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The Lagrangian in eq. (2.1) of JHEP 11 (2020) 005 has an erroneous factor of 1/2. The analysis code used for the results reported in the paper does not have this factor. The results remain unchanged.
In the original HTML version of this article, one affiliation of the author V. O. Tikhomirov was missing. He is affiliated to the following two affiliations: P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia and National Research Nuclear University MEPhI, Moscow, Russia. The original article has been corrected.
A search for new phenomena has been performed in final states with at least one isolated high-momentum photon, jets and missing transverse momentum in proton– proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. The data, collected by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 fb –1 . The experimental results are interpreted in a supersymmetric model in which pair-produced gluinos decay into neutralinos, which in turn decay into a gravitino, at least one photon, and jets. No significant deviations from the predictions of the Standard Model are observed. Upper limits are set on the visible cross section due to physics beyond the Standard Model, and lower limits are set on the masses of the gluinos and neutralinos, all at 95% confidence level. Visible cross sections greater than 0.022 fb are excluded and pair-produced gluinos with masses up to 2200 GeV are excluded for most of the NLSP masses investigated.
A search for phenomena beyond the standard model in final states with two oppositely charged same-flavor leptons and missing transverse momentum is presented. The search uses a data sample of proton-proton collisions at $ \sqrt{s} $ = 13 TeV, corresponding to an integrated luminosity of 137 fb$^{−1}$, collected by the CMS experiment at the LHC. Three potential signatures of physics beyond the standard model are explored: an excess of events with a lepton pair, whose invariant mass is consistent with the Z boson mass; a kinematic edge in the invariant mass distribution of the lepton pair; and the nonresonant production of two leptons. The observed event yields are consistent with those expected from standard model backgrounds. The results of the first search allow the exclusion of gluino masses up to 1870 GeV, as well as chargino (neutralino) masses up to 750 (800) GeV, while those of the searches for the other two signatures allow the exclusion of light-flavor (bottom) squark masses up to 1800 (1600) GeV and slepton masses up to 700 GeV, respectively, at 95% confidence level within certain supersymmetry scenarios.[graphic not available: see fulltext]
From the near-Earth solar wind to the intracluster medium of galaxy clusters, collisionless, high-beta, magnetized plasmas pervade our universe. Energy and momentum transport from large-scale fields and flows to small-scale motions of plasma particles is ubiquitous in these systems, but a full picture of the underlying physical mechanisms remains elusive. The transfer is often mediated by a turbulent cascade of Alfvénic fluctuations as well as a variety of kinetic instabilities; these processes tend to be multi-scale and/or multi-dimensional, which makes them difficult to study using spacecraft missions and numerical simulations alone. Meanwhile, existing laboratory devices struggle to produce the collisionless, high ion beta (β i ≳ 1), magnetized plasmas across the range of scales necessary to address these problems. As envisioned in recent community planning documents, it is therefore important to build a next generation laboratory facility to create a β i ≳ 1, collisionless, magnetized plasma in the laboratory for the first time. A working group has been formed and is actively defining the necessary technical requirements to move the facility towards a construction-ready state. Recent progress includes the development of target parameters and diagnostic requirements as well as the identification of a need for source-target device geometry. As the working group is already leading to new synergies across the community, we anticipate a broad community of users funded by a variety of federal agencies (including National Aeronautics and Space Administration, Department of Energy and National Science Foundation) to make copious use of the future facility.
This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.
A search for new phenomena giving rise to pairs of opposite electrically charged muons with impact parameters in the millimetre range is presented, using 139 fb -1 of $\sqrt{s}$ = 13 TeV pp collision data from the ATLAS detector at the LHC. The search targets the gap in coverage between existing searches targeting final states with leptons with large displacement and prompt leptons. No significant excess over the background expectation is observed and exclusion limits are set on the mass of long-lived scalar supersymmetric muon-partners (smuons) with much lower lifetimes than previously targeted by displaced muon searches. Smuon lifetimes down to 1 ps are excluded for a smuon mass of 100 GeV, and smuon masses up to 520 GeV are excluded for a proper lifetime of 10 ps, at 95% confidence level. Finally, model-independent limits are set on the contribution from new phenomena to the signal-region yields.
