Tootfinder

Spatial-Temporal Reinforcement Learning for Network Routing with Non-Markovian Traffic
Molly Wang
https://arxiv.org/abs/2507.22174 https://arxiv.org/pdf/25…

Spatial-Temporal Reinforcement Learning for Network Routing with Non-Markovian Traffic
Reinforcement Learning (RL) has become a well-established approach for optimizing packet routing in communication networks. Standard RL algorithms typically are based on the Markov Decision Process (MDP), which assumes that the current state of the environment provides all the necessary information for system evolution and decision-making. However, this Markovian assumption is invalid in many practical scenarios, making the MDP and RL frameworks inadequate to produce the optimal solutions. Addi…

On the emergence of quantum memory in non-Markovian dynamics
Alexander Yosifov, Aditya Iyer, Vlatko Vedral, Jinzhao Sun
https://arxiv.org/abs/2507.21907 https://

On the emergence of quantum memory in non-Markovian dynamics
Quantum systems are often hindered by decoherence due to impact from the environment. While memoryless Markovian collision models are commonly used to approximate such evolution, non-Markovian dynamics (with memory) is typical in practice, with memory effects being harnessed as a resource for many tasks like quantum error correction and information processing. Yet, the type of memory, classical or quantum, necessary to realize the dynamics of many collision models is not known. In this work, we…

Age of Estimates: When to Submit Jobs to a Markov Machine to Maximize Revenue
Sahan Liyanaarachchi, Sennur Ulukus
https://arxiv.org/abs/2507.22865 https://…

Age of Estimates: When to Submit Jobs to a Markov Machine to Maximize Revenue
With the dawn of AI factories ushering a new era of computing supremacy, development of strategies to effectively track and utilize the available computing resources is garnering utmost importance. These computing resources are often modeled as Markov sources, which oscillate between free and busy states, depending on their internal load and external utilization, and are commonly referred to as Markov machines (MMs). Most of the prior work solely focuses on the problem of tracking these MMs, wh…

Python is also the most desired programming language in the Stack Overflow developer survey, while Rust remains the most admired: https://survey.stackoverflow.co/2025/technology#2-programming-scripting-and-markup-languages

Markov Decision Processes with Value-at-Risk Criterion
Li Xia, Jinyan Pan
https://arxiv.org/abs/2507.22355 https://arxiv.org/pdf/2507.22355

Markov Decision Processes with Value-at-Risk Criterion
Value-at-risk (VaR), also known as quantile, is a crucial risk measure in finance and other fields. However, optimizing VaR metrics in Markov decision processes (MDPs) is challenging because VaR is non-additive and the traditional dynamic programming is inapplicable. This paper conducts a comprehensive study on VaR optimization in discrete-time finite MDPs. We consider VaR in two key scenarios: the VaR of steady-state rewards over an infinite horizon and the VaR of accumulated rewards over a fi…

Non Markovian electron Brownian motion with radiation reaction force
Juan Francisco Garc\'ia-Camacho, Oliver Contreras-Vergara, Norma S\'anchez-Salas, Gonzalo Ares de Parga, Jos\'e In\'es Jim\'enez-Aquino
https://arxiv.org/abs/2505.22952

Non Markovian electron Brownian motion with radiation reaction force
In this work, we study non-Markovian electronic plasma diffusion from a classical point of view, taking into account the effects of the radiation reaction force. The electron Brownian motion is described by a Generalized Langevin Equation (GLE) characterized by an Ornstein-Uhlenbeck-type friction memory kernel. To take into account the effects of the radiation reaction force, an effective memory time which accounts for the thermal interaction of the Brownian particle with its surroundings is pr…

Decoherence-free subspaces and Markovian revival of genuine multipartite entanglement in a dissipative system
Shubhodeep Gangopadhyay, Vinayak Jagadish, R. Srikanth
https://arxiv.org/abs/2507.22796

Decoherence-free subspaces and Markovian revival of genuine multipartite entanglement in a dissipative system
We analyze a system of three or more qubits collectively interacting with a zero-temperature bosonic bath characterized by a Lorentzian spectral density. Our study focuses on the emergence of decoherence-free subspaces and the genuine-entanglement dynamics. Specifically, we study the three qubit system in detail, where the genuine entanglement is quantified through the convex roof extension of negativity. By examining the transition between Markovian and non-Markovian regimes, we reveal how the…

Mean-Variance Optimization and Algorithm for Finite-Horizon Markov Decision Processes
Li Xia, Zhihui Yu
https://arxiv.org/abs/2507.22327 https://arxiv.org/…

Mean-Variance Optimization and Algorithm for Finite-Horizon Markov Decision Processes
Multi-period mean-variance optimization is a long-standing problem, caused by the failure of dynamic programming principle. This paper studies the mean-variance optimization in a setting of finite-horizon discrete-time Markov decision processes (MDPs), where the objective is to maximize the combined metrics of mean and variance of the accumulated rewards at terminal stage. By introducing the concepts of pseudo mean and pseudo variance, we convert the original mean-variance MDP to a bilevel MDP,…

Making Non-Markovian master equations accessible with approximate environments
Gerardo Su\'arez, Michal Horodecki
https://arxiv.org/abs/2506.22346 http…

Making Non-Markovian master equations accessible with approximate environments
Accurate and efficient simulation of open quantum systems remains a significant challenge, particularly for Non-Markovian dynamics. We demonstrate the profound utility of expressing the environmental correlation function as a sum of damped sinusoidals within master equations. While not strictly required, this decomposition offers substantial benefits, crucially reducing the cost of Lamb-shift and decay rates calculations without sacrificing accuracy. Furthermore, this approach enables straightf…

This https://arxiv.org/abs/2411.05559 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum processes as thermodynamic resources: the role of non-Markovianity
Quantum thermodynamics studies how quantum systems and operations may be exploited as sources of work to perform useful thermodynamic tasks. In real-world conditions, the evolution of open quantum systems typically displays memory effects, resulting in a non-Markovian dynamics. The associated information backflow has been observed to provide advantage in certain thermodynamic tasks. However, a general operational connection between non-Markovianity and thermodynamics in the quantum regime has r…