Approximate Message Passing for Quantum State Tomography
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914233642385408 |
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| author | Siekierski, Noah Chandramouli, Kausthubh Kümmerle, Christian Bakalov, Bojko N. Baron, Dror |
| author_facet | Siekierski, Noah Chandramouli, Kausthubh Kümmerle, Christian Bakalov, Bojko N. Baron, Dror |
| contents | Quantum state tomography (QST) is an indispensable tool for characterizing many-body quantum systems. However, due to the exponential scaling of the cost of the protocol with system size, many approaches have been developed for quantum states with specific structure, such as low-rank states. In this paper, we show how approximate message passing (AMP), an algorithmic framework for sparse signal recovery, can be used to perform low-rank QST. AMP provides asymptotically optimal performance guarantees for large sparse recovery problems, which suggests its utility for QST. We discuss the design challenges that come with applying AMP to QST, and show that by properly designing the AMP algorithm, we can reduce the reconstruction error by over an order of magnitude compared to existing approaches to low-rank QST. We also performed tomographic experiments on IBM Kingston and considered the effect of device noise on the reliability of the predicted fidelity of state preparation. Our work advances the state of low-rank QST and may be applicable to other quantum tomography protocols. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_12857 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Approximate Message Passing for Quantum State Tomography Siekierski, Noah Chandramouli, Kausthubh Kümmerle, Christian Bakalov, Bojko N. Baron, Dror Quantum Physics Data Structures and Algorithms Information Theory Optimization and Control Quantum state tomography (QST) is an indispensable tool for characterizing many-body quantum systems. However, due to the exponential scaling of the cost of the protocol with system size, many approaches have been developed for quantum states with specific structure, such as low-rank states. In this paper, we show how approximate message passing (AMP), an algorithmic framework for sparse signal recovery, can be used to perform low-rank QST. AMP provides asymptotically optimal performance guarantees for large sparse recovery problems, which suggests its utility for QST. We discuss the design challenges that come with applying AMP to QST, and show that by properly designing the AMP algorithm, we can reduce the reconstruction error by over an order of magnitude compared to existing approaches to low-rank QST. We also performed tomographic experiments on IBM Kingston and considered the effect of device noise on the reliability of the predicted fidelity of state preparation. Our work advances the state of low-rank QST and may be applicable to other quantum tomography protocols. |
| title | Approximate Message Passing for Quantum State Tomography |
| topic | Quantum Physics Data Structures and Algorithms Information Theory Optimization and Control |
| url | https://arxiv.org/abs/2511.12857 |