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Related papers: Efficient tomography of a quantum many-body system

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We propose an approach to reconstruct any superconducting charge qubit state by using quantum state tomography. This procedure requires a series of measurements on a large enough number of identically prepared copies of the quantum system.…

Quantum Physics · Physics 2009-11-10 Yu-xi Liu , L. F. Wei , Franco Nori

We perform quantum simulation on classical and quantum computers and set up a machine learning framework in which we can map out phase diagrams of known and unknown quantum many-body systems in an unsupervised fashion. The classical…

Quantum Physics · Physics 2022-10-21 Korbinian Kottmann

Sampling problems have emerged as a central avenue for demonstrating quantum advantage on noisy intermediate-scale quantum devices. However, physical noise can fundamentally alter their computational complexity, often making them…

Quantum Physics · Physics 2025-11-07 Sojeong Park , Changhun Oh

Quantum state tomography via local measurements is an efficient tool for characterizing quantum states. However it requires that the original global state be uniquely determined (UD) by its local reduced density matrices (RDMs). In this…

Quantum state tomography (QST), the process through which the density matrix of a quantum system is characterized from measurements of specific observables, is a fundamental pillar in the fields of quantum information and computation. In…

Quantum Physics · Physics 2024-01-30 J. L. Montenegro Ferreira , B. de Lima Bernardo

Debugging quantum states transformations is an important task of modern quantum computing. The use of quantum tomography for these purposes significantly expands the range of possibilities. However, the presence of preparation and…

Quantum Physics · Physics 2022-01-11 B. I. Bantysh , Yu. I. Bogdanov

Quantum state tomography is a daunting challenge of experimental quantum computing even in moderate system size. One way to boost the efficiency of state tomography is via local measurements on reduced density matrices, but the…

Quantum Physics · Physics 2019-12-03 Tao Xin , Sirui Lu , Ningping Cao , Galit Anikeeva , Dawei Lu , Jun Li , Guilu Long , Bei Zeng

In the era of noisy, intermediate-scale quantum (NISQ) devices, the efficient preparation of many-body resource states is a task of paramount importance. In this paper we focus on the deterministic preparation of matrix-product states (MPS)…

Quantum Physics · Physics 2025-12-11 David T. Stephen , Oliver Hart

Inspired by the advancements in large language models based on transformers, we introduce the transformer quantum state (TQS): a versatile machine learning model for quantum many-body problems. In sharp contrast to Hamiltonian/task specific…

Quantum Physics · Physics 2023-03-08 Yuan-Hang Zhang , Massimiliano Di Ventra

Quantum computation has been growing rapidly in both theory and experiments. In particular, quantum computing devices with a large number of qubits have been developed by IBM, Google, IonQ, and others. The current quantum computing devices…

Quantum Physics · Physics 2021-02-10 Rishabh Gupta , Rongxin Xia , Raphael D. Levine , Sabre Kais

In this letter, we address the problem of developing quantum state tomography (QST) methods that remain valid at any time during a sequence of measurements. Specifically, the aim is to provide a rigorous quantification of the uncertainty…

Information Theory · Computer Science 2026-05-18 Aldo Cumitini , Luca Barletta , Osvaldo Simeone

Matrix product states (MPS) are a central language for one-dimensional quantum matter and a practical target for near-term quantum simulators and variational algorithms. Yet, while substantial effort has focused on preparing MPS with…

Quantum Physics · Physics 2026-04-21 Hyunho Cha , Subin Kim , Jungwoo Lee

We introduce Sketch Tomography, an efficient procedure for quantum state tomography based on the classical shadow protocol used for quantum observable estimations. The procedure applies to the case where the ground truth quantum state is a…

Quantum Physics · Physics 2026-05-27 Xun Tang , Haoxuan Chen , Yuehaw Khoo , Lexing Ying

Measurements are central in all quantitative sciences, and a fundamental challenge is to make observations without systematic measurement errors. This holds in particular for quantum information processing, where other error sources, such…

Improved measurement techniques are central to technological development and foundational scientific exploration. Quantum optics relies upon detectors sensitive to non-classical features of light, enabling precise tests of physical laws and…

Quantum Physics · Physics 2014-07-18 Merlin Cooper , Michal Karpinski , Brian J. Smith

The development of large-scale platforms for quantum information requires new methods for verification and validation of quantum behavior. Quantum tomography (QT) is the standard tool for diagnosing quantum states, process, and readout…

Quantum Physics · Physics 2017-01-10 Charles H. Baldwin

To obtain a complete description of a quantum system, one usually employs standard quantum state tomography, which however requires exponential number of measurements to perform and hence is impractical when the system's size grows large.…

Quantum Physics · Physics 2020-01-17 Tao Xin , Xinfang Nie , Xiangyu Kong , Jingwei Wen , Dawei Lu , Jun Li

Effective quantum computation relies upon making good use of the exponential information capacity of a quantum machine. A large barrier to designing quantum algorithms for execution on real quantum machines is that, in general, it is…

Quantum Physics · Physics 2020-05-12 Adam Holmes , A. Y. Matsuura

Numerical simulations are a powerful tool to study quantum systems beyond exactly solvable systems lacking an analytic expression. For one-dimensional entangled quantum systems, tensor network methods, amongst them Matrix Product States…

Quantum Gases · Physics 2018-02-28 Daniel Jaschke , Michael L. Wall , Lincoln D. Carr

Matrix-product states (MPS) have proven to be a versatile ansatz for modeling quantum many-body physics. For many applications, and particularly in one-dimension, they capture relevant quantum correlations in many-body wavefunctions while…

Machine Learning · Statistics 2025-10-03 Joshua B. Moore , Hugo P. Stackhouse , Ben D. Fulcher , Sahand Mahmoodian