IP Library Granted Patent US 11,699,004
Granted Patent B2
US 11,699,004 · App. 17/207,124 · Granted Jul 11, 2023

Method and system for quantum computing

Inventors: Jianxin Chen (Hangzhou, CN); Fang Zhang (Hangzhou, CN); Yaoyun Shi (Hangzhou, CN); Jiachen Huang (Hangzhou, CN); Michael Newman (Sunnyvale, CA)
Assignee: Alibaba Group Holding Limited
G06F30/20G06F17/16G06F30/3308G06N10/00
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,699,004
App. No.
17/207,124
Granted
Jul 11, 2023
Kind
B2
Abstract

One embodiment described herein provides a system and method for simulating behavior of a quantum circuit that includes a plurality of quantum gates. During operation, the system receives information that represents the quantum circuit and constructs an undirected graph corresponding to the quantum circuit. A respective vertex within the undirected graph corresponds to a distinct variable in a Feynman path integral used for computing amplitude of the quantum circuit, and a respective edge corresponds to one or more quantum gates. The system identifies a vertex within the undirected graph that is coupled to at least two two-qubit quantum gates; simplifies the undirected graph by removing the identified vertex, thereby effectively removing the two-qubit quantum gates coupled to the identified vertex; and evaluates the simplified undirected graph, thereby facilitating simulation of the behavior of the quantum circuit.

Claims (40)

1. A computer-implemented method, the method comprising:

constructing, by a computer, a graph corresponding to a quantum circuit comprising a plurality of quantum gates, wherein each vertex within the graph corresponds to a distinct variable used for computing amplitude of the quantum circuit, and wherein the graph comprises at least one edge corresponding to one or more single-qubit gates and at least one edge corresponding to one or more two-qubit quantum gates;

performing a search on the graph to identify a vertex within the graph that is coupled to at least two edges, with each coupled edge corresponding to at least one two-qubit quantum gate;

simplifying the graph by removing the identified vertex, thereby removing the at least two edges coupled to the identified vertex; and

simulating behavior of the quantum circuit, which comprises evaluating the simplified graph.

2. The computer-implemented method of claim 1 , wherein performing the search to identify the vertex comprises traversing all vertices in the graph.

3. The computer-implemented method of claim 1 , wherein performing the search to identify the vertex comprises performing a greedy-search operation based on an objective function associated with an execution time for evaluating the simplified graph.

4. The computer-implemented method of claim 3 , further comprising computing an initial tensor-contraction ordering by performing a treewidth computing operation.

5. The computer-implemented method of claim 3 , wherein performing the greedy-search operation comprises:

selecting a local range based on the initial tensor-contraction ordering; and

selecting an optimal vertex for removal within the local range in such a way that removing the optimal vertex results in a minimum time cost associated with evaluating the graph.

6. The computer-implemented method of claim 1 , wherein performing the search to identify the vertex comprises performing a dynamic programming operation.

7. The computer-implemented method of claim 1 , wherein the two-qubit quantum gates comprise a two-qubit diagonal quantum gate.

8. The computer-implemented method of claim 7 , wherein the two-qubit diagonal quantum gate comprises a controlled-Z (CZ) gate.

9. The computer-implemented method of claim 1 , wherein the quantum circuit has at least 50 qubits and a depth of at least 30.

10. A computer system, comprising:

a processor; and

a storage device coupled to the processor and storing instructions which when executed by the processor cause the processor to perform a method, the method comprising:

constructing a graph corresponding to a quantum circuit comprising a plurality of quantum gates, wherein each vertex within the graph corresponds to a distinct variable used for computing amplitude of the quantum circuit, and wherein the graph comprises at least one edge corresponding to one or more single-qubit gates and at least one edge corresponding to one or more two-qubit quantum gates;

performing a search on the graph to identify a vertex within the graph that is coupled to at least two edges, with each coupled edge corresponding to at least one two-qubit quantum gate;

simplifying the graph by removing the identified vertex, thereby removing the at least two edges coupled to the identified vertex; and

simulating behavior of the quantum circuit, which comprises evaluating the simplified graph.

11. The computer system of claim 10 , wherein performing the search to identify the vertex comprises traversing all vertices in the graph.

12. The computer system of claim 10 , wherein performing the search to identify the vertex comprises performing a greedy-search operation based on an objective function associated with an execution time for evaluating the simplified graph.

13. The computer system of claim 12 , wherein the method further comprises computing an initial tensor-contraction ordering by performing a treewidth computing operation.

14. The computer system of claim 13 , wherein performing the greedy-search operation comprises:

selecting a local range based on the initial tensor-contraction ordering; and

selecting an optimal vertex for removal within the local range in such a way that removing the optimal vertex results in a minimum time cost associated with evaluating the graph.

15. The computer system of claim 10 , wherein performing the search to identify the vertex comprises performing a dynamic programming operation.

16. The computer system of claim 10 , wherein the two-qubit quantum gates comprise a two-qubit diagonal quantum gate, and wherein the two-qubit diagonal quantum gate comprises a controlled-Z (CZ) gate.

17. The computer system of claim 10 , wherein the quantum circuit has at least 50 qubits and a depth of at least 30.

18. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:

constructing a graph corresponding to a quantum circuit comprising a plurality of quantum gates, wherein each vertex within the graph corresponds to a distinct variable used for computing amplitude of the quantum circuit, and wherein the graph comprises at least one edge corresponding to one or more single-qubit gates and at least one edge corresponding to one or more two-qubit quantum gates;

performing a search on the graph to identify a vertex within the graph that is coupled to at least two edges, with each coupled edge corresponding to at least one two-qubit quantum gate;

simplifying the graph by removing the identified vertex, thereby removing the at least two edges coupled to the identified vertex; and

simulating behavior of the quantum circuit, which comprises evaluating the simplified graph.

19. The non-transitory computer-readable storage medium of claim 18 , wherein performing the search to identify the vertex comprises performing a greedy-search operation based on an objective function associated with an execution time for evaluating the simplified graph.

20. The non-transitory computer-readable storage medium of claim 18 , wherein the method further comprises computing an initial tensor-contraction ordering by performing a treewidth computing operation, and wherein performing the greedy-search operation comprises:

selecting a local range based on the initial tensor-contraction ordering; and

selecting an optimal vertex for removal within the local range in such a way that removing the optimal vertex results in a minimum time cost associated with evaluating the graph.

Priority Claims (1)
CN 201810398402.X · Apr 27, 2018 · national
Continuity (2)
Continuation 16387408 · Apr 17, 2019
Related Publication 20210350056A1 · Nov 11, 2021