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Related papers: Matrix product states for quantum metrology

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We optimize two-mode, entangled, number states of light in the presence of loss in order to maximize the extraction of the available phase information in an interferometer. Our approach optimizes over the entire available input Hilbert…

We present a compressive quantum process tomography scheme that fully characterizes any rank-deficient completely-positive process with no a priori information about the process apart from the dimension of the system on which the process…

With the rapid development of quantum technologies in recent years, the need for high sensitivity measuring techniques has become a key issue. In particular, optical sensors based on quantum states of light have proven to be optimal…

Quantum Physics · Physics 2023-03-29 Laura T. Knoll , Gustavo M. Bosyk

Quantum metrology allows for a huge boost in the precision of parameters estimation. However, it seems to be extremely sensitive on the noise. Bound entangled states are states with large amount of noise what makes them unusable for almost…

Quantum Physics · Physics 2015-12-09 L. Czekaj , A. Przysiezna , M. Horodecki , P. Horodecki

Quantum tomography requires repeated measurements of many copies of the physical system, all prepared by a source in the unknown state. In the limit of very many copies measured, the often-used maximum-likelihood (ML) method for converting…

Quantum Physics · Physics 2014-10-09 Hui Khoon Ng , Berthold-Georg Englert

We present a novel method to perform quantum state tomography for many-particle systems which are particularly suitable for estimating states in lattice systems such as of ultra-cold atoms in optical lattices. We show that the need for…

Quantum Physics · Physics 2015-06-04 M. Ohliger , V. Nesme , J. Eisert

We introduce the concept of quantum field tomography, the efficient and reliable reconstruction of unknown quantum fields based on data of correlation functions. At the basis of the analysis is the concept of continuous matrix product…

Quantum Physics · Physics 2015-06-22 A. Steffens , C. A. Riofrío , R. Hübener , J. Eisert

The task of reconstructing a low rank matrix from incomplete linear measurements arises in areas such as machine learning, quantum state tomography and in the phase retrieval problem. In this note, we study the particular setup that the…

Information Theory · Computer Science 2016-12-12 Holger Rauhut , Ulrich Terstiege

We prove that the results of a finite set of general quantum measurements on an arbitrary dimensional quantum system can be simulated using a polynomial (in measurements) number of hidden-variable states. In the limit of infinitely many…

Quantum Physics · Physics 2008-11-11 Borivoje Dakic , Milovan Suvakov , Tomasz Paterek , Caslav Brukner

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

Quantum state tomography (QST) is the gold standard technique for obtaining an estimate for the state of small quantum systems in the laboratory. Its application to systems with more than a few constituents (e.g. particles) soon becomes…

As one of the main pillars of quantum technologies, quantum metrology aims to improve measurement precision using techniques from quantum information. The two main strategies to achieve this are the preparation of nonclassical states and…

Quantum Physics · Physics 2025-09-16 Matteo Fadel , Noah Roux , Manuel Gessner

The initialization of a quantum system into a certain state is a crucial aspect of quantum information science. While a variety of measurement strategies have been developed to characterize how well the system is initialized, for a given…

We consider the problem of recovering low-rank matrices from random rank-one measurements, which spans numerous applications including covariance sketching, phase retrieval, quantum state tomography, and learning shallow polynomial neural…

Information Theory · Computer Science 2018-12-04 Yuanxin Li , Cong Ma , Yuxin Chen , Yuejie Chi

In this paper, we explore an efficient online algorithm for quantum state estimation based on a matrix-exponentiated gradient method previously used in the context of machine learning. The state update is governed by a learning rate that…

Quantum Physics · Physics 2019-03-28 Akram Youssry , Christopher Ferrie , Marco Tomamichel

The paper deals with quantum pulse position modulation (PPM), both in the absence (pure states) and in the presence (mixed states) of thermal noise, using the Glauber representation of coherent laser radiation. The objective is to find…

Quantum Physics · Physics 2009-11-16 G. Cariolaro , G. Pierobon

Quantum information theory has generated several interesting conjectures involving products of completely positive maps on matrix algebras, also known as quantum channels. In particular it is conjectured that the output state with maximal…

Quantum Physics · Physics 2007-05-23 C. King

Matrix completion and quantum tomography are two unrelated research areas with great current interest in many modern scientific studies. This paper investigates the statistical relationship between trace regression in matrix completion and…

Statistics Theory · Mathematics 2013-11-21 Yazhen Wang

Identification of the optimal quantum metrological protocols in realistic many particle quantum models is in general a challenge that cannot be efficiently addressed by the state-of-the-art numerical and analytical methods. Here we provide…

We analyze quantum state tomography in scenarios where measurements and states are both constrained. States are assumed to live in a semi-algebraic subset of state space and measurements are supposed to be rank-one POVMs, possibly with…

Quantum Physics · Physics 2017-01-24 Michael Kech , Michael M. Wolf