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Bosonic and fermionic statistics are well known to give rise to antinomic behaviors, most notably boson bunching vs fermion antibunching. Here, we establish a fundamental relation that combines bosonic and fermionic multiparticle…

Quantum Physics · Physics 2026-05-20 Michael G. Jabbour , Nicolas J. Cerf

It is known that computing the permanent of the matrix $1+A$, where $A$ is a finite-rank matrix, requires a number of operations polynomial in the matrix size. Motivated by the boson-sampling proposal of restricted quantum computation, I…

Quantum Physics · Physics 2023-05-31 Dmitri A. Ivanov

In this paper we provide a novel and general way to construct the result of the action of any bosonic or fermionic operator represented in second quantized form on a state vector, without resorting to the matrix representation of operators…

Quantum Physics · Physics 2010-03-09 Alexej I. Streltsov , Ofir E. Alon , Lorenz S. Cederbaum

We construct a quantum-inspired classical algorithm for computing the permanent of Hermitian positive semidefinite matrices, by exploiting a connection between these mathematical structures and the boson sampling model. Specifically, the…

Quantum Physics · Physics 2017-09-01 L. Chakhmakhchyan , N. J. Cerf , R. Garcia-Patron

Every square matrix $A=(a_{uv})\in \mathcal{C}^{n\times n}$ can be represented as a digraph having $n$ vertices. In the digraph, a block (or 2-connected component) is a maximally connected subdigraph that has no cut-vertex. The determinant…

Computational Complexity · Computer Science 2018-10-12 Ranveer Singh , Vivek Vijay , RB Bapat

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

Given a square, nonsingular matrix of univariate polynomials $\mathbf{F}\in\mathbb{K}[x]^{n\times n}$ over a field $\mathbb{K}$, we give a deterministic algorithm for finding the determinant of $\mathbf{F}$. The complexity of the algorithm…

Symbolic Computation · Computer Science 2014-09-22 Wei Zhou , George Labahn

Continuous-time determinantal algorithm is proposed for the quantum Monte Carlo simulation of the interacting fermions. The scheme does not invoke Hubbard-Stratonovich transformation. The fermionic action is divided into two parts. One of…

Strongly Correlated Electrons · Physics 2007-05-23 A. N. Rubtsov

We derive a rigorous, quantum mechanical map of fermionic creation and annihilation operators to continuous Cartesian variables that exactly reproduces the matrix structure of the many-fermion problem. We show how our scheme can be used to…

Chemical Physics · Physics 2018-03-20 Andrés Montoya-Castillo , Thomas E. Markland

We introduce a new mathematical object, the "fermionant" ${\mathrm{Ferm}}_N(G)$, of type $N$ of an $n \times n$ matrix $G$. It represents certain $n$-point functions involving $N$ species of free fermions. When N=1, the fermionant reduces…

Strongly Correlated Electrons · Physics 2011-08-12 Shailesh Chandrasekharan , Uwe-Jens Wiese

We consider two strongly correlated two-component quantum systems, consisting of quantum mobile particles and classical immobile particles. The both systems are described by Falicov-Kimball-like Hamiltonians on a square lattice, extended by…

Strongly Correlated Electrons · Physics 2009-11-10 Volodymyr Derzhko , Janusz Jedrzejewski

For the one-dimensional spin-1/2 XX model with either periodic or open boundary conditions, it is shown by using a fermionic approach that the matrix element of the spin operator $S^-_j$ ($S^-_{j}S^+_{j'}$) between two eigenstates with…

Statistical Mechanics · Physics 2018-01-10 Ning Wu

In this paper we study the computational complexity of computing the noncommutative determinant. We first consider the arithmetic circuit complexity of computing the noncommutative determinant polynomial. Then, more generally, we also…

Computational Complexity · Computer Science 2009-10-26 V. Arvind , Srikanth Srinivasan

Computing the permanent of a non-negative matrix is a computationally challenging, \#P-complete problem with wide-ranging applications. We introduce a novel permanental analogue of Schur's determinant formula, leveraging a newly defined…

Discrete Mathematics · Computer Science 2025-09-11 Aditi Laddha , Madhusudhan Reddy Pittu

We continue the discussion of the fermion models on graphs that started in the first paper of the series. Here we introduce a Graphical Gauge Model (GGM) and show that : (a) it can be stated as an average/sum of a determinant defined on the…

Statistical Mechanics · Physics 2010-05-27 Vladimir Y. Chernyak , Michael Chertkov

Determinants are useful to represent the state of an interacting system of (effectively) repulsive and independent elements, like fermions in a quantum system and training samples in a learning problem. A computationally challenging problem…

Statistical Mechanics · Physics 2024-08-01 A. Ramezanpour , M. A. Rajabpour

In order to find the outcome probabilities of quantum mechanical systems like the optical networks underlying Boson sampling, it is necessary to be able to compute the permanents of unitary matrices, a computationally hard task. Here we…

Quantum Physics · Physics 2022-02-10 P. H. Lundow , K. Markström

We report on a computational and experimental study of permanents. On the computational side, we use the GPU to greaatly accelerate the computation of permanents over $\mathbb{C},$ $\mathbb{R},$ $\mathbb{F}_p$ and $\mathbb{Q}.$ First, for…

Quantum Physics · Physics 2026-02-17 Igor Rivin

The permanent of a square matrix is defined in a way similar to the determinant, but without using signs. The exact computation of the permanent is hard, but there are Monte-Carlo algorithms that can estimate general permanents. Given a…

Quantum Algebra · Mathematics 2012-03-01 Martin Loebl , Iain Moffatt

We show an algorithm for computing the permanent of a random matrix with vanishing mean in quasi-polynomial time. Among special cases are the Gaussian, and biased-Bernoulli random matrices with mean 1/lnln(n)^{1/8}. In addition, we can…

Data Structures and Algorithms · Computer Science 2018-10-11 Lior Eldar , Saeed Mehraban
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