the social media network", they amount to generally linking the use of a judicial exception to a particular technological environment.
This judicial exception is not integrated into a practical application of the exception (2019 PEG Step 2A, Prong Two: Additional elements that integrate the Judicial exception/Abstract idea into a practical application? = NO).
Dependent claims Step 2B: As discussed with respect to Step 2A, Prong two, the claims recite the additional elements quantum registers and qubits at a high level of generality and as performing generic computer functions routinely used in computer applications. (See Independent claims, Step 2A Prong two and 2B above).
As discussed with respect to Step 2A, Prong two, the claims recite data gathering, these limitations are recited at a high level of generality; and therefore, remain insignificant extra-solution activity even upon reconsideration.
As to the limitations identified as generally linking the use of a judicial exception to a particular technological environment. see MPEP 2106.05(h) Field of Use and Technological Environment [R-10.2019], 2106.05(e) Other Meaningful Limitations [R-10.2019].
Therefore, the claims do not amount to significantly more than the abstract idea itself (2019 PEG Step 2B: NO).
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) 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.
Examiner would like to point out that any reference to specific figures, columns and lines should not be considered limiting in any way, the entire reference is considered to provide disclosure relating to the claimed invention.
Claims 1, 3, 4, 6, 9, 11, 12, 14, and 17-19 are rejected under 35 U.S.C. 103(a) as being unpatentable over Christian Negre et al., (Negre hereinafter), "Detecting multiple communities using quantum annealing on the D-Wave system" (see IDS dated 10/06/2023), taken in view of Andrew M. Childs, (Childs hereinafter), "Quantum algorithm for systems of linear equations with exponentially improved dependence on precision" (see IDS dated 03/30/2022).
As to claim 1, Negre discloses a method, comprising: obtaining an optimization problem that includes a plurality of discrete variable choices (see "maximum modularity for at most two communities is given by… (7) which are clearly unconstrained quadratic optimization problems, suitable to be solved by quantum annealers" in page 4, col. 2, 2nd paragraph); performing one or more operations to configure the optimization problem in a manner that allows for the optimization problem to be solved using a quantum computing system (see 'the quantum computer can render a highly optimized community structure' in page 8, next to last paragraph) determining a quadratic form corresponding to the optimization problem (see "Quantum computers of the annealer type, such as the D-Wave 2X and 2000Q, minimize the Ising objective function as follows making use of the quantum entanglement effect [31]. The objective function can be written as follows… (1)… The formulation where variables take values of either 0 or 1 is called the quadratic unconstrained binary optimization or QUBO formulation and it is an alternative representation that can easily be translated to or from the Ising model" in page 3, col. 1, last paragraph to col. 2, 1st paragraph); identifying a plurality of vectors that represents the quadratic form, setting a dimensionality of each vector included in the plurality of vectors, the dimensionality indicating a number of terms included in each vector (see "dimensionality" as "n", "Since each node must be in exactly one community, the following constraint needs to be fulfilled… (9)
Let | x1,j |
| x2,j |
| . |
xj = | . |,
| . |
| xn,j |
be the vector state, then… (10)" in page 5, col. 1, last paragraph to col. 2, 1st paragraph);
the setting of the dimensionality including: computing a square of each term included in the vector; summing the square of each term – see in page 6, 1st paragraph:
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… generating a first set of unit vectors based on the dimensionality of one or more vectors from the plurality of vectors and based on a coefficient corresponding to each of the vectors (see "x is a vector such that xi ϵ {0,1}, 1 is a vector of all ones" in page 5, col. 1, last paragraph to col. 2, 1st paragraph;
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in page 5, last paragraph)… setting a respective final quantum state corresponding to each respective indexed quantum state; and determining, using the quantum computing system (see 'quantum computers… quantum computer' in page 3, col. 1, last paragraph to col. 2, 1st paragraph), one or more solutions to the optimization problem based on the final quantum state corresponding to each respective indexed quantum state (see 'superposition lasts until an outside event causes it to collapse into either a “-1” or a “+1” state. The result of the annealing process is a low-energy ground state s, consisting of an Ising spin for each qubit value ϵ {−1,+1}. This allows quantum computers to solve NP-hard complex problems including optimization' in page 3, col. 2, 1st paragraph).
