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Quantum algorithms for ground-state energy estimation of chemical systems require a high-quality initial state. However, initial state preparation is commonly either neglected entirely, or assumed to be solved by a simple product state like…

Multi-photon system has been studied by many groups, however the biggest challenge faced is the number of copies of an unknown state are limited and far from detecting quantum entanglement. The difficulty to prepare copies of the state is…

Quantum Physics · Physics 2017-09-13 Yiping Lu , Qing Zhao

Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain. Recent developments in deep neural networks and normalizing flows…

Quantum Physics · Physics 2023-06-27 Leopoldo Sarra , Florian Marquardt

Quantum process tomography is a necessary tool for verifying quantum gates and diagnosing faults in architectures and gate design. We show that the standard approach of process tomography is grossly inaccurate in the case where the states…

Quantum State Tomography is the task of inferring the state of a quantum system from measurement data. A reliable tomography scheme should not only report an estimate for that state, but also well-justified error bars. These may be…

Quantum Physics · Physics 2019-05-22 Jinzhao Wang , Volkher B. Scholz , Renato Renner

Self-calibrating quantum state tomography aims at reconstructing the unknown quantum state and certain properties of the measurement devices from the same data. Since the estimates of the state and device parameters come from the same data,…

Quantum Physics · Physics 2019-09-09 Jun Yan Sim , Jiangwei Shang , Hui Khoon Ng , Berthold-Georg Englert

The deployment of intermediate- and large-scale quantum devices necessitates the development of efficient full state tomographical techniques for quantum benchmarks. Here, we introduce a matrix filling-based method for tomography of pure…

Quantum Physics · Physics 2021-11-23 Ahmad Farooq , Junaid ur Rehman , Hyundong Shin

Bayesian optimization has attracted huge attention from diverse research areas in science and engineering, since it is capable of efficiently finding a global optimum of an expensive-to-evaluate black-box function. In general, a…

Machine Learning · Computer Science 2025-07-29 Jungtaek Kim

Mutually unbiased bases determine an optimal set of measurements to extract complete information about the quantum state of a system. However, quite often a priori information about the state exist, making some of the measurement bases…

Quantum Physics · Physics 2015-06-12 A. B. Klimov , G. Bjork , L. L. Sanchez-Soto

This paper offers examples of concrete numerical applications of Bayesian quantum-state assignment methods to a three-level quantum system. The statistical operator assigned on the evidence of various measurement data and kinds of prior…

Quantum Physics · Physics 2016-08-14 A. Månsson , P. G. L. Porta Mana , G. Björk

Simulating the nonequilibrium dynamics of thermal states is a fundamental problem across scales from high energy to condensed matter physics. Quantum computers may provide a way to solve this problem efficiently. Preparing a thermal state…

Quantum Physics · Physics 2023-11-03 Jason Saroni , Henry Lamm , Peter P. Orth , Thomas Iadecola

Measurement based (MB) quantum computation allows for universal quantum computing by measuring individual qubits prepared in entangled multipartite states, known as graph states. Unless corrected for, the randomness of the measurements…

Quantum Physics · Physics 2018-02-28 Rawad Mezher , Joe Ghalbouni , Joseph Dgheim , Damian Markham

Quantum tomography is an essential method of the photonic technology toolbox and is routinely used for evaluation of experimentally prepared states of light and characterization of devices transforming such states. The tomography procedure…

Quantum Physics · Physics 2018-12-18 Radim Hošák , Robert Stárek , Miroslav Ježek

As an alternative to variable selection or shrinkage in high dimensional regression, we propose to randomly compress the predictors prior to analysis. This dramatically reduces storage and computational bottlenecks, performing well when the…

Machine Learning · Statistics 2013-03-26 Rajarshi Guhaniyogi , David B. Dunson

Quantum state tomography is an important tool for quantum communication, computation, metrology, and simulation. Efficient quantum state tomography on a high dimensional quantum system is still a challenging problem. Here, we propose a…

Quantum Physics · Physics 2019-08-07 Ruifeng Liu , Junling Long , Pei Zhang , Russell E. Lake , Hong Gao , David P. Pappas , Fuli Li

Every quantum state can be represented as a probability distribution over the outcomes of an informationally complete measurement. But not all probability distributions correspond to quantum states. Quantum state space may thus be thought…

Quantum Physics · Physics 2011-02-14 D. M. Appleby , Asa Ericsson , Christopher A. Fuchs

Recently quantum tomography has been proposed as a fundamental tool for prototyping a few qubit quantum device. It allows the complete reconstruction of the state produced from a given input into the device. From this reconstructed density…

Quantum Physics · Physics 2009-11-07 R. T. Thew , K. Nemoto , A. G. White , W. J. Munro

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

Quantum state tomography (QST) is a crucial tool for characterizing quantum states. However, QST becomes impractical for reconstructing multi-qubit density matrices since data sets and computational costs grow exponentially with qubit…

Quantum Physics · Physics 2026-04-02 Aniket Patel , Akshay Gaikwad , Tangyou Huang , Anton Frisk Kockum , Tahereh Abad

We consider the properties of a specific distribution of mixed quantum states of arbitrary dimension that can be biased towards a specific mean purity. In particular, we analyze mixtures of Haar-random pure states with Dirichlet-distributed…

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