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We define a discrete-time, coined quantum walk on weighted graphs that is inspired by Szegedy's quantum walk. Using this, we prove that many lackadaisical quantum walks, where each vertex has $l$ integer self-loops, can be generalized to a…

Quantum Physics · Physics 2017-10-26 Thomas G. Wong

In this paper we consider a random walk of a particle in $\mathbb{R}^d$. Convergence of different transformations of trajectories of random flights with Poisson switching moments has been obtained by Davydov and Konakov, as well as…

Probability · Mathematics 2019-10-10 Alexander Falaleev , Valentin Konakov

Particle filters are a widely used Monte Carlo based data assimilation technique that estimates the probability distribution of a system's state conditioned on observations through a collection of weights and particles. A known problem for…

Applications · Statistics 2025-10-29 Shay Gilpin , Michael Herty

The Wasserstein metric is broadly used in optimal transport for comparing two probabilistic distributions, with successful applications in various fields such as machine learning, signal processing, seismic inversion, etc. Nevertheless, the…

Optimization and Control · Mathematics 2022-02-22 Qichen Liao , Jing Chen , Zihao Wang , Bo Bai , Shi Jin , Hao Wu

We consider the Wigner quasi-probability distribution function of a single mode of an electromagnetic or matter-wave field to address the question of whether a direct stochastic sampling and binning of the absolute square of the complex…

Quantum Physics · Physics 2016-09-13 R. J. Lewis-Swan , M. K. Olsen , K. V. Kheruntsyan

A variation of Rosenstock's trapping model in which $N$ independent random walkers are all initially placed upon a site of a one-dimensional lattice in the presence of a {\em one-sided} random distribution (with probability $c$) of…

Statistical Mechanics · Physics 2015-06-24 S. B. Yuste , L. Acedo

In this paper, we propose a new method to measure the probabilistic robustness of stochastic jump linear system with respect to both the initial state uncertainties and the randomness in switching. Wasserstein distance which defines a…

Systems and Control · Computer Science 2014-10-03 Kooktae Lee , Abhishek Halder , Raktim Bhattacharya

CConsider a bipartite quantum system consisting of two subsystems A and B. The reduced density matrix ofA a is obtained by taking the partial trace with respect to B. In this work, we will show that the Wigner distribution of this reduced…

Quantum Physics · Physics 2022-11-17 Maurice de Gosson , Charlyne de Gosson

Simulating mixtures of distributions with signed weights proves a challenge as standard simulation algorithms are inefficient in handling the negative weights. In particular, the natural representation of mixture variates as associated with…

Computation · Statistics 2025-06-17 Julien Stoehr , Christian P. Robert

We report the experimental measurement of the winding number in an unitary chiral quantum walk. Fundamentally, the spin-orbit coupling in discrete time quantum walks is implemented via birefringent crystal collinearly cut based on…

This work deals with the stationary analysis of two-dimensional partially homogeneous nearest-neighbour random walks. Such type of random walks in the quarter plane are characterized by the fact that the one-step transition probabilities…

Networking and Internet Architecture · Computer Science 2019-07-11 Ioannis Dimitriou

Randomized compilation protocols have recently attracted attention as alternatives to traditional deterministic Trotter-Suzuki methods, potentially reducing circuit depth and resource overhead. These protocols determine gate application…

Quantum Physics · Physics 2025-12-22 Yun-Zhuo Fan , Yu-Xia Wu , Dan-Bo Zhang

In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not scale well due to the quadratic complexity. In this paper, a…

Machine Learning · Computer Science 2012-10-19 Saeed Amizadeh , Bo Thiesson , Milos Hauskrecht

In typical discrete-time quantum walk algorithms, one measures the position of the walker while ignoring its internal spin/coin state. Rather than neglecting the information in this internal state, we show that additionally measuring it…

Quantum Physics · Physics 2016-10-20 Krišjānis Prūsis , Jevgēnijs Vihrovs , Thomas G. Wong

We consider a branching random walk on a $d$-ary tree of height $n$ ($n \in \mathbb{N}$), under the presence of a hard wall which restricts each value to be positive, where $d$ is a natural number satisfying $d\geqslant2$. The question of…

Probability · Mathematics 2024-02-23 Rishideep Roy

Double (or parity conserving) branching annihilating random walk, introduced by Sudbury in '90, is a one-dimensional non-attractive particle system in which positive and negative particles perform nearest neighbor hopping, produce two…

Probability · Mathematics 2015-09-04 Márton Balázs , Attila László Nagy

Consider $N$ particles performing random walks on the $\epsilon$-grid $(\epsilon Z)^d$, $\epsilon>0$ with branching and density-dependent selection: When one of the particles branches, a particle is removed from the most populated site. The…

Probability · Mathematics 2026-01-30 Rami Atar , Leonid Mytnik , Gershon Wolansky

With photonics, the quantum computational advantage has been demonstrated on the task of boson sampling. Next, developing quantum-enhanced approaches for practical problems becomes one of the top priorities for photonic systems. Quantum…

The paper introduces an efficient implementation of the Deutsch-Jozsa and Bernstein-Vazirani algorithm using the single-particle discrete-time quantum walk. We also provide a detailed optical framework with specific optical components to…

Quantum Physics · Physics 2026-01-05 Ravi Sangwan , Vikas Ramaswamy , Henry Sukumar , Gudapati Naresh Raghava

We introduce the so called DeepParticle method to learn and generate invariant measures of stochastic dynamical systems with physical parameters based on data computed from an interacting particle method (IPM). We utilize the expressiveness…

Machine Learning · Computer Science 2022-06-22 Zhongjian Wang , Jack Xin , Zhiwen Zhang