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. Drawings The drawings are objected to because figures 1 and 3, filed 08/30/23 are not secured with solid black lines. See 37 CRF 1.84.(a)(2) Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance. Claim Rejections - 35 USC § 102 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale , or otherwise available to the public before the effective filing date of the claimed invention. Claim s 1-2 , 6-8, 15, and 18-20 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by US 20210303704 A1 Chen et al., (hereinafter “ Chen ”) . Regarding claim 1, Chen teaches the following: reading a first Quadratic Unconstrained Binary Optimization (QUBO) model comprising a first matrix ([0026], “receive inputs, for selection of a combinatorial optimization problems and a set of datapoints as input from the selected combinatorial optimization problem. The system may g enerate a QUBO formation based on the se lected o p tim i z a tion problem and the set of datapoints ”, [0038] , the QUBO formulation may include a matrix, claim 1 lines 1-10 , fig 7-702 ) ; constructing from the first QUBO model and an initial solution, a second QUBO model comprising a second matrix (claim 1 lines 10-15 “encoding, … the first QUBO formulation to generate a second QUBO formulation”, [ 0127- 0128] , “arranging an initial sequence”, “a second QUBO formulation may be generated by calculating (or recalculation) a Q-matrix of the updated first QUBO formulation” , fig 7-704 ) ; sending the second QUBO model to a quantum annealer (fig 7-710, claim 1 lines 16-18, [0129], [0045] “ the optimization solver may be a quantum annealing computer”) ; receiving from the quantum annealer, a first computed solution in response to sending the second QUBO model (fig 7-712, [0130] “a first solution … may be received from the optimization solver”) ; constructing a first intermediate solution from the initial solution and the first computed solution (claim 1 line 21-22 “decoding the first solution to produce a second solution of the first QUBO formulation”, fig 7-716 , [0132] ) ; and writing the first intermediate solution to a non-transitory computer readable storage medium (fig 7-218, claim 1 line 23-25 “publishing an output of the first combinatorial optimization problem on a user device based on the second solution”, [0079] “the processor may store the generated output in the memory”) . Regarding claim 2, in addition to the teachings addressed in the claim 1 analysis, Chen teaches the following: transforming the first intermediate solution into a final solution ([0025] return the solution for the QUBO formulation); and communicating the final solution to a user ([0025] output to the users) . Regarding claim 6, in addition to the teachings addressed in the claim 1 analysis, Chen teaches the following: constructi ng the initial solution from data read from a source (fig 3A, 3B, [0065] , [0076] ). Regarding claim 7, in addition to the teachings addressed in the claim 1 analysis, Chen teaches the following: constructi ng the first QUBO model from data read from a source ([0025]). Regarding claim 8 , in addition to the teachings addressed in the claim 1 analysis, Chen teaches the following: wherein the quantum annealer comprises at least one of a digital annealer, a simulated annealer, and a classical solver ([0045] simulated annealing). Regarding claim 1 5 , Chen teaches the following: a computer system comprising (fig 1, fig 2 ([0053]): one or more processors (fig 2-202, [0054]); a software program, executable on said computer system, the software program configured to cause in in-memory database engine of an in-memory database to ([0054] , [0058]) : r ead from the in-memory database, a first Quadratic Unconstrained Binary Optimization (QUBO) model comprising a first matrix ([0026], “receive inputs, for selection of a combinatorial optimization problems and a set of datapoints as input from the selected combinatorial optimization problem. The system may generate a QUBO formation based on the selected optimization problem and the set of datapoints”, [0038], the QUBO formulation may include a matrix, claim 1 lines 1-10, fig 7-702) ; construct from the first QUBO model and an initial solution, a second QUBO model comprising a second matrix (claim 1 lines 10-15 “encoding, … the first QUBO formulation to generate a second QUBO formulation”, [0127-0128], “arranging an initial sequence”, “a second QUBO formulation may be generated by calculating (or recalculation) a Q-matrix of the updated first QUBO formulation”, fig 7-704) ; send