Error reduction and, or, correction in analog computing including quantum processor-based computing
The systems, devices, articles, and methods described herein generally relate to analog computers, for example quantum processors comprising qubits, couplers, and, or cavities. Analog computers, for example quantum processor based computers, are the subject of various sources of error which can hinder operation, potentially reducing computational accuracy and speed. Sources of error can be broadly characterized, for example as i) a background susceptibility do to inherently characteristics of the circuitry design, ii) as an h/J ratio imbalance, iii) bit flip errors, iv) fidelity, and v) Anderson localization, and various combinations of the aforesaid.
1. A method of operation in a computational system that comprises both a quantum processor and at least one processor-based device communicatively coupled to one another, the quantum processor comprising a plurality of qubits and a plurality of coupling devices, wherein each coupling device is operable to provide controllable communicative coupling between two of the plurality of qubits, the method comprising:
producing a problem graph representation of a first problem;
identifying each of the qubits that will be operated as a problem qubit, the problem qubit to be used when generating solutions to the first problem;
for each of at least a non-zero number of the qubits that will be operated as problem qubits, identifying a respective ancilla qubit that is exclusively coupled to one qubit of the qubits that will be operated as problem qubits, the ancilla qubits operable to apply an external flux bias to respective problem qubits;
embedding the problem graph representation of the first problem into the problem qubits of the quantum processor;
applying an external flux bias to each problem qubit to at least partially reduce a qubit bias to coupling strength (h/J) ratio misbalance of a respective qubit; and
evolving the quantum processor with the problem graph representation embedded therein to generate solutions to the first problem via the quantum processor.
2. The method of claim 1 , further comprising:
identifying a problem type of the first problem;
determining whether the identified problem type of the first problem is a problem type that is relatively sensitive to h/J misbalance error or is a problem type that is relatively insensitive to h/J misbalance error; and
wherein the identifying each of the qubits that will be operated as a problem qubit to be used when generating solutions to the first problem and the identifying a respective ancilla qubit to apply an external flux bias to the respective problem qubits is responsive to a determination that the problem type of the first problem is one that is relatively sensitive to h/J misbalance, employing existing hardware of the quantum processor to compensate for h/J misbalance when evolving the quantum processor to generate solutions to the first problem via the quantum processor.
3. The method of claim 2 , the method comprising:
in response to a determination that the problem type is one that is relatively insensitive to h/J misbalance error, employing the existing hardware to embed a problem graph of the first problem in a hardware graph of the quantum processor without using the existing hardware of the quantum processor to compensate for h/J misbalance error.
4. The method of claim 3 wherein employing the existing hardware to embed the problem graph of the first problem in the hardware graph of the quantum processor without using the existing hardware of the quantum processor to compensate for h/J misbalance error includes embedding the problem graph of the first problem in the hardware graph of the quantum processor without any ancilla qubits to compensate for h/J misbalance error.
5. The method of claim 2 wherein determining whether the identified problem type of the first problem is a problem type that is relatively sensitive to h/J misbalance error or is a problem type that is relatively insensitive to h/J misbalance error includes determining whether the first problem is an optimization problem and hence is relatively sensitive to h/J misbalance error.
6. The method of claim 2 wherein determining whether the identified problem type of the first problem is a problem type that is relatively sensitive to h/J misbalance error or is a problem type that is relatively insensitive to h/J misbalance error includes querying at least one of a data schema or a piece of metadata, logically associated with the first problem via one or more stored relationships.
7. The method of claim 2 wherein determining whether the identified problem type of the first problem is a problem type that is relatively sensitive to h/J misbalance error x or is a problem type that is relatively insensitive to h/J misbalance error includes analyzing the first problem to determine a broad class of problems to which the first problem belongs.
8. The method of claim 2 , the method further comprising:
identifying a problem type of a second problem;
determining whether the identified problem type of the second problem is a problem type that is relatively sensitive to h/J misbalance error or is a problem type that is relatively insensitive to h/J misbalance error; and
in response to a determination that the problem type of the second problem is a problem type that is relatively insensitive to h/J misbalance error, employing the existing hardware of the quantum processor to embed a problem graph of the second problem without using the existing hardware to compensate for h/J misbalance error when evolving the quantum processor to generate solutions to the second problem via the quantum processor.
9. The method of claim 8 wherein employing the existing hardware of the quantum processor to embed the problem graph of the second problem without using the existing hardware to compensate for h/J misbalance error when evolving the quantum processor to generate solutions to the second problem via the quantum processor includes embedding the problem graph of the second problem in a hardware graph of the quantum processor without any ancilla qubits to compensate for h/J misbalance error.
10. The method of claim 8 wherein employing the existing hardware of the quantum processor to embed the problem graph of the second problem without using the existing hardware to compensate for h/J misbalance error when evolving the quantum processor to generate solutions to the second problem via the quantum processor includes embedding the problem graph of the second problem in the hardware graph of the quantum processor employing one or more of the qubits of the quantum processor that were used as ancilla qubits when evolving the quantum processor to generate solutions for the first problem as problem qubits when generating solutions for the second problem.
