Application US20190019103

METHODS AND SYSTEMS FOR QUANTUM COMPUTING
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US20190019103

1. A method for generating one or more instructions for execution by a solver layer comprising a common interface, wherein the one or more instructions are generated by a digital computer comprising at least one computer processor and memory, the digital computer coupled to a quantum-ready or quantum-enabled computing system comprising the solver layer, and wherein the solver layer executes the one or more instructions to generate an output, the method comprising: (12) (4)

a. accepting user input from an application at an application interface, which application is executed on the digital computer;

b. implementing one or more algorithms, at an algorithms layer, that are solved heuristically or exactly depending at least in part on requirements of the user input, wherein the one or more algorithms abstract away a complexity of the application;

c. transforming the one or more algorithms from the application space into the one or more instructions in polynomial unconstrained binary optimization (PUBO) form; and

d. executing the one or more instructions in PUBO form at the common interface of the solver layer, wherein the common interface comprises one or more polynomial unconstrained binary optimization (PUBO) solvers that provide an interface that is agnostic to quantum or classical computers.

2. The method of claim 1, wherein the quantum-ready or quantum-enabled computing system comprises a quantum annealer, an Ising solver, an optical parametric oscillator (OPO), a gate model of quantum computing, or another type of quantum computer. (0)

3. The method of claim 1, wherein the polynomial unconstrained binary optimization (PUBO) form is a quadratic unconstrained binary optimization (QUBO) form. (0)

4. The method of claim 1, wherein the one or more polynomial unconstrained binary optimization (PUBO) solvers of the common interface of the solver layer comprise one or more quadratic unconstrained binary optimization (QUBO) solvers. (0)

5. The method of claim 1, wherein the one or more algorithms are transformed at the algorithms layer. (0)

6. The method of claim 1, wherein the one or more algorithms are transformed using a binary polynomial layer. (0)

7. The method of claim 1, wherein the one or more algorithms are transformed at a polynomial constrained integer optimization layer. (0)

8. The method of claim 1, wherein the one or more algorithms are transformed at a polynomial constrained binary optimization layer. (0)

9. The method of claim 1, wherein the one or more algorithms are transformed by the common interface of the solver layer. (0)

10. The method of claim 1, wherein the algorithms layer comprises one or more of: max (maximum) k-quasi clique, chromatic number, graph similarity, coloring feasibility, max co-k-plex, minimum clique cover, k-clique cover feasibility, linear knapsack, and balanced partitioning. (0)

11. The method of claim 1, wherein transforming the one or more algorithms comprises the use of one or more of: a transformation of the polynomial unconstrained binary optimization (PUBO) form to a quadratic unconstrained binary optimization (QUBO) form, binary polynomial operations, and efficient search in binary space. (0)

12. The method of claim 1, wherein the one or more polynomial unconstrained binary optimization (PUBO) solvers comprise one or more of: D-Wave, multi-agent Tabu 1-Opt solver, Tabu 1-Opt solver, PTICM solver, path-relinking solver, and a GPU-based simulated quantum annealing solver. (0)

13. The method of claim 1, wherein the one or more algorithms are implemented using a classical optimization system or a quantum oracle. (0)

14. A system for generating one or more instructions for execution by a solver layer comprising a common interface, comprising: (12) (3)

a. a quantum-ready or quantum-enabled computing system comprising the solver layer;

b. a digital computer comprising at least one computer processor, the digital computer coupled to the quantum-ready or quantum-enabled computing system;

c. a computer memory storing computer processor executable instructions which, when executed by the at least one computer processor, implement a method comprising: i. accepting user input from an application at an application interface, which application is executed on the digital computer;

ii. implementing one or more algorithms, at an algorithms layer, that are solved heuristically or exactly depending at least in part on requirements of the user input, wherein the one or more algorithms abstract away a complexity of the application;

iii. transforming the one or more algorithms from the application space into the one or more instructions in polynomial unconstrained binary optimization (PUBO) form; and

iv. executing the one or more instructions in PUBO form at the common interface of the solver layer, wherein the common interface comprises one or more polynomial unconstrained binary optimization (PUBO) solvers that provide an interface that is agnostic to quantum or classical computers.

