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Related papers: Rank Reduction for the Local Consistency Problem

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It is well known that any $N$ orthogonal pure states can always be perfectly distinguished under local operation and classical communications (LOCC) if $(N-1)$ copies of the state are available [Phys. Rev. Lett. 85, 4972 (2000)]. It is…

Quantum Physics · Physics 2024-05-21 Xing-Chen Guo , Mao-Sheng Li

Necessary and sufficient conditions for the equivalence of arbitrary n-qubit pure quantum states under Local Unitary (LU) operations are derived. First, an easily computable standard form for multipartite states is introduced. Two generic…

Quantum Physics · Physics 2015-05-14 B. Kraus

This paper deals with a method for the approximation of a spectral density function among the solutions of a generalized moment problem a` la Byrnes/Georgiou/Lindquist. The approximation is pursued with respect to the Kullback-Leibler…

Optimization and Control · Mathematics 2009-11-04 Augusto Ferrante , Federico Ramponi , Francesco Ticozzi

Fabrication process variations can significantly influence the performance and yield of nano-scale electronic and photonic circuits. Stochastic spectral methods have achieved great success in quantifying the impact of process variations,…

Machine Learning · Statistics 2021-06-29 Zichang He , Zheng Zhang

A central challenge in quantum simulation is to prepare low-energy states of strongly interacting many-body systems. In this work, we study the problem of preparing a quantum state that optimizes a random all-to-all, sparse or dense, spin…

Quantum Physics · Physics 2024-11-06 Joao Basso , Chi-Fang Chen , Alexander M. Dalzell

We describe an algorithm for sampling a low-rank random matrix $Q$ that best approximates a fixed target matrix $P\in\mathbb{C}^{n\times m}$ in the following sense: $Q$ is unbiased, i.e., $\mathbb{E}[Q] = P$; $\mathsf{rank}(Q)\leq r$; and…

Data Structures and Algorithms · Computer Science 2026-03-18 Leighton Pate Barnes , Stephen Cameron , Benjamin Howard

The problem of partitioning a large and sparse tensor is considered, where the tensor consists of a sequence of adjacency matrices. Theory is developed that is a generalization of spectral graph partitioning. A best rank-$(2,2,\lambda)$…

Numerical Analysis · Mathematics 2020-12-17 Lars Eldén , Maryam Dehghan

Low-rank matrix models have been universally useful for numerous applications, from classical system identification to more modern matrix completion in signal processing and statistics. The nuclear norm has been employed as a convex…

Statistics Theory · Mathematics 2023-03-06 Kiryung Lee , Rakshith Sharma Srinivasa , Marius Junge , Justin Romberg

We prove a rank-two potential automorphy theorem for mod $l$ representations satisfying an ordinary condition. Combined with an ordinary automorphy lifting theorem, we prove a rank-two, $p \ne l$ case of local-global compatibility for…

Number Theory · Mathematics 2024-01-10 Yuji Yang

We consider the problem of deterministically cloning quantum channels with respect to the best attainable rate and the highest quality, so-called optimal cloning. We demonstrate that cloning quantum states is, in-fact, equivalent to cloning…

The problem of estimating the spectrum of a density matrix is considered. Other problems, such as bipartite pure state entanglement, can be reduced to spectrum estimation. A local operations and classical communication (LOCC) measurement…

Quantum Physics · Physics 2007-05-23 Manuel A. Ballester

A systematic numerical approach to approximate high dimensional Lindblad equations is described. It is based on a deterministic rank m approximation of the density operator, the rank m being the only parameter to adjust. From a known…

Computational Physics · Physics 2013-03-14 Claude Le Bris , Pierre Rouchon

Quantum supremacy poses that a realistic quantum computer can perform a calculation that classical computers cannot in any reasonable amount of time. It has become a topic of significant research interest since the birth of the field, and…

Quantum Physics · Physics 2023-01-10 Kabgyun Jeong

The quantum marginal problem asks whether a set of given density matrices are consistent, i.e., whether they can be the reduced density matrices of a global quantum state. Not many non-trivial analytic necessary (or sufficient) conditions…

Quantum Physics · Physics 2016-03-09 Jianxin Chen , Zhengfeng Ji , Nengkun Yu , Bei Zeng

We study the problem of bivariate discrete or continuous probability density estimation under low-rank constraints.For discrete distributions, we assume that the two-dimensional array to estimate is a low-rank probability matrix. In the…

Statistics Theory · Mathematics 2024-10-23 Julien Chhor , Olga Klopp , Alexandre Tsybakov

We study generalization properties of kernel regularized least squares regression based on a partitioning approach. We show that optimal rates of convergence are preserved if the number of local sets grows sufficiently slowly with the…

Statistics Theory · Mathematics 2019-02-26 Nicole Mücke

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

Given L-qubit states with the fixed spectra of reduced one-qubit density matrices, we find a formula for the minimal number of invariant polynomials needed for solving local unitary (LU) equivalence problem, that is, problem of deciding if…

Quantum Physics · Physics 2014-07-18 Tomasz Maciazek , Michał Oszmaniec , Adam Sawicki

We propose a novel optimization scheme designed to find optimally correctable subspace codes for a known quantum noise channel. To each candidate subspace code we first associate a universal recovery map, as if the code was perfectly…

Quantum Physics · Physics 2024-10-29 Miguel Casanova , Kentaro Ohki , Francesco Ticozzi

In this paper, we investigate the sample complexity of recovering tensors with low symmetric rank from symmetric rank-one measurements. This setting is particularly motivated by the study of higher-order interactions and the analysis of…

Statistics Theory · Mathematics 2025-02-10 Eren C. Kızıldağ