Automatic Extraction of Figures from Scientific Publications in High-Energy Physics by Piotr Adam Praczyk, Javier Nogueras-Iso

“…Emphasis has been placed oncorrectly processing documents in High Energy Physics. The described approach makesdistinction between different classes of objects appearing in PDF documents and usesspatial clustering techniques to group objects into larger logical entities. …”
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Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics by Eyup B. Unlu, Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong, Roy T. Forestano, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva

“…In this work, we construct several variations of a quantum hybrid vision transformer for a classification problem in high-energy physics (distinguishing photons and electrons in the electromagnetic calorimeter). …”
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Tsallis Statistics in High Energy Physics: Chemical and Thermal Freeze-Outs by Jean Cleymans, Masimba Wellington Paradza

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Originality and competition in science : a study of the British high energy physics community/ by 404213 Gaston, Jerry

Research on streaming data acquisition framework for high energy physics tracking system by WU Ye, ZHANG Hongyu, ZHU Kejun, WANG Zhibin, CHEN Mali, QI Huirong

Subjects: “…high energy physics experiment…”
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Graph Variational Autoencoder for Detector Reconstruction and Fast Simulation in High-Energy Physics by Hariri Ali, Dyachkova Darya, Gleyzer Sergei

“…Accurate and fast simulation of particle physics processes is crucial for the high-energy physics community. Simulating particle interactions with the detector is both time consuming and computationally expensive. …”
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Classification without labels: learning from mixed samples in high energy physics by Eric M. Metodiev, Benjamin Nachman, Jesse Thaler

“…Journal of High Energy Physics…”
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Thunderstorm Ground Enhancements Measured on Aragats and Progress of High-Energy Physics in the Atmosphere by Ashot Chilingarian

“…High-energy physics in the atmosphere (HEPA) has undergone an intense reformation in the last decade. …”
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Bringing high energy physics to the classroom with HY.P.A.T.I.A. by Vourakis Stylianos

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Improved extrapolation methods of data-driven background estimations in high energy physics by Suyong Choi, Hayoung Oh

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PC-JeDi: Diffusion for particle cloud generation in high energy physics by Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant, John Andrew Raine, Knut Zoch, Tobias Golling

“…In this paper, we present a new method to efficiently generate jets in High Energy Physics called PC-JeDi. This method utilises score-based diffusion models in conjunction with transformers which are well suited to the task of generating jets as particle clouds due to their permutation equivariance. …”
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SYMBA: symbolic computation of squared amplitudes in high energy physics with machine learning by Abdulhakim Alnuqaydan, Sergei Gleyzer, Harrison Prosper

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Evolutionary algorithms for hyperparameter optimization in machine learning for application in high energy physics by Laurits Tani, Diana Rand, Christian Veelken, Mario Kadastik

“…Abstract The analysis of vast amounts of data constitutes a major challenge in modern high energy physics experiments. Machine learning (ML) methods, typically trained on simulated data, are often employed to facilitate this task. …”
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Powerful Raman Lidar systems for atmospheric analysis and high-energy physics experiments by Avdikos George

“…In this paper the author presents modern commercial Raman Lidar systems which can be applied to high-energy physics experiments. Raymetrics is a world-leader in laser remote (lidar) sensing applications. …”
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Classification without labels: learning from mixed samples in high energy physics by Nachman, Benjamin, Metodiev, Eric Mario, Thaler, Jesse

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Classification without labels: learning from mixed samples in high energy physics by Nachman, Benjamin, Metodiev, Eric Mario, Thaler, Jesse

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GPU coprocessors as a service for deep learning inference in high energy physics by Krupa, Jeffrey, Lin, Kelvin, Acosta Flechas, Maria, Dinsmore, Jack, Duarte, Javier, Harris, Philip, Hauck, Scott, Holzman, Burt, Hsu, Shih-Chieh, Klijnsma, Thomas, Liu, Mia, Pedro, Kevin, Rankin, Dylan, Suaysom, Natchanon, Trahms, Matt, Tran, Nhan

“…We present a comprehensive exploration of the use of GPU-based hardware acceleration for deep learning inference within the data reconstruction workflow of high energy physics. We present several realistic examples and discuss a strategy for the seamless integration of coprocessors so that the LHC can maintain, if not exceed, its current performance throughout its running.…”
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10 Gbps TCP/IP streams from the FPGA for High Energy Physics by Lavinia Darlea, Georgiana, Gomez-Ceballos, Guillelmo, Paus, Christoph M. E., Raginel, Olivier, Veverka, Jan, Bauer, Gerry P, Sumorok, Konstanty C

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MAXIMUM-LIKELIHOOD OR EXTENDED MAXIMUM-LIKELIHOOD - AN EXAMPLE FROM HIGH-ENERGY PHYSICS by Lyons, L, Allison, W, Comellas, J

In search of the rings: Approaches to Cherenkov ring finding and reconstruction in high energy physics by Wilkinson, G