11. A computational annealing system, comprising:
a quantum processor, the quantum processor comprising a plurality of qubits and a plurality of coupling devices, wherein each coupling device is operable to provide controllable communicative coupling between two of the plurality of qubits; and
at least one processor-based device communicatively coupled to the quantum processor;
at least one non-transitory processor-readable medium that stores at least one of processor-executable instructions or data which, when executed, cause at least one processor to:
produce a problem graph representation of a first problem;
identify each of the qubits that will be operated as a problem qubit, the problem qubit to be used when generating solutions to the first problem;
for each of at least a number of the qubits that will be operated as problem qubits, identify a respective ancilla qubit to apply an external flux bias to respective problem qubits;
embed the problem graph representation of the first problem into the problem qubits of the quantum processor; and
evolve the quantum processor with the problem graph representation embedded therein to generate solutions to the first problem via the quantum processor.
12. The computational annealing system of claim 11 wherein the at least one of processor-executable instructions or data, when executed, further cause the at least one processor to:
identify a problem type of the first problem; and
determine whether the identified problem type of the first problem is a problem type that is relatively sensitive to a qubit bias to coupling strength (h/J) misbalance error or is a problem type that is relatively insensitive to h/J misbalance error,
wherein when the at least one processor identifies each of the qubits that will be operated as a problem qubit to be used when generating solutions to the first problem and identifies a respective ancilla qubit to apply an external flux bias to the respective problem qubits the at least one processor is responsive to a determination that the problem type of the first problem is one that is relatively sensitive to h/J misbalance, and
wherein when the at least one processor evolves the quantum processor to generate solutions to the first problem via the quantum processor the at least one processor employs existing hardware of the quantum processor to compensate for h/J misbalance.
13. The computational annealing system of claim 12 wherein the at least one of processor-executable instructions or data, when executed, further cause the at least one processor to:
in response to a determination that the problem type is one that is relatively insensitive to h/J misbalance error, employ the existing hardware to embed a problem graph of the first problem in a hardware graph of the quantum processor without using the existing hardware of the quantum processor to compensate for h/J misbalance error.
14. The computational annealing system of claim 13 wherein when the at least one processor employs the existing hardware to embed the problem graph of the first problem in the hardware graph of the quantum processor without using the existing hardware of the quantum processor to compensate for h/J misbalance error the at least one processor embeds the problem graph of the first problem in the hardware graph of the quantum processor without any ancilla qubits to compensate for h/J misbalance error.
15. The computational annealing system of claim 12 wherein when the at least one processor determines whether the identified problem type of the first problem is a problem type that is relatively sensitive to h/J misbalance error or is a problem type that is relatively insensitive to h/J misbalance error the at least one processor determines whether the first problem is an optimization problem and hence is relatively sensitive to h/J misbalance error.
16. The computational annealing system of claim 12 wherein when the at least one processor determines whether the identified problem type of the first problem is a problem type that is relatively sensitive to h/J misbalance error or is a problem type that is relatively insensitive to h/J misbalance error the at least one processor queries at least one of a data schema or a piece of metadata, logically associated with the first problem via one or more stored relationships.
17. The computational annealing system of claim 12 wherein when the at least one processor determines whether the identified problem type of the first problem is a problem type that is relatively sensitive to h/J misbalance error x or is a problem type that is relatively insensitive to h/J misbalance error the at least one processor analyzes the first problem to determine a broad class of problems to which the first problem belongs.
18. The computational annealing system of claim 12 wherein the at least one of processor-executable instructions or data, when executed, further cause the at least one processor to:
identify a problem type of a second problem;
determine whether the identified problem type of the second problem is a problem type that is relatively sensitive to h/J misbalance error or is a problem type that is relatively insensitive to h/J misbalance error; and
in response to a determination that the problem type of the second problem is a problem type that is relatively insensitive to h/J misbalance error, employ the existing hardware of the quantum processor to embed a problem graph of the second problem without using the existing hardware to compensate for h/J misbalance error when the at least one processor-based device evolves the quantum processor to generate solutions to the second problem via the quantum processor.
19. The computational annealing system of claim 18 wherein when the at least one processor employs the existing hardware of the quantum processor to embed the problem graph of the second problem without using the existing hardware to compensate for h/J misbalance error when the at least one processor-based device evolves the quantum processor to generate solutions to the second problem via the quantum processor includes the at least one processor embeds the problem graph of the second problem in a hardware graph of the quantum processor without any ancilla qubits to compensate for h/J misbalance error.
20. The computational annealing system of claim 18 wherein when the at least one processor employs the existing hardware of the quantum processor to embed the problem graph of the second problem without using the existing hardware to compensate for h/J misbalance error when the at least one processor-based device evolves the quantum processor to generate solutions to the second problem via the quantum processor the at least one processor embeds the problem graph of the second problem in a hardware graph of the quantum processor employing one or more of the qubits of the quantum processor that were used as ancilla qubits when the at least one processor-based device evolves the quantum processor to generate solutions for the first problem as problem qubits.