Synergies between astroparticle, particle and nuclear physics

One overarching objective of science is to further our understanding of the universe, from its early stages to its current state and future evolution. This depends on gaining insight on the universe's most macroscopic components, for example galaxies and stars, as well as describing its smallest components, namely elementary particles and nuclei and their interactions. It is clear that this endeavour requires combined expertise from the fields of astroparticle physics, particle physics and nuclear physics. Pursuing common scientific drivers also require mastering challenges related to instrumentation (e.g. beams and detectors), data acquisition, selection and analysis, and making data and results available to the broader science communities. Joint work and recognition of these "foundational" topics will help all communities grow towards their individual and common scientific goals. The talk corresponding to this contribution has been presented during the special ECFA session of EPS-HEP 2019 focused on the update of the European Strategy of Particle Physics.Comment: Late submission to the Proceedings of the EPS-HEP 2019 Conference, Special ECFA session (https://indico.cern.ch/event/577856/sessions/291392

Dark Matter Science Project

A Dark Matter Science Project is being developed in the context of the ESCAPE (European Science Cluster of Astronomy and Particle physics ESFRI research infrastructure) project as a collaboration between scientists in European Research Infrastructures and experiments seeking to explain the nature of dark matter (such as HL-LHC, KM3NeT, CTA, DarkSide). The goal of this ESCAPE Science Project is to highlight the synergies between different dark matter communities and experiments, by producing new scientific results as well as by making the necessary data and software tools fully available. As part of this Science Project, we use experimental data and software algorithms from selected direct detection, indirect detection, and particle collider experiments involved in ESCAPE as prototypes for end-to-end analysis pipelines on a Virtual Research Environment that is being prepared as one of the building blocks of the European Open Science Cloud (EOSC). This contribution focuses on the implementation of the workflows on the Virtual Research Environment using ESCAPE tools (such as the Data Lake and REANA), and on the prospects for data management, data analysis and computing in the EOSC-Future project

Uncovering tau leptons-enriched semi-visible jets at the LHC

This Letter proposes a new signature for confining dark sectors at the Large Hadron Collider. Under the assumption of a QCD-like hidden sector, hadronic jets containing stable dark bound states could manifest in proton-proton collisions. We present a simplified model with a $Z'$ boson yielding the production of jets made up of dark bound states and subsequently leading to the decays of those that are unstable to $\tau$ leptons and Standard Model quarks. The resulting signature is characterised by non-isolated $\tau$ lepton pairs inside semi-visible jets. We estimate the constraints on our model from existing CMS and ATLAS analyses. We propose a set of variables that leverage the leptonic content of the jet and exploit them in a supervised jet tagger to enhance the signal-to-background separation. Furthermore, we discuss the performance and limitations of current triggers for accessing sub-TeV $Z'$ masses, as well as possible strategies that can be adopted by experiments to access such low mass regions. We estimate that with the currently available triggers, a high mass search can claim a $5 \sigma$ discovery (exclusion) of the $Z'$ boson with a mass up to 4.5TeV (5.5TeV) with the full Run2 data of the LHC when the fraction of unstable dark hadrons decaying to $\tau$ lepton pairs is around $50\%$, and with a coupling of the $Z'$ to right-handed up-type quarks of 0.25. Furthermore, we show that, with new trigger strategies for Run3, it may be possible to access $Z'$ masses down to 700 GeV, for which the event topology is still composed of two resolved semi-visible jets.Comment: 11 pages, 8 figures, 2 tables, (published on EPJ C as Letter

Baler -- Machine Learning Based Compression of Scientific Data

Storing and sharing increasingly large datasets is a challenge across scientific research and industry. In this paper, we document the development and applications of Baler - a Machine Learning based data compression tool for use across scientific disciplines and industry. Here, we present Baler's performance for the compression of High Energy Physics (HEP) data, as well as its application to Computational Fluid Dynamics (CFD) toy data as a proof-of-principle. We also present suggestions for cross-disciplinary guidelines to enable feasibility studies for machine learning based compression for scientific data.Comment: 10 pages and 6 figures, excluding appendi

