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At least 1,459 records · Page 81

Correlated signals of first-order phase transitions and primordial black hole evaporation

Fermi balls produced in a cosmological first-order phase transition may collapse to primordial black holes (PBHs) if the fermion dark matter particles that comprise them interact via a sufficiently strong Yukawa force. We show that phase transitions described by a quartic thermal effective potential with vacuum energy, 0.1 ≲ B 1/4 /MeV ≲ 10 3 , generate PBHs of mass, 10 –20 ≲ M PBH /M ⊙ ≲ 10 –16 , and gravitational waves from the phase transition (at THEIA/μAres) can be correlated with an isotropic extragalactic X-ray/γ-ray background from PBH