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The speed of light $c$ sets a strict upper bound on the speed of information transfer in both classical and quantum systems. In nonrelativistic quantum systems, the Lieb-Robinson Theorem imposes an emergent speed limit $v \hspace{-0.2mm}…

Quantum Physics · Physics 2023-07-06 Aaron J. Friedman , Chao Yin , Yifan Hong , Andrew Lucas

We consider the tributary structure of Howard's drainage model studied by Gangopadhyay et. al. Conditional on the event that the tributary survives up to time $n$, we show that, as a sequence of random metric spaces, scaled tributary…

Probability · Mathematics 2020-08-11 Kumarjit Saha

We study the robustness of the evolution of a quantum system against small uncontrolled variations in parameters in the Hamiltonian. We show that the fidelity susceptibility, which quantifies the perturbative error to leading order, can be…

Quantum Physics · Physics 2024-05-09 Pablo M. Poggi , Gabriele De Chiara , Steve Campbell , Anthony Kiely

We introduce an algorithm for the uniform generation of infinite runs in concurrent systems under a partial order probabilistic semantics. We work with trace monoids as concurrency models. The algorithm outputs on-the-fly approximations of…

Combinatorics · Mathematics 2017-12-07 Samy Abbes , Vincent Jugé

A well-known class of non-stationary self-similar time series is the fractional Brownian motion (fBm) considered to model ubiquitous stochastic processes in nature. In this paper, we study the homology groups of high-dimensional point cloud…

Algebraic Topology · Mathematics 2022-12-21 H. Masoomy , S. Tajik , S. M. S. Movahed

The times of Brownian local minima, maxima and their union are three distinct examples of local, stationary, dense, random countable sets associated with classical Wiener noise. Being local means, roughly, determined by the local behavior…

Probability · Mathematics 2022-12-13 Matija Vidmar , Jon Warren

We consider a generic class of stochastic particle-based models whose state at an instant in time is described by a set of continuous degrees of freedom (e.g. positions), and the length of this set changes stochastically in time due to…

Statistical Mechanics · Physics 2025-09-03 Samuel Cameron , Elsen Tjhung

Characterizing the efficiency of movements is important for a better management of the cities. More specifically, the connection between the efficiency and uncertainty (entropy) production of a transport process is not established yet. In…

Physics and Society · Physics 2021-05-13 Indaco Biazzo , Mohsen Ghasemi Nezhadhaghighi , Abolfazl Ramezanpour

Analytical work probability distributions for open classical systems are scarce; they can only be calculated in a few examples. In this work, I present a new method to derive such quantities for weakly driven processes in the overdamped…

Statistical Mechanics · Physics 2025-04-09 Pierre Nazé

The Lieb-Robinson theorem states that locality is approximately preserved in the dynamics of quantum lattice systems. Whenever one has finite-dimensional constituents, observables evolving in time under a local Hamiltonian will essentially…

Quantum Physics · Physics 2010-03-03 M. Cramer , A. Serafini , J. Eisert

We consider the model of Brownian motion indexed by the Brownian tree, which has appeared in a variety of different contexts in probability, statistical physics and combinatorics. For this model, the total occupation measure is known to…

Probability · Mathematics 2023-06-16 Jean-François Le Gall

Complex networks are often used to represent systems that are not static but grow with time: people make new friendships, new papers are published and refer to the existing ones, and so forth. To assess the statistical significance of…

Physics and Society · Physics 2018-06-01 Zhuo-Ming Ren , Manuel Sebastian Mariani , Yi-Cheng Zhang , Matus Medo

We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, i) the…

We show how random unitary dynamics arise from the coupling of an open quantum system to a static environment. Subsequently, we derive a master equation for the reduced system random unitary dynamics and study three specific cases:…

Quantum Physics · Physics 2018-01-17 Chahan M. Kropf , Vyacheslav N. Shatokhin , Andreas Buchleitner

We study the random acceleration model, which is perhaps one of the simplest, yet nontrivial, non-Markov stochastic processes, and is key to many applications. For this non-Markov process, we present exact analytical results for the…

Statistical Mechanics · Physics 2019-09-04 Satya N. Majumdar , Alberto Rosso , Andrea Zoia

We study the behaviour of the rescaled minimal subtree containing the origin and K random vertices selected from a random critical (sufficiently spread-out, and in dimensions d > 8) lattice tree conditioned to survive until time ns, in the…

Probability · Mathematics 2025-03-30 Manuel Cabezas , Alexander Fribergh , Mark Holmes , Edwin Perkins

We construct the conditional version of $k$ independent and identically distributed random walks on $\R$ given that they stay in strict order at all times. This is a generalisation of so-called non-colliding or non-intersecting random…

Probability · Mathematics 2007-05-23 Peter Eichelsbacher , Wolfgang Konig

We investigate operator growth in a Brownian spin Sachdev--Ye--Kitaev (SYK) model with random all-to-all interactions, focusing on the full operator-size distribution. For Hamiltonians containing interactions of order two up to $L$, we…

Quantum Physics · Physics 2026-02-20 Tingfei Li , Miao Wang , Jianghui Yu

Generating function equation has been derived for the probability distribution of the number of nodes with $k \ge 0$ outgoing lines in randomly evolving special trees. The stochastic properties of end-nodes (k=0) have been analyzed, and it…

Statistical Mechanics · Physics 2007-05-23 L. Pal

We present a novel set of rigorous and computationally efficient topology-based complexity notions that exhibit a strong correlation with the generalization gap in modern deep neural networks (DNNs). DNNs show remarkable generalization…

Machine Learning · Computer Science 2024-12-17 Rayna Andreeva , Benjamin Dupuis , Rik Sarkar , Tolga Birdal , Umut Şimşekli