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Parameter calibration is essential for reducing uncertainty and improving predictive fidelity in physics-based models, yet it is often limited by the high computational cost of model evaluations. Bayesian calibration methods provide a…

Methodology · Statistics 2026-01-21 Maike F. Holthuijzen , Atlanta Chakraborty , Elizabeth Krath , Tommie Catanach

In this work, we propose a novel end-to-end sinkhorn autoencoder with noise generator for efficient data collection simulation. Simulating processes that aim at collecting experimental data is crucial for multiple real-life applications,…

Machine Learning · Computer Science 2020-06-15 Kamil Deja , Jan Dubiński , Piotr Nowak , Sandro Wenzel , Tomasz Trzciński

The total cross section for Compton scattering off atomic electrons, $\gamma+e\rightarrow\gamma'+e'$, was measured using photons with energies between 6.5 and 11.1 GeV incident on a $^9$Be target as part of the PrimEx-eta experiment in Hall…

Nuclear Experiment · Physics 2025-07-31 GlueX Collaboration , F. Afzal , C. S. Akondi , M. Albrecht , M. Amaryan , S. Arrigo , V. Arroyave , A. Asaturyan , A. Austregesilo , Z. Baldwin , F. Barbosa , J. Barlow , E. Barriga , R. Barsotti , D. Barton , V. Baturin , V. V. Berdnikov , T. Black , W. Boeglin , M. Boer , W. J. Briscoe , T. Britton , R. Brunner , S. Cao , E. Chudakov , G. Chung , P. L. Cole , O. Cortes , V. Crede , M. M. Dalton , D. Darulis , A. Deur , S. Dobbs , A. Dolgolenko , M. Dugger , R. Dzhygadlo , D. Ebersole , M. Edo , T. Erbora , P. Eugenio , A. Fabrizi , C. Fanelli , S. Fang , M. Fritsch , S. Furletov , L. Gan , H. Gao , A. Gardner , A. Gasparian , D. I. Glazier , C. Gleason , V. S. Goryachev , B. Grube , J. Guo , L. Guo , J. Hernandez , K. Hernandez , N. D. Hoffman , D. Hornidge , G. M. Huber , P. Hurck , W. Imoehl , D. G. Ireland , M. M. Ito , I. Jaegle , N. S. Jarvis , T. Jeske , M. Jing , R. T. Jones , V. Kakoyan , G. Kalicy , V. Khachatryan , C. Kourkoumelis , A. LaDuke , I. Larin , D. Lawrence , D. I. Lersch , H. Li , B. Liu , K. Livingston , L. Lorenti , V. Lyubovitskij , A. Mahmood , H. Marukyan , V. Matveev , M. McCaughan , M. McCracken , C. A. Meyer , R. Miskimen , R. E. Mitchell , K. Mizutani , P. Moran , V. Neelamana , L. Ng , E. Nissen , S. Orešić , A. I. Ostrovidov , Z. Papandreou , C. Paudel , R. Pedroni , L. Pentchev , K. J. Peters , E. Prather , L. Puthiya Veetil , S. Rakshit , J. Reinhold , A. Remington , B. G. Ritchie , J. Ritman , G. Rodriguez , D. Romanov , K. Saldana , C. Salgado , S. Schadmand , A. M. Schertz , K. Scheuer , A. Schick , A. Schmidt , R. A. Schumacher , J. Schwiening , M. Scott , N. Septian , P. Sharp , V. J. Shen , X. Shen , M. R. Shepherd , J. Sikes , H. Singh , A. Smith , E. S. Smith , D. I. Sober , A. Somov , S. Somov , J. R. Stevens , I. I. Strakovsky , B. Sumner , K. Suresh , V. V. Tarasov , S. Taylor , A. Teymurazyan , A. Thiel , M. Thomson , T. Viducic , T. Whitlatch , N. Wickramaarachchi , Y. Wunderlich , B. Yu , J. Zarling , Z. Zhang , X. Zhou , B. Zihlmann

Artificial neural networks (ANNs) have demonstrated outstanding performance in numerous tasks, but deployment in resource-constrained environments remains a challenge due to their high computational and memory requirements. Spiking neural…

Machine Learning · Computer Science 2025-06-04 Chang Liu , Jiangrong Shen , Xuming Ran , Mingkun Xu , Qi Xu , Yi Xu , Gang Pan

The process of calibrating computer models of natural phenomena is essential for applications in the physical sciences, where plenty of domain knowledge can be embedded into simulations and then calibrated against real observations. Current…