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We present the analysis techniques developed to explore the keV-scale energy region of the Cryogenic Underground Observatory for Rare Events (CUORE) experiment, based on more than 2 metric ton yr of data collected over five years. By prioritizing a stricter selection over a larger exposure, we are able to optimize data selection for thresholds at 10 keV and 3 keV with 691 kg yr and 11 kg yr of data, respectively. We study how the performance varies among the 988-detector array with different detector characteristics and data-taking conditions. We achieve an average baseline resolution of 2.54 ±0.14 keV FWHM and 1.18 ±0.02 keV FWHM for the data selection at 10 keV and 3 keV, respectively. The analysis methods employed reduce the overall background by about an order of magnitude, reaching 2.06±0.05 counts/(keV kg days) and 16±2 counts/(keV kg days) at the thresholds of 10 keV and 3 keV. We evaluate for the first time the near-threshold reconstruction efficiencies of the CUORE experiment, and find these to be 50 ±2% and 26 ±4% at 10 keV and 3 keV, respectively. This analysis provides crucial insights into rare decay studies, new physics searches, and keV-scale background modeling with CUORE. We demonstrate that ton-scale cryogenic calorimeters can operate across a wide energy range, from keV to MeV, establishing their scalability as versatile detectors for rare event and dark matter physics. These findings also inform the optimization of future large mass cryogenic calorimeters to enhance the sensitivity to low-energy phenomena.
Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb − 1 of p p collisions at s = 13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton ( e , μ ) , photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions. © 2024 CERN, for the ATLAS Collaboration 2024 CERN
A search for new physics with non-resonant signals in dielectron and dimuon final states in the mass range above 2 TeV is presented. This is the first search for non-resonant signals in dilepton final states at the LHC to use a background estimate from the data. The data, corresponding to an integrated luminosity of 139 fb –1 , were recorded by the ATLAS experiment in proton-proton collisions at a center-of-mass energy of √s = 13 TeV during Run 2 of the Large Hadron Collider. The benchmark signal signature is a two-quark and two-lepton contact interaction, which would enhance the dilepton event rate at the TeV mass scale. To model the contribution from background processes a functional form is fit to the dilepton invariant-mass spectra in data in a mass region below the region of interest. It is then extrapolated to a high-mass signal region to obtain the expected background there. No significant deviation from the expected background is observed in the data. Upper limits at 95% CL on the number of events and the visible cross-section times branching fraction for processes involving new physics are provided. Observed (expected) 95% CL lower limits on the contact interaction energy scale reach 35.8 (37.6) TeV.
A search is presented for new phenomena in events characterised by high jet multiplicity, no leptons (electrons or muons), and four or more jets originating from the fragmentation of b -quarks ( b -jets). The search uses 139 fb -1 of $\sqrt{s}$ = 13 TeV proton–proton collision data collected by the ATLAS experiment at the Large Hadron Collider during Run 2. The dominant Standard Model background originates from multijet production and is estimated using a data-driven technique based on an extrapolation from events with low b -jet multiplicity to the high b -jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits that constrain simplified models of R-parity-violating supersymmetry are determined. The exclusion limits reach 950 GeV in top-squark mass in the models considered.
Understanding thermal transport across interfaces which give rise to a thermal resistance (also known as Kapitza resistance) is a critical issue affecting the development of nanotechnologies. Much modern and emergent nanotechnology consist of adjacent materials, and phonon mediated heat transfer governs thermal behavior across internal interfaces in these devices. The physics of thermal transport in solids are governed both by phenomena occurring at the atomic scale and interactions with the material's microstructure. The forecasting of fundamental quantities such as temperature, heat flux and thermal conductivity typically employs the semi-classical Boltzmann transport equation to predict the macroscopic behavior of materials in terms of the microscopic dynamics of its heat carriers. Kapitza resistance was first discovered in liquid helium experiments and has led to a fundamental research thrust in micro and nano-scale heat transport, the behavior of thermal carriers across internal interfaces. Thermal interfacial resistance (TIR) is a widely studied phenomenon, first engaged by Swartz and Pohl through their development of the acoustic and diffuse mismatch methods, then continued through myriad efforts with varying methods and approaches in an attempt to resolve carrier behavior at thermal interfaces. Many of the fundamental approaches to TIR have been at the nanoscale, and research is conducted with molecular dynamics (MD) and density functional theory (DFT) methods. The limitations of these methods is system size; atomistic methods tend to be limited to system sizes of 100,000 atoms or less. Larger length-scale methods have also been pursued, based on the principles of acoustic or diffuse mismatch, but not all include simulation of TIR using a full phonon band spectrum, or temperature dependent