Negre does not disclose, but Childs discloses computing a square root of the sum of the square of each term – see page 16, 4.1 A quantum walk for any Hamiltonian, 2nd paragraph:
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… performing one or more unitary operations to quantize each respective unit vector included in the first set as a respective indexed quantum state (see "QLSP is equivalent to applying the (non-unitary) operator A-1 to the state |b>… represent A-1, the operator we would like to perform, as a linear combination of unitaries we know how to perform" in page 5, 2nd paragraph).
Negre and Childs are analogous art because they are related to quadratic form optimization.
Therefore, it would have been obvious to one of ordinary skill in this art before the effective filing date of the claimed invention to use Childs with Negre, because Childs shows "how to circumvent the limitations of phase estimation, giving an algorithm for the QLSP that uses ideas from recent quantum simulation algorithms to apply the inverse of a matrix directly" (see page 1, last paragraph), and as a result, Childs reports that his "improved performance… may be especially useful when the quantum linear systems algorithm is used as a subroutine polynomially many times, so that its output must have inverse polynomial precision to guarantee that the final algorithm succeeds with high probability. An algorithm with poly(1/ϵ) scaling incurs a polynomial overhead in running time due to error reduction, whereas an algorithm with poly(log(1/ϵ)) scaling incurs only logarithmic overhead" (see page 2, 3rd paragraph).
As to claim 3, Negre discloses wherein the coefficient corresponding to each of the vectors is determined from a coefficient matrix, a particular coefficient representing an intersection between a matrix row and a matrix column (see "Quantum computers of the annealer type, such as the D-Wave 2X and 2000Q, minimize the Ising objective function as follows making use of the quantum entanglement effect [31]. The objective function can be written as follows: O(h,J,s) = ∑i hisi + ∑i<j Jijsisj (1)" in page 3, col. 1, last paragraph to col. 2, 1st paragraph); and Childs discloses the unitary operations include first unitary operations corresponding to each matrix row and second unitary operations corresponding to each matrix column (see "implementing a linear combination of unitary operations… Let M = ∑i αiUi be a linear combination of unitary matrices Ui with αi > 0" in page 6, next to last paragraph).
As to claim 4, Childs discloses wherein performing the unitary operations to quantize each respective unit vector and setting a respective final quantum state corresponding to each respective indexed quantum state comprises: setting a first quantum register and a second quantum register as zeroes, the first quantum register representing a quantum state index and the second quantum register representing the unit vectors; setting a threshold amplitude for the first quantum register and the second quantum register (see "setting a threshold amplitude" as "setting the jth qubit of a special clock register to 1", "At time tj, the algorithm can indicate that it wants to stop by setting the jth qubit of a special clock register to 1, where the algorithm starts with all clock qubits set to 0" in page 23, 2nd paragraph); performing first unitary operations on the first quantum register and second unitary operations on the second quantum register until the threshold amplitude is exceeded (see "QLSP is equivalent to applying the (non-unitary) operator A-1 to the state |b>… represent A-1, the operator we would like to perform, as a linear combination of unitaries we know how to perform… consider implementing the operator M = U0+U1, where U0 and U1 are unitaries with known quantum circuits… If we have the ability to create multiple copies of |ψ> or reflect about |ψ>, then we can create the output state with high probability by repeating this process until we get the desired measurement outcome or by using amplitude amplification" in page 5, 2nd & 3rd paragraphs), wherein: the first unitary operations and the second unitary operations are related to the coefficients corresponding to the unit vectors (see "implementing a linear combination of unitary operations… Let M = ∑i αiUi be a linear combination of unitary matrices Ui with αi > 0… The operation U := |i><i| ⊗ Ui implements Ui conditioned on the value of a control register. The operation V maps |0m> to 1/√α ∑i √αi|i, where α := ||α||1 = ∑i αi" in page 6, last paragraph); and performing the first unitary operations and the second unitary operations increases an amplitude of the first quantum register and the second quantum register (see "consider implementing the operator M = U0+U1, where U0 and U1 are unitaries with known quantum circuits… If we have the ability to create multiple copies of |ψ> or reflect about |ψ>, then we can create the output state with high probability by repeating this process until we get the desired measurement outcome or by using amplitude amplification" in page 5, 3rd paragraph); and determining a final coefficient based on a first value of the first quantum register and a second value of the second quantum register after the threshold amplitude is exceeded (see "consider QLSP as an inherently quantum problem, where the goal is to output a quantum state |x>" in page 2, 2nd paragraph).
