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 .
Status of Claims
Claims 1-20 are pending and examined on the merits.
Priority
The instant application claims no benefit of priority. Thus, the effective filing date of the claims is 3/17/2023.
The applicant is reminded that amendments to the claims and specification must comply with 35 U.S.C. § 120 and 37 C.F.R. § 1.121 to maintain priority to an earlier-filed application. Claim amendments may impact the effective filing date if new subject matter is introduced that lacks support in the originally filed disclosure. If an amendment adds limitations that were not adequately described in the parent application, the claim may no longer be entitled to the priority date of the earlier filing.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation (BRI) using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2 and 12 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 2 and 12 recite "determining an ideal ground state based on the trial wave function by using a phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) algorithm". It is not clear what is meant by the modifier term "ideal" in this context, and the instant specification does not expand upon its meaning. The term "ground state" is already defined in the table of the specification on page 5 as "the lowest-energy state of a quantum system, such as an atom, molecule, or solid". If a "ground state" is already the lowest-energy state, what would an "ideal ground state" then be (i.e. the term “idea” placed before “ground state” appears to be redundant)? To further prosecution, the limitation quoted above is interpreted as "determining a ground state based on the trial wave function by using a phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) algorithm".
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process, a mathematical concept, organizing human activity, or a law of nature or natural phenomenon without significantly more. In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claims 1, 11, and 20: “obtaining a plurality of active spaces of a molecular system” provides an observation (involves making determinations based on data or experience) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
“determining a plurality of coefficient tensors for the plurality of active spaces respectively; determining a composite coefficient tensor based on a tensor product of the plurality of coefficient tensors of the plurality of active spaces” provides a mathematical calculation (using "tensor network-based methods" [item 28 in the table on page 7 of the instant specification] involves mathematical techniques for efficient and accurate computation of quantum properties) that is considered a mathematical concept, which is an abstract idea.
“determining a trial wave function based on the composite coefficient tensor and a cutoff value” provides a mathematical relationship (determining a trial wave function) that is considered a mathematical concept, which is an abstract idea.
Claim 2: “determining an ground state based on the trial wave function by using a phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) algorithm” (as interpreted above) provides a mathematical calculation (using a ph-AFQMC algorithm to determine an ideal ground state involves mathematical calculation such as equation 1 [instant specification para.0029]) that is considered a mathematical concept, which is an abstract idea.
Claims 3 and 13: “receiving an indication of the cutoff value input by a user” provides for organizing information (gathering data) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claims 4 and 14: “a rank of the composite coefficient tensor is not less than the cutoff value” provides a comparison (ensuring a rank is greater than the cutoff value requires a comparison) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claims 5-10 and 15-19: Depend from independent claims 1 and 11, respectively, and therefore recite the same identified abstract ideas above.
These recitations are similar to the concepts of collecting information, analyzing it, and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind or are mathematical relationships. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. Additionally, while claims 11-20 recite performing some aspects of the analysis on “A device comprising: at least one processor; and at least one memory storing instructions” (claim 11) and “A non-transitory computer readable storage medium having computer executable instructions” (claim 20), there are no additional limitations that indicate that this requires anything other than carrying out the recited mental processes or mathematical concepts in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental processes” grouping of abstract ideas. As such, claims 1-20 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). Claims 11 and 20 recite the additional elements of “A device comprising: at least one processor; and at least one memory storing instructions” (claim 11) and “A non-transitory computer readable storage medium having computer executable instructions” (claim 20).
There are no additional elements among the claims to integrate the recited judicial exceptions into a practical application. The limitations regarding implementing program instructions do not indicate that they require anything other than mere instructions to implement the abstract idea in a generic way or in a generic computing environment. As such, this limitation equates to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. Therefore, claims 1-20 are directed to an abstract idea (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims do not recite any additional elements which might serve to integrate the recited judicial exceptions into a practical application, or equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment.
As discussed above, there are no additional elements to indicate that the claimed “A device comprising: at least one processor; and at least one memory storing instructions” (claim 11) and “A non-transitory computer readable storage medium having computer executable instructions” (claim 20) requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. MPEP 2106.05(f) discloses that mere instructions to apply the judicial exception cannot provide an inventive concept to the claims.
Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3-5, 7-11, 13-15, and 17-20 rejected under 35 U.S.C. 103 as being unpatentable over Hong et al. (Physical Review B 105.16 (2022): 165116) in view of Pandharkar et al. (Journal of Chemical Theory and Computation 18.11 (2022): 6557-6566) and Liu et al. (Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. 2021).
