Using classical logic to design quantum circuits for compression of quantum data
- The use of near term quantum devices for compression of information is an exciting prospect which can enable the use of quantum resources for complex tasks. To this end, different compression algorithms, including the quantum autoencoder, have been proposed. These algorithms rely on trained parameterized quantum circuits to perform the compression. The success of the training depends on the structure of the employed circuit, whose design can be difficult to generalize. In this work we propose a novel strategy to design quantum circuits using an evolutionary algorithm, with a restricted gate set based on classical logic operations. The use of the limited gate set enables efficient simulation of the quantum circuit. We show initial applications for compression of different family of states, including single particle states, two particle states, random states, prime states, among others. This opens a new path for using near term quantum devices for compressing quantum data andThe use of near term quantum devices for compression of information is an exciting prospect which can enable the use of quantum resources for complex tasks. To this end, different compression algorithms, including the quantum autoencoder, have been proposed. These algorithms rely on trained parameterized quantum circuits to perform the compression. The success of the training depends on the structure of the employed circuit, whose design can be difficult to generalize. In this work we propose a novel strategy to design quantum circuits using an evolutionary algorithm, with a restricted gate set based on classical logic operations. The use of the limited gate set enables efficient simulation of the quantum circuit. We show initial applications for compression of different family of states, including single particle states, two particle states, random states, prime states, among others. This opens a new path for using near term quantum devices for compressing quantum data and facilitating efficient quantum simulations for various tasks.…
Author: | Abhinav Anand, Jakob S. KottmannORCiDGND, Alán Aspuru-Guzik |
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Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/102009 |
URL: | https://meetings.aps.org/Meeting/MAR22/Session/Q36.8 |
Parent Title (English): | Bulletin of the American Physical Society |
Publisher: | American Physical Society (APS) |
Place of publication: | College Park, MD |
Type: | Article |
Language: | English |
Year of first Publication: | 2022 |
Release Date: | 2023/02/14 |
Volume: | 67 |
Issue: | 3 |
First Page: | Q36.00008 |
Note: | APS March Meeting 2022, Chicago, Ill., USA |
Institutes: | Fakultät für Angewandte Informatik |
Fakultät für Angewandte Informatik / Institut für Informatik | |
Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Quantenalgorithmik |