Non-Final Action
This is to replace the prior non-final rejection; objections remain pertinent, but are moot now.
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.
1. Claims 1–20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception without reciting significantly more.
The claims are directed to the abstract idea of a mathematical relationship--analysis and data processing, including determining a unitary operation, processing sampling bosonic states, generating Fourier components, and inverse-transforming those Fourier components to estimate a transition spectra. These concepts fall within the category of mathematical concepts, which is a judicial exception. See Alice Corp. v. CLS Bank Int’l, 573 U.S. 208 (2014); Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66 (2012); USPTO, 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019).
Although the claims recite a bosonic system and, in some dependent claims, additional quantum-optical limitations such as a positive P-representation, Gaussian or non-Gaussian states, molecular vibronic modes, and operator decompositions involving dressing, displacement, and squeezing, these additional limitations merely place the abstract mathematical analysis in the context of a particular field of use. The claims do not recite a specific improvement to computer functionality, a particular machine, or another technological implementation that integrates the abstract idea into a practical application.
Individually and as an ordered combination, the additional claim elements amount to no more than generic computer implementation of the abstract idea using conventional processors, memory, and routine processing steps. Accordingly, the claims do not include an inventive concept sufficient to transform the judicial exception into patent-eligible subject matter.
Therefore, claims 1–20 are ineligible under 35 U.S.C. § 101.
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 factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
2. Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over STOJEVIC, Vid (US-20210398621-A1) in view of applicant’s admitted prior art.
As per claims 1 and 13:
Stojević teaches quantum circuit-based tensor-network methods / systems for modeling physical and chemical systems, including effectively infinite systems, and for computing properties and expectation values of such systems. See Stojević at [0001], [0011]–[0014], [0084]–[0099], [0390], [0402]–[0459], [0473]–[0499], and [0763]. Stojević further teaches representing quantum circuits as tensor networks and using such representations to sample outputs and evaluate system properties. See id. at [0390] and [0763].
It would have been obvious to a person having ordinary skill in the art, at the time the invention was filed, to modify Stojević’s framework to estimate a transition spectra in a bosonic system because bosonic systems are a known class of quantum systems, spectra estimation is a routine property-analysis task, and Fourier-based reconstruction techniques are standard analytical tools for recovering spectra from sampled data. Accordingly, it would have been obvious to determine a unitary operation modified from a transition operator associated with the bosonic system, process each of N sampling bosonic states in a representation space to generate N sets of samples using at least the unitary operation, generate Fourier components of the transition spectra based on the N sets of samples, and inverse-transform the Fourier components to estimate the transition spectra.
As per claims 2-12 and 14-20:
Stojević teaches a generalized tensor-network and quantum-circuit framework for modeling and analyzing complex physical and chemical systems, including effectively infinite systems, and for computing properties and expectation values thereof. See Stojević at [0001], [0011]–[0014], [0084]–[0099], [0272]–[0273], [0390], [0402]–[0459], [0473]–[0499], and [0763].
It would have been obvious to include the additional limitations recited in claims 2–12 and 14–20 because the recited bosonic-state types, representation choices, vibronic and auxiliary modes, positive P-representation, and operator decompositions are known and conventional modeling features in the quantum optics and molecular-simulation arts, and their use would have been a predictable extension of Stojević’s framework.
3. Claim(s) 1-20 alternatively are rejected under 35 U.S.C. 103 as being unpatentable over Oh, Changhun et al., "Classical simulation of lossy boson sampling using matrix product operators," Phys. Rev. A 104, 022407, Year: 20211 in view of STOJEVIC, Vid (US-20210398621-A1).
Oh teaches bosonic systems having multiple modes, unitary transformations acting on those bosonic modes, and processing of bosonic states in a representation space to generate sampled output using tensor-network-based simulation techniques. See, e.g., Oh at II. Lossy Boson Sampling and III. Method, including the discussion of passive unitary circuits over bosonic modes, the transformation a^j↦∑kUjka^k, and the use of MPS/MPO simulation and sampling procedures. See also Oh at B. MPO simulation, C. MPS and MPO approximability, and Appendix B (MPS/MPO representations and sampling), as well as Appendix C (entanglement entropy and bosonic-system analysis).
