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Related papers: A New Monte-Carlo Model for the Space Environment

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The key to Black-Box Optimization is to efficiently search through input regions with potentially widely-varying numerical properties, to achieve low-regret descent and fast progress toward the optima. Monte Carlo Tree Search (MCTS) methods…

Machine Learning · Computer Science 2022-11-03 Yaoguang Zhai , Sicun Gao

The space mission CoRoT (COnvection, ROtation and planetary Transits) will offer the possibility to detect extrasolar planets by means of the transit method. The satellite will observe about 60000 targets in the range 11.0<V<16.0, located…

Astrophysics · Physics 2007-05-23 E. Poretti , A. F. Lanza , C. Maceroni , I. Pagano , V. Ripepi

This paper develops a robust optimization based method to design orbits on which the sensory perception of the desired physical quantities are maximized. It also demonstrates how to incorporate various constraints imposed by many spacecraft…

Optimization and Control · Mathematics 2013-12-30 Hamidreza Nourzadeh , John E. McInroy

Three ongoing microlensing experiments have found more candidate events than expected from the known stars. These experiments measure only one parameter of the massive compact halo objects (machos), the magnification time scale of the…

Astrophysics · Physics 2009-10-28 Thomas Boutreux , Andrew Gould

Dynamical mean-field theory allows access to the physics of strongly correlated materials with nontrivial orbital structure, but relies on the ability to solve auxiliary multi-orbital impurity problems. The most successful approaches to…

Strongly Correlated Electrons · Physics 2023-11-29 Dolev Goldberger , Yehonatan Fridman , Emanuel Gull , Eitan Eidelstein , Guy Cohen

Particle Markov Chain Monte Carlo (PMCMC) is a general computational approach to Bayesian inference for general state space models. Our article scales up PMCMC in terms of the number of observations and parameters by generating the…

Methodology · Statistics 2023-07-04 David Gunawan , Chris Carter , Robert Kohn

Neglecting small fragments in space debris evolutionary models can lead to a significant underestimation of the collision risk for operational satellites. However, when scaling down to the millimeter range, the debris population grows to…

Space Physics · Physics 2023-09-08 Lorenzo Giudici , Juan Luis Gonzalo , Camilla Colombo

We summarize a series of numerical experiments of collisional dynamics in dense stellar systems such as globular clusters (GCs) and in weakly collisional plasmas using a novel simulation technique, the so-called Multi-particle collision…

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be…

High Energy Physics - Phenomenology · Physics 2011-01-17 N. Davidson , P. Golonka , T. Przedzinski , Z. Was

I simulate the evolution of a stellar system hosting two stellar populations whose initial set up is defined according to the two main scenarios proposed for the origin of multiple populations in Galactic globular clusters: (i) formation of…

Astrophysics of Galaxies · Physics 2021-02-17 A. Sollima

In terms of the excursion set model, we used Monte Carlo methods in order to study the non-Markovian stochastic evolution of the smoothed overdensity $\delta$ at scale $S$. For a Gaussian density field, smoothed by the top-hat filter, in…

Cosmology and Nongalactic Astrophysics · Physics 2022-06-23 Nicos Hiotelis

In this work, we introduce three algorithmic improvements to reduce the cost and improve the scaling of orbital space variational Monte Carlo (VMC). First, we show that by appropriately screening the one- and two-electron integrals of the…

Chemical Physics · Physics 2018-07-30 Iliya Sabzevari , Sandeep Sharma

The risk of collision between resident space objects has significantly increased in recent years. As a result, spacecraft collision avoidance procedures have become an essential part of satellite operations. To ensure safe and effective…

Machine Learning · Computer Science 2023-11-17 Marta Guimarães , Cláudia Soares , Chiara Manfletti

We describe and analyze some Monte Carlo methods for manifolds in Euclidean space defined by equality and inequality constraints. First, we give an MCMC sampler for probability distributions defined by un-normalized densities on such…

Numerical Analysis · Mathematics 2017-09-21 Emilio Zappa , Miranda Holmes-Cerfon , Jonathan Goodman

Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncertain values. This article introduces a framework for…

Astronauts participating in deep-space exploration missions will be exposed to significantly greater amounts of radiation than is typically encountered on Earth or in low Earth orbit (LEO), which poses significant risks to crew health and…

Computational Physics · Physics 2025-09-12 Joseph L. Hesse-Withbroe , Katya S. Arquilla

In recent years, space weather research has focused on developing modelling techniques to predict the arrival time and properties of coronal mass ejections (CMEs) at the Earth. The aim of this paper is to propose a new modelling technique…

Solar and Stellar Astrophysics · Physics 2018-02-22 P. Pagano , D. H. Mackay , A. R. Yeates

Building and maintaining a space object catalog is necessary for space situational awareness. To realize this, one great challenge is uncooperative spacecraft maneuver detection because unknown maneuver events can lead to deviated orbital…

Optimization and Control · Mathematics 2025-06-16 Xuejian Mao , Pei Liu , Pei Chen

Interstellar methanol is considered to be a parent species of larger, more complex organic molecules. A physicochemical simulation of infalling parcels of matter is performed for a low-mass star-forming system to trace the chemical…

Solar and Stellar Astrophysics · Physics 2014-09-09 Maria N. Drozdovskaya , Catherine Walsh , Ruud Visser , Daniel Harsono , Ewine F. van Dishoeck

Deploying robots at scale demands robustness to the long tail of everyday situations. The countless variations in scene layout, object geometry, and task specifications that characterize real environments are vast and underrepresented in…

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