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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

Quantum networks allow in principle for completely novel forms of quantum correlations. In particular, quantum nonlocality can be demonstrated here without the need of having various input settings, but only by considering the joint…

We show that, assuming that quantum mechanics holds locally, the finite speed of information is the principle that limits all possible correlations between distant parties to be quantum mechanical as well. Local quantum mechanics means that…

Quantum Physics · Physics 2010-04-28 H. Barnum , S. Beigi , S. Boixo , M. B. Elliott , S. Wehner

Several important measures of quantum correlations of a state of a finite-dimensional composite system are defined as linear combinations of marginal entropies of this state. This paper is devoted to the infinite-dimensional generalizations…

Quantum Physics · Physics 2017-08-23 M. E. Shirokov

The locality issue of quantum mechanics is a key issue to a proper understanding of quantum physics and beyond. What has been commonly emphasized as quantum nonlocality has received an inspiring examination through the notion of Heisenberg…

Quantum Physics · Physics 2024-06-11 Otto C. W. Kong

Quantum state discrimination involves identifying a given state out of a set of possible states. When the states are mutually orthogonal, perfect state discrimination is always possible using a global measurement. In the case of…

Quantum Physics · Physics 2023-09-13 Scott M. Cohen

Understanding the emergence of chaos in many-body quantum systems away from semi-classical limits, particularly in spatially local interacting spin Hamiltonians, has been a long-standing problem. In these intrinsically quantum regimes,…

Statistical Mechanics · Physics 2025-01-24 Christopher M. Langlett , Cheryne Jonay , Vedika Khemani , Joaquin F. Rodriguez-Nieva

In quantum mechanics, joint measurements of non-commuting observables are only possible if a minimal unavoidable measurement uncertainty is accepted. On the other hand, correlations between non-commuting observables can exceed classical…

Quantum Physics · Physics 2019-07-24 Holger F. Hofmann

A quantum spin-$\frac{1}{2}$ chain with an axial symmetry is normally described by quasiparticles associated with the spins oriented along the axis of rotation. Kinetic constraints can enrich such a description by setting apart different…

Quantum Physics · Physics 2024-04-25 Maurizio Fagotti

Measurements play an important role in quantum computing (QC), by either providing the nonlinearity required for two-qubit gates (linear optics QC), or by implementing a quantum algorithm using single-qubit measurements on a highly…

Quantum Physics · Physics 2008-11-17 Radu Ionicioiu , Anca E. Popescu , William J. Munro , Timothy P. Spiller

We develop a general theoretical framework for measurement protocols employing statistical correlations of randomized measurements. We focus on locally randomized measurements implemented with local random unitaries in quantum lattice…

Quantum Physics · Physics 2019-05-21 Andreas Elben , Benoît Vermersch , Christian F. Roos , Peter Zoller

Quantum computation can proceed solely through single-qubit measurements on an appropriate quantum state, such as the ground state of an interacting many-body system. We investigate a simple spin-lattice system based on the cluster-state…

Quantum Physics · Physics 2009-07-16 Andrew C. Doherty , Stephen D. Bartlett

The Lasso is a method for high-dimensional regression, which is now commonly used when the number of covariates $p$ is of the same order or larger than the number of observations $n$. Classical asymptotic normality theory does not apply to…

Statistics Theory · Mathematics 2023-09-20 Michael Celentano , Andrea Montanari , Yuting Wei

We construct a canonical quantization of the two dimensional theory of a parametrized scalar field on noncompact spatial slices. The kinematics is built upon generalized charge-network states which are labelled by smooth embedding…

General Relativity and Quantum Cosmology · Physics 2014-04-09 Sandipan Sengupta

Quantum state tomography is a technique in quantum information science used to reconstruct the density matrix of an unknown quantum state, providing complete information about the quantum state. It is of significant importance in fields…

Quantum Physics · Physics 2025-07-23 Wenlong Zhao , Da Zhang , Huili Zhang , Haifeng Yu , Zhang-qi Yin

In characterization of quantum systems, adapting measurement settings based on data while it is collected can generally outperform in efficiency conventional measurements that are carried out independently of data. The existing methods for…

Quantum Physics · Physics 2016-11-21 Markku P. V. Stenberg , Frank K. Wilhelm

We perform numerical tests on quantum nonlocality of two-level quantum systems (qubits) observed by a uniformly moving observer. Under a suitable momentum setting, the quantum nonlocality of two-qubit nonmaximally entangled states could be…

Quantum Physics · Physics 2015-06-15 Hong-Yi Su , Yu-Chun Wu , Jing-Ling Chen , Chunfeng Wu , L. C. Kwek

We discuss quantum speed limits (QSLs) for finite-dimensional quantum systems undergoing general physical processes. These QSLs were obtained using Schatten $\alpha$-norms, firstly exploiting geometric features of the quantum state space,…

Quantum Physics · Physics 2025-07-23 Alberto J. B. Rosal , Diogo O. Soares-Pinto , Diego Paiva Pires

We consider one of the most important problems in directional statistics, namely the problem of testing the null hypothesis that the spike direction $\theta$ of a Fisher-von Mises-Langevin distribution on the $p$-dimensional unit…

Statistics Theory · Mathematics 2019-03-05 Davy Paindaveine , Thomas Verdebout

We study the distribution of a fully connected neural network with random Gaussian weights and biases in which the hidden layer widths are proportional to a large constant $n$. Under mild assumptions on the non-linearity, we obtain…

Machine Learning · Computer Science 2024-06-18 Stefano Favaro , Boris Hanin , Domenico Marinucci , Ivan Nourdin , Giovanni Peccati
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