Diboson Physics at the Tevatron

At the Fermilab Tevatron, the CDF and D0 detectors are being used to study diboson production in $p\bar{p}$ collisions at $\sqrt{s}=1.96$ TeV. We summarize recent measurements of the W$\gamma$, Z$\gamma$, and WW cross-sections and limits on WZ and ZZ production. Limits on anomalous trilinear gauge couplings are also presented.Comment: 4 pages, Talk presented at the XLIrst Rencontres de Moriond - QCD and High Energy Hadronic Interactions, La Thuile, Italy, 18-25 March 200

Search for the Standard Model Higgs Boson in the Lepton + Missing Transverse Energy + Jets Final State in ATLAS

A search for the Standard Model Higgs boson has been performed in the H \rightarrow WW \rightarrow l{\nu}jj channel in 1.04 fb-1 of pp collisions at \surds = 7 TeV collected with the ATLAS detector at the Large Hadron Collider. No significant excess of events is observed over the expected background and limits on the Higgs boson production cross section are derived for a Higgs boson mass in the range 240 GeV < mH < 600 GeV. The best sensitivity is reached for mH = 400 GeV, where the 95% confidence level upper bound on the cross-section for Higgs boson production times the branching ratio for H \rightarrow W W is 3.1 pb, or 2.7 times the Standard Model prediction.Comment: 6 pages, 3 figures. Proceedings of the DPF-2011 Conference, Providence, RI, August 8-13, 201

A Fast Hardware Tracker for the ATLAS Trigger System

In hadron collider experiments, triggering the detector to store interesting events for offline analysis is a challenge due to the high rates and multiplicities of particles produced. Maintaining high trigger efficiency for the physics we are most interested in while at the same time suppressing high rate physics from inclusive QCD processes is a difficult but important problem. It is essential that the trigger system be flexible and robust, with sufficient redundancy and operating margin. Providing high quality track reconstruction over the full ATLAS detector by the start of processing at LVL2 is an important element to achieve these needs. As the instantaneous luminosity increases, the computational load on the LVL2 system will significantly increase due to the need for more sophisticated algorithms to suppress backgrounds. The Fast Tracker (FTK) is a proposed upgrade to the ATLAS trigger system. It is designed to enable early rejection of background events and thus leave more LVL2 execution time by moving track reconstruction into a hardware system that takes massively parallel processing to the extreme. The FTK system completes global track reconstruction with near offline resolution shortly after the start of LVL2 processing by rapidly finding and fitting tracks in the inner detector for events passing LVL1 using pattern recognition from a large, pre-computed bank of possible hit patterns. We describe the FTK system design and expected performance in the areas of b-tagging, {\tau}-tagging, and lepton isolation which play and important role in the ATLAS physics program

A Detailed Study of Interpretability of Deep Neural Network based Top Taggers

Recent developments in the methods of explainable AI (xAI) methods allow us to explore the inner workings of deep neural networks (DNNs), revealing crucial information about input-output relationships and realizing how data connects with machine learning models. In this paper we explore interpretability of DNN models designed for identifying jets coming from top quark decay in the high energy proton-proton collisions at the Large Hadron Collider (LHC). We review a subset of existing such top tagger models and explore different quantitative methods to identify which features play the most important roles in identifying the top jets. We also investigate how and why feature importance varies across different xAI metrics, how feature correlations impact their explainability, and how latent space representations encode information as well as correlate with physically meaningful quantities. Our studies uncover some major pitfalls of existing xAI methods and illustrate how they can be overcome to obtain consistent and meaningful interpretation of these models. We additionally illustrate the activity of hidden layers as Neural Activation Pattern (NAP) diagrams and demonstrate how they can be used to understand how DNNs relay information across the layers and how this understanding can help us to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. While the primary focus of this work remains a detailed study of interpretability of DNN-based top tagger models, it also features state-of-the art performance obtained from modified implementation of existing networks.Comment: Repository: https://github.com/FAIR4HEP/xAI4toptagge

