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Unveiling Dark Forces with Measurements of the Large Scale Structure of the Universe
No full textCosmology offers opportunities to test dark matter independently of its interactions with the standard model. We study the imprints of long-range forces acting solely in the dark sector on the distribution of galaxies, the so-called large scale structure (LSS). We derive the strongest constraint on such forces from a combination of Planck and BOSS data. Along the way we consistently develop, for the first time, the effective field theory of LSS in the presence of new dynamics in the dark sector. We forecast that future surveys will improve the current bound by an order of magnitude
Iteration on the Higgs portal for vector dark matter and its effective field theory description
No full textWe reanalyze the effective field theory (EFT) approach for the scenario in which the particles that account for the dark matter (DM) in the universe are vector states that interact only through the Standard Model-like Higgs boson. These DM particles are searched for in direct and indirect detection in astrophysical experiments and in invisible Higgs decays at the LHC. The constraints obtained in these two search types are complementary and correlated. In recent years, it has been advocated that the EFT approach is problematic for small DM mass and that it does not capture all the aspects of vector DM; one should thus rather interpret the searches in ultraviolet complete theories that are more realistic. In this paper, we show that a more appropriate definition of the EFT with the introduction of an effective new physics scale parameter, can encompass such issues. We illustrate this by matching the EFT to two examples of ultraviolet completions for it: the U(1) model with a dark photon and a model that was recently adopted by the LHC experiments in which vectorlike fermions generate an effective interaction between the Higgs and the DM states at the one-loop level. Additionally, we find that the region of parameter space that is relevant for DM phenomenology is well inside the range of validity of the EFT. It thus provides a general parametrization of the effects of any ultraviolet model in the regime under exploration, making it the ideal framework for model-independent analyses of the vector DM Higgs-portal
Effective Field Theory descriptions of Higgs boson pair production
No full textHiggs boson pair production is traditionally considered to be of particular interest for a measurement of the trilinear Higgs self-coupling. Yet it can offer insights into other couplings as well, since - in an effective field theory (EFT) parameterisation of potential new physics - both the production cross section and kinematical properties of the Higgs boson pair depend on various other Wilson coefficients of EFT operators. This note summarises the ongoing efforts related to the development of EFT tools for Higgs boson pair production in gluon fusion, and provides recommendations for the use of distinct EFT parameterisations in the Higgs boson pair production process. This document also outlines where further efforts are needed and provides a detailed analysis of theoretical uncertainties. Additionally, benchmark scenarios are updated. We also re-derive a parameterisation of the next-to-leading order (NLO) QCD corrections in terms of the EFT Wilson coefficients both for the total cross section and the distribution in the invariant mass of the Higgs boson pair, providing for the first time also the covariance matrix. A reweighting procedure making use of the newly derived coefficients is validated, which can be used to significantly speed up experimental analyses
An improved limit on the neutrinoless double-electron capture of Ar with GERDA
No full textThe GERmanium Detector Array (Gerda) experiment operated enriched high-purity germanium detectors in a liquid argon cryostat, which contains 0.33% of Ar, a candidate isotope for the two-neutrino double-electron capture (2ECEC) and therefore for the neutrinoless double-electron capture (0ECEC). If detected, this process would give evidence of lepton number violation and the Majorana nature of neutrinos. In the radiative 0ECEC of Ar, a monochromatic photon is emitted with an energy of 429.88 keV, which may be detected by the Gerda germanium detectors. We searched for the Ar 0ECEC with Gerda data, with a total live time of 4.34 year (3.08 year accumulated during Gerda Phase II and 1.26 year during Gerda Phase I). No signal was found and a 90% CL lower limit on the half-life of this process was established T_{1/2} >1.5\cdot 10^{22} year
Hadronization mechanism (via heavy-flavor hadrons): Experiment
