DETAILED ACTION The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Specification The abstract of the disclosure is objected to because the abstract refers to speculative applications of the invention, with numerous instances stating what the invention “may include”. See MPEP 608.01(b).I.B. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b). 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 appl icant regards as his invention. Claims 5, 12 and 19 are 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. Claim 5 last two lines recite “determining a solution to the optimization problem based on one or more penalty scores each associated with a particular candidate solution”. For antecedent basis reasons, it is unclear whether this is the same determining a solution to the optimization problem or an additional or different solution determined. For purposes of examination, Examiner interprets as the same. Claim 12 and claim 19 recite substantially the same limitation and rejected for the same reason. 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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea ) without significantly more. As to treatment of claims, apparatus claims 15-20 will be addressed first, followed by the method and non-transitory computer-readable storage media claims. Regarding claim 1 5 , under the Alice framework Step 2A prong 1, the claim recites Mathematical concepts. The claim recites mathem atical calculation s and mathematical relationships for solving an optimization problem . Specifically, the claim recites the following: identifying a plurality of variables corresponding to an optimization problem, each variable of the plurality of variables having a corresponding initial value (mathematical relationships, see e.g., p. 7 block 210 description) ; calculating an objective function value based on the initial values of the plurality of variables (mathematical calculation, see e.g., p. 7 lines 29-31) ; calculating a plurality of function value changes of the objective function value, wherein each function value change of the plurality of function value changes is calculated based on a different one of a plurality of variable value changes and each of the variable value changes corresponds to a respective change made to a different one of the initial values (mathematical calculation, see e.g., p. 7 line 32 – p. 10 line 11 ) ; selecting a subset of the variables based on the respective function value changes that correspond to corresponding variable value changes made to the respective initial values of the variables of the subset of variables (mathematical relationships , see e.g., p. 10 line 12 - 27 ) ; generating a surrogate quadratic unconstrained binary optimization (QUBO) model of the optimization problem using the selected subset of variables (mathematical relationships, see e.g. p. 10 bottom – p. 11 , ) ; determining one or more candidate solutions to the optimization problem using the surrogate QUBO model, each of the one or more candidate solutions comprising a set of solution values and each of the solution values of the set of solution values corresponding to a different variable of the plurality of variables (mathematical calculations , see e.g., p. 10 line 28- p. 11 line 27 ) ; and determining a solution to the optimization problem based on the one or more candidate solutions. (mathematical calculations , see e.g., p. 11 line 28 – p. 12 line 8 ) For these reasons, claim 15 recites mathematical concepts. Under the Alice framework Step 2A prong 2 analysis, additional elements not reciting Mathematical equations and mathematical calculation s thereof include: a system comprising: one or more processors; and one or more non-transitory computer-readable storage media configured to store instructions that, in response to being executed, cause the system to perform operations . Th ese additional element s do no more than generally link the mathematical relationships and mathematical calculations to a computer in a manner that in effect merely recites “apply it” to the math , or recite mere instructions to apply the mathematical relationships and mathematical calculations to the computer . Furthermore, the specification supports this conclusion be disclosing a wide variety of generic hardware and software solutions may implement the optimization algorithm. See specification p. 6 lines 7 - 18 . For this reason the claim is not integrated into a practical application. Moreover, under the Alice Framework Step 2B analysis, the claim, considered individually and as an ordered combination does not include additional elements that are sufficient to amount to significantly more than the abstract idea. As discussed in the Step 2A prong 2 analysis, the claim merely generally links the additional element to the math. Furthermore as stated in the Step 2A prong 2 analysis, the claims recite mere instructions to “ apply ” the judicial exception to a computer , which cannot provide an inventive concept. For these reasons claim 1 5 elements considered individually and as an ordered combination does not amount to significantly more than the abstract idea. Claims 16-20 are rejected for at least the reasons cited with respect to the claim 1 5 analysis. Under the Step 2A prong 1 analysis, claims 16-19 merely further mathematically limit the claim 1 5 mathematica l elements recited. Claims 16-19 contain no further additional elements that would require further consideration under Step 2A prong 2 or Step 2B. Claim 20 further recites the following further additional element , beyond those recited in claim 15 : wherein the optimization problem includes determining a prescribed radiation dosage to be delivered to a tumor and one or more organs using Intensity-Modulated Radiation Therapy. Under the Step 2A prong 2 analysis and Step 2B analysis , this additional element merely generally links the mathematical relationships and mathematical calculations to a particular field of use. For these reasons claim 20 is neither integrated into a practical application nor amounting to significantly more that the abstract idea. Regarding claim 1, under the Alice framework Step 2A prong 1, the claim recites Mathematical concepts. The claim recites mathematical calculations and mathematical relationships for solving an optimization problem. Specifically, the claim recites the following: identifying a plurality of variables corresponding to an optimization problem, each variable of the plurality of variables having a corresponding initial