methods. Our approach to enabling phonon transport in layered materials draws upon our previous work of demonstrating spectrally coupled phonon transport in homogeneous and heterogeneous materials. We use a semi-analytical approach in which the Bose-Einstein (B-E) statistics set the strength of the phonon radiance in a frequency group, but the B-E statistics are informed with information from the transport system. The B-E statistics in a single frequency group feels the influence of all the groups through the spatial temperature. We also include a new field term which is an indicator of the amount of non-equilibrium behavior of the phonon spectrum---this is added to the phonon source term in all groups to ensure closure and conservation of energy, as the phonon groups in the transport system and the analytical systems are coupled. This work builds upon our previous approach by adding a phonon coupling term at an internal interface, using the principles of the DMM through transmission and reflection coefficients. In this work, the coefficients are determined through computing a common temperature at the interface, influenced by the phonon band structure of both materials, in effect, providing mixing between the two material systems and using the common temperature to set the strength of the phonon radiance at the boundaries on either side of the interface. Our approach uses material properties computed along various crystallographic orientations, and while some isotropy is built into the interface condition, the material properties weight the phonon distributions in the proper crystalline direction. Greater resolution of phonon behavior in proximity to an interface, and more accurate predictions of TIR are obtained. While it is true the assumption of diffuse mismatch can yield inconsistent results compared to experiment especially at low temperatures, this work focuses on room temperature and beyond effects, for future applications in nuclear fuel, or thermoelectric devices; a modified mismatch approach may be feasible if applied properly. Additionally, our methods focus on bridging mesoscale to engineering scale
In ordered magnets, the elementary excitations are spin waves (magnons), which obey Bose–Einstein statistics. Similarly to Cooper pairs in superconductors, magnons can be paired into bound states under attractive interactions. The Zeeman coupling to a magnetic field is able to tune the particle density through a quantum critical point, beyond which a ‘hidden order’ is predicted to exist. Here, in this work, we report direct observation of the Bose–Einstein condensation of the two-magnon bound state in Na 2 BaNi(PO 4 ) 2 . Comprehensive thermodynamic measurements confirmed the two-dimensional Bose–Einstein condensation quantum critical point at the saturation field. Inelastic neutron scattering experiments were performed to establish the microscopic model. An exact solution revealed stable two-magnon bound states that were further confirmed by electron spin resonance and nuclear magnetic resonance experiments, demonstrating that the quantum critical point is due to the pair condensation, and the phase below the saturation field is likely the long-sought-after spin nematic phase.
This manuscript reports on the direct observation of a 𝛽-delayed two-neutron emission in a study of 134 In at the ISOLDE Decay Station using neutron spectroscopy. We also report on the first measurement in 𝛽 − decay of the long-sought 13/2 + excited state in 133 Sn, attributed to be the neutron single-particle 𝑖 13/2 orbital. The observation of sequential neutron emission is used to extract the relative population of the 𝑖 13/2 state, which was found to be much smaller than the predictions of the statistical model. The experiment was possible because of the innovative use of a neutron array with neutron discrimination and interaction tracking capabilities. This is the first study of the details of the two-neutron emission for a nucleus, which belongs to the 𝑟-process path. Understanding 𝛽-delayed two-neutron emission probabilities is essential to validate models used in astrophysical 𝑟-process nucleosynthesis calculations. Observing two-neutron emissions in 𝛽 − decay paves the way for new experiments to study energy and angular correlations for 𝛽-delayed multineutron emitters.
Low-temperature plasmas (LTPs) are essential to both fundamental scientific research and critical industrial applications. As in many areas of science, numerical simulations have become a vital tool for uncovering new physical phenomena and guiding technological development. Code benchmarking remains crucial for verifying implementations and evaluating performance. This work continues the Landmark benchmark initiative, a series specifically designed to support the verification of LTP codes. In this study, seventeen simulation codes from a collaborative community of nineteen international institutions modeled a partially magnetized E × B Penning discharge. The emergence of large scale coherent structures, or rotating plasma spokes, endows this configuration with an enormous range of time scales, making it particularly challenging to simulate. The codes showed excellent agreement on the rotation frequency of the spoke as well as key plasma properties, including time-averaged ion density, plasma potential, and electron temperature profiles. Achieving this level of agreement came with challenges, and we share lessons learned on how to conduct future benchmarking campaigns. Comparing code implementations, computational hardware, and simulation runtimes also revealed interesting trends, which are summarized with the aim of guiding future plasma simulation software development.