As to claim 6, Negre discloses wherein the optimization problem is a community detection problem relating to users on a social media network and wherein each of the one or more solutions to the optimization problem includes one or more groups of users on the social media network (see "problem in combinatorial optimization is partitioning a network into communities of densely connected nodes; where the connectivity between nodes inside a particular community is large compared to the connectivity between nodes belonging to different ones. This problem is known as community detection… in… social sciences" in page 1, 1st paragraph; "The use of networks spans across many scientific domains… social media speeds up human communication" in page 1, next to last paragraph).
As to claims 9, 11, 12, 14, and 17-19, these claims recite storage media and a system for performing the method of claims 1, 3, 4, and 6. Negre discloses "Quantum computers of the annealer type, such as the D-Wave 2X and 2000Q" (see page 3, col. 1, last paragraph) for performing a method that teaches claims 1, 3, 4, and 6. Therefore, claims 9, 11, 12, 14, and 17-19 are rejected for the same reasons given above.
Claims 5, 13, and 20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Negre taken in view of Childs as applied to claims 4, 12, and 19 above, and further in view of Joran van Apeldoorn, (Apeldoorn hereinafter), Quantum SDP-Solvers: Better upper and lower bounds (see IDS dated 03/30/2022).
As to claims 5, 13, and 20, Childs discloses wherein setting a respective final quantum state corresponding to each respective indexed quantum state and determining the one or more solutions to the optimization problem comprises: generating one or more copies of each respective indexed quantum state (see "create copies of the input state, we can repeat this process O((α/||M|ψ||)2) times until the measurement yields the desired outcome" in page 7, 4th paragraph); setting a random quantum state corresponding to each of the generated copies (see "consider implementing the operator M = U0+U1, where U0 and U1 are unitaries with known quantum circuits… If we have the ability to create multiple copies of |ψ> or reflect about |ψ>, then we can create the output state with high probability by repeating this process until we get the desired measurement outcome or by using amplitude amplification" in page 5, 2nd & 3rd paragraphs)… determining whether a probability of the resulting qubit is more likely to be positive or more likely to be negative based on the measuring (see "consider a variable-time quantum algorithm that prepares a state |ψsucc> probabilistically… the algorithm has a single-qubit flag register that is measured at the end of the algorithm: if we observe the outcome 1 on measuring this register, we have successfully prepared the state |ψsucc>. Let psucc denote the probability of obtaining the desired outcome. If the algorithm’s complexity is tm, then simply repeating the algorithm O(1/psucc) times will yield an algorithm that creates the state |ψsucc> with high probability" in page 23, 5th paragraph); and setting the respective final quantum state corresponding to each respective indexed quantum state as -1 responsive to the probability of the resulting qubit being more likely to be negative (see "consider QLSP as an inherently quantum problem, where the goal is to output a quantum state |x>" in page 2, 2nd paragraph).
