Quantum computers hold promise to improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties that are more complex than tractable at present on classical architectures. Here, we discuss computational frameworks to carry out electronic structure calculations of solids on noisy intermediate-scale quantum computers using embedding theories, and we give examples for a specific class of materials, that is, solid materials hosting spin defects. These are promising systems to build future quantum technologies, such as quantum computers, quantum sensors and quantum communication devices. Although quantum simulations on quantum architectures are in their infancy, promising results for realistic systems appear to be within reach.

Quantum embedding theories to simulate condensed systems on quantum computers / Vorwerk, Christian; Sheng, Nan; Govoni, Marco; Huang, Benchen; Galli, Giulia. - In: NATURE COMPUTATIONAL SCIENCE. - ISSN 2662-8457. - 2:7(2022), pp. 424-432. [10.1038/s43588-022-00279-0]

Quantum embedding theories to simulate condensed systems on quantum computers

Govoni Marco
;
2022-01-01

Abstract

Quantum computers hold promise to improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties that are more complex than tractable at present on classical architectures. Here, we discuss computational frameworks to carry out electronic structure calculations of solids on noisy intermediate-scale quantum computers using embedding theories, and we give examples for a specific class of materials, that is, solid materials hosting spin defects. These are promising systems to build future quantum technologies, such as quantum computers, quantum sensors and quantum communication devices. Although quantum simulations on quantum architectures are in their infancy, promising results for realistic systems appear to be within reach.
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Quantum embedding theories to simulate condensed systems on quantum computers / Vorwerk, Christian; Sheng, Nan; Govoni, Marco; Huang, Benchen; Galli, Giulia. - In: NATURE COMPUTATIONAL SCIENCE. - ISSN 2662-8457. - 2:7(2022), pp. 424-432. [10.1038/s43588-022-00279-0]
Vorwerk, Christian; Sheng, Nan; Govoni, Marco; Huang, Benchen; Galli, Giulia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1295283
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