Software Citation in HEP: Current State and Recommendations for the Future

In November 2022, the HEP Software Foundation (HSF) and the Institute for Research and Innovation for Software in High-Energy Physics (IRIS-HEP) organized a workshop on the topic of Software Citation and Recognition in HEP. The goal of the workshop was to bring together different types of stakeholders whose roles relate to software citation and the associated credit it provides in order to engage the community in a discussion on: the ways HEP experiments handle citation of software, recognition for software efforts that enable physics results disseminated to the public, and how the scholarly publishing ecosystem supports these activities. Reports were given from the publication board leadership of the ATLAS, CMS, and LHCb experiments and HEP open source software community organizations (ROOT, Scikit-HEP, MCnet), and perspectives were given from publishers (Elsevier, JOSS) and related tool providers (INSPIRE, Zenodo). This paper summarizes key findings and recommendations from the workshop as presented at the 26th International Conference on Computing In High Energy and Nuclear Physics (CHEP 2023).Comment: 7 pages, 2 listings. Contribution to the Proceedings of the 26th International Conference on Computing In High Energy and Nuclear Physics (CHEP 2023

Towards Real-World Applications of ServiceX, an Analysis Data Transformation System

One of the biggest challenges in the High-Luminosity LHC (HL- LHC) era will be the significantly increased data size to be recorded and analyzed from the collisions at the ATLAS and CMS experiments. ServiceX is a software R&D project in the area of Data Organization, Management and Access of the IRIS- HEP to investigate new computational models for the HL- LHC era. ServiceX is an experiment-agnostic service to enable on-demand data delivery specifically tailored for nearly-interactive vectorized analyses. It is capable of retrieving data from grid sites, on-the-fly data transformation, and delivering user-selected data in a variety of different formats. New features will be presented that make the service ready for public use. An ongoing effort to integrate ServiceX with a popular statistical analysis framework in ATLAS will be described with an emphasis of a practical implementation of ServiceX into the physics analysis pipeline.Comment: 8 pages, 3 figures, 2 listings, 1 table, submitted to the 25th International Conference on Computing in High Energy & Nuclear Physic

Selective inhibition of FLT3 by gilteritinib in relapsed or refractory acute myeloid leukaemia: a multicentre, first-in-human, open-label, phase 1-2 study.