Regarding claims 1, 11, and 20, Hong teaches determining a plurality of coefficient tensors for the plurality of active spaces respectively (Page 1 abstract "we represent the coefficients of the many-body wave function as a tensor network").
Hong also teaches determining a composite coefficient tensor based on a tensor product of the plurality of coefficient tensors of the plurality of active spaces (Page 3 col 2 "A. Matrix product state representation for the coefficients of a multivariable function [. . .] One key of our proposal is using the TN [tensor network] to represent the coefficients").
Hong also teaches determining a trial wave function based on the composite coefficient tensor (FIG. 1 and Page 1 abstract "Provided the orthonormal functional bases, we represent the coefficients of the many-body wave function as a tensor network").
Hong does not explicitly teach obtaining a plurality of active spaces of a molecular system; nor determining a trial wave function based on a cutoff value.
However, Pandharkar teaches obtaining a plurality of active spaces of a molecular system (Page 1 col 1 paragraph 1 "A commonly used multireference method, the complete active space self-consistent field (CASSCF)model, provides a qualitatively correct description of the system that captures the so-called static correlation. This method requires the user to define an active space - a set of active orbitals and the number of electrons collectively occupying these orbitals").
However, Liu teaches determining a trial wave function based on a cutoff value (Page 9 col 2 section 5.3 "SpTC [sparse tensor contraction] expressions with different tensors (SpTC1 to SpTC10) are from a well-known quantum physics model (Hubbard-2D) [16]in ITensor [17], and those tensors are formed by cutting off values smaller than 1×10−8").
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Hong as taught by Pandharkar in order to extend the applications of tensor network from quantum lattice models to systems in continuous space (Hong, page 1 abstract "Our work extends the applications of the tensor network from quantum lattice models to systems in continuous space"). One skilled in the art would have a reasonable expectation of success because both methods are concerned with simulating the ground state of molecular systems.
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Hong as taught by Liu in order to gain performance advantages from the resulting sparse tensor (page 10 col 2 last paragraph "Our work proposes an efficient element-sparse tensor contraction and shows its performance advantages if a practical cutoff value gets quantum chemistry or physics"). One skilled in the art would have a reasonable expectation of success because both methods are concerned with applying tensor networks to quantum physics modeling.
Regarding claims 3-4, 9, 13-14 and 19, Hong in view of Pandharkar and Liu teach the methods of Claims 1 and 11 on which this claim depends/these claims depend, respectively. Liu also suggests receiving an indication of the cutoff value input by a user; a rank of the composite coefficient tensor is not less than the cutoff value; and the composite coefficient tensor is a sparse tensor (Page 9 col 2 section 5.3 "SpTC [sparse tensor contraction] expressions with different tensors (SpTC1 to SpTC10) are from a well-known quantum physics model (Hubbard-2D) [16]in ITensor [17], and those tensors are formed by cutting off values smaller than 1×10−8").
Regarding claims 5 and 15, Hong in view of Pandharkar and Liu teach the methods of Claims 1 and 11 on which this claim depends/these claims depend, respectively. Hong also teaches the composite coefficient tensor is a direct product of the plurality of coefficient tensors (Page 3 col 2 "A. Matrix product state representation for the coefficients of a multivariable function [. . .] One key of our proposal is using the TN [tensor network] to represent the coefficients").
Regarding claims 7 and 17, Hong in view of Pandharkar and Liu teach the methods of Claims 1 and 11 on which this claim depends/these claims depend, respectively. Hong also teaches the trial wave function is determined further based on a plurality of basis states for the plurality of active spaces (Page 2 Figure 1 legend "An illustration of the functional MPS approach. By representing the trial wave function in MPS (matrix product state), the loss function L becomes the inner product of two MPSs. One MPS is the summation of several MPSs, each of which results from the trial wave function acted upon by an operator. The inset illustrates the gradient descent [Eq. (29)] to update the tensors in the trial MPS").
Regarding claims 8 and 18, Hong in view of Pandharkar and Liu teach the methods of Claims 7 and 17 on which this claim depends/these claims depend, respectively. Pandharkar also teaches the plurality of basis states for the plurality of active spaces are determined by using one of: an algorithm of active space decomposition (ASD), an algorithm of low-rank approximation (LRA) using rank-one basis states, or an algorithm of localized-active space self-consistent field (LASSCF) (Page 3 col 2 paragraph 1 "In the production algorithm, up to two particle transition density matrices between states i and j are constructed locally for each fragment and multiplied together with the Hamiltonian amplitudes, as in the ASD method (cf. eq 6 of ref 24)", page 2 col 1 paragraph 2 "Another recent approach, rank-one basis states, by Nishio and Kurashige, also uses similar ideas and has been shown to work for large π-stacked systems", and page 2 col 2 paragraph 1 "in this paper, we explore the new state interaction (SI)-LASSCF formalism that builds on the LAS approach").