value (mathematical relationships, see e.g., p. 7 block 210 description) ; calculating an objective function value based on the initial values of the plurality of variables (mathematical calculation, see e.g., p. 7 lines 29-31) ; calculating a plurality of function value changes of the objective function value, wherein each function value change of the plurality of function value changes is calculated based on a different one of a plurality of variable value changes and each of the variable value changes corresponds to a respective change made to a different one of the initial values (mathematical calculation, see e.g., p. 7 line 32 – p. 10 line 11) ; selecting a subset of the variables based on the respective function value changes that correspond to corresponding variable value changes made to the respective initial values of the variables of the subset of variables (mathematical relationships, see e.g., p. 10 line 12 - 27) ; generating a surrogate quadratic unconstrained binary optimization (QUBO) model of the optimization problem using the selected subset of variables (mathematical relationships, see e.g. p. 10 bottom – p. 11,) ; determining one or more candidate solutions to the optimization problem using the surrogate QUBO model, each of the one or more candidate solutions comprising a set of solution values and each of the solution values of the set of solution values corresponding to a different variable of the plurality of variables (mathematical calculations, see e.g., p. 10 line 28- p. 11 line 27) ; and determining a solution to the optimization problem based on the one or more candidate solutions. (mathematical calculations, see e.g., p. 11 line 28 – p. 12 line 8) For these reasons, claim 15 recites mathematical concepts. Claim 1 recites no additional elements that would require further consideration under Step 2A prong 2 or Step 2B. For these reasons, claim 1 is not integrated into a practical application and does not amount to significantly more than the abstract idea. Claims 2-7 are rejected for at least the reasons cited with respect to the claim 1 analysis. Under the Step 2A prong 1 analysis, claims 2-5 merely further mathematically limit the claim 1 mathematical elements recited. Claims 2-5 contain no further additional elements that would require further consideration under Step 2A prong 2 or Step 2B. Claim 6 further recites the following additi onal element : wherein the optimization problem includes determining a prescribed radiation dosage to be delivered to a tumor and one or more organs using Intensity-Modulated Radiation Therapy. Under the Step 2A prong 2 analysis and Step 2B analysis, this additional element merely generally links the mathematical relationships and mathematical calculations to a particular field of use. For these reasons claim 6 is neither integrated into a practical application nor amounting to significantly more tha n the abstract idea. Claim 7 recites no further additional elements beyond those recited in claim 6, wherein the claim merely recites a variable in a mathematical calculation represents. For these reasons claim 7 is neither integrated into a practical application nor amounting to significantly more than the abstract idea. Claim 8 is directed to one or more non-transitory computer-readable storage media configured to store instructions that, when executed by the apparatus of claim 15 would cause the apparatus of claim 15 to perform the steps of claim 15 as configured. All steps performed by the non-transitory computer-readable storage media of claim 8 are performed by the apparatus of claim 15 as configured. The claim 15 analysis applies equally to claim 8. Claims 9-12 are rejected for at least the reasons cited with respect to the claim 8 analysis. Under the Step 2A prong 1 analysis, claims 9-12 merely further mathematically limit the claim 8 mathematical elements recited. Claims 9-12 contain no further additional elements that would require further consideration under Step 2A prong 2 or Step 2B. Claim 13 further recites the following further additional element: wherein the optimization problem includes determining a prescribed radiation dosage to be delivered to a tumor and one or more organs using Intensity-Modulated Radiation Therapy. Under the Step 2A prong 2 analysis and Step 2B analysis, this additional element merely generally links the mathematical relationships and mathematical calculations to a particular field of use. For these reasons claim 13 is neither integrated into a practical application nor amounting to significantly more tha n the abstract idea. Claim 14 recites no further additional elements, wherein the claim merely recites a variable in a mathematical calculation represents. For these reasons claim 14 is neither integrated into a practical application nor amounting to significantly more than the abstract idea. Allowable Subject Matter Claims 1 - 20 would be allowable if rewritten to overcome the rejections under 35 USC 101 , and further with respect to claim 5, 12, and 19, the rejection under 35 USC 112(b). The following is a statement of reasons for the indication of allowable subject matter. Applicant claims apparatus, method s , a nd non-transitory computer-readable storage media for solving an optimization problem, wherein the method as in claim 1 comprises: identifying a plurality of variables corresponding to an optimization problem, each variable of the plurality of variables having a corresponding initial value; calculating an objective function value based on the initial values of the plurality of variables; calculating a plurality of function value changes of the objective function value, wherein each function value change of the plurality of function value changes is calculated based on a different one of a plurality of variable value changes and each of the variable value changes corresponds to a respective change made to a different one of the initial values; selecting a subset of the variables based on the respective function value changes that correspond to corresponding variable value changes made to the respective initial values of the variables of the subset of variables; generating a surrogate quadratic unconstrained binary optimization (QUBO) model of the optimization problem using the selected subset of variables; determining one or more candidate solutions to the optimization problem using the surrogate QUBO model, each of the one or more candidate solutions comprising a set of solution values and each of the solution values of the