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Computer experiments have become ubiquitous in science and engineering. Commonly, runs of these simulations demand considerable time and computing, making experimental design extremely important in gaining high quality information with…

Statistics Theory · Mathematics 2017-05-15 Benjamin Haaland , Wenjia Wang , Vaibhav Maheshwari

Large pre-trained language models perform remarkably well on tasks that can be done "in one pass", such as generating realistic text or synthesizing computer programs. However, they struggle with tasks that require unbounded multi-step…

One way to investigate the precision of estimates likely to result from planned experiments and planned epidemiological studies is to simulate a large number of possible outcomes and analyse the sets of possible results. This appears to be…

Computation · Statistics 2013-06-28 G. K. Robinson , L. M. Ryan

The requirements for accurate numerical simulation are increasing constantly. Modern high precision physics experiments now exceed the achievable numerical accuracy of standard commercial and scientific simulation tools. One example are…

Computational Physics · Physics 2015-05-28 M. Andres , L. Banz , A. Costea , E. Hackmann , S. Herrmann , C. Lämmerzahl , L. Nesemann , B. Rievers , E. P. Stephan

Computer simulators are nowadays widely used to understand complex physical systems in many areas such as aerospace, renewable energy, climate modeling, and manufacturing. One fundamental issue in the study of computer simulators is known…

Methodology · Statistics 2019-02-05 Feng Yang , C. Devon Lin , Pritam Ranjan

Many parallel and distributed computing research results are obtained in simulation, using simulators that mimic real-world executions on some target system. Each such simulator is configured by picking values for parameters that define the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-03 Jesse McDonald , Maximilian Horzela , Frédéric Suter , Henri Casanova

We propose an extrapolation technique that allows accuracy improvement of the discrete dipole approximation computations. The performance of this technique was studied empirically based on extensive simulations for 5 test cases using many…

Optics · Physics 2008-07-29 Maxim A. Yurkin , Valeri P. Maltsev , Alfons G. Hoekstra

Simulation models often have parameters as input and return outputs to understand the behavior of complex systems. Calibration is the process of estimating the values of the parameters in a simulation model in light of observed data from…

Methodology · Statistics 2024-11-15 Özge Sürer

Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator of the simulation model built on simulation output at…

Methodology · Statistics 2023-08-24 Özge Sürer , Matthew Plumlee , Stefan M. Wild

Most surrogate models for computer experiments are interpolators, and the most common interpolator is a Gaussian process (GP) that deliberately omits a small-scale (measurement) error term called the nugget. The explanation is that computer…

Computation · Statistics 2010-11-23 Robert B. Gramacy , Herbert K. H. Lee

Simulation design is the choice of locations in parameter space at which simulations are to be run and is the first step in building an emulator capable of quickly providing estimates of simulation results for arbitrary locations in the…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-13 Michael D. Schneider , Oskar Holm , Lloyd Knox

The vast use of computers on scientific numerical computation makes the awareness of the limited precision that these machines are able to provide us an essential matter. A limited and insufficient precision allied to the truncation and…

Numerical Analysis · Computer Science 2009-11-13 B. O. Rodrigues , L. A. C. P. da Mota , L. G. S. Duarte

Almost every numerical task can be cast as extrapolation with respect to the fidelity or tolerance parameters of a consistent numerical method. This perspective enables probabilistic uncertainty quantification and optimal experimental…

Methodology · Statistics 2026-04-03 Chris. J. Oates , Richard Howey , Toni Karvonen

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

In most of the cases, the experimental study of Nanotechnology involves high cost for Laboratory set-up and the experimentation processes were also slow. So, one cannot rely on experimental nanotechnology alone. As such, the Computer-Based…

Emerging Technologies · Computer Science 2011-09-09 Tamal Sarkar , Samir Chandra Das , Ardhendu Mandal

Making good predictions of a physical system using a computer code requires the inputs to be carefully specified. Some of these inputs called control variables have to reproduce physical conditions whereas other inputs, called parameters,…

Computation · Statistics 2018-04-04 Guillaume Damblin , Pierre Barbillon , Merlin Keller , Alberto Pasanisi , Eric Parent

Target trial emulation has improved comparative effectiveness research by making the causal question, assumptions, and analysis plan explicit. However, target trial protocols are usually developed iteratively. After examining the data,…

Methodology · Statistics 2026-04-30 Mats Julius Stensrud

Differences between computer simulation of dynamical systems and laboratory experiments are common in teaching and research in engineering. Normally, numerical inaccuracy and the non-ideal behaviour of the devices involved in the experiment…

Numerical Analysis · Mathematics 2016-12-14 M. L. C. Peixoto , E. G. Nepomuceno , H. M. Rodrigues , S. A. M. Martins , G. F. V. Amaral

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

The analysis of computer models can be aided by the construction of surrogate models, or emulators, that statistically model the numerical computer model. Increasingly, computer models are becoming stochastic, yielding different outputs…

Methodology · Statistics 2020-04-10 Evan Baker , Peter Challenor , Matt Eames
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