Regarding claim 10, Hong in view of Pandharkar and Liu teach the methods of Claim 1 on which this claim depends/these claims depend. Pandharkar also teaches the plurality of active spaces of the molecular system are determined based on chemical bonding between a plurality of subsystems of the molecular system (Page 2 col 1 paragraph 4 "These models often use concepts that are easy to envision, even if they are not accurate representations of the underlying fundamental physics. For example, bonding in molecules is usually interpreted using concepts from valence bond theory (like bonding/antibonding orbitals, bond orders, etc.), even if the methods used for the calculations are not tied to such a representation" suggests using concepts such as bonding in molecules using valence bond theory).
Claims 2, 6, 12, and 16 rejected under 35 U.S.C. 103 as being unpatentable over Hong et al. (Physical Review B 105.16 (2022): 165116) in view of Pandharkar et al. (Journal of Chemical Theory and Computation 18.11 (2022): 6557-6566) and Liu et al. (Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. 2021) as applied to claims 1, 3-5, 7-11, 13-15, and 17-20 above, and further in view of Mahajan et al. (The Journal of Chemical Physics 156.17 (2022)).
Hong et al. in view of Pandharkar et al. and Liu et al. are applied to claims 1, 3-5, 7-11, 13-15, and 17-20.
Regarding claims 2 and 12, Hong in view of Pandharkar and Liu teach the method of Claims 1 and 11 on which this claim depends/these claims depend, respectively. Hong, Pandharkar, nor Liu explicitly teach determining a ground state based on the trial wave function by using a phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) algorithm.
However, Mahajan teaches determining a ground state based on the trial wave function by using a phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) algorithm (Page 2 col 1 paragraph 1 "When the trial wave function approaches the exact ground state, the corresponding ph-AFQMC energy tends to the ground state energy" and page 3 col 1 paragraph 3 "we show how phaseless errors in the ground state energy and dipole moments change as a function of the number of determinants in hydrogen chains, transition metal oxides, and a few small molecules (Sec. IV)").
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Hong, Pandharkar, and Liu as taught by Mahajan in order to apply the determined wave function of Hong and Liu in an accurate and efficient method for tackling the quantum many-body problem, as taught by Mahajan (page 2 col 1 paragraph 1 "Quantum Monte Carlo (QMC) is a powerful tool in our arsenal to tackle the quantum many-body problem.1–7 Among various QMC approaches, phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC)8 has emerged as an accurate and efficient method. While originally from the condensed matter community [therein usually referred to as constrained-path auxiliary field quantum Monte Carlo (AFQMC)],9–11 ph-AFQMC has gained popularity in chemistry in recent years.12–24 The accuracy and scalability of ph-AFQMC are determined in large part by the choice of the trial wave function. The use of a trial wave function becomes necessary for retaining statistical efficiency (in sample complexity) to control the fermionic phase (or sign) problem.25,26 The constraint imposed to control the phase problem is called the phaseless approximation"). One skilled in the art would have a reasonable expectation of success because both methods are concerned with applying tensor networks to quantum physics modeling.
Regarding claims 6 and 16, Hong in view of Pandharkar and Liu teach the methods of Claims 1 and 11 on which this claim depends/these claims depend, respectively. Mahajan also teaches each of the plurality of coefficient tensors is a configuration interaction (CI) expansion of corresponding activespace (Page 2 abstract "We present efficient algorithms for using selected configuration interaction (sCI) trial wave functions in phaseless auxiliary field quantum Monte Carlo (ph-AFQMC)").
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US-20180096085, Rubin, Simulating quantum systems with quantum computation
US-20210089955, Bondesan et al., Quantum inspired convolutional kernels for convolutional neural networks
US-20220108218, Wall et al., Quantum-assisted machine learning with tensor networks
US-20230016119, Wei, Monte Carlo quantum computing
Conclusion
No claims are allowed.
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/R.A.P./Examiner, Art Unit 1686
/KAITLYN L MINCHELLA/Primary Examiner, Art Unit 1685
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