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Related papers: Lower Bounds on Coherent State Rank

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We study extremal and algorithmic questions of subset and careful synchronization in monotonic automata. We show that several synchronization problems that are hard in general automata can be solved in polynomial time in monotonic automata,…

Formal Languages and Automata Theory · Computer Science 2017-11-27 Andrew Ryzhikov , Anton Shemyakov

We give a general method for proving quantum lower bounds for problems with small range. Namely, we show that, for any symmetric problem defined on functions $f:\{1, ..., N\}\to\{1, ..., M\}$, its polynomial degree is the same for all…

Quantum Physics · Physics 2008-05-12 Andris Ambainis

We study the entanglement of tripartite quantum states and provide analytical lower bound of concurrence in terms of the concurrence of sub-states. The lower bound may improve all the existing lower bounds of concurrence. The approach is…

Quantum Physics · Physics 2012-08-09 Xue-Na Zhu , Ming-Jing Zhao , Shao-Ming Fei

Low-rank tensor approximations have shown great potential for uncertainty quantification in high dimensions, for example, to build surrogate models that can be used to speed up large-scale inference problems (Eigel et al., Inverse Problems…

Numerical Analysis · Mathematics 2020-11-30 Paul B. Rohrbach , Sergey Dolgov , Lars Grasedyck , Robert Scheichl

We consider the Low Rank Approximation problem, where the input consists of a matrix $A \in \mathbb{R}^{n_R \times n_C}$ and an integer $k$, and the goal is to find a matrix $B$ of rank at most $k$ that minimizes $\| A - B \|_0$, which is…

Data Structures and Algorithms · Computer Science 2023-11-03 Vincent Cohen-Addad , Chenglin Fan , Suprovat Ghoshal , Euiwoong Lee , Arnaud de Mesmay , Alantha Newman , Tony Chang Wang

Recently, fundamental conditions on the sampling patterns have been obtained for finite completability of low-rank matrices or tensors given the corresponding ranks. In this paper, we consider the scenario where the rank is not given and we…

Machine Learning · Computer Science 2017-11-03 Morteza Ashraphijuo , Xiaodong Wang , Vaneet Aggarwal

Given an input matrix polynomial whose coefficients are floating point numbers, we consider the problem of finding the nearest matrix polynomial which has rank at most a specified value. This generalizes the problem of finding a nearest…

Symbolic Computation · Computer Science 2017-12-13 Mark Giesbrecht , Joseph Haraldson , George Labahn

Tensor networks are used to efficiently approximate states of strongly-correlated quantum many-body systems. More generally, tensor network approximations may allow to reduce the costs for operating on an order-$N$ tensor from exponential…

Strongly Correlated Electrons · Physics 2022-05-31 Hao Chen , Thomas Barthel

We prove lower bounds on complexity measures, such as the approximate degree of a Boolean function and the approximate rank of a Boolean matrix, using quantum arguments. We prove these lower bounds using a quantum query algorithm for the…

Quantum Physics · Physics 2018-07-18 Shalev Ben-David , Adam Bouland , Ankit Garg , Robin Kothari

In our work, we show how, for a network of bosonic modes, canonical commutation relations constrain the coefficients relating input and internal modes. Based on these constraints, we derive a lower bound on the total steady-state squeezing…

Quantum Physics · Physics 2026-04-27 Xin Zhou , Francesco Massel

We propose upper and lower bounds on the maximum success probability for discriminating given quantum states. The proposed upper bound is obtained from a suboptimal solution to the dual problem of the corresponding optimal state…

Quantum Physics · Physics 2018-01-12 Kenji Nakahira , Tsuyoshi Sasaki Usuda , Kentaro Kato

We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems include submodular load balancing, which generalizes load…

Data Structures and Algorithms · Computer Science 2010-06-02 Zoya Svitkina , Lisa Fleischer

Coherent states (CS) for non-Hermitian systems are introduced as eigenstates of pseudo-Hermitian boson annihilation operators. The set of these CS includes two subsets which form bi-normalized and bi-overcomplete system of states. The…

Quantum Physics · Physics 2010-06-15 D. A. Trifonov

Subspace inference for neural networks assumes that a subspace of their parameter space suffices to produce a reliable uncertainty quantification. In this work, we underpin the validity of this assumption by using low rank techniques. We…

Machine Learning · Computer Science 2026-04-13 Josua Faller , Jörg Martin

A lower bound on the amount of noise that must be added to a GHZ-like entangled state to make it separable (also called the random robustness) is found using the transposition condition. The bound is applicable to arbitrary numbers of…

Quantum Physics · Physics 2009-11-06 P. Deuar , W. J. Munro , K. Nemoto

In this paper we provide new compact integral expressions and associated simple asymptotic approximations for converse and achievability bounds in the finite blocklength regime. The chosen converse and random coding union bounds were taken…

Information Theory · Computer Science 2016-10-25 Tomaso Erseghe

In this work, we present number-theoretic and algebraic-geometric techniques for bounding the stabilizer rank of quantum states. First, we refine a number-theoretic theorem of Moulton to exhibit an explicit sequence of product states with…

Quantum Physics · Physics 2022-04-20 Benjamin Lovitz , Vincent Steffan

Fock states and their superpositions are exotic testbeds for nonclassical physics and valuable resources for quantum technologies. We provide a simple protocol for the quantum measurement to generate an arbitrary Fock state and certain…

Quantum Physics · Physics 2024-10-22 Chen-yi Zhang , Jun Jing

Efficient and accurate numerical approximation of the full Boltzmann equation has been a longstanding challenging problem in kinetic theory. This is mainly due to the high dimensionality of the problem and the complicated collision…

Numerical Analysis · Mathematics 2021-12-07 Jingwei Hu , Yubo Wang

In this paper, we propose a low rank approximation method for efficiently solving stochastic partial differential equations. Specifically, our method utilizes a novel low rank approximation of the stiffness matrices, which can significantly…

Numerical Analysis · Mathematics 2023-10-20 Yujun Zhu , Ju Ming , Jie Zhu , Zhongming Wang