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Algorithms based on the particle flow approach are becoming increasingly utilized in collider experiments due to their superior jet energy and missing energy resolution compared to the traditional calorimeter-based measurements. Such…

High Energy Physics - Experiment · Physics 2015-03-20 Andrey Elagin , Pavel Murat , Alexandre Pranko , Alexei Safonov

The physics programs of current and future collider experiments necessitate the development of surrogate simulators for calorimeter showers. While much progress has been made in the development of generative models for this task, they have…

High Energy Physics - Experiment · Physics 2025-11-24 Thorsten Buss , Henry Day-Hall , Frank Gaede , Gregor Kasieczka , Katja Krüger , Anatolii Korol , Thomas Madlener , Peter McKeown

In particle physics, homogeneous calorimeters are used to measure the energy of particles as they interact with the detector material. Although not as precise as trackers or muon detectors, these calorimeters provide valuable insights into…

Chromatic calorimetry (CCAL) analyses particle detection by utilizing scintillators with distinct emission wavelengths to measure the longitudinal energy deposition of particle showers in high-energy physics, improving particle…

High Energy Physics - Experiment · Physics 2025-09-12 Devanshi Arora

The CALICE collaboration has constructed highly granular electromagnetic and hadronic calorimeter prototypes to evaluate technologies for the use in detector systems at a future Linear Collider. The hadron calorimeter uses small…

Instrumentation and Detectors · Physics 2019-08-13 Katja Seidel

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles.…

The CALICE collaboration is developing highly granular calorimeters for experiments at a future lepton collider primarily to establish technologies for particle flow event reconstruction. These technologies also find applications elsewhere,…

Instrumentation and Detectors · Physics 2017-06-28 Yong Liu

The CALICE collaboration has constructed a highly granular hadronic sampling calorimeter prototype with small scintillator tiles individually read out by silicon photomultipliers (SiPM) to evaluate technologies for the ILC. The imaging…

Instrumentation and Detectors · Physics 2019-08-13 Shaojun Lu

In the previous work carried out in the scope of the \emph{Validation of Aerothermochemistry Models for Re-Entry Applications}, it was verified that the G\"{o}k\c{c}en chemical dataset provided increasingly diverging results from…

Chemical Physics · Physics 2022-12-21 Mário Lino da Silva , João Vargas

The Particle Flow Analysis (PFA) is currently under intense studies as the most promising way to achieve precision jet energy measurements required at the future linear $e^+e^-$ collider. In order to optimize detector configurations and to…

Computational Physics · Physics 2015-05-13 Sumie Yamamoto , Keisuke Fujii , Akiya Miyamoto

Discovering heterogeneous catalysts tailored for specific reaction intermediates remains a fundamental bottleneck in materials science. While traditional trial-and-error methods and recent generative models have shown promise, they struggle…

Materials Science · Physics 2026-05-19 Minkyu Kim , Nayoung Kim , Honghui Kim , Sungsoo Ahn

In this paper, we study the problem of jointly estimating the optical flow and scene flow from synchronized 2D and 3D data. Previous methods either employ a complex pipeline that splits the joint task into independent stages, or fuse 2D and…

Computer Vision and Pattern Recognition · Computer Science 2022-04-13 Haisong Liu , Tao Lu , Yihui Xu , Jia Liu , Wenjie Li , Lijun Chen

Diffusion models have achieved remarkable success across various domains. However, their slow generation speed remains a critical challenge. Existing acceleration methods, while aiming to reduce steps, often compromise sample quality,…

Machine Learning · Computer Science 2025-03-26 Huiyang Shao , Xin Xia , Yuhong Yang , Yuxi Ren , Xing Wang , Xuefeng Xiao

In this paper, we propose an efficient, fast, and versatile distillation method to accelerate the generation of pre-trained diffusion models: Flash Diffusion. The method reaches state-of-the-art performances in terms of FID and CLIP-Score…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Clément Chadebec , Onur Tasar , Eyal Benaroche , Benjamin Aubin

The highly granular calorimeter prototypes of the CALICE collaboration have provided large data samples with precise three-dimensional information on hadronic showers with steel and tungsten absorbers and silicon, scintillator and gas…

Instrumentation and Detectors · Physics 2019-08-13 Naomi van der Kolk

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of…

High Energy Physics - Experiment · Physics 2024-11-25 ATLAS Collaboration

The energy calibration of calorimeters at collider experiments, such as the ones at the CERN Large Hadron Collider, is crucial for achieving the experiments physics objectives. Standard calibration approaches have limitations that become…

The next generation of collider detectors will make full use of Particle Flow Algorithms, requiring high-precision tracking and full imaging calorimeters. The latter, thanks to granularity improvements by two to three orders of magnitude…

Instrumentation and Detectors · Physics 2022-11-15 Roman Pöschl

This talk reviews the development of imaging calorimeters for the purpose of applying Particle Flow Algorithms (PFAs) to the measurement of hadronic jets at a future lepton collider. After a short introduction, the current status of PFA…

Instrumentation and Detectors · Physics 2011-10-11 Jose Repond

Recent advances in generative neural networks, particularly flow matching (FM), have enabled the generation of high-fidelity samples while significantly reducing computational costs. A promising application of these models is accelerating…

Machine Learning · Computer Science 2025-07-28 Maksymilian Wojnar