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The characterization of collective behavior and nonequilibrium phase transitions in quantum systems is typically rooted in the analysis of suitable system observables, so-called order parameters. These observables might not be known a…

Quantum Physics · Physics 2026-02-20 Erik Fitzner , Francesco Carnazza , Federico Carollo , Igor Lesanovsky

Feedback optimization enables autonomous optimality seeking of a dynamical system through its closed-loop interconnection with iterative optimization algorithms. Among various iteration structures, model-based approaches require the…

Optimization and Control · Mathematics 2026-05-26 Zhiyu He , Saverio Bolognani , Michael Muehlebach , Florian Dörfler

A model for cross-over designs with repeated measures within each period was developed. It is obtained using an extension of generalized estimating equations that includes a parametric component to model treatment effects and a…

Methodology · Statistics 2023-03-21 N. A. Cruz , O. O. Melo , C. A. Martinez

In this report, we apply an input-output transformation passivation method, described in our previous works, to an Adaptive Cruise Control system. We analyze the system's performance under a co-simulation framework that makes use of an…

Optimization and Control · Mathematics 2016-07-15 Arash Rahnama , Meng Xia , Shige Wang , Panos J. Antsaklis

We propose a cross-entropy minimization method for finding the reaction coordinate from a large number of collective variables in complex molecular systems. This method is an extension of the likelihood maximization approach describing the…

Chemical Physics · Physics 2020-08-06 Yusuke Mori , Kei-ichi Okazaki , Toshifumi Mori , Kang Kim , Nobuyuki Matubayasi

Modeling microstructure evolution in electrochemical systems is vital for understanding the mechanism of various electrochemical processes. In this work, we propose a general phase field framework that is fully variational and thus…

Materials Science · Physics 2023-12-12 Jin Zhang , Alexander F. Chadwick , Peter W. Voorhees

We present a new method that enables the identification and analysis of both transition and metastable conformational states from atomistic or coarse-grained molecular dynamics (MD) trajectories. Our algorithm is presented and studied by…

Chemical Physics · Physics 2017-10-04 Linda Martini , Adam Kells , Gerhard Hummer , Nicolae-Viorel Buchete , Edina Rosta

In order to model realistic quantum devices it is necessary to simulate quantum systems strongly coupled to their environment. To date, most understanding of open quantum systems is restricted either to weak system-bath couplings, or to…

Quantum Physics · Physics 2018-09-25 Aidan Strathearn , Peter Kirton , Dainius Kilda , Jonathan Keeling , Brendon W. Lovett

The method of positive commutators, developed for zero temperature problems over the last twenty years, has been an essential tool in the spectral analysis of Hamiltonians in quantum mechanics. We extend this method to positive…

Mathematical Physics · Physics 2009-11-10 Marco Merkli

Quantum critical systems offer promising advancements in quantum sensing and metrology, yet face limitations like critical slowing down and a restricted criticality-enhanced region. Here, we introduce a critical sensing scheme that mitigate…

Thermal models have proven to be an useful and simple tool used to make theoretical predictions and data analysis in relativistic and ultra-relativistic heavy ion collisions. A new version of these models is presented here, incorporating a…

A hallmark of living systems is the ability to employ a common set of versatile building blocks that can self-organize into a multitude of different structures, in a way that can be controlled with minimal cost. This capability can only be…

Statistical Mechanics · Physics 2022-01-26 Saeed Osat , Ramin Golestanian

In this paper, we provide a graphic formulation of non-isothermal reaction systems and show that a non-isothermal detailed balanced network system converges (locally) asymptotically to the unique equilibrium within the invariant manifold…

Dynamical Systems · Mathematics 2020-10-01 Zhou Fang , Arjan van der Schaft , Chuanhou Gao

We consider non-parametric estimation problems in the presence of dependent data, notably non-parametric regression with random design and non-parametric density estimation. The proposed estimation procedure is based on a dimension…

Statistics Theory · Mathematics 2016-02-02 Nicolas Asin , Jan Johannes

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also…

Statistical Mechanics · Physics 2014-05-27 Jerome P. Nilmeier , Gavin E. Crooks , David D. L. Minh , John D. Chodera

A Bayesian non-parametric framework for studying time-to-event data is proposed, where the prior distribution is allowed to depend on an additional random source, and may update with the sample size. Such scenarios are natural, for…

Methodology · Statistics 2025-05-06 Martin Bladt , Jorge González Cázares

A nonparametric learning solution framework is proposed for the global nonlinear robust output regulation problem. We first extend the assumption that the steady-state generator is linear in the exogenous signal to the more relaxed…

Systems and Control · Electrical Eng. & Systems 2024-06-21 Shimin Wang , Martin Guay , Zhiyong Chen , Richard D. Braatz

We study the dynamics of a macroscopic superconducting qubit coupled to two independent non-stationary reservoirs by using time-dependent perturbation theory. We show that an equilibrium environment surpasses the coherent evolution of the…

Quantum Physics · Physics 2018-12-13 Nasim Shahmansoori , Farhad Taher Ghahramani , Afshin Shafiee

We describe a parallel linear-scaling computational framework developed to implement arbitrarily large multi-state empirical valence bond (MS-EVB) calculations within CHARMM. Forces are obtained using the Hellman-Feynmann relationship,…

Chemical Physics · Physics 2019-07-08 David R. Glowacki , Andrew J. Orr-Ewing , Jeremy N. Harvey

One's ability to learn a generative model of the world without supervision depends on the extent to which one can construct abstract knowledge representations that generalize across experiences. To this end, capturing an accurate…

Machine Learning · Computer Science 2021-10-28 Zahra Sheikhbahaee , Dongshu Luo , Blake VanBerlo , S. Alex Yun , Adam Safron , Jesse Hoey
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