Machine Learning · Computer Science 2025-01-20 Rafael Oliveira , Dino Sejdinovic , David Howard , Edwin V. Bonilla

Third-generation gravitational wave detectors such as Einstein Telescope and Cosmic Explorer will have significantly better sensitivities than current detectors, as well as a wider frequency bandwidth. This will increase the number and…

General Relativity and Quantum Cosmology · Physics 2025-10-22 Tomasz Baka , Harsh Narola , Justin Janquart , Anuradha Samajdar , Tim Dietrich , Chris Van Den Broeck

Deep learning models for atrial fibrillation (AF) detection are increasingly trained on heterogeneous electrocardiogram (ECG) datasets with varying sampling frequencies, yet the specific consequences of these discrepancies on model…

The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods…

Applications · Statistics 2017-09-13 Vahid Yaghoubi , Majid K. Vakilzadeh , Thomas J. S. Abrahamsson

Switched capacitor arrays (SCA) ASICs are becoming more and more popular for the readout of detector signals, since the sampling frequency of typically several gigasamples per second allows excellent pile-up rejection and time measurements.…

Instrumentation and Detectors · Physics 2014-11-24 D. Stricker-Shaver , S. Ritt , B. J. Pichler

Scintillation detectors with excellent timing resolution enable more precise localization of radiation sources in positron emission tomography, leading to substantial improvements in diagnostic capability for diseases such as cancer and…

Instrumentation and Detectors · Physics 2026-05-28 Yuya Onishi , Ryosuke Ota , Fumio Hashimoto , Kibo Ote , Go Akamatsu , Hideaki Tashima , Taiga Yamaya

Precise measurement of the absolute light yield (LY) of scintillators has long been limited by systematic effects inherent in realistic readout geometries. Large-angle incidence, multiple reflections inside the optical housing, and…

High Energy Physics - Experiment · Physics 2026-03-03 Ge Ma , Zhiyang Yuan , Chencheng Feng , Zirui Yang , Zhenwei Yang , Ming Zeng

``Oversimplified'' and ``simplified'' methods based on true coincidence summing effect used in uncomplicated determination of the photo-peak efficiency of the semiconductor High Purity Germanium (HPGe) detector system are suggested and…

Instrumentation and Detectors · Physics 2022-06-22 Victor V. Golovko

The recent development of scintillation crystals combined with $\gamma$-rays sources opens the way to an imaging concept based on Compton scattering, namely Compton scattering tomography (CST). The associated inverse problem rises many…

Numerical Analysis · Mathematics 2023-02-22 Janek Gödeke , Gaël Rigaud

Accurately simulating molecular vibronic spectra remains computationally challenging due to the exponential scaling of required calculations. Here, we show that employing the linear coupling model within the gaussian boson sampling…

Quantum Physics · Physics 2025-08-07 I. Konyshev , R. Pradip , O. Page , C. Ünlüer , R. T. Nasibullin , V. V. Rybkin , W. Pernice , S. Ferrari

Many optimally scaling quantum simulation algorithms employ controlled time evolution of the Hamiltonian, which is typically the major bottleneck for their efficient implementation. This work establishes a compression protocol for encoding…

Quantum Physics · Physics 2026-04-09 Erenay Karacan

This paper introduces a practical and accurate calibration method for camera spectral sensitivity using a diffraction grating. Accurate calibration of camera spectral sensitivity is crucial for various computer vision tasks, including color…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Lilika Makabe , Hiroaki Santo , Fumio Okura , Michael S. Brown , Yasuyuki Matsushita

Background: When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If…

Methodology · Statistics 2020-04-07 Deukwoo Kwon , Isildinha M. Reis

The requirement of uncertainty quantification for anomaly detection systems has become increasingly important. In this context, effectively controlling Type I error rates ($\alpha$) without compromising the statistical power ($1-\beta$) of…

Machine Learning · Statistics 2025-02-21 Oliver Hennhöfer , Christine Preisach

We present a convolution-based data assimilation method tailored to neuronal electrophysiology, addressing the limitations of traditional value-based synchronization approaches. While conventional methods rely on nudging terms and pointwise…

Neurons and Cognition · Quantitative Biology 2025-06-16 Dawei Li , Henry D. I. Abarbanel

The alignment of biological sequences such as DNA, RNA, and proteins, is one of the basic tools that allow to detect evolutionary patterns, as well as functional/structural characterizations between homologous sequences in different…

Quantitative Methods · Quantitative Biology 2023-05-01 Louise Budzynski , Andrea Pagnani
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