No full textThe formation of hadrons is a fundamental process in nature that can be investigated at particle colliders. Given their large mass, heavy quarks (charm and beauty) are produced only in initial hard-scatterings, prior to hadronisation, which determines instead the relative abundances and the kinematics of the various heavy-flavour hadron species. As several recent findings demonstrate, with \ee collisions as a "vacuum-like" reference at one extreme, and central AA as a dense, extended-size system characterised by flow and local equilibrium at the opposite extreme, different collision systems offer a lever arm that can be exploited to probe with a range of heavy-flavour hadron species the onset of various hadronisation processes. In these proceedings, a selection of the experimental results related to heavy-flavour hadronisation shown for the first time at the Hard Probes 2023 conference is presented together with some of the most important ones of the last years. The focus is on open-heavy flavour measurements. The comparison with model predictions and connections among the results in electron-positron, proton--proton, proton--nucleus, nucleus--nucleus collisions are discussed
Anomalous spin precession systematic effects in the search for a muon EDM using the frozen-spin technique
No full textAt the Paul Scherrer Institut (PSI), we are developing a high-precision apparatus with the aim of searching for the muon electric dipole moment (EDM) with unprecedented sensitivity. The underpinning principle of this experiment is the frozen-spin technique, a method that suppresses the spin precession due to the anomalous magnetic moment, thereby enhancing the signal-to-noise ratio for EDM signals. This increased sensitivity enables measurements that would be difficult to achieve with conventional muon storage rings. Given the availability of the muon beam at PSI, the anticipated statistical sensitivity for the EDM after a year of data collection is To achieve this goal, it is imperative to do a detailed analysis of any potential spurious effects that could mimic EDM signals. In this study, we present a quantitative methodology to evaluate the systematic effects that might arise in the context of the frozen-spin technique utilised within a compact storage ring. Our approach involves the analytical derivation of equations governing the motion of the muon spin in the electromagnetic (EM) fields intrinsic to the experimental setup, validated through numerical simulations. We also illustrate a method to calculate the cumulative geometric (Berry's) phase. This work complements ongoing experimental efforts to detect a muon EDM at PSI and contributes to a broader understanding of spin-precession systematic effects
Measurement of the transverse single-spin asymmetry for forward neutron production in a wide <math display="inline"><mrow><msub><mrow><mi>p</mi></mrow><mrow><mi mathvariant="normal">T</mi></mrow></msub></mrow></math> range in polarized <math display="inline"><mi>p</mi><mo>+</mo><mi>p</mi></math> collisions at <math display="inline"><mrow><msqrt><mrow><mi>s</mi></mrow></msqrt><mo>=</mo><mn>510</mn><mtext> </mtext><mtext> </mtext><mi>GeV</mi></mrow></math>
No full textTransverse single-spin asymmetries AN of forward neutrons at pseudorapidities larger than 6 had only been studied in the transverse momentum range of pT<0.4 GeV/c. The RHICf Collaboration has extended the previous measurements up to 1.0 GeV/c in polarized p+p collisions at s=510 GeV, using an electromagnetic calorimeter installed in the zero-degree area of the STAR detector at the Relativistic Heavy Ion Collider. The resulting AN values increase in magnitude with pT in the high longitudinal momentum fraction xF range, but they reach a plateau at lower pT for lower xF values. For low transverse momenta, the AN's show little xF dependence and level off from intermediate values. For higher transverse momenta, the AN's also show a tendency to reach a plateau at increased magnitudes. The results are consistent with previous measurements at lower collision energies, suggesting no s dependence of the neutron asymmetries. A theoretical model based on the interference of π and a1 exchange between two protons could partially reproduce the current results; however, an additional mechanism is necessary to describe the neutron AN's over the whole kinematic region measured
Femtoscopic correlations of identical charged pions and kaons in <math><mrow><mi>p</mi><mi>p</mi></mrow></math> collisions at <math><mrow><msqrt><mi>s</mi></msqrt><mo>=</mo><mn>13</mn></mrow></math> TeV with event-shape selection
