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Spatial pattern formation is a key feature of many natural systems in physics, chemistry and biology. The essential theoretical issue in understanding pattern formation is to explain how a spatially homogeneous initial state can undergo…

Pattern Formation and Solitons · Physics 2015-06-04 Timothy Killingback , Gregory Loftus , Bala Sundaram

Under certain conditions, the dynamics of coarse-grained models of solvated proteins can be described using a Markov state model, which tracks the evolution of populations of configurations. The transition rates among states that appear in…

Soft Condensed Matter · Physics 2022-09-26 Margarita Colberg , Jeremy Schofield

In many real world chaotic systems, the interest is typically in determining when the system will behave in an extreme manner. Flooding and drought, extreme heatwaves, large earthquakes, and large drops in the stock market are examples of…

Applications · Statistics 2019-08-19 Michael LuValle

There is a growing interest, inspired by advances in technology, in the low temperature physics of thin films. These quasi-2D systems show a wide range of ordering effects including formation of striped states, reorientation transitions,…

Statistical Mechanics · Physics 2009-11-13 Alessandro Giuliani , Joel L. Lebowitz , Elliott H. Lieb

Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training efficiency and unpredictable errors when applied to structures…

Computational Physics · Physics 2019-11-21 Jonathan Vandermause , Steven B. Torrisi , Simon Batzner , Yu Xie , Lixin Sun , Alexie M. Kolpak , Boris Kozinsky

We analyse biased ensembles of trajectories for the random-field Ising model on a fully-connected lattice, which is described exactly by mean-field theory. By coupling the activity of the system to a dynamical biasing field, we find a range…

Statistical Mechanics · Physics 2021-10-27 Jules Guioth , Robert L. Jack

Rich out of equilibrium collective dynamics of strongly interacting large assemblies emerge in many areas of science. Some intriguing and not fully understood examples are the glassy arrest in atomic, molecular or colloidal systems,…

Statistical Mechanics · Physics 2023-05-03 Leticia F. Cugliandolo

Anisotropic magnetic colloids with permanent dipole moments exhibit rich field-responsive behavior arising from the interplay between particle geometry, dipolar interactions, and external driving. Modeling these systems remains challenging…

Soft Condensed Matter · Physics 2026-04-07 Jorge L. C. Domingos

The recently proposed many-body expanded full configuration interaction (MBE-FCI) method is extended to excited states and static first-order properties different from total, ground state correlation energies. Results are presented for…

Chemical Physics · Physics 2020-10-20 Janus J. Eriksen , Jürgen Gauss

Steady states are frequently used to investigate the long-term behaviors of (bio)-chemical systems. Recently, there has been a growing interest in network-based approaches due to their efficiency in deriving parametrizations of positive…

Dynamical Systems · Mathematics 2024-04-02 Bryan S. Hernandez , Patrick Vincent N. Lubenia

Resonant dipole-dipole interaction modifies the energy and decay rate of electronic excitations for finite one dimensional chains of ultracold atoms in an optical lattice. We show that collective excited states of the atomic chain can be…

Quantum Physics · Physics 2012-12-07 Hashem Zoubi , Helmut Ritsch

Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical…

Chemical Physics · Physics 2021-03-15 Julia Westermayr , Philipp Marquetand

We study how to efficiently control an interacting few-body system consisting of three harmonically trapped bosons. Specifically we investigate the process of modulating the interparticle interactions to drive an initially non-interacting…

Quantum Gases · Physics 2019-09-02 Alan Kahan , Thomás Fogarty , Jing Li , Thomas Busch

Force matching is an established technique to generate effective potentials for molecular dynamics simulations from first-principles data. This method has been implemented in the open source code potfit. Here, we present a review of the…

We introduce a variational method for the approximation of ground states of strongly interacting spin systems in arbitrary geometries and spatial dimensions. The approach is based on weighted graph states and superpositions thereof. These…

Quantum Physics · Physics 2007-05-23 S. Anders , M. B. Plenio , W. Dür , F. Verstraete , H. -J. Briegel

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

Data-driven, model-free analytics are natural choices for discovery and forecasting of complex, nonlinear systems. Methods that operate in the system state-space require either an explicit multidimensional state-space, or, one approximated…

Machine Learning · Statistics 2021-03-15 Joseph Park , Gerald M Pao , Erik Stabenau , George Sugihara , Thomas Lorimer

Photoactive iridium complexes are of broad interest due to their applications ranging from lighting to photocatalysis. However, the excited state property prediction of these complexes challenges ab initio methods such as time-dependent…

Chemical Physics · Physics 2022-09-20 Gianmarco Terrones , Chenru Duan , Aditya Nandy , Heather J. Kulik

We develop a cubic scaling approach to excited-state-specific second order perturbation theory in which the completeness of a local correlation treatment is carefully matched between the ground and excited state. With this matching, the…

Chemical Physics · Physics 2025-05-14 Rachel Clune , Eric Neuscamman

We compare the predicted phase behaviour of lead (Pb) using three different interatomic potential models, including an embedded atom method (EAM), a modified embedded atom method (MEAM), and a neural network-based machine-learned model in…

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