15. The system of claim 14, wherein the quantum-ready or quantum-enabled computing system comprises a quantum annealer, an Ising solver, an optical parametric oscillator (OPO), a gate model of quantum computing, or another type of quantum computer. (0)

16. The system of claim 14, wherein the polynomial unconstrained binary optimization (PUBO) form is a quadratic unconstrained binary optimization (QUBO) form. (0)

17. The method of claim 14, wherein the one or more polynomial unconstrained binary optimization (PUBO) solvers of the common interface of the solver layer comprise one or more quadratic unconstrained binary optimization (QUBO) solvers. (0)

18. The system of claim 14, wherein the one or more algorithms are transformed at the algorithms layer. (0)

19. The system of claim 14, wherein the one or more algorithms are transformed using a binary polynomial layer. (0)

20. The method of claim 14, wherein the one or more algorithms are transformed at a polynomial constrained integer optimization layer. (0)

21. The method of claim 14, wherein the one or more algorithms are transformed at a polynomial constrained binary optimization layer. (0)

22. The system of claim 14, wherein the one or more algorithms are transformed by the common interface of the solver layer. (0)

23. The system of claim 14, wherein the algorithms layer comprises one or more of: max (maximum) k-quasi clique, chromatic number, graph similarity, coloring feasibility, max co-k-plex, minimum clique cover, k-clique cover feasibility, linear knapsack, and balanced partitioning. (0)

24. The system of claim 14, wherein transforming the one or more algorithms comprises the use of one or more of: a transformation of the polynomial unconstrained binary optimization (PUBO) form to a quadratic unconstrained binary optimization (QUBO) form, binary polynomial operations, and efficient search in binary space. (0)

25. The system of claim 14, wherein the one or more polynomial unconstrained binary optimization (PUBO) solvers comprise one or more of: D-Wave, multi-agent Tabu 1-Opt solver, Tabu 1-Opt solver, PTICM solver, path-relinking solver, and a GPU-based simulated quantum annealing solver. (0)

26. The system of claim 14, wherein the one or more algorithms are implemented using a classical optimization system or a quantum oracle. (0)

27. A non-transitory computer-readable medium comprising machine-executable code that, upon execution by one or more computer processors, generates an application that is executable by a digital computer comprising at least one computer processor and memory to generate one or more instructions for execution by a solver layer of a quantum-ready or quantum-enabled computing system, the solver layer comprising a common interface, to generate an output, the application comprising: (8) (4)

a. a software module programmed or otherwise configured to accept user input from an application at an application interface, which application is executed on the digital computer;

b. a software module programmed or otherwise configured to implement one or more algorithms, at an algorithms layer, that are solved heuristically or exactly at least in part depending on the requirements of the user input, wherein the one or more algorithms abstract away a complexity of the application;

c. a software module programmed or otherwise configured to transform the one or more algorithms from the application space into one or more instructions in polynomial unconstrained binary optimization (PUBO) form; and

d. a software module programmed or otherwise configured to execute the one or more instructions in PUBO form at the common interface of the solver layer, wherein the common interface comprises one or more polynomial unconstrained binary optimization (PUBO) solvers that provide an interface that is agnostic to quantum or classical computers.

28. The non-transitory computer-readable medium of claim 27, wherein the polynomial unconstrained binary optimization (PUBO) form is a quadratic unconstrained binary optimization (QUBO) form. (0)

29. The non-transitory computer-readable medium of claim 27, wherein the one or more polynomial unconstrained binary optimization (PUBO) solvers of the common interface of the solver layer comprise one or more quadratic unconstrained binary optimization (QUBO) solvers. (0)

30. The non-transitory computer-readable medium of claim 27, wherein the one or more algorithms are transformed at the algorithms layer. (0)

31. The non-transitory computer-readable medium of claim 27, wherein the one or more algorithms are transformed using a binary polynomial layer. (0)

32. The non-transitory computer-readable medium of claim 27, wherein the one or more algorithms are transformed by the common interface of the solver layer. (0)

33. The non-transitory computer-readable medium of claim 27, wherein the algorithms layer comprises one or more of: max (maximum) k-quasi clique, chromatic number, graph similarity, coloring feasibility, max co-k-plex, minimum clique cover, k-clique cover feasibility, linear knapsack, and balanced partitioning. (0)

34. The non-transitory computer-readable medium of claim 27, wherein the transforming of the one or more algorithms comprises the use of one or more of: a transformation of the polynomial unconstrained binary optimization (PUBO) form to a quadratic unconstrained binary optimization (QUBO) form, binary polynomial operations, and efficient search in binary space. (0)

35. The non-transitory computer-readable medium of claim 27, wherein the one or more polynomial unconstrained binary optimization (PUBO) solvers comprise one or more of: D-Wave, multi-agent Tabu 1-Opt solver, Tabu 1-Opt solver, PTICM solver, path-relinking solver, and a GPU-based simulated quantum annealing solver. (0)

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Application US20190019103

METHODS AND SYSTEMS FOR QUANTUM COMPUTING

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