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Whole-cell computational models aim to predict cellular phenotypes from genotype by representing the entire genome, the structure and concentration of each molecular species, each molecular interaction, and the extracellular environment.…

Quantitative Methods · Quantitative Biology 2019-09-05 Arthur P. Goldberg , Balázs Szigeti , Yin Hoon Chew , John A. P. Sekar , Yosef D. Roth , Jonathan R. Karr

With the advent of large language models (LLMs), there is a growing interest in applying LLMs to scientific tasks. In this work, we conduct an experimental study to explore applicability of LLMs for configuring, annotating, translating,…

Human-Computer Interaction · Computer Science 2025-10-13 Orcun Yildiz , Tom Peterka

Modeling galaxy formation in a cosmological context presents one of the greatest challenges in astrophysics today, due to the vast range of scales and numerous physical processes involved. Here we review the current status of models that…

Astrophysics of Galaxies · Physics 2015-09-23 Rachel S. Somerville , Romeel Davé

We examine the interaction of multigrid methods and shape optimization in appropriate shape spaces. Our aim is a scalable algorithm for application on supercomputers, which can only be achieved by mesh-independent convergence. The impact of…

Optimization and Control · Mathematics 2021-04-12 Martin Siebenborn , Kathrin Welker

Reduced wavenumber models of turbulence, shell models, show cascade processes and anomalous scaling of correlators which might be analogous to what is observed in Navier-Stokes (N-S) turbulence. The scaling properties of the shell models…

chao-dyn · Physics 2007-05-23 P. D. Ditlevsen

This is the first work to look at the application of large language models (LLMs) for the purpose of model space edits in automated planning tasks. To set the stage for this union, we explore two different flavors of model space problems…

Artificial Intelligence · Computer Science 2024-03-06 Turgay Caglar , Sirine Belhaj , Tathagata Chakraborti , Michael Katz , Sarath Sreedharan

We discuss the results of using large language models (LLMs) to conduct original scientific research in an unfamiliar subject area during the Fall 2025 semester. Students in a graduate astronomy and astrophysics course were asked to test…

Instrumentation and Methods for Astrophysics · Physics 2026-03-30 Ann Zabludoff , Chen-Yu Chuang , Parker Thomas Johnson , Yichen Liu , Brina Bianca Martinez , Neev Shah , Lucille Steffes , Gabriel Glen Weible

We discuss the shape dependence of the finite-size scaling limit in a strongly anisotropic O(N) model in the large-N limit. We show that scaling is observed even if an incorrect value for the anisotropy exponent is considered. However, the…

Statistical Mechanics · Physics 2007-05-23 Sergio Caracciolo , Andrea Gambassi , Massimiliano Gubinelli , Andrea Pelissetto

Shell-model calculations in a large model space are performed for _{\Lambda}^{16}O and_{\Lambda}^{17}O. Effective interactions with degrees of freedom of \Sigma in addition to \Lambda and nucleons are derived from hyperon-nucleon and…

Nuclear Theory · Physics 2009-11-07 S. Fujii , R. Okamoto , K. Suzuki

The exterior and interior Schwarzschild solutions are rewritten replacing the usual radial variable with an angular one. This allows to obtain some results otherwise less apparent or even hidden in other coordinate systems.

General Relativity and Quantum Cosmology · Physics 2007-05-23 A. G. Agnese , M. La Camera

Motion of two gravitating spherical stellar shells around a massive central body is considered. Each shell consists of point particles with the same specific angular momenta and energies. In the case when one can neglect the influence of…

Chaotic Dynamics · Physics 2009-11-10 M. V. Barkov , G. S. Bisnovatyi-Kogan , A. I. Neishtadt , V. A. Belinski

In one of our earlier works, we proposed to approximate Pareto fronts to multiobjective optimization problems by two-sided approximations, one from inside and another from outside of the feasible objective set, called, respectively, lower…

Optimization and Control · Mathematics 2018-04-24 Ignacy Kaliszewski , Janusz Miroforidis

We discuss some aspects of the approach of the mass parameters by means of the simple cranking model. In particular, it is well known that the numerical application of this formula is often subject to ambiguities or contradictions. It is…

Nuclear Theory · Physics 2015-06-04 B. Mohammed-Azizi

Sphere packings are essential to the development of physical models for powders, composite materials, and the atomic structure of the liquid state. There is a strong scientific need to be able to assess the fit of packing models to data,…

Methodology · Statistics 2009-10-31 Jeffrey Picka

In molecular simulations, one of the most difficult points is to track the real dynamics of many-body systems from the first principle. The present study shows that step-size dependences have an unexpected effect on simulation results, even…

chao-dyn · Physics 2008-02-03 Ken Umeno

In a recent paper it was proposed that for some nonlinear shell models of turbulence one can construct a linear advection model for an auxiliary field such that the scaling exponents of all the structure functions of the linear and…

Chaotic Dynamics · Physics 2009-11-11 Roberto Benzi , Boris Levant , Itamar Procaccia , Edriss S. Titi

Ongoing investigations to introduce software techniques suitable to support new experimental requirements for multi-scale simulation are discussed.

Empirical models of galaxy formation require assumptions about the correlations between galaxy and halo properties. These may be calibrated against observations or inferred from physical models such as hydrodynamical simulations. In this…

Astrophysics of Galaxies · Physics 2017-07-17 Harry Desmond , Yao-Yuan Mao , Risa Wechsler , Robert Crain , Joop Schaye

We explore the possibility of putting constraints on quintessence models with large-scale structure observations. In particular we compute the linear and second order growth rate of the fluctuations in different flavors of quintessence…

Astrophysics · Physics 2009-11-06 K. Benabed , F. Bernardeau

Several machine learning methods aim to learn or reason about complex physical systems. A common first-step towards reasoning is to infer system parameters from observations of its behavior. In this paper, we investigate the performance of…

Computation and Language · Computer Science 2024-02-07 Sean Memery , Mirella Lapata , Kartic Subr