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Studying the impact of systematic effects, optimizing survey strategies, assessing tensions between different probes and exploring synergies of different data sets require a large number of simulated likelihood analyses, each of which cost…

Cosmology and Nongalactic Astrophysics · Physics 2022-12-07 Supranta S. Boruah , Tim Eifler , Vivian Miranda , Sai Krishanth P. M

The dynamic emulation of non-linear deterministic computer codes where the output is a time series, possibly multivariate, is examined. Such computer models simulate the evolution of some real-world phenomenon over time, for example models…

Machine Learning · Statistics 2022-03-22 Hossein Mohammadi , Peter Challenor , Marc Goodfellow

The modern study of the dynamics of stellar systems requires the use of high-performance computers. Indeed, an accurate modelization of the structure and evolution of self-gravitating systems like planetary systems, open clusters, globular…

Astrophysics · Physics 2015-06-10 R. Capuzzo-Dolcetta , P. Di Matteo , P. Miocchi

Risk assessment of hurricane-driven storm surge relies on deterministic computer models that produce outputs over a large spatial domain. The surge models can often be run at a range of fidelity levels, with greater precision yielding more…

Methodology · Statistics 2026-03-31 Cyrus S. McCrimmon , Pulong Ma

The scientific understanding of real-world processes has dramatically improved over the years through computer simulations. Such simulators represent complex mathematical models that are implemented as computer codes which are often…

Computation · Statistics 2020-04-20 Alfredo Garbuno-Inigo , F. Alejandro DiazDelaO , Konstantin M. Zuev

Simulations inform all aspects of modern astrophysical research, ranging in scale from 1D and 2D test problems that can run in seconds on an astronomer's laptop all the way to large-scale 3D calculations that run on the largest…

Instrumentation and Methods for Astrophysics · Physics 2017-11-29 Nathan J Goldbaum

Computer models are widely used to study complex real world physical systems. However, there are major limitations to their direct use including: their complex structure; large numbers of inputs and outputs; and long evaluation times.…

Methodology · Statistics 2025-05-05 Jonathan Owen , Ian Vernon

Computer experiments refer to the study of real systems using complex simulation models. They have been widely used as alternatives to physical experiments. Design and analysis of computer experiments have attracted great attention in past…

Methodology · Statistics 2025-04-29 Anita Shahrokhian , Xinwei Deng , C. Devon Lin

Design of experiments is a fundamental topic in applied statistics with a long history. Yet its application is often limited by the complexity and costliness of constructing experimental designs, which involve searching a high-dimensional…

Methodology · Statistics 2022-03-29 Matthew T. Pratola , C. Devon Lin , Peter F. Craigmile

Computer simulations that demonstrate the valueof novel approaches are crucial to developing more flexibleand robust power systems operations with high penetrations ofrenewable energy at multiple geographic and temporal scales.However,…

Systems and Control · Electrical Eng. & Systems 2020-09-01 Jose Daniel Lara , Jonathan T. Lee , Duncan Callaway , Bri-Mathias Hodge

Excellent computer simulations are done for a purpose. The most valid purposes are to explore uncharted territory, to resolve a well-posed scientific or technical question, or to make a design choice. Stand-alone modeling can serve the…

Numerical Analysis · Mathematics 2025-10-20 Leo P. Kadanoff

Complex computer codes are often too time expensive to be directly used to perform uncertainty propagation studies, global sensitivity analysis or to solve optimization problems. A well known and widely used method to circumvent this…

Applications · Statistics 2008-04-06 Amandine Marrel , Bertrand Iooss , Francois Van Dorpe , Elena Volkova

This paper addresses the use of experimental data for calibrating a computer model and improving its predictions of the underlying physical system. A global statistical approach is proposed in which the bias between the computer model and…

Applications · Statistics 2013-02-27 François Bachoc , Guillaume Bois , Josselin Garnier , Jean-Marc Martinez

The ubiquitous presence of computer simulations in all kinds of research areas evidence their role as the new driving force for the advancement of science and engineering research. Nothing seems to escape the image of success that computer…

Other Computer Science · Computer Science 2019-04-03 Juan M. Durán

Gaussian Process (GP) emulators are widely used to approximate complex computer model behaviour across the input space. Motivated by the problem of coupling computer models, recently progress has been made in the theory of the analysis of…

Applications · Statistics 2022-04-20 Victoria Volodina , Nikki Sonenberg , Peter Challenor , Jim Q. Smith

Design space exploration is commonly performed in embedded system, where the architecture is a complicated piece of engineering. With the current trend of many-core systems, design space exploration in general-purpose computers can no…

Hardware Architecture · Computer Science 2013-09-24 Irfan Uddin

Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…

Instrumentation and Methods for Astrophysics · Physics 2020-12-29 James Bird , Kellan Colburn , Linda Petzold , Philip Lubin

High performance computing numerical simulations are today one of the more effective instruments to implement and study new theoretical models, and they are mandatory during the preparatory phase and operational phase of any scientific…

Instrumentation and Methods for Astrophysics · Physics 2019-04-29 Giuliano Taffoni , Giuseppe Murante , Luca Tornatore , David Goz , Stefano Borgani , Manolis Katevenis , Nikolaos Chrysos , Manolis Marazakis

Numerical models based on physics represent the state-of-the-art in earth system modeling and comprise our best tools for generating insights and predictions. Despite rapid growth in computational power, the perceived need for higher model…

Machine Learning · Computer Science 2022-01-10 Kate Duffy , Thomas Vandal , Weile Wang , Ramakrishna Nemani , Auroop R. Ganguly

Galaxy simulations have come a long way from the early days of simple N-body calculations, which considered only gravitational interactions, to the complex, multi-physics models used today. Beginning with initial conditions representative…

Astrophysics of Galaxies · Physics 2025-07-15 Robert Feldmann , Rebekka Bieri