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For a large class of processes with an absorbing state, statistical properties of the surviving sample attain time-independent values in the quasi-stationary (QS) regime. We propose a practical simulation method for studying…

Statistical Mechanics · Physics 2007-05-23 Marcelo Martins de Oliveira , Ronald Dickman

Quasi-steady state reductions for the irreversible Michaelis--Menten reaction mechanism are of interest both from a theoretical and an experimental design perspective. A number of publications have been devoted to extending the parameter…

Chemical Physics · Physics 2023-03-21 Justin Eilertsen , Santiago Schnell , Sebastian Walcher

Partial equilibrium approximation (PEA) and quasi-steady-state approximation (QSSA) are two classical methods for reducing complex macroscopic chemical reactions into simple computable ones. Previous studies mainly focus on the accuracy of…

Chemical Physics · Physics 2023-08-15 Liangrong Peng , Liu Hong

In this paper, a theoretical foundation for the Quasi Steady-State (QSS) model in power system long-term stability analysis is developed. Sufficient conditions under which the QSS model gives accurate approximations of the long-term…

Systems and Control · Computer Science 2013-11-26 Xiaozhe Wang , Hsiao-Dong Chiang

Semiclassical approximations for quantum dynamic simulations in complex chemical systems range from rigorously accurate methods that are computationally expensive to methods that exhibit near-classical scaling with system size but are…

Chemical Physics · Physics 2022-09-09 Shreyas Malpathak , Matthew S. Church , Nandini Ananth

A preceding paper demonstrated that explicit asymptotic methods generally work much better for extremely stiff reaction networks than has previously been shown in the literature. There we showed that for systems well removed from…

Solar and Stellar Astrophysics · Physics 2022-10-19 M. W. Guidry , J. A. Harris

The quasi steady-state (QSS) model tries to reach a good compromise between accuracy and efficiency in long-term stability analysis. However, the QSS model is unable to provide correct approximations and stability assessment for the…

Systems and Control · Computer Science 2014-05-07 Xiaozhe Wang , Hsiao-Dong Chiang

We construct a class of quantum stochastic models of reservoir driven many-particle systems that are the natural counterparts of certain extensively studied classical ones, which have been shown to exhibit good hydrodynamical behaviour. Our…

Mathematical Physics · Physics 2009-11-11 Geoffrey Sewell

Ultrastable glasses, amorphous solids with exceptionally low-energy states and enhanced kinetic, thermodynamic and mechanical stability, have long been a subject of intense experimental interest. Over the past decade, their computational…

Disordered Systems and Neural Networks · Physics 2026-05-05 Fabio Leoni , Misaki Ozawa , John Russo , Taiki Yanagishima , Andrea Ninarello

Quantum plasma physics is a rapidly evolving research field with a very inter-disciplinary scope of potential applications, ranging from nano-scale science in condensed matter to the vast scales of astrophysical objects. The theoretical…

Plasma Physics · Physics 2013-10-02 Shabbir A. Khan , Michael Bonitz

We use the invariant-based inverse engineering subject to the quasiadiabatic condition to produce robust and high fidelity coherent superposition of quantum states. The inverse engineering provides shortcuts to the desired quantum-state…

Quantum Physics · Physics 2017-09-12 Yen-Huang Liu , Shuo-Yen Tseng

The conditions for the validity of the standard quasi-steady-state approximation in the Michaelis--Menten mechanism in a closed reaction vessel have been well studied, but much less so the conditions for the validity of this approximation…

Dynamical Systems · Mathematics 2023-03-21 Justin Eilertsen , Marc R. Roussel , Santiago Schnell , Sebastian Walcher

We introduce the notion of a quasistatic dynamical system, which generalizes that of an ordinary dynamical system. Quasistatic dynamical systems are inspired by the namesake processes in thermodynamics, which are idealized processes where…

Dynamical Systems · Mathematics 2016-05-18 Neil Dobbs , Mikko Stenlund

The development of consistent and stable quasicontinuum models for multi-dimensional crystalline solids remains a challenge. For example, proving stability of the force-based quasicontinuum (QCF) model remains an open problem. In 1D and 2D,…

Numerical Analysis · Mathematics 2011-12-13 Xingjie Helen Li , Mitchell Luskin , Christoph Ortner

The adoption of detailed mechanisms for chemical kinetics often poses two types of severe challenges: First, the number of degrees of freedom is large; and second, the dynamics is characterized by widely disparate time scales. As a result,…

Dynamical Systems · Mathematics 2025-10-01 Eliodoro Chiavazzo , C. William Gear , Carmeline J. Dsilva , Neta Rabin , Ioannis G. Kevrekidis

We address the problem of estimating steady-state quantities associated to systems of stochastic chemical kinetics. In most cases of interest these systems are analytically intractable, and one has to resort to computational methods to…

Quantitative Methods · Quantitative Biology 2014-01-21 Andreas Milias-Argeitis , John Lygeros , Mustafa Khammash

Studies of strongly nonlinear dynamical systems such as turbulent flows call for superior computational prowess. With the advent of quantum computing, a plethora of quantum algorithms have demonstrated, both theoretically and…

Quantum Physics · Physics 2025-04-30 Sachin S. Bharadwaj , Katepalli R. Sreenivasan

Stochastic unravelings represent a useful tool to describe the dynamics of open quantum systems and standard methods, such as quantum state diffusion (QSD), call for the complete positivity of the open-system dynamics. Here, we present a…

Quantum Physics · Physics 2017-07-04 Matteo Caiaffa , Andrea Smirne , Angelo Bassi

The operation of near-term quantum technologies requires the development of feasible, implementable, and robust strategies of controlling complex many body systems. To this end, a variety of techniques, so-called "shortcuts to adiabaticty",…

Quantum Physics · Physics 2022-10-21 Artur Soriani , Eduardo Miranda , Sebastian Deffner , Marcus V. S. Bonança

Normalizing Flows are a powerful technique for learning and modeling probability distributions given samples from those distributions. The current state of the art results are built upon residual flows as these can model a larger hypothesis…

Machine Learning · Computer Science 2020-09-17 Achintya Gopal