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Related papers: High precision modeling at the 10^{-20} level

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The development of algorithms for automation of subtasks during robotic surgery can be accelerated by the availability of realistic simulation environments. In this work, we focus on one aspect of the realism of a surgical simulator, which…

Robotics · Computer Science 2024-06-12 Juan Antonio Barragan , Hisashi Ishida , Adnan Munawar , Peter Kazanzides

This paper presents a study of accuracy issues in thermal modeling of high power LED modules on system level. Both physical as well as numerical accuracy issues are addressed. Incorrect physical assumptions may result in seemingly correct,…

Materials Science · Physics 2007-09-13 D. Benoy

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision…

Computational Engineering, Finance, and Science · Computer Science 2025-09-09 Aditya Kashi , Hao Lu , Wesley Brewer , David Rogers , Michael Matheson , Mallikarjun Shankar , Feiyi Wang

Precision is a crucial performance indicator for robot arms, as high precision manipulation allows for a wider range of applications. Traditional methods for improving robot arm precision rely on error compensation. However, these methods…

Robotics · Computer Science 2023-02-28 Qu Weiming , Liu Tianlin , Luo Dingsheng

Many glass products require thermoformed geometry with high precision. However, the traditional approach of developing a thermoforming process through trials and errors can cause large waste of time and resources and often end up with…

Computational Engineering, Finance, and Science · Computer Science 2025-05-07 Yuzhou Zhang , Mohan Hua , Jinan Liu , Haihui Ruan

We address potential deviations of radiation field from the bosonic behaviour and employ local quantum estimation theory to evaluate the ultimate bounds to precision in the estimation of these deviations using quantum-limited measurements…

Quantum Physics · Physics 2014-07-09 Giovanni De Cillis , Matteo G. A. Paris

Measurements of angular correlations between initial and final particles in $\beta$ decay remain one of the most promising ways of probing the Standard Model and looking for new physics. As experiments reach unprecedented precision well…

Nuclear Theory · Physics 2020-10-07 Leendert Hayen , Albert R. Young

Display-camera communication has become a promising direction in both computer vision and wireless communication communities. However, the consistency of the channel measurement is an open issue since precise calibration of the experimental…

Multimedia · Computer Science 2021-09-06 Changsheng Chen , Wai Ho Mow

A combination of reaction-diffusion models with moving-boundary problems yields a system in which the diffusion (spreading and penetration) and reaction (transformation) evolve the system's state and geometry over time. These systems can be…

Computational Engineering, Finance, and Science · Computer Science 2020-08-26 Mojtaba Barzegari , Liesbet Geris

This paper gives a brief overview of the present and expected future limits on physics beyond the Standard Model (SM) from neutron beta decay, which is described by two parameters only within the SM. Since more than two observables are…

Nuclear Experiment · Physics 2012-11-05 G. Konrad , W. Heil , S. Baeßler , D. Počanić , F. Glück

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

Achieving the ultimate precisions for multiple parameters simultaneously is an outstanding challenge in quantum physics, because the optimal measurements for incompatible parameters cannot be performed jointly due to the Heisenberg…

Quantum Physics · Physics 2023-10-12 Binke Xia , Jingzheng Huang , Hongjing Li , Han Wang , Guihua Zeng

The application of machine learning to physics problems is widely found in the scientific literature. Both regression and classification problems are addressed by a large array of techniques that involve learning algorithms. Unfortunately,…

Machine Learning · Computer Science 2022-10-03 Umberto Michelucci , Francesca Venturini

Simulation is a useful tool in situations where training data for machine learning models is costly to annotate or even hard to acquire. In this work, we propose a reinforcement learning-based method for automatically adjusting the…

Machine Learning · Computer Science 2019-05-15 Nataniel Ruiz , Samuel Schulter , Manmohan Chandraker

Spatial approximations have been traditionally used in spatial databases to accelerate the processing of complex geometric operations. However, approximations are typically only used in a first filtering step to determine a set of candidate…

The rheological characterisation of complex fluids is mostly performed under simple shear flow in rotational rheometers. Their modern commercial versions are extremely sensitive instruments which are able to provide very accurate…

Fluid Dynamics · Physics 2021-03-05 Ahmad Fakhari , Francisco J. Galindo-Rosales

The computational cost for high energy physics detector simulation in future experimental facilities is going to exceed the current available resources. To overcome this challenge, new ideas on surrogate models using machine learning…

Quite a few future high precision space missions for testing Special and General Relativity will use optical resonators which are used for laser frequency stabilization. These devices are used for carrying out tests of the isotropy of light…

Classical Physics · Physics 2009-11-11 S. Scheithauer , C. Lämmerzahl

In this paper we review different expansions for neutrino oscillation probabilities in matter in the context of long-baseline neutrino experiments. We examine the accuracy and computational efficiency of different exact and approximate…

High Energy Physics - Phenomenology · Physics 2019-03-14 Gabriela Barenboim , Peter B. Denton , Stephen J. Parke , Christoph A. Ternes

Complex phenomena in engineering and the sciences are often modeled with computationally intensive feed-forward simulations for which a tractable analytic likelihood does not exist. In these cases, it is sometimes necessary to estimate an…

Methodology · Statistics 2020-06-18 Niccolò Dalmasso , Ann B. Lee , Rafael Izbicki , Taylor Pospisil , Ilmun Kim , Chieh-An Lin
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