Granted Patent B2

US 12,333,379 · App. 17/540,485 · Granted Jun 17, 2025

Inventors: Frederik Frank Flöther (Schlieren, CH); Michele Grossi (Prevessin-Möens, FR); Vaibhaw Kumar (Frederick, MD); Robert E. Loredo (North Miami Beach, FL)

Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION

G06N10/00G06F11/3428G06F18/2135

Abstract

Claims (44)

1. A system, comprising:

a processor that executes computer-executable components stored in memory, wherein the computer-executable components comprise:

a data selection component that, for an iteration of a data selection routine, selects, from a set of data, a subset of the data to be processed by a quantum algorithm on a quantum device; and

a metric assessment component that, for the iteration of the data selection routine, generates a metric score for a result of processing the subset of the data by the quantum algorithm, the metric score representing a degree to which the result satisfies a processing performance metric,

wherein

the data selection component modifies the subset of the data selected for a subsequent iteration of the data selection routine based on the metric score to yield a modified subset of the data, and the computer-executable components further comprise a device interface component that, in response to a determination that a termination criterion for the data selection routine is satisfied, outputs the modified subset of the data generated by a most recent iteration of the data selection routine as input to the quantum device, and wherein the device interface component, for the iteration of the data selection routine, selects the quantum device on which to process the subset of the clustered data from multiple available quantum devices, and the data selection component selects the subset of the data based on at least one of a capability or a constraint of the quantum device determined based on device property information for the quantum device.

2. The system of claim 1 , further comprising a clustering component that clusters the set of data to yield clustered data,

wherein the data selection component selects the subset of the data from the clustered data.

3. The system of claim 2 , further comprising a compression component that compresses the set of data or the clustered data.

4. The system of claim 3 , wherein the compression component compresses the set of data or the clustered data using at least one of principal component analysis or autoencoding.

5. The system of claim 2 , wherein the clustering component clusters the set of data into data clusters according to at least one of a characteristic, a feature, or a classification determined based on a type of the quantum algorithm.

6. The system of claim 5 , wherein the data selection component selects the subset of the data such that each of the data clusters is represented in the subset of the clustered data.

7. The system of claim 1 , wherein the processing performance metric is at least one of accuracy, execution time, calculation robustness.

8. The system of claim 1 , wherein the metric assessment component selects the processing performance metric based on a type of the quantum algorithm.

9. The system of claim 1 , wherein

the device determination component determines an upper limit on an amount of data that can be input to the quantum device based on device property information for the quantum device, and

the data selection component selects, as the subset of the data, an amount of the data equal to or less than the upper limit.

10. The system of claim 1 , wherein the data selection component modifies the subset of the data selected for the subsequent iteration based on a determination of whether the metric score has improved or worsened relative to a previous metric score generated for a previous iteration of the data selection routine.

11. The system of claim 1 , wherein the termination criterion is at least one of the metric score being within a defined range of a target value, execution of a specified number of iterations of the data selection routine, or expiration of a time limit for execution of the data selection routine.

12. The system of claim 1 , wherein the device interface component modifies selection of the quantum device for the subsequent iteration of the data selection routine based on the metric score.

13. A computer-implemented method, comprising:

for respective iterations of a data selection routine:

selecting, by a system operatively coupled to a processor, from a set of data, a subset of the data to be processed by an algorithm on a quantum device;

generating, by the system based on analysis of a result of processing the subset of the data by the algorithm, a metric score that represents a degree to which the result satisfies a processing performance metric; and

modifying, by the system, selection of the subset of the data for a next iteration of the data selection routine based on the metric score to yield a modified subset of the data; and

in response to determining that a termination criterion for the data selection routine is satisfied, outputting, by the system, the modified subset of the data generated by a most recent iteration of the data selection routine as input to the quantum device, and wherein for the iteration of the data selection routine, selecting the quantum device on which to process the subset of the clustered data from multiple available quantum devices, and selecting the subset of data based on at least one of a capability or a constraint of the quantum device determined based on device property information for the quantum device.

14. The computer-implemented method of claim 13 , further comprising clustering, by the system, the set of data to yield clustered data,

wherein the selecting of the subset of the data comprises selecting the subset of the data from the clustered data.

15. The computer-implemented method of claim 14 , further comprising at least one of:

compressing, by the system, the set of data prior to the clustering, or

compressing, by the system, the subset of the data prior to the sending.

16. The computer-implemented method of claim 14 , wherein

the clustering comprises clustering the set of data into data clusters according to at least one of a characteristic, a feature, or a classification determined based on a type of the algorithm, and

the selecting comprises selecting the subset of the data such that each of the data clusters is represented in the subset of the data.

17. The computer-implemented method of claim 13 , wherein the processing performance metric comprises at least one of accuracy, execution time, or calculation robustness.

18. A computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

for respective iterations of a data selection routine:

select, by the processor, from a set of data, a subset of the data to be processed by an algorithm on a quantum device;

generate, by the processor based on analysis of a result of processing the subset of the data by the algorithm, a metric score that represents a degree to which the result satisfies a processing performance metric; and

modify, by the processor, selection of the subset of the data for a next iteration of the data selection routine based on the metric score to yield a modified subset of the data; and

in response to determining that a termination criterion for the data selection routine is satisfied, output, by the processor, the modified subset of the data generated by a most recent iteration of the data selection routine as input to the quantum device, and wherein for the iteration of the data selection routine, selecting the quantum device on which to process the subset of the clustered data from multiple available quantum devices, and selecting the subset of data based on at least one of a capability or a constraint of the quantum device determined based on device property information for the quantum device.

19. The computer program product of claim 18 , wherein the program instructions executable by the processor further cause the processor to:

cluster, by the processor, the set of data to yield clustered data; and

select the subset of the data from the clustered data.

Assignments (1)

Continuity (1)

References Cited (33)