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We study a non-Hermitian generalization of strongly correlated quantum systems in which the transfer energy of electrons is asymmetric. It is known that a non-Hermitian critical point is equal to the inverse localization length of a…

Strongly Correlated Electrons · Physics 2007-05-23 Yuichi Nakamura , Naomichi Hatano

Quantum computers provide a super-exponential speedup for performing a Fourier transform over the symmetric group, an ability for which practical use cases have remained elusive so far. In this work, we leverage this ability to unlock…

Quantum Physics · Physics 2026-03-25 Vasilis Belis , Giulio Crognaletti , Matteo Argenton , Michele Grossi , Maria Schuld

We study quantum equivalents of non-commutative operators in quantum mechanics. Any matrix "$B$" satisfying the non-commuting relation $[A,B]\neq 0$ with "$A$", can be used via $B^{-1} AB$ to reproduce eigenvalues of "$A$". This…

Quantum Physics · Physics 2023-01-24 Biswanath Rath

The density matrices are positively semi-definite Hermitian matrices of unit trace that describe the state of a quantum system. The goal of the paper is to develop minimax lower bounds on error rates of estimation of low rank density…

Machine Learning · Statistics 2016-04-19 Vladimir Koltchinskii , Dong Xia

Pickrell has fully characterized the unitarily invariant probability measures on infinite Hermitian matrices, and an alternative proof of this classification has been found by Olshanski and Vershik. Borodin and Olshanski deduced from this…

Probability · Mathematics 2020-04-27 Joseph Najnudel

Random matrices are used in fields as different as the study of multi-orthogonal polynomials or the enumeration of discrete surfaces. Both of them are based on the study of a matrix integral. However, this term can be confusing since the…

Mathematical Physics · Physics 2009-11-30 Nicolas Orantin

Quantum parameter estimation with Hermitian systems has been applied in various fields, but there are relatively few results concerning non-Hermitian systems. Here, we study the quantum parameter estimation for general non-Hermitian…

Quantum Physics · Physics 2023-09-06 Xinglei Yu , Chengjie Zhang

We study the asymptotic distribution of the eigenvalues of random Hermitian periodic band matrices, focusing on the spectral edges. The eigenvalues close to the edges converge in distribution to the Airy point process if (and only if) the…

Mathematical Physics · Physics 2011-01-25 Sasha Sodin

We investigate the set of quantum states that can be shown to be $k$-incoherent based only on their eigenvalues (equivalently, we explore which Hermitian matrices can be shown to have small factor width based only on their eigenvalues). In…

Quantum Physics · Physics 2022-11-21 Nathaniel Johnston , Shirin Moein , Rajesh Pereira , Sarah Plosker

Solving non-Hermitian quantum many-body systems on a quantum computer by minimizing the variational energy is challenging as the energy can be complex. Here, based on energy variance, we propose a variational method for solving the…

Quantum Physics · Physics 2024-02-21 Xu-Dan Xie , Zheng-Yuan Xue , Dan-Bo Zhang

We study the eigenvalue spectrum of a large real antisymmetric random matrix $J_{ij}$. Using a fermionic approach and replica trick, we obtain a semicircular spectrum of eigenvalues when the mean value of each matrix element is zero, and in…

High Energy Physics - Theory · Physics 2023-09-06 Andrei Katsevich , Pavel Meshcheriakov

The Ginibre ensemble of nonhermitean random Hamiltonian matrices $K$ is considered. Each quantum system described by $K$ is a dissipative system and the eigenenergies $Z_{i}$ of the Hamiltonian are complex-valued random variables. The…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

The spectral densities of ensembles of non-Hermitian sparse random matrices are analysed using the cavity method. We present a set of equations from which the spectral density of a given ensemble can be efficiently and exactly calculated.…

Disordered Systems and Neural Networks · Physics 2009-11-13 Tim Rogers , Isaac Perez Castillo

Conjugation covariants of matrices are applied to study the real algebraic variety consisting of complex Hermitian matrices with a bounded number of distinct eigenvalues. A minimal generating system of the vanishing ideal of degenerate…

Representation Theory · Mathematics 2013-02-22 M. Domokos

We prove quadratic eigenvalue perturbation bounds for generalized Hermitian eigenvalue problems. The bounds are proportional to the square of the norm of the perturbation matrices divided by the gap between the spectrums. Using the results…

Numerical Analysis · Mathematics 2010-09-21 Yuji Nakatsukasa

We investigate the quantum-mechanical interpretation of models with non-Hermitian Hamiltonians and real spectra. After describing a general framework to reformulate such models in terms of Hermitian Hamiltonians defined on the Hilbert space…

Quantum Physics · Physics 2009-11-10 R. Kretschmer , L. Szymanowski

Deformations of the canonical commutation relations lead to non-Hermitian momentum and position operators and therefore almost inevitably to non-Hermitian Hamiltonians. We demonstrate that such type of deformed quantum mechanical systems…

High Energy Physics - Theory · Physics 2014-11-20 Bijan Bagchi , Andreas Fring

We generalize a recently proposed algebraic method in order to treat non-Hermitian Hamiltonians. The approach is applied to several quadratic Hamiltonians studied earlier by other authors. Instead of solving the Schr\"odinger equation we…

Quantum Physics · Physics 2020-09-04 Francisco M. Fernández

We provide a perturbative expansion for the empirical spectral distribution of a Hermitian matrix with large size perturbed by a random matrix with small operator norm whose entries in the eigenvector basis of the first one are independent…

Probability · Mathematics 2017-10-03 Florent Benaych-Georges , Nathanaël Enriquez , Alkéos Michaïl

The spectra of random feature matrices provide essential information on the conditioning of the linear system used in random feature regression problems and are thus connected to the consistency and generalization of random feature models.…

Machine Learning · Statistics 2022-12-13 Zhijun Chen , Hayden Schaeffer , Rachel Ward