Universal compilation for quantum state tomography

Abstract Universal compilation is a training process that compiles a trainable unitary into a target unitary. It has vast potential applications from depth-circuit compressing to device benchmarking and quantum error mitigation. Here we propose a universal compilation algorithm for quantum state tom...

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Main Authors: Vu Tuan Hai, Le Bin Ho
Format: Article
Language:English
Published: Nature Portfolio 2023-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-30983-4
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author Vu Tuan Hai
Le Bin Ho
author_facet Vu Tuan Hai
Le Bin Ho
author_sort Vu Tuan Hai
collection DOAJ
description Abstract Universal compilation is a training process that compiles a trainable unitary into a target unitary. It has vast potential applications from depth-circuit compressing to device benchmarking and quantum error mitigation. Here we propose a universal compilation algorithm for quantum state tomography in low-depth quantum circuits. We apply the Fubini-Study distance as a trainable cost function and employ various gradient-based optimizations. We evaluate the performance of various trainable unitary topologies and the trainability of different optimizers for getting high efficiency and reveal the crucial role of the circuit depth in robust fidelity. The results are comparable with the shadow tomography method, a similar fashion in the field. Our work expresses the adequate capability of the universal compilation algorithm to maximize the efficiency in the quantum state tomography. Further, it promises applications in quantum metrology and sensing and is applicable in the near-term quantum computers for various quantum computing tasks.
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spelling doaj.art-580c056fdd5a481784756d00a6b25cf72023-03-22T11:03:01ZengNature PortfolioScientific Reports2045-23222023-03-0113111210.1038/s41598-023-30983-4Universal compilation for quantum state tomographyVu Tuan Hai0Le Bin Ho1University of Information TechnologyHo Chi Minh City Institute of Physics, National Institute of Applied Mechanics and Informatics, Vietnam Academy of Science and TechnologyAbstract Universal compilation is a training process that compiles a trainable unitary into a target unitary. It has vast potential applications from depth-circuit compressing to device benchmarking and quantum error mitigation. Here we propose a universal compilation algorithm for quantum state tomography in low-depth quantum circuits. We apply the Fubini-Study distance as a trainable cost function and employ various gradient-based optimizations. We evaluate the performance of various trainable unitary topologies and the trainability of different optimizers for getting high efficiency and reveal the crucial role of the circuit depth in robust fidelity. The results are comparable with the shadow tomography method, a similar fashion in the field. Our work expresses the adequate capability of the universal compilation algorithm to maximize the efficiency in the quantum state tomography. Further, it promises applications in quantum metrology and sensing and is applicable in the near-term quantum computers for various quantum computing tasks.https://doi.org/10.1038/s41598-023-30983-4
spellingShingle Vu Tuan Hai
Le Bin Ho
Universal compilation for quantum state tomography
Scientific Reports
title Universal compilation for quantum state tomography
title_full Universal compilation for quantum state tomography
title_fullStr Universal compilation for quantum state tomography
title_full_unstemmed Universal compilation for quantum state tomography
title_short Universal compilation for quantum state tomography
title_sort universal compilation for quantum state tomography
url https://doi.org/10.1038/s41598-023-30983-4
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