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The circum-galactic medium (CGM) can feasibly be mapped by multiwavelength surveys covering broad swaths of the sky. With multiple large datasets becoming available in the near future, we develop a likelihood-free Deep Learning technique…

As the particle count escalates, the computational demands of diverse simulation algorithms surge, paralleled by a marked enhancement in accuracy. The question arises whether this heightened precision asymptotically dwindles towards zero or…

Computational Physics · Physics 2025-01-08 Yonglong Ding

Physical simulations based on partial differential equations typically generate spatial fields results, which are utilized to calculate specific properties of a system for engineering design and optimization. Due to the intensive…

Machine Learning · Computer Science 2022-09-09 Shihong Wang , Xueying Zhang , Yichen Meng , Wei W. Xing

We construct effective 2- and 3-body Hamiltonians for the p-shell by performing 12\hbar\Omega ab initio no-core shell model (NCSM) calculations for A=6 and 7 nuclei and explicitly projecting the many-body Hamiltonians onto the 0\hbar\Omega…

Nuclear Theory · Physics 2009-01-14 A. F. Lisetskiy , B. R. Barrett , M. K. G. Kruse , P. Navratil , I. Stetcu , J. P. Vary

Deep neural state-space models (SSMs) provide a powerful tool for modeling dynamical systems solely using operational data. Typically, neural SSMs are trained using data collected from the actual system under consideration, despite the…

Machine Learning · Computer Science 2022-11-16 Ankush Chakrabarty , Gordon Wichern , Christopher R. Laughman

We introduce an emulator approach to predict the non-linear matter power spectrum for broad classes of beyond-$\Lambda$CDM cosmologies, using only a suite of $\Lambda$CDM $N$-body simulations. By including a range of suitably modified…

Cosmology and Nongalactic Astrophysics · Physics 2019-10-02 Benjamin Giblin , Matteo Cataneo , Ben Moews , Catherine Heymans

A realistic description of halo nuclei, characterized by low-lying breakup thresholds, requires a proper treatment of continuum effects. We have developed an ab initio approach, the no-core shell model with continuum (NCSMC), capable of…

Nuclear Theory · Physics 2026-05-26 Petr Navratil , Sofia Quaglioni , Guillaume Hupin , Michael Gennari , Kostas Kravvaris

Model-based planning holds great promise for improving both sample efficiency and generalization in reinforcement learning (RL). We show that energy-based models (EBMs) are a promising class of models to use for model-based planning. EBMs…

Machine Learning · Computer Science 2021-03-09 Yilun Du , Toru Lin , Igor Mordatch

A previously published neural network potential for the description of protonated water clusters up to the protonated water tetramer, H$^+$(H$_2$O)$_4$, at essentially converged coupled cluster accuracy (J. Chem. Theory Comput. 16, 88…

Chemical Physics · Physics 2021-02-04 Christoph Schran , Fabien Brieuc , Dominik Marx

Calculations in the ab initio no-core shell model (NCSM) have conventionally been carried out using the harmonic-oscillator many-body basis. However, the rapid falloff (Gaussian asymptotics) of the oscillator functions at large radius makes…

Nuclear Theory · Physics 2014-09-02 M. A. Caprio , P. Maris , J. P. Vary

Energy based models (EBMs) are appealing due to their generality and simplicity in likelihood modeling, but have been traditionally difficult to train. We present techniques to scale MCMC based EBM training on continuous neural networks,…

Machine Learning · Computer Science 2020-07-01 Yilun Du , Igor Mordatch

Machine Learning (ML) has deeply changed some fields recently, like Language and Vision and we may expect it to be relevant also to the analysis of of complex systems. Here we want to tackle the question of how and to which extent can one…

Disordered Systems and Neural Networks · Physics 2026-02-02 Anaclara Alvez-Canepa , Cyril Furtlehner , François Landes

Accurately determining the size of the atomic nucleus with realistic nuclear forces is a long outstanding issue of nuclear physics. The no-core shell model (NCSM), one of the powerful ab initio methods for nuclear structure, can achieve…

Nuclear Theory · Physics 2025-02-07 Xiang-Xiang Sun , Hoai Le , Ulf-G. Meißner , Andreas Nogga

We demonstrate the existence of multiple converging sequences in the ab initio no-core shell model. By examining the underlying theory of effective operators, we expose the physical foundations for the alternative pathways to convergence.…

Nuclear Theory · Physics 2008-11-26 C. Forssén , J. P. Vary , E. Caurier , P. Navrátil

The energies and decay widths of the states of the exotic 7He nucleus are studied in an ab initio approach. The spectrum of these states is calculated using No-Core Shell Model and corresponding extrapolation procedure. Well-proven on a…

Nuclear Theory · Physics 2021-04-22 D. M. Rodkin , Yu. M. Tchuvil'sky

In this work, we revisit nonlinear generalized minimal residual method (NGMRES) applied to nonlinear problems. NGMRES is used to accelerate the convergence of fixed-point iterations, which can substantially improve the performance of the…

Numerical Analysis · Mathematics 2025-11-25 Yunhui He

Modern machine learning systems based on neural networks have shown great success in learning complex data patterns while being able to make good predictions on unseen data points. However, the limited interpretability of these systems…

Machine Learning · Computer Science 2020-07-22 Sarath Shekkizhar , Antonio Ortega

The no-core shell model (NCSM) is an \textit{ab initio} method that solves the nuclear many-body problem by expanding the many-particle wave function into a (typically) harmonic oscillator basis and minimizing the energy to obtain the…

Nuclear Theory · Physics 2024-02-06 Konstantinos Kravvaris , Sofia Quaglioni , Petr Navratil

Electromagnetic Navigation Systems (eMNS) can be used to control a variety of multiscale devices within the human body for remote surgery. Accurate modeling of the magnetic fields generated by the electromagnets of an eMNS is crucial for…

Systems and Control · Electrical Eng. & Systems 2025-12-01 Ruoxi Yu , Samuel L. Charreyron , Quentin Boehler , Cameron Weibel , Carmen C. Y. Poon , Bradley J. Nelson

The availability of low-energy antiproton beams at the CERN Antiproton Decelerator has renewed interest in using antimatter as a probe of nuclear structure and in forming exotic antiprotonic few-body systems. In this work, we extend the ab…

Nuclear Theory · Physics 2026-02-23 Alireza Dehghani , Guillaume Hupin , Sofia Quaglioni , Petr Navrátil
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