REVIEW 10 cited by
AtlFast3: the next generation of fast simulation in ATLAS
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
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 simulated Monte Carlo events. Detector simulation with \textsc{Geant4} is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation -- the calorimeter shower simulation -- with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
Forward citations
Cited by 10 Pith papers
-
Learning Standard Model structure from LHC data with Riemannian flow matching
ShellFlow, a Riemannian flow-matching transformer fed only on-shell and invariant-mass priors and ~8×10^8 recorded ATLAS events, reproduces the SM's dilepton resonances, Weinberg angle, and top/W mass peaks in a singl...
-
Search for new scalars via $X \rightarrow SH \rightarrow b\bar{b}b\bar{b}$ in proton-proton collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector
No excess over background is found in ATLAS's first search for X→SH→4b, which sets 95% CL upper limits of 0.7 fb–2.6 pb on the production cross-section times branching ratio.
-
CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters
Presents CaloTrilogy, a unified one-step generative model for high-granularity calorimeter showers that combines velocity field integration, learned priors, and physics losses to match SOTA quality.
-
A universal vision transformer for fast calorimeter simulations
A vision-transformer flow-matching model generates calorimeter showers across regular and irregular detector geometries at millisecond speeds, and pretraining plus fine-tuning cuts training cost by about half.
-
GPT-like transformer model for silicon tracking detector simulation
A decoder-only transformer trained on tokenized Geant4 hit sequences generates silicon tracker hits that reconstruct to near-Geant4-quality tracks for single muons.
-
Measurement of the Higgs boson decay to a low-mass dilepton system and a photon in $pp$ collisions at $\sqrt{s} =$ 13 and 13.6 TeV with the ATLAS detector
Combined Run-2+Run-3 ATLAS measurement of H to ell ell gamma (m_ll < 30 GeV) gives mu = 1.03 (+0.35/-0.32) with 3.4 sigma observed (3.3 sigma expected) significance, consistent with the Standard Model.
-
Study of $t\bar{t}H$ and $tH$ production in the $H\to\tau\tau$ channel in $pp$ collisions at $\sqrt{s}=13$ TeV and 13.6 TeV with the ATLAS detector
Simultaneous measurement of ttH (mu=1.51) and tH (mu=-0.4) in fully hadronic H→tau tau final states at 13/13.6 TeV, consistent with the Standard Model.
-
Improved analysis of non-resonant Higgs boson pair production in the $b\bar{b}\tau^+\tau^-$ final state with $196$ fb$^{-1}$ of data collected at $\sqrt{s}$ = 13 TeV and 13.6 TeV with the ATLAS detector
ATLAS finds μ_HH = 2.6^{+1.4}_{-1.0} in bbττ with Run 2+3 data, 2.6σ over background-only, and first 3.5σ evidence for ZH in this final state.
-
Search for the Higgs boson decay to a $Z$ boson and a photon in $pp$ collisions at $\sqrt{s}=13$ TeV and $13.6$ TeV with the ATLAS detector
ATLAS measures the Higgs to Z and photon signal yield as 1.3 +0.6 -0.5 times the Standard Model prediction in the combined 305 inverse femtobarn dataset, with 2.5 sigma observed significance.
-
Machine Learning for Complex Instrument Design and Optimization
A review chapter summarizing machine-learning pipelines for complex instrument operations and design, with no new experimental or theoretical contribution.
Discussion (0). Continue with ORCID to comment.