相关论文: PhyGHT: Physics-Guided HyperGraph Transformer for …

Efficient processing and feature extraction of largescale point clouds are important in related computer vision and cyber-physical systems. This work investigates point cloud resampling based on hypergraph signal processing (HGSP) to better…

Chapter 12 in High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary Design Report. The Large Hadron Collider (LHC) is one of the largest scientific instruments ever built. Since opening up a new energy frontier for exploration in…

Tensor decomposition is an effective tool for learning multi-way structures and heterogeneous features from high-dimensional data, such as the multi-view images and multichannel electroencephalography (EEG) signals, are often represented by…

High-quality surface normal can help improve geometry estimation in problems faced by autonomous vehicles, such as collision avoidance and occlusion inference. While a considerable volume of literature focuses on densely scanned indoor…

This document summarises proposed searches for new physics accessible in the heavy-ion mode at the CERN Large Hadron Collider (LHC), both through hadronic and ultraperipheral $\gamma\gamma$ interactions, and that have a competitive or,…

We discuss the physics opportunities and detector challenges at future hadron colliders. As guidelines for energies and luminosities we use the proposed luminosity and/or energy upgrade of the LHC (SLHC), and the Fermilab design of a Very…

Experimental insight into the elementary processes underlying charge transfer across interfaces has blossomed with the wide-spread availability of ultra-high vacuum set-ups that allow the preparation and characterization of solid surfaces…

The Large Hadron Collider (LHC) experiments ATLAS and CMS have established hybrid pixel detectors as the instrument of choice for particle tracking and vertexing in high rate and radiation environments, as they operate close to the LHC…

Run 1 at the LHC was very successful with the discovery of a new boson. The boson's properties are found to be compatible with those of the Standard Model Higgs boson. It is now revealing the mechanism of electroweak symmetry breaking and…

We introduce a Python package that provides simply and unified access to a collection of datasets from fundamental physics research - including particle physics, astroparticle physics, and hadron- and nuclear physics - for supervised…

Molecular property prediction is a critical task in computational drug discovery. While recent advances in Graph Neural Networks (GNNs) and Transformers have shown to be effective and promising, they face the following limitations:…

We present projections for the sensitivity of future high-energy colliders to new physics through precision measurements of the Standard Model (SM) interactions, focusing on near-term electron-positron facilities: FCC-ee, LEP3, and the…

Real-time particle transverse momentum ($p_T$) estimation in high-energy physics demands algorithms that are both efficient and accurate under strict hardware constraints. Static machine learning models degrade under high pileup and lack…

The determination of charged particle trajectories (tracking) in collisions at the CERN Large Hadron Collider (LHC) is one of the most important aspects for event reconstruction at hadron colliders. This is especially true in the high…

The hadron-hadron based Future Circular Collider (FCC-hh) is a project with the goal to collide proton-proton beams at a center of mass energy of sqrt(s)=100 TeV with a bunch crossing rate of 25 ns. Some of the major challenges that the…

Scene Graph Generation (SGG) unifies object localization and visual relationship reasoning by predicting boxes and subject-predicate-object triples. Yet most pipelines treat SGG as a one-shot, deterministic classification problem rather…

Generating realistic synthetic electronic health records (EHRs) holds tremendous promise for accelerating healthcare research, facilitating AI model development and enhancing patient privacy. However, existing generative methods typically…

A new concept, the Triplet Track Trigger (TTT), is proposed for stand-alone tracking at the first trigger level of the FCC-hh detector. The concept is based on a highly scalable monolithic pixel sensor technology and uses a very simple and…

Recently, deep learning-based computer-generated holography (CGH) has demonstrated tremendous potential in three-dimensional (3D) displays and yielded impressive display quality. However, most existing deep learning-based CGH techniques can…

We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN Large Hadron Collider (LHC). Collision events produced at the LHC and represented as…