Stojević teaches a quantum-circuit-based system configured to model effectively infinite physical or chemical systems using infinite tensor network representations, including computing environments of infinite tensor networks, optimizing properties such as energy or expectation values, and applying tensor-network-based methods to molecular, chemical, and materials problems. See Stojević at [0001]–[0014], [0084]–[0099], [0272]–[0273], [0390], [0402]–[0459], [0473]–[0501], and [0763].
It would have been obvious to a person of ordinary skill in the art to combine the teachings of Oh and Stojević because both references are directed to efficient representation, simulation, and analysis of complex quantum systems using tensor-network-based methods. Oh provides the bosonic-mode, unitary-processing, and sampling framework, while Stojević provides the quantum-circuit and infinite tensor-network framework for modeling large or effectively infinite systems and computing or optimizing properties thereof. The proposed combination would merely apply known techniques according to their established functions to achieve predictable results, namely estimation of a transition spectra or other properties of a bosonic system through tensor-network-based quantum or hybrid processing. See Oh, II. Lossy Boson Sampling, III. Method, and Appendices B–C; and Stojević, [0084]–[0094], [0097]–[0099], and [0390].
More specifically, claim 1 would have been obvious because Oh teaches bosonic systems with multiple modes, unitary transformations, and sampled processing of bosonic states, and Stojević teaches using quantum circuits as tensor-network representations for modeling and optimizing properties of complex systems. See Oh, II. Lossy Boson Sampling (bosonic modes, unitary circuits, sampling) and III. Method; Stojević, [0084]–[0092], [0093]–[0097], [0390]. Thus, it would have been obvious to determine a unitary operation modified from a transition operator associated with a bosonic system, process sampling bosonic states in a representation space to generate sample sets, and use the sampled data to estimate a transition spectra. Generating Fourier components from the sampled data and inverse-transforming those components would have been routine mathematical analysis steps for reconstructing a spectra from sampled system data.
The dependent claims are likewise unpatentable. To the extent the claims recite a complex mixed position and momentum operator, Gaussian or non-Gaussian sampling bosonic states, positive P-representation, or molecular vibronic modes, these are known bosonic and quantum-optical modeling choices that would have been obvious to incorporate when extending the bosonic simulation framework of Oh into the quantum-circuit and molecular modeling framework of Stojević. See Oh, II. Lossy Boson Sampling, III.B MPO simulation, and Appendix C; Stojević, [0091]–[0098], [0404]–[0415], [0417]–[0453], [0482]–[0497]. To the extent the claims recite decomposition of the transition operator into a unitary operation, dressing operation, displacement operation, and two-mode squeezing operation, such operator decompositions are standard bosonic-state transformation tools that would have been obvious to use in the combined framework. See Oh, Appendix A and Appendix B for bosonic unitary transformations and bosonic-state processing; Stojević, [0763] and [0390] for tensor-network/quantum-circuit embeddings. To the extent the claims recite molecular vibronic systems, auxiliary modes, or chemical and material applications, Stojević expressly teaches application of tensor-network-based quantum-circuit methods to physical and chemical systems, and it would have been obvious to apply the combined teachings to such systems. See Stojević, [0001]–[0014], [0084]–[0098], [0404]–[0459], [0473]–[0501].
The computing system claims are unpatentable for the same reasons. Claim 13 recites a computing system configured to perform substantially the same steps as claim 1. Oh teaches tensor-network-based classical simulation of bosonic systems, and Stojević teaches quantum-circuit-based tensor-network modeling and property optimization of infinite physical or chemical systems. See Oh, III.B MPO simulation, III.C MPS and MPO approximability, Appendix B; Stojević, [0084]–[0097], [0390], [0451]–[0453], [0763]. It would have been obvious to implement the claimed computing system using the combined teachings of Oh and Stojević, with the same predictable results. Claims 14–20 add limitations corresponding to those in claims 2–12, and for the reasons stated above those limitations would have been obvious in view of the combined references.
Accordingly, claims 1–20 would have been obvious over Oh in view of Stojević under 35 U.S.C. § 103.
Conclusion
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/MICHAEL FUELLING/ Supervisory Patent Examiner, Art Unit 3992
1 The article is prior art because, inter alia, it was co-authored by a person who is not an inventor of this application, thus, it would not be entitled to any grace period, even if applicable.
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