BackgroundInternal tandem duplication mutations in FLT3 are common in acute myeloid leukaemia and are associated with rapid relapse and short overall survival. The clinical benefit of FLT3 inhibitors in patients with acute myeloid leukaemia has been limited by rapid generation of resistance mutations, particularly in codon Asp835 (D835). We aimed to assess the highly selective oral FLT3 inhibitor gilteritinib in patients with relapsed or refractory acute myeloid leukaemia.MethodsIn this phase 1-2 trial, we enrolled patients aged 18 years or older with acute myeloid leukaemia who either were refractory to induction therapy or had relapsed after achieving remission with previous treatment. Patients were enrolled into one of seven dose-escalation or dose-expansion cohorts assigned to receive once-daily doses of oral gilteritinib (20 mg, 40 mg, 80 mg, 120 mg, 200 mg, 300 mg, or 450 mg). Cohort expansion was based on safety and tolerability, FLT3 inhibition in correlative assays, and antileukaemic activity. Although the presence of an FLT3 mutation was not an inclusion criterion, we required ten or more patients with locally confirmed FLT3 mutations (FLT3mut+) to be enrolled in expansion cohorts at each dose level. On the basis of emerging findings, we further expanded the 120 mg and 200 mg dose cohorts to include FLT3mut+ patients only. The primary endpoints were the safety, tolerability, and pharmacokinetics of gilteritinib. Safety and tolerability were assessed in the safety analysis set (all patients who received at least one dose of gilteritinib). Responses were assessed in the full analysis set (all patients who received at least one dose of study drug and who had at least one datapoint post-treatment). Pharmacokinetics were assessed in a subset of the safety analysis set for which sufficient data for concentrations of gilteritinib in plasma were available to enable derivation of one or more pharmacokinetic variables. This study is registered with ClinicalTrials.gov, number NCT02014558, and is ongoing.FindingsBetween Oct 15, 2013, and Aug 27, 2015, 252 adults with relapsed or refractory acute myeloid leukaemia received oral gilteritinib once daily in one of seven dose-escalation (n=23) or dose-expansion (n=229) cohorts. Gilteritinib was well tolerated; the maximum tolerated dose was established as 300 mg/day when two of three patients enrolled in the 450 mg dose-escalation cohort had two dose-limiting toxicities (grade 3 diarrhoea and grade 3 elevated aspartate aminotransferase). The most common grade 3-4 adverse events irrespective of relation to treatment were febrile neutropenia (97 [39%] of 252), anaemia (61 [24%]), thrombocytopenia (33 [13%]), sepsis (28 [11%]), and pneumonia (27 [11%]). Commonly reported treatment-related adverse events were diarrhoea (92 [37%] of 252]), anaemia (86 [34%]), fatigue (83 [33%]), elevated aspartate aminotransferase (65 [26%]), and increased alanine aminotransferase (47 [19%]). Serious adverse events occurring in 5% or more of patients were febrile neutropenia (98 [39%] of 252; five related to treatment), progressive disease (43 [17%]), sepsis (36 [14%]; two related to treatment), pneumonia (27 [11%]), acute renal failure (25 [10%]; five related to treatment), pyrexia (21 [8%]; three related to treatment), bacteraemia (14 [6%]; one related to treatment), and respiratory failure (14 [6%]). 95 people died in the safety analysis set, of which seven deaths were judged possibly or probably related to treatment (pulmonary embolism [200 mg/day], respiratory failure [120 mg/day], haemoptysis [80 mg/day], intracranial haemorrhage [20 mg/day], ventricular fibrillation [120 mg/day], septic shock [80 mg/day], and neutropenia [120 mg/day]). An exposure-related increase in inhibition of FLT3 phosphorylation was noted with increasing concentrations in plasma of gilteritinib. In-vivo inhibition of FLT3 phosphorylation occurred at all dose levels. At least 90% of FLT3 phosphorylation inhibition was seen by day 8 in most patients receiving a daily dose of 80 mg or higher. 100 (40%) of 249 patients in the full analysis set achieved a response, with 19 (8%) achieving complete remission, ten (4%) complete remission with incomplete platelet recovery, 46 (18%) complete remission with incomplete haematological recovery, and 25 (10%) partial remission INTERPRETATION: Gilteritinib had a favourable safety profile and showed consistent FLT3 inhibition in patients with relapsed or refractory acute myeloid leukaemia. These findings confirm that FLT3 is a high-value target for treatment of relapsed or refractory acute myeloid leukaemia; based on activity data, gilteritinib at 120 mg/day is being tested in phase 3 trials.FundingAstellas Pharma, National Cancer Institute (Leukemia Specialized Program of Research Excellence grant), Associazione Italiana Ricerca sul Cancro

Low Latency Edge Classification GNN for Particle Trajectory Tracking on FPGAs

In-time particle trajectory reconstruction in the Large Hadron Collider is challenging due to the high collision rate and numerous particle hits. Using GNN (Graph Neural Network) on FPGA has enabled superior accuracy with flexible trajectory classification. However, existing GNN architectures have inefficient resource usage and insufficient parallelism for edge classification. This paper introduces a resource-efficient GNN architecture on FPGAs for low latency particle tracking. The modular architecture facilitates design scalability to support large graphs. Leveraging the geometric properties of hit detectors further reduces graph complexity and resource usage. Our results on Xilinx UltraScale+ VU9P demonstrate 1625x and 1574x performance improvement over CPU and GPU respectively