Negre and Childs do not disclose, but Apeldoorn discloses applying a Hadamard transformation to the random quantum state corresponding to each of the generated copies; measuring a resulting qubit based on the Hadamard transformation applied to the random quantum state (see "initialize two log(n)-qubit registers in a maximally entangled state 1/√n ∑n-1j=0 |j>|j>. This can be done using log(n) Hadamard and CNOT gates" in page 63, last paragraph; "a unit-cost QRAM gate that allows us to store and retrieve qubits in a memory" in page 10, last paragraph).
Negre, Childs, and Apeldoorn are analogous art because they are related to quadratic form optimization.
Therefore, it would have been obvious to one of ordinary skill in this art before the effective filing date of the claimed invention to use Apeldoorn with Negre and Childs, because Apeldoorn develops "new techniques for quantum algorithms, for instance a general way to efficiently implement smooth functions of sparse Hamiltonians, and a generalized minimum-finding procedure" (see page 1, 1st paragraph), and as a result, Apeldoorn reports that "our generalized quantum minimum-finding algorithm, which we are going to apply to finding an approximation of the ground state energy of a Hamiltonian… has the benefit over binary search that it removes a logarithmic factor from the complexity" (see page 58, last paragraph).
Claims 7, 8, 15, and 16 are rejected under 35 U.S.C. 103(a) as being unpatentable over Negre taken in view of Childs as applied to claims 1 and 9, and further in view of Chaitanya Swamy, (Swamy hereinafter), Correlation Clustering: Maximizing Agreements via Semidefinite Programming (see IDS dated 03/30/2022).
As to claims 7 and 15, Negre and Childs do not disclose, but Swamy discloses wherein the optimization problem is a correlation clustering problem involving a plurality of data points and wherein each of the one or more solutions to the optimization problem includes partitioning one or more of the data points of the plurality into one or more groups (see "Abstract We consider the Correlation Clustering problem" in page 1, 1st paragraph; "2 hyperplanes passing through the origin independently at random with normals distributed uniformly in the unit sphere. Let q1, q2 be the normals to the hyperplanes. These partition the vertices into 4 sets, some possibly empty, based on xv. qi. Let Rs1,s2 = |{v|: (-1)sixv . qi | ≥0, | i = 1, 2} where si | ϵ {0, 1}. Each such non-empty set defines a cluster" in page 2, 4th paragraph).
Negre, Childs, and Swamy are analogous art because they are related to quadratic form optimization.
Therefore, it would have been obvious to one of ordinary skill in this art before the effective filing date of the claimed invention to use Swamy with Negre and Childs, because Swamy considers "a semidefinite programming relaxation of the problem and round its optimal solution… two rounding procedures", and as a result, Swamy shows "that by randomly choosing one of these we obtain a clustering in which the total weight of agreements is at least 0.7666 times the optimal solution value. Thus choosing the better of the two rounding procedures gives a 0.7666-approximation algorithm" (see page 1, next to last paragraph).
As to claims 8 and 16, Swamy discloses wherein the optimization problem is a maximum cut problem (see "We extend the Goemans-Williamson rounding for MAX CUT by choosing multiple hyperplanes" in page 2, 4th paragraph) involving a graph dataset including a plurality of nodes and a plurality of edges connecting each node of the plurality of nodes (see "We consider the Correlation Clustering problem introduced in [2]. Given a graph G = (V,E) where each edge is labeled either “+” (similar) or “−” (different), we want to cluster the nodes so that the + edges lie within the clusters and the − edges lie between clusters" in page 1, 1st paragraph), wherein each of the one or more solutions to the optimization problem includes a division of the graph dataset into a first set of nodes and a second set of nodes that maximizes a number of edges between nodes included in the first set of nodes and nodes included in the second set of nodes (see "2 hyperplanes passing through the origin independently at random with normals distributed uniformly in the unit sphere. Let q1, q2 be the normals to the hyperplanes. These partition the vertices into 4 sets, some possibly empty, based on xv. qi. Let Rs1,s2 = |{v|: (-1)sixv . qi | ≥0, | i = 1, 2} where si | ϵ {0, 1}. Each such non-empty set defines a cluster" in page 2, 4th paragraph).
