Invention Grant
- Patent Title: Short-depth active learning quantum amplitude estimation without eigenstate collapse
-
Application No.: US18193082Application Date: 2023-03-30
-
Publication No.: US12159195B2Publication Date: 2024-12-03
- Inventor: Ismail Yunus Akhalwaya , Kenneth Clarkson , Lior Horesh , Mark Squillante , Shashanka Ubaru , Vasileios Kalantzis
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: G06N10/00
- IPC: G06N10/00 ; G06F17/11 ; G06N20/00

Abstract:
Techniques and a system to facilitate estimation of a quantum phase, and more specifically, to facilitate estimation of an expectation value of a quantum state, by utilizing a hybrid of quantum and classical methods are provided. In one example, a system is provided. The system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can include an encoding component and a learning component. The encoding component can encode an expectation value associated with a quantum state. The learning component can utilize stochastic inference to determine the expectation value based on an uncollapsed eigenvalue pair.
Public/Granted literature
- US20240193448A1 SHORT-DEPTH ACTIVE LEARNING QUANTUM AMPLITUDE ESTIMATION WITHOUT EIGENSTATE COLLAPSE Public/Granted day:2024-06-13
Information query