Implementation of quantum compression on IBM quantum computers

PIVOLUSKA, Matej and Martin PLESCH. Implementation of quantum compression on IBM quantum computers. Nature Scientific Reports. USA: NATURE PUBLISHING GROUP, 2022, vol. 12, No 1, p. 5841-5849. ISSN 2045-2322. Available from: https://dx.doi.org/10.1038/s41598-022-09881-8.

Basic information

• Original name: Implementation of quantum compression on IBM quantum computers
• Authors: PIVOLUSKA, Matej (703 Slovakia, guarantor, belonging to the institution) and Martin PLESCH (703 Slovakia, belonging to the institution).
• Edition: Nature Scientific Reports, USA, NATURE PUBLISHING GROUP, 2022, 2045-2322.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Germany
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Impact factor: Impact factor: 4.600
• RIV identification code: RIV/00216224:14610/22:00125784
• Organization unit: Institute of Computer Science
• Doi: http://dx.doi.org/10.1038/s41598-022-09881-8
• UT WoS: 000779768200001
• Keywords in English: quantum computing; compression
• Tags: J-D1, rivok
• Tags: International impact, Reviewed

Abstract

Advances in development of quantum computing processors brought ample opportunities to test the performance of various quantum algorithms with practical implementations. In this paper we report on implementations of quantum compression algorithm that can efficiently compress unknown quantum information. We restricted ourselves to compression of three pure qubits into two qubits, as the complexity of even such a simple implementation is barely within the reach of today's quantum processors. We implemented the algorithm on IBM quantum processors with two different topological layouts - a fully connected triangle processor and a partially connected line processor. It turns out that the incomplete connectivity of the line processor affects the performance only minimally. On the other hand, it turns out that the transpilation, i.e. compilation of the circuit into gates physically available to the quantum processor, crucially influences the result. We also have seen that the compression followed by immediate decompression is, even for such a simple case, on the edge or even beyond the capabilities of currently available quantum processors.

Links

• MUNI/G/1596/2019, interní kód MU: Name: Development of algorithms for application of quantum computers in electronic-structure calculations in solid-state physics and chemistry (Acronym: Qubits4PhysChem)

Investor: Masaryk University, INTERDISCIPLINARY - Interdisciplinary research projects