No full textCollective behavior has been observed in high-energy heavy-ion collisions for several decades. Collectivity is driven by the high particle multiplicities that are produced in these collisions. At the CERN Large Hadron Collider (LHC), features of collectivity have also been seen in high-multiplicity proton-proton collisions that can attain particle multiplicities comparable to peripheral Pb-Pb collisions. One of the possible signatures of collective behavior is the decrease of femtoscopic radii extracted from pion and kaon pairs emitted from high-multiplicity collisions with increasing pair transverse momentum. This decrease can be described in terms of an approximate transverse mass scaling. In the present work, femtoscopic analyses are carried out by the ALICE Collaboration on charged pion and kaon pairs produced in pp collisions at s=13TeV from the LHC to study possible collectivity in pp collisions. The event-shape analysis method based on transverse sphericity is used to select for spherical versus jetlike events, and the effects of this selection on the femtoscopic radii for both charged pion and kaon pairs are studied. This is the first time this selection method has been applied to charged kaon pairs. An approximate transverse-mass scaling of the radii is found in all multiplicity ranges studied when the difference in the Lorentz boost for pions and kaons is taken into account. This observation does not support the hypothesis of collective expansion of hot and dense matter that should only occur in high-multiplicity events. A possible alternate explanation of the present results is based on a scenario of common emission conditions for pions and kaons in pp collisions for the multiplicity ranges studied
Il diritto di ripubblicazione da PlanS ai giorni nostri: memorie e pensieri sparsi
Get PDF<p>Presentazione IX convegno AISA Pisa 2024</p>
AI Platform for INFN Scientific Use Cases
Get PDF<p>Talk given at the International Symposium on Grids & Clouds (ISGC), Taipei 24-29/03/2024</p>\n\n<p><strong>Abstract</strong></p>\n\n<p>Researchers at INFN (National Institute for Nuclear Physics) face challenges from basic to hard science<br>\nuse cases (e.g., big-data latest generation experiments) in many areas: HEP (High Energy Physics),<br>\nAstrophysics, Quantum Computing, Genomics, etc.<br>\nMachine Learning (ML) adoption is ubiquitous in these areas, requiring researchers to solve problems<br>\nrelated to the specificity of applications (e.g., tailored models and intricate domain knowledge), but also<br>\nrequiring solving general infrastructure-level and ML-workflow related problems.<br>\nAs the demand for ML solutions continues to rise across the diverse research domains, there exists a<br>\ncritical need for an innovative approach to accelerate ML adoption.<br>\nIn this regard we propose an AI platform designed as an application-agnostic MLaaS (Machine Learning<br>\nas a Service) solution, which provides a paradigm shift by offering a flexible and generalized<br>\ninfrastructure that decouples the ML development process from specific use cases.<br>\nThe AI platform is implemented as a software layer on top of our cloud platform, the INFN Cloud, which<br>\noffers composable, scalable, and open-source solutions on a dedicated geographically distributed<br>\ninfrastructure. The INFN Cloud core mission is to facilitate resource sharing and enhance accessibility for<br>\nINFN users, encompassing a wide range of resources, including GPUs and storage.<br>\nThe AI platform leverages INFN Cloud resources and principles, gathering and orchestrating technologies<br>\nto support end-to-end scalable ML solutions: Kubernetes, Kubeflow, KServe, KNative, Kueue, Horovod,<br>\netc., ensuring support for many ML frameworks: TensorFlow, PyTorch, Apache MXNet, XGBoost, etc.<br>\nThis contribution will describe the platform’s design and principles, as well as some selected use cases<br>\nfrom NLP and HEP domains that benefitted from the “aaS” approach.<br>\nThe platform's agnostic nature extends beyond model compatibility to address the practical challenges<br>\nassociated with deploying ML solutions in real hard science scenarios: streaming services, exabyte-scale<br>\nstorage solutions, high-bandwidth networking, support for native HEP data (e.g., CERN ROOT data<br>\nformat), etc.<br>\nFurthermore, the AI platform promotes transfer learning and model reuse, to accelerate the ML<br>\ndevelopment lifecycle. Developers can leverage pre-trained models and share knowledge across<br>\ndifferent applications, reducing the time and resources required for training new models from scratch.<br>\nThis collaborative aspect not only enhances efficiency but also promotes a collective learning<br>\nenvironment within the research community.<br>\nIn conclusion, the application-agnostic AI platform serves as a unified ecosystem where developers, data<br>\nscientists, and domain experts can collaborate seamlessly. By providing a standardized framework for<br>\nML model development, training, and deployment, the platform eliminates the need for extensive<br>\ndomain expertise in every application area. This democratization of ML empowers a broader audience<br>\nto leverage the benefits of machine learning, breaking down barriers and fostering innovation across<br>\ndiverse research domains.</p>