set of solution values corresponding to a different variable of the plurality of variables; and determining a solution to the optimization problem based on the one or more candidate solutions. The primary reason for indication of allowable subj ect matter is the combination of the specific steps claimed and specifically in the context of the highlighted limitations above. Prior art was found with respect to aspects of the above claim elements, but each limitation in the combination claimed. T. Yokota et al., Derivation of QUBO formulations for sparse estimation , arXiv:2001.03715v2 [quant-ph], 27 Jan 2020 (hereinafter “Yokota”), discloses a quadratic a QUBO formulation, which enables performing a sparse estimation, including removing a redundant variable (abstract, section 3.1, section 4). Yokota further discloses a minimization function associated with an objective function (section 2.4). Yokota does not, however teach or suggest in combination with the remaining limitations calculating a n objective function value based on the initial values of the plurality of values; calculating a plurality of function value changes of the objective function value, wherein each function value change of the plurality of function value changes is calculated based on a different one of a plurality of variable value changes and each of the variable value changes corresponds to a respective change made to a different one of the initial values; selecting a subset of the variables based on the respective function value changes that correspond to corresponding variable value changes made to the respective initial values of the variables of the subset of variables in combination with the remaining limitations. H. Ishikawa, Transformation of General Binary MRP Minimization to the First-Order Case , IEEE Transactions on Pattern Analysis and Machine Intelligence, vol 33, No. 6, 2011 (hereinafter “Ishikawa”) disclos e s a transformation of general higher-order Markov random field with binary lab el s into a fir s t-order with the same minima as the original, and a framework for approximately minimizing higher-order multilabel MRF energies that combines the new reduction with QPBO algorithms (abstract). Ishikawa further discloses initializing X followed by a minimization algorithm (section 8.2). Ishikawa does not, however teach or suggest in combination with the remaining limitations calculating a plurality of function value changes of the objective function value, wherein each function value change of the plurality of function value changes is calculated based on a different one of a plurality of variable value changes and each of the variable value changes corresponds to a respective change made to a different one of the initial values; selecting a subset of the variables based on the respective function value changes that correspond to corresponding variable value changes made to the respective initial values of the variables of the subset of variables in combination with the remaining limitations; generating a surrogate QUBO model of the optimization problem using the selected subset of variables. US 20160071021 A1 Raymond (hereinafter “Raymond’) discloses techniques for improving performance of a quantum processor (abstract). Raymond further discloses solving an optimization problem by formulating the problem into a QUBO with N variables, and written as a cost function ([0012]). Raymond further discloses a sparse QUBO wherein starting from an initial configuration, a subset of variables is identified and minimized ([0112]). Raymond further discloses a majority voting post processing that applies bit flips in the unembedded problem and selecting those configurations which improve an objective function ([0151]). Raymond does not, however, teach or suggest in combination with the remaining limitations calculating a plurality of function value changes of the objective function value, wherein each function value change of the plurality of function value changes is calculated based on a different one of a plurality of variable value changes and each of the variable value changes corresponds to a respective change made to a different one of the initial values; selecting a subset of the variables based on the respective function value changes that correspond to corresponding variable value changes made to the respective initial values of the variables of the subset of variables; generating a surrogate quadratic unconstrained binary optimization (QUBO) model of the optimization problem using the selected subset of variables; determining one or more candidate solutions to the optimization problem using the surrogate QUBO model, each of the one or more candidate solutions comprising a set of solution values and each of the solution values of the set of solution values corresponding to a different variable of the plurality of variables. US 20180137083 A1 Aramon et al., (hereinafter “Aramon”) discloses a method and system for setting parameters of a discrete optimization , including a QUBO, problem embedding to an optimization solver , including setting parameters of a reduced embedding graph and solving a reduced variable K-spin problem, and including optimiz ation of objective functions (abstract, [0106], [0109]). Aramon does not, however, teach or suggest in combination with the remaining limitations calculating an objective function value based on the initial values of the plurality of variables; calculating a plurality of function value changes of the objective function value, wherein each function value change of the plurality of function value changes is calculated based on a different one of a plurality of variable value changes and each of the variable value changes corresponds to a respective change made to a different one of the initial values; selecting a subset of the variables based on the respective function value changes that correspond to corresponding variable value changes made to the respective initial values of the variables of the subset of variables . Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Enter examiner's name" \* MERGEFORMAT EMILY E LAROCQUE whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (469)295-9289 . The examiner can normally be reached on FILLIN "Work schedule?" \* MERGEFORMAT 10:00am - 1200pm, 2:00pm - 8pm ET M-F . Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor Andrew Caldwell can be reached on 571-27 2-3702 . The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /EMILY E LAROCQUE/ Primary Examiner, Art Unit 2182