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Conservation laws can constrain entanglement dynamics in isolated quantum systems, manifest in a slowdown of higher R\'enyi entropies. Here, we explore this phenomenon in a class of long-range random Clifford circuits with U$(1)$ symmetry…

Statistical Mechanics · Physics 2023-03-06 Jonas Richter , Oliver Lunt , Arijeet Pal

Recent works have revealed the intricate effect of long-range interactions on information transport in quantum many-body systems: In $D$ spatial dimensions, interactions decaying as a power-law $r^{-\alpha}$ with $\alpha > 2 D+1$ exhibit a…

Mathematical Physics · Physics 2025-09-23 Marius Lemm , Tom Wessel

The capacity of long-term memory seems to be extremely large, capable of storing information spanning almost a lifetime. Why does it have such a vast capacity? Why are some memories so enduring? What is the actual physical form of long-term…

Neurons and Cognition · Quantitative Biology 2024-11-05 Hui Wei , Surun Yang , Yangwang Li

Federated learning has emerged as a viable distributed solution to train machine learning models without the actual need to share data with the central aggregator. However, standard neural network-based federated learning models have been…

Complex networks, such as transportation networks, social networks, or biological networks, capture the complex system they model often by representing only one type of interactions. In real world systems, there may be many different…

Physics and Society · Physics 2020-10-16 Blaž Škrlj , Benjamin Renoust

Complex network theory provides a unifying framework for the study of structured dynamic systems. The current literature emphasizes a widely reported phenomenon of intermittent interaction among network vertices. In this paper, we introduce…

Social and Information Networks · Computer Science 2025-02-17 Ziyan Zeng , Minyu Feng , Pengfei Liu , Jurgen Kurths

Quantum spin models with variable-range interactions can exhibit certain quantum characteristics that a short-ranged model cannot possess. By considering the quantum XYZ model whose interaction strength between different sites varies either…

Quantum Physics · Physics 2020-12-24 Leela Ganesh Chandra Lakkaraju , Srijon Ghosh , Aditi Sen De

We study energy transport in the paradigmatic Hamiltonian mean-field (HMF) model and other related long-range interacting models using molecular dynamics simulations. We show that energy diffusion in the HMF model is subdiffusive in nature,…

Statistical Mechanics · Physics 2017-10-13 Debarshee Bagchi

Molecular materials have been studied as a potential platform for highly efficient transport such as exciton transport and quantum information spreading. However, one detrimental factor to transport efficiency is the inherent disorder of…

Quantum Physics · Physics 2024-09-12 Weijun Wu , Ava N. Hejazi , Gregory D. Scholes

The study of dynamical systems defined on complex networks provides a natural framework with which to investigate myriad features of neural dynamics, and has been widely undertaken. Typically, however, networks employed in theoretical…

Neurons and Cognition · Quantitative Biology 2013-02-22 Reuben O'Dea , Jonathan J. Crofts , Marcus Kaiser

The prominent collective character of long-range interacting quantum systems makes them promising candidates for quantum technological applications. Yet, lack of additivity overthrows the traditional picture for entanglement scaling and…

Quantum Physics · Physics 2023-08-07 Guido Giachetti , Nicolo Defenu

Efficient communication between qubits relies on robust networks which allow for fast and coherent transfer of quantum information. It seems natural to harvest the remarkable properties of systems characterized by topological invariants to…

Quantum Physics · Physics 2017-11-23 Nicolai Lang , Hans Peter Büchler

Federated learning enables collaborative model training across multiple clients without sharing raw data, thereby enhancing privacy. However, the exchange of model updates can still expose sensitive information. Quantum teleportation, a…

Quantum Physics · Physics 2024-12-31 Koffka Khan

Long-range interactions slow down the excitation trapping in quantum transport processes on a one-dimensional chain with traps at both ends. This is counter intuitive and in contrast to the corresponding classical processes with long-range…

Quantum Physics · Physics 2009-11-13 Oliver Muelken , Volker Pernice , Alexander Blumen

Effects of the propagation of particles, which have a finite life-time and an according width in their mass spectrum, are discussed in the context of transport description. First, the importance of coherence effects…

Nuclear Theory · Physics 2009-09-25 Yu. B. Ivanov , J. Knoll , H. van Hees , D. N. Voskresensky

Efficient transport and harvesting of excitation energy under low light conditions is an important process in nature and quantum technologies alike. Here we formulate a quantum optics perspective to excitation energy transport in…

Quantum Physics · Physics 2024-03-06 Raphael Holzinger , Jonah Peter , Stefan Ostermann , Helmut Ritsch , Susanne Yelin

Quantum networks can enable various applications such as distributed quantum computing, long-distance quantum communication, and network-based quantum sensing with unprecedented performances. One of the most important building blocks for a…

Quantum Physics · Physics 2024-05-01 Sheng Zhang , Jixuan Shi , Zhaibin Cui , Ye Wang , Yukai Wu , Luming Duan , Yunfei Pu

Coherent evolution governs the behaviour of all quantum systems, but in nature it is often subjected to influence of a classical environment. For analysing quantum transport phenomena quantum walks emerge as suitable model systems. In…

The coherent quantum transport of matter wave through a ring-shaped circuit attached to leads defines an iconic system in mesoscopic physics that has allowed both to explore fundamental questions in quantum science and to draw important…

Quantum Gases · Physics 2025-06-17 Francesco Perciavalle , Oliver Morsch , Davide Rossini , Luigi Amico

Increasing the size of a Transformer does not always lead to enhanced performance. This phenomenon cannot be explained by the empirical scaling laws. Furthermore, the model's enhanced performance is closely associated with its memorization…

Machine Learning · Computer Science 2024-12-02 Xueyan Niu , Bo Bai , Lei Deng , Wei Han