HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers

Many graph representation learning (GRL) problems are dynamic, with millions of edges added or removed per second. A fundamental workload in this setting is dynamic link prediction: using a history of graph updates to predict whether a given pair of vertices will become connected. Recent schemes for link prediction in such dynamic settings employ Transformers, modeling individual graph updates as single tokens. In this work, we propose HOT: a model that enhances this line of works by harnessing higher-order (HO) graph structures; specifically, k-hop neighbors and more general subgraphs containing a given pair of vertices. Harnessing such HO structures by encoding them into the attention matrix of the underlying Transformer results in higher accuracy of link prediction outcomes, but at the expense of increased memory pressure. To alleviate this, we resort to a recent class of schemes that impose hierarchy on the attention matrix, significantly reducing memory footprint. The final design offers a sweetspot between high accuracy and low memory utilization. HOT outperforms other dynamic GRL schemes, for example achieving 9%, 7%, and 15% higher accuracy than - respectively - DyGFormer, TGN, and GraphMixer, for the MOOC dataset. Our design can be seamlessly extended towards other dynamic GRL workloads

TOTEM Physics program, analysis and results

The seminar will focus on the physics programme of the TOTEM experiment at the LHC. The published results will be quickly reviewed. The current analyses of the data taken in the joint TOTEM-CMS runs will be discussed, including forward multiplicities, jets physics, soft diffractive processes, and related cross-sections. Progress in the study of low-t elastic scattering will be presented

Reconstruction of protons in the TOTEM Roman Pot detectors at the LHC

The TOTEM experiment at the LHC will measure the total proton-proton cross-section with precision of 1%, elastic proton scattering over a wide range in momentum transfer and diffractive dissociation, including single, double and central diffraction topologies. This dissertation reports on the tracking performance of the Roman Pots in view of the physics programme of TOTEM.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

LHC Optics Measurement with Proton Tracks Detected by the Roman Pots of the TOTEM Experiment

Precise knowledge of the beam optics at the LHC is crucial to fulfill the physics goals of the TOTEM experiment, where the kinematics of the scattered protons is reconstructed with the near-beam telescopes – so-called Roman Pots (RP). Before being detected, the protons’ trajectories are influenced by the magnetic fields of the accelerator lattice. Thus precise understanding of the proton transport is of key importance for the experiment. A novel method of optics evaluation is proposed which exploits kinematical distributions of elastically scattered protons observed in the RPs. Theoretical predictions, as well as Monte Carlo studies, show that the residual uncertainty of the optics estimation method is smaller than 2.5 permille

Kinematic Analysis Towards Glueballs

In the present work a consistent kinematic-based framework for glueball states is proposed. It relates the glueball, the Pomeron, QCD lattice calculations, the $0^{++}$ scalar states $f_0(1710)$ and $\chi_{c0}(1P)$, the $2^{++}$ states $f_J(2220)$ and $\chi_{c2}(2P)$, the baryonic charmed state $\Xi_c^+(2645)$ and color transparency

Graph of Thoughts: Solving Elaborate Problems with Large Language Models

ISSN:2159-5399ISSN:2374-346