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We prove local laws, i.e. optimal concentration estimates for arbitrary products of resolvents of a Wigner random matrix with deterministic matrices in between. We find that the size of such products heavily depends on whether some of the…

Probability · Mathematics 2022-11-02 Giorgio Cipolloni , László Erdős , Dominik Schröder

Without wasting time and effort on philosophical justifications and implications, we write down the conditions for the Hamiltonian of a quantum system for rendering it mathematically equivalent to a deterministic system. These are the…

Quantum Physics · Physics 2020-06-09 Gerard t Hooft

Motivated by the asymptotic collective behavior of random and deterministic matrices, we propose an approximation (called "free deterministic equivalent") to quite general random matrix models, by replacing the matrices with operators…

Information Theory · Computer Science 2011-10-07 Roland Speicher , Carlos Vargas , Tobias Mai

A universal deterministic noiseless quantum amplifier has been shown to be impossible. However, probabilistic noiseless amplification of a certain set of states is physically permissible. Regarding quantum state amplification as quantum…

Quantum Physics · Physics 2015-09-02 M. J. Hu , Y. S. Zhang

We discuss the possibility of applying some standard statistical methods (the least square method, the maximum likelihood method, the method of statistical moments for estimation of parameters) to deterministically chaotic low-dimensional…

Data Analysis, Statistics and Probability · Physics 2009-11-10 V. F. Pisarenko , D. Sornette

A new class of stochastic variables, governed by a specifice set of rules, is introduced. These rules force them to loose some properties usually assumed for this kind of variables. We demonstrate that stochastic processes driven by these…

Quantum Physics · Physics 2007-05-23 J. M. A. Figueiredo

The estimation of parameters in a linear model is considered under the hypothesis that the noise, with finite second order statistics, can be represented in a given deterministic basis by random coefficients. An extended underdetermined…

Statistics Theory · Mathematics 2014-05-06 Piero Barone , Isabella Lari

A determinantal approximation is obtained for the permanent of a doubly stochastic matrix. For moderate-deviation matrix sequences, the asymptotic relative error is of order $O(n^{-1})$.

Combinatorics · Mathematics 2012-05-28 Peter McCullagh

A randomized algorithm for a search problem is *pseudodeterministic* if it produces a fixed canonical solution to the search problem with high probability. In their seminal work on the topic, Gat and Goldwasser posed as their main open…

Computational Complexity · Computer Science 2025-12-05 Lijie Chen , Zhenjian Lu , Igor C. Oliveira , Hanlin Ren , Rahul Santhanam

We prove that when suitably normalized, small enough powers of the absolute value of the characteristic polynomial of random Hermitian matrices, drawn from one-cut regular unitary invariant ensembles, converge in law to Gaussian…

Probability · Mathematics 2017-09-19 Nathanaël Berestycki , Christian Webb , Mo Dick Wong

We introduce a new notion of the determinant, called symmetrized determinant, for a square matrix with the entries in an associative algebra $\AA$. The monomial expansion of the symmetrized determinant is obtained from the standard…

Combinatorics · Mathematics 2007-05-23 Alexander Barvinok

We present a quantum algorithm for estimating the matrix determinant based on quantum spectral sampling. The algorithm estimates the logarithm of the determinant of an $n \times n$ positive sparse matrix to an accuracy $\epsilon$ in time…

Quantum Physics · Physics 2025-05-02 Vittorio Giovannetti , Seth Lloyd , Lorenzo Maccone

We consider ontological models of a quantum system, assuming that not all probability distributions over the space $\Lambda$ of ontic states are preparable, only those belonging to a certain set C. We assume further that every POVM with a…

Quantum Physics · Physics 2022-05-10 Roderich Tumulka

The estimation of parameters characterizing dynamical processes is central to science and technology. The estimation error changes with the number N of resources employed in the experiment (which could quantify, for instance, the number of…

Quantum Physics · Physics 2012-01-10 B. M. Escher , R. L. de Matos Filho , L. Davidovich

We establish a central limit theorem for the log-determinant $\log|\det(M_n)|$ of a Wigner matrix $M_n$, under the assumption of four matching moments with either the GUE or GOE ensemble. More specifically, we show that this log-determinant…

Probability · Mathematics 2012-03-30 Terence Tao , Van Vu

The singular values of a product of $M$ independent Ginibre matrices of size $N\times N$ form a determinantal point process. Near the soft edge, as both $M$ and $N$ go to infinity in such a way that $M/N\to \alpha$, $\alpha>0$, a scaling…

Probability · Mathematics 2021-12-21 Sergey Berezin , Eugene Strahov

The discrete logarithm problem in a finite group is the basis for many protocols in cryptography. The best general algorithms which solve this problem have time complexity of $\mathcal{O}(\sqrt{N}\log N)$, and a space complexity of…

Computational Complexity · Computer Science 2022-03-16 Simran Tinani , Joachim Rosenthal

There exists a Hamiltonian formulation of the factorisation problem which also needs the definition of a factorisation ensemble (a set to which factorable numbers, $N'=x'y'$, having the same trivial factorisation algorithmic complexity,…

Quantum Physics · Physics 2020-08-27 Jose Luis Rosales , Samira Briongos , Vicente Martin

We present a deterministic algorithm, which, for any given 0< epsilon < 1 and an nxn real or complex matrix A=(a_{ij}) such that | a_{ij}-1| < 0.19 for all i, j computes the permanent of A within relative error epsilon in n^{O(ln n -ln…

Combinatorics · Mathematics 2014-06-25 Alexander Barvinok

In this paper we explore fundamental concepts in computational complexity theory and the boundaries of algorithmic decidability. We examine the relationship between complexity classes \textbf{P} and \textbf{NP}, where $L \in \textbf{P}$…

Computational Complexity · Computer Science 2025-12-30 Duaa Abdullah , Jasem Hamoud
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