Response to Arguments
Regarding the rejections under 112, the amendment corrected the deficiencies pointed out, and those objections are withdrawn.
Regarding the rejections under 101, Applicant's arguments have been considered, but they are not persuasive. Applicant argues, (see page 11, next to last paragraph to page 12, 3rd paragraph):
‘… amended claims 1, 9, and 17 recite elements related to configuring an optimization problem in a manner that allows for it to be solved using a quantum computing system. Therefore, the claims recite elements that improve the technical field of quantum computing by expanding the capabilities of quantum computing systems. As such, rather than being merely directed toward an abstract idea, the claims provide a specific and tangible practical application that improves a technological field…’
The MPEP reads (underline emphasis added):
‘2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]… (1) Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it"…
By way of example, in Intellectual Ventures… In addition to the abstract idea, the claims also recited the additional element of modifying the underlying XML document in response to modifications made in the dynamic document.… Although the claims purported to modify the underlying XML document in response to modifications made in the dynamic document, nothing in the claims indicated what specific steps were undertaken other than merely using the abstract idea in the context of XML documents. The court thus held the claims ineligible, because the additional limitations provided only a result-oriented solution and lacked details as to how the computer performed the modifications, which was equivalent to the words "apply it"’.
Examiner's response: Applicant's argument is not persuasive, because as to the limitations "performing one or more operations to configure the optimization problem in a manner that allows for the optimization problem to be solved using a quantum computing system" and "determining, using the quantum computing system, one or more solutions to the optimization problem based on the final quantum state corresponding to each respective indexed quantum state", they are recited so generically (no details whatsoever are provided) that they represent no more than just “apply it” limitations. These claim limitations recite only the idea of a solution or outcome i.e., these claim limitations fail to recite details of how a solution to a problem is accomplished. There is no elaboration of any special meanings for these amended limitations in the claims and Application description. (See MPEP 2106.05(f)(1) supra and Independent claim 1, Step 2B above).
Regarding the rejections under 103, Applicant's arguments have been considered, but they are not persuasive. Applicant argues, (see page 12, 4th paragraph to page 13, next to last paragraph):
‘… this equation is part of showing the derivation of another equation that uses "n" as an input, not as an output. Therefore, this equation does not appear to have anything to do with determining "n" even if "n" is construed as the dimensionality of the vector…'
Examiner does not see these argued features expressed in the claims: '"n"… as an output… determining "n"'. Examiner is not allowed to bring limitations set forth in the description into the claims. Although a claim should be interpreted in light of the Specification disclosure, it is generally considered improper to read limitations contained in the Specification into the claims. See In re Prater2 and In re Winkhaus3, which discuss the premise that one cannot rely on the Specification to impart limitations to the claim that are not recited in the claim. Claims must stand on their own. Setting a number of terms included in a vector (dimensionality) is not an output nor a determination. The claim merely reads: 'setting a dimensionality of each vector included in the plurality of vectors, the dimensionality indicating a number of terms included in each vector, the setting of the dimensionality including: computing a square of each term included in the vector; summing the square of each term; and computing a square root of the sum of the square of each term'. Therefore, it is the Examiner's position that the cited references teach the claims and the rejections are maintained.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Examiner would like to point out that any reference to specific figures, columns and lines should not be considered limiting in any way, the entire reference is considered to provide disclosure relating to the claimed invention.
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/JUAN C OCHOA/Primary Examiner, Art Unit 2186
1 Electric Power Group, LLC v. Alstom S.A., 119 USPQ2d 1739 Fed. Cir. 2016
2 In re Prater, 415 F.2d 1393, 162 USPQ 541 (CCPA 1969)
3 In re Winkhaus, 527 F.2d 637, 188 USPQ 129 (CCPA 1975)