Simplified Models for Dark Matter and Missing Energy Searches at the LHC

The study of collision events with missing energy as searches for the dark matter (DM) component of the Universe are an essential part of the extensive program looking for new physics at the LHC. Given the unknown nature of DM, the interpretation of such searches should be made broad and inclusive. This report reviews the usage of simplified models in the interpretation of missing energy searches. We begin with a brief discussion of the utility and limitation of the effective field theory approach to this problem. The bulk of the report is then devoted to several different simplified models and their signatures, including s-channel and t-channel processes. A common feature of simplified models for DM is the presence of additional particles that mediate the interactions between the Standard Model and the particle that makes up DM. We consider these in detail and emphasize the importance of their inclusion as final states in any coherent interpretation. We also review some of the experimental progress in the field, new signatures, and other aspects of the searches themselves. We conclude with comments and recommendations regarding the use of simplified models in Run-II of the LHC.Comment: v2. references added, version submitted to journal. v1. 47 pages, 13 plot

Baler - Machine Learning Based Compression of Scientific Data

A common and growing issue in scientific research and industry is that of storing and sharing ever-increasing datasets. In this paper we document the development and applications of Baler - a Machine Learning based tool for tailored compression of data across multiple disciplines

Recommendations of the LHC Dark Matter Working Group: Comparing LHC searches for heavy mediators of dark matter production in visible and invisible decay channels

Weakly-coupled TeV-scale particles may mediate the interactions between normal matter and dark matter. If so, the LHC would produce dark matter through these mediators, leading to the familiar "mono-X" search signatures, but the mediators would also produce signals without missing momentum via the same vertices involved in their production. This document from the LHC Dark Matter Working Group suggests how to compare searches for these two types of signals in case of vector and axial-vector mediators, based on a workshop that took place on September 19/20, 2016 and subsequent discussions. These suggestions include how to extend the spin-1 mediated simplified models already in widespread use to include lepton couplings. This document also provides analytic calculations of the relic density in the simplified models and reports an issue that arose when ATLAS and CMS first began to use preliminary numerical calculations of the dark matter relic density in these models.Comment: 19 pages, 4 figures; v2: author list and LaTeX problem fixe

Prognostic and predictive role of EGFR pathway alterations in biliary cancer patients treated with chemotherapy and anti-EGFR

The association of anti-EGFR to gemcitabine and oxaliplatin (GEMOX) chemotherapy did not improve survival in biliary tract carcinoma (BTC) patients. Multiple mechanisms might be involved in the resistance to anti-EGFR. Here, we explored the mutation profile of EGFR extracellular domain (ECD), of tyrosine kinase domain (TKD), and its amplification status. EGFR mutational status of exons 12, 18-21 was analyzed in 57 tumors by Sanger sequencing. EGFR amplification was evaluated in 37 tumors by Fluorescent In Situ Hybridization (FISH). Kaplan-Meier curves were calculated using the log-rank test. Six patients had mutations in exon 12 of EGFR ECD and 7 in EGFR TKD. Neither EGFR ECD nor TKD mutations affected progression free survival (PFS) or overall survival (OS) in the entire population. In the panitumumab plus GEMOX (P-GEMOX) arm, ECD mutated patients had a worse OS, while EGFR TKD mutated patients had a trend towards shorter PFS and OS. Overall, the presence of mutations in EGFR or in its transducers did not affect PFS or OS, while the extrahepatic cholangiocarcinoma (ECC) mutated patients had a worse prognosis compared to WT. Nineteen out of 37 tumors were EGFR amplified, but the amplification did not correlate with survival. ECC EGFR amplified patients had improved OS, whereas the amplification significantly correlated with poor PFS (p = 0.03) in gallbladder carcinoma patients. The high molecular heterogeneity is a predominant feature of BTC: the alterations found in this work seem to have a prognostic impact rather than a predictive role towards anti-EGFR therapy