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We derive a Markovian master equation that models the evolution of systems subject to driving and control fields. Our approach combines time rescaling and weak-coupling limits for the system-environment interaction with a secular…

Quantum Physics · Physics 2024-11-26 Giovanni Di Meglio , Martin B. Plenio , Susana F. Huelga

We introduce the non-Hermitian mosaic Maryland model, where a discrete modulation period and a non-Hermitian phase are incorporated into the potential, rendering the originally exactly solvable system generally non-integrable. This model…

Disordered Systems and Neural Networks · Physics 2026-03-27 Zhenning Wang , Ni Lu , Dan Liu , Xiaosen Yang , Xianqi Tong

We present improvements of a recently introduced numerical method [Arrigoni etal, Phys. Rev. Lett. 110, 086403 (2013)] to compute steady state properties of strongly correlated electronic systems out of equilibrium. The method can be…

Strongly Correlated Electrons · Physics 2015-12-22 Irakli Titvinidze , Antonius Dorda , Wolfgang von der Linden , Enrico Arrigoni

This paper proposes a new nonlinear stability analysis for the acceleration-based robust position control of robot manipulators by using Disturbance Observer (DOb). It is shown that if the nominal inertia matrix is properly tuned in the…

Systems and Control · Computer Science 2019-02-22 Emre Sariyildiz , Hiromu Sekiguchi , Takahiro Nozaki , Barkan Ugurlu , Kouhei Ohnishi

Quantum feedback can stabilize a two-level atom against decoherence (spontaneous emission), putting it into an arbitrary (specified) pure state. This requires perfect homodyne detection of the atomic emission, and instantaneous feedback.…

Quantum Physics · Physics 2009-11-06 Jin Wang , H. M. Wiseman , G. J. Milburn

In many hierarchical inverse problems, not only do we want to estimate high- or infinite-dimensional model parameters in the parameter-to-observable maps, but we also have to estimate hyperparameters that represent critical assumptions in…

Computation · Statistics 2020-02-18 Johnathan Bardsley , Tiangang Cui

Momentum relaxation can be built into many holographic models without sacrificing homogeneity of the bulk solution. In this paper we study two such models: one in which translational invariance is broken in the dual theory by…

High Energy Physics - Theory · Physics 2015-04-24 Tomas Andrade , Simon A. Gentle

We study the collective decay of two-level emitters coupled to a nonlinear waveguide, for example, a nanophotonic lattice or a superconducting resonator array with strong photon-photon interactions. Under these conditions a new decay…

Quantum Physics · Physics 2020-06-01 Zhihai Wang , Tuomas Jaako , Peter Kirton , Peter Rabl

We analyze the dynamical Coulomb blockade of multiple Andreev reflections (MAR) in a superconducting quantum point contact coupled to a macroscopic impedance. We find that at very low transmission the blockade scales as $n^2$ with $n =…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 A. Levy Yeyati , J. C. Cuevas , A. Martin-Rodero

In this work we present a modified neural network model which is capable to simulate Markov Chains. We show how to express and train such a network, how to ensure given statistical properties reflected in the training data and we…

Machine Learning · Computer Science 2018-05-03 Maren Awiszus , Bodo Rosenhahn

Adaptive Markov chain Monte Carlo (MCMC) algorithms, which automatically tune their parameters based on past samples, have proved extremely useful in practice. The self-tuning mechanism makes them `non-Markovian', which means that their…

Probability · Mathematics 2024-08-28 Pietari Laitinen , Matti Vihola

Within the quantum field-theoretical approach describing the evolution of a quadratic Liouvillian in the basis of Keldysh contour coherent states, we investigate the spectral and transport properties of a dissipative superconducting system…

Mesoscale and Nanoscale Physics · Physics 2026-02-17 S. V. Aksenov , M. S. Shustin , I. S. Burmistrov

Learning from Demonstration (LfD) techniques enable robots to learn and generalize tasks from user demonstrations, eliminating the need for coding expertise among end-users. One established technique to implement LfD in robots is to encode…

To bridge the gap between empirical success and theoretical understanding in transfer reinforcement learning (RL), we study a principled approach with provable performance guarantees. We introduce a novel composite MDP framework where…

Machine Learning · Statistics 2025-02-04 Jinhang Chai , Elynn Chen , Lin Yang

By using the effective Hamiltonian approach, we present a self-consistent framework for the analysis of geometric phases and dynamically stable decoherence-free subspaces in open systems. Comparisons to the earlier works are made. This…

Quantum Physics · Physics 2009-11-13 X. L. Huang , X. X. Yi , Chunfeng Wu , X. L. Feng , S. X. Yu , C. H. OH

Two-level-system (TLS) defects in amorphous dielectrics are a major source of noise and decoherence in solid-state qubits. Gate-dependent non-Markovian errors caused by TLS-qubit coupling are detrimental to fault-tolerant quantum…

It is well known that, for mass-action systems, complex-balanced equilibria are asymptotically stable. For generalized mass-action systems, even if there exists a unique complex-balanced equilibrium (in every stoichiometric class and for…

Dynamical Systems · Mathematics 2022-09-14 Balazs Boros , Stefan Müller , Georg Regensburger

By modeling the interaction of a system with an environment through a renewal approach, we demonstrate that completely positive non-Markovian dynamics may develop some unexplored non-standard statistical properties. The renewal approach is…

Quantum Physics · Physics 2009-08-07 Adrian A. Budini Paolo Grigolini

Topological superconductivity in quasi-one-dimensional systems is a novel phase of matter with possible implications for quantum computation. Despite years of effort, a definitive signature of this phase in experiments is still debated. A…

Mesoscale and Nanoscale Physics · Physics 2021-07-12 Omri Lesser , Andrew Saydjari , Marie Wesson , Amir Yacoby , Yuval Oreg

This paper introduces a novel approach to evaluating the asymptotic stability of equilibrium points in both continuous-time (CT) and discrete-time (DT) nonlinear autonomous systems. By utilizing indirect Lyapunov methods and linearizing…

Systems and Control · Electrical Eng. & Systems 2025-08-08 Sadredin Hokmi , Mohammad Khajenejad