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The temporal evolution of a quantum system can be characterized by quantum process tomography, a complex task that consumes a number of physical resources scaling exponentially with the number of subsystems. An alternative approach to the…

We present a method for quantum state tomography that enables the efficient estimation, with fixed precision, of any of the matrix elements of the density matrix of a state, provided that the states from the basis in which the matrix is…

Quantum Physics · Physics 2015-06-12 Ariel Bendersky , Juan Pablo Paz

Classical shadows are an efficient method for constructing an approximate classical description of a quantum state using very few measurements. In the paper we propose to enhance classical shadow methods using bootstrap resampling methods.…

Quantum Physics · Physics 2025-11-18 Eric Ghysels , Jack Morgan

This paper presents a novel non-linear model reduction method: Probabilistic Manifold Decomposition (PMD), which provides a powerful framework for constructing non-intrusive reduced-order models (ROMs) by embedding a high-dimensional system…

Numerical Analysis · Mathematics 2026-01-09 Jiaming Guo , Dunhui Xiao

The recent development of scintillation crystals combined with $\gamma$-rays sources opens the way to an imaging concept based on Compton scattering, namely Compton scattering tomography (CST). The associated inverse problem rises many…

Numerical Analysis · Mathematics 2023-02-22 Janek Gödeke , Gaël Rigaud

In general, the state of a quantum system represented by density operator and its determination is a fundamental problem in quantum mechanics. A method of direct measurement of matrix element of density operator of a single two dimensional…

Quantum Physics · Physics 2022-02-16 Yusuf Turek

Classical shadow tomography provides an efficient method for predicting functions of an unknown quantum state from a few measurements of the state. It relies on a unitary channel that efficiently scrambles the quantum information of the…

Quantum Physics · Physics 2022-02-01 Hong-Ye Hu , Yi-Zhuang You

Dark matter (DM) is currently searched for with a variety of detection strategies. Accelerator searches are particularly promising, but even if Weakly Interacting Massive Particles (WIMPs) are found at the Large Hadron Collider (LHC), it…

High Energy Physics - Phenomenology · Physics 2010-10-13 Gianfranco Bertone , David G. Cerdeno , Mattia Fornasa , Roberto Ruiz de Austri , Roberto Trotta

Reconstruction of a quantum state is of prime importance for quantum-information science. Specifically, means of efficient determination of a state of atoms of room-temperature vapor may enable applications in quantum computations and…

Quantum Physics · Physics 2022-09-07 Marek Kopciuch , Szymon Pustelny

Accurately establishing the state of large-scale quantum systems is an important tool in quantum information science; however, the large number of unknown parameters hinders the rapid characterisation of such states, and reconstruction…

Quantum Physics · Physics 2014-07-30 Francesco Tonolini , Susan Chan , Megan Agnew , Alan Lindsay , Jonathan Leach

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…

High-quality quantum state generation is essential for advanced quantum information processing, including quantum communication, quantum sensing, and quantum computing. In practice, various error sources degrade the quality of quantum…

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

In this work, we investigate the diffusive optical tomography (DOT) problem in the case that limited boundary measurements are available. Motivated by the direct sampling method (DSM), we develop a deep direct sampling method (DDSM) to…

Numerical Analysis · Mathematics 2021-05-10 Jiahua Jiang , Yi Li , Ruchi Guo

Quantum state tomography (QST) via local measurements on reduced density matrices (LQST) is a promising approach but becomes impractical for large systems. To tackle this challenge, we developed an efficient quantum state tomography method…

Measuring global quantum properties-such as the fidelity to complex multipartite states-is both an essential and experimentally challenging task. Classical shadow estimation offers favorable sample complexity, but typically relies on…

Quantum Physics · Physics 2026-02-11 Qingyue Zhang , Dayue Qin , Zhou You , Feng Xu , Jens Eisert , You Zhou

Partial tomography, which focuses on reconstructing reduced density matrices (RDMs), has emerged as a promising approach for characterizing complex quantum systems, particularly when full state tomography is impractical. Recently,…

Quantum Physics · Physics 2024-10-18 Chao Wei , Tao Xin

The number of measurements required to reconstruct the states of quantum systems increases exponentially with the quantum system dimensions, which makes the state reconstruction of high-qubit quantum systems have a great challenge in…

Quantum Physics · Physics 2017-11-08 J. Yang , S. Cong , X. Liu , Z. Li , K. Li

We discuss a scheme for reconstructing experimentally the diagonal elements of the density matrix of quantum optical states. Applications to PDC heralded photons, multi-thermal and attenuated coherent states are illustrated and discussed in…

Quantum Physics · Physics 2007-05-23 G. Brida , M. Genovese , M. Gramegna , M. G. A. Paris , E. Predazzi , E. Cagliero

Quantum learning encounters fundamental challenges when estimating non-linear properties, owing to the inherent linearity of quantum mechanics. Although recent advances in single-copy randomized measurement protocols have achieved optimal…

Quantum Physics · Physics 2026-03-30 Zhenyu Du , Yifan Tang , Andreas Elben , Ingo Roth , Jens Eisert , Zhenhuan Liu
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