the second QUBO model to a quantum annealer (fig 7-710, claim 1 lines 16-18, [0129], [0045] “the optimization solver may be a quantum annealing computer”) ; receiv e from the quantum annealer, a first computed solution in response to sending the second QUBO model (fig 7-712, [0130] “a first solution … may be received from the optimization solver”) ; construct a first intermediate solution from the initial solution and the first computed solution (claim 1 line 21-22 “decoding the first solution to produce a second solution of the first QUBO formulation”, fig 7-716, [0132]) ; and writ e the first intermediate solution to a non-transitory computer readable storage medium (fig 7-218, claim 1 line 23-25 “publishing an output of the first combinatorial optimization problem on a user device based on the second solution”, [0079] “the processor may store the generated output in the memory”) . Regarding claim 18 , in addition to the teachings addressed in the claim 1 5 analysis, Chen teaches the following: wherein the in-memory database engine is further configured to construct a final solution from an intermediate solution ( [0051] output committed as an update on a database, [0025] return the solution for the QUBO formulation). Regarding claim 19 , in addition to the teachings addressed in the claim 1 5 analysis, Chen teaches the following: wherein the in-memory database engine is further configured to construct the initial solution from data read from a source (fig 3A, 3B, [0065], [0076]). Regarding claim 20 , in addition to the teachings addressed in the claim 1 5 analysis, Chen teaches the following: w herein the in-memory database engine is further configured to construct the first QUBO model from data read from a source ([0025]). 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. Cla im s 3-5 , 10-14 , and 16-17 are rejected unde r 35 U.S.C. 103 as being unpatentable over Chen in view of US 20230325461 A1 Dudash et al., (hereinafter “ Dudash ”) . Regarding claim 3 , Chen teaches the claim 1 limitations. Chen is silent with respect to determining the first intermediate solution does not satisfy a stopping criterion; constructing from the second QUBO model and the first solution, a third QUBO model; sending the third QUBO model to the quantum annealer; receiving a second computed solution from the quantum annealer in response to sending the third QUBO model; constructing a second intermediate solution from the initial solution and the second computed solution; and overwriting the first intermediate solution with the second intermediate solution. However, in the same field of endeavor, Dudash discloses an apparatus similar to Chen for solving a QUBP problem, generated in a classical computer, and embedding the QUBO problem in a quantum annealer (abstract, fig 1, fig 5). Dudash further discloses: determining the first intermediate solution does not satisfy a stopping criterion (fig 7 repeat t times not satisfied ) ; constructing from the second QUBO model and the first solution, a third QUBO model (fig 7-708 -706 repeated) ; sending the third QUBO model to the quantum annealer ( fig 7- 7 20 [0110] It would have been obvious to one of ordinary skill in the art before the effective filing date to add Dudash’s iteration (Dudash fig 7-708-714,716) with the QUBO formulation of Chen (Chen fig 7-704-708). In so doing a second iteration would result in Chen in view of Dudash constructing a second intermediate solution from the initial solution and the second computed solution; and overwriting the first intermediate solution with the second intermediate solution. It would have been obvious to one of ordinary skill in the art before the effective filing date to add the iterative feedback loop of Dudash to achieve the benefit of a final solution to the user that is the optimized global solution ([0091-0092]). Regarding claim 4, Chen in view of Dudash teach the claim 3 limitations. Dudash further discloses: wherein the stopping criterion comprises at least one of a number of iterations and a time limit (fig 7 repeat t times). The motivation provided with respect to claim 3 applies equally to claim 4. Regarding claim 5, Chen in view of Dudash teach the claim 3 limitations. Dudash further discloses: determining a solution quality of the first solution (fig 7-710, [0104]) , wherein the stopping criterion comprises a no-progress clause referencing the solution quality (fig 7-712, 716 if no progress is made the best local graph remains the same) . The motivation provided with respect to claim 3 applies equally to claim 5. Regarding claim 10, Chen teaches the following: reading a first Quadratic Unconstrained Binary Optimization (QUBO) model comprising a first matrix ([0026], “receive inputs, for selection of a combinatorial optimization problems and a set of datapoints as input from the selected combinatorial optimization problem. The system may generate a QUBO formation based on the selected optimization problem and the set of datapoints”, [0038], the QUBO formulation may include a matrix, claim 1 lines 1-10, fig 7-702) ; constructing from the first QUBO model and an initial solution, a second QUBO model comprising a second matrix (claim 1 lines 10-15 “encoding, … the first QUBO formulation to generate a second QUBO formulation”, [0127-0128], “arranging an initial sequence”, “a second QUBO formulation may be generated by calculating (or recalculation) a Q-matrix of the updated first QUBO formulation”, fig 7-704) ; sending the second QUBO model to a quantum annealer (fig 7-710, claim 1 lines 16-18, [0129], [0045] “the optimization solver may be a quantum annealing computer”) ; receiving from the quantum annealer, a first computed solution in response to sending the second QUBO model (fig 7-712, [0130] “a first solution … may be received from the optimization solver”) ; constructing a first intermediate solution from the initial solution and the first computed solution (claim 1 line 21-22 “decoding the first solution to produce a second solution of the first QUBO formulation”, fig 7-716, [0132]) ; writing the first intermediate solution to a non-transitory computer readable storage medium (fig 7-218, claim 1 line 23-25 “publishing an output of the first combinatorial optimization problem on a user device based on the second solution”, [0079] “the processor may store the generated output in the memory”); Chen is silent with respect to determining the first intermediate solution does not satisfy a stopping criterion; constructing from the second QUBO model and the first solution, a third QUBO model; sending the third QUBO model to the quantum annealer; receiving a second computed solution from the quantum annealer in response to sending the third QUBO model; constructing a second intermediate solution from the initial solution and the second computed solution; and overwriting the first intermediate solution with the second intermediate solution. However, in the same field of endeavor, Dudash discloses an apparatus similar to Chen for solving a QUB O problem, generated in a classical computer, and embedding the QUBO problem in a quantum annealer (abstract, fig 1, fig 5). Dudash further discloses: determining the first intermediate solution does not satisfy a stopping criterion (fig 7 repeat t times not satisfied) ; constructing from the second QUBO model and the first solution, a third QUBO model (fig 7-708-706 repeated) ; sending the third QUBO model to the quantum annealer (fig 7-720 [0110] receiving a second computed solution from the quantum annealer in response to sending the third QUBO model; It would have been obvious to one of ordinary skill in the art before the effective filing date to add Dudash’s iteration (Dudash fig 7-708-714,716) with the QUBO formulation of Chen (Chen fig 7-704-708). In so doing a second iteration would result in Chen in view of Dudash constructing a second intermediate solution from the initial solution and the second computed solution; and overwriting the first intermediate solution with the second intermediate solution. It would have been obvious to one of ordinary skill in the art before the effective filing date to add the iterative feedback loop of Dudash to achieve the benefit of a final solution to the user that is the optimized global solution ([0091-0092]). Regarding claim 11 , Chen in view of Dudash teach the claim 10 limitations. Dudash further discloses: wherein the stopping criterion comprises at least one of a number of iterations and a time limit (fig 7 repeat t times). The motivation provided with respect to claim 10 applies equally to claim 11 . Regarding claim 12 , Chen in view of Dudash teach the claim 10 limitations. Dudash further discloses: wherein the stopping criterion comprises at least one of a number of iterations and a time limit (fig 7 repeat t times). The motivation provided with respect to claim 10 applies equally to claim 12 . Regarding claim 13 , in addition to the teachings addressed in the claim 1 0 analysis, Chen teaches the following: constructi ng the initial solution from data read from a source (fig 3A, 3B, [0065], [0076]). Regarding claim 14 , in addition to the teachings addressed in the claim 1 0 analysis, Chen teaches the following: construction the first QUBO model from data read from a source ([0025]). Regarding claim 16 , Chen teaches the claim 1 5 limitations. Chen is silent with respect to determining the first intermediate solution does not satisfy a stopping criterion; constructing from the second QUBO model and the first solution, a third QUBO model; sending the third QUBO model to the quantum annealer; receiving a second computed solution from the quantum annealer in response to sending the third QUBO model; constructing a second intermediate solution from the initial solution and the second computed solution; and overwriting the first intermediate solution with the second intermediate solution. However, in the same field of endeavor, Dudash discloses an apparatus similar to Chen for solving a QUB O problem, generated in a classical computer, and embedding the QUBO problem in a quantum annealer (abstract, fig 1, fig 5). Dudash further discloses: determin e the first intermediate solution does not satisfy a stopping criterion (fig 7 repeat t times not satisfied) ; construct from the second QUBO model and the first solution, a third QUBO model (fig 7-708-706 repeated) ; send the third QUBO model to the quantum annealer (fig 7-720 [0110] receiv e a second computed solution from the quantum annealer in response to sending the third QUBO model; It would have been obvious to one of ordinary skill in the art before the effective filing date to add Dudash’s iteration (Dudash fig 7-708-714,716) with the QUBO formulation of Chen (Chen fig 7-704-708). In so doing a second iteration would result in Chen in view of Dudash constructing a second intermediate solution from the initial solution and the second computed solution; and overwriting the first intermediate solution with the second intermediate solution. It would have been obvious to one of ordinary skill in the art before the effective filing date to add the iterative feedback loop of Dudash to achieve the benefit of a final solution to the user that is the optimized global solution ([0091-0092]). Regarding claim 17 , Chen in view of Dudash teach the claim 16 limitations. Dudash further discloses: wherein the stopping criterion comprises at least on e of a number of iterations , a time limit , and a stopping criterion (fig 7 repeat t times). The motivation provided with respect to claim 16 applies equally to claim 17 . Cla im 9 is rejected unde r 35 U.S.C. 103 as being unpatentable over Chen in view of US 20240127122 A1 Ide et al., (hereinafter “Ide”) . Regarding claim 9, in addition to the teachings addressed in the claim 1 analysis, Chen teaches: an in-memory database engine of an in-memory database ([0051], [0058]) ; and the non-transitory computer readable storage medium comprises the in-memory database ([0051-0058]) . Chen does not, however, explicitly disclose wherein the in-memory database engine constructs the second QUBO model from the first QUBO model and the initial solution. However, in the same field of endeavor, Ide discloses an apparatus similar to Chen including a QUBO coefficient calculation unit ([0121]). Ide further discloses a database providing configuration information for optimization coefficient extraction ([0121]). It would have been obvious to one of ordinary skill in the art to use Ide’s database including configuration for optimization coefficient extraction for Chen to use to construct the second QUBO model from the first model and the initial solution. It would have been obvious to achieve the benefit of optimizing available coefficients based on advantage, strengths and weakness that have been learned and stored in the database ([0115] , [0119] ). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 20220389414 A1 Aspuru-Guzik et al., (hereinafter “Aspuru-Guzik”) discloses a Hamiltonian problem solver, wherein the problem is expressed as a QUBO representation and using quantum annealing (abstract, [0183-0195]). Aspuru-Guzik further discloses iterating on a final solution based on meeting an end condition ([0226], fig 1). US 20170242824 A1 Karimi et al., (hereinafter “Karimi”) disclose a method for solving a lagrangian dual using a unconstrained binary quadratic programming problem using a digital computer and a quantum annealer (abstract, fig 1). Karimi further discloses an iterative solver, iterating based on a convergence (fig 1). 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 . 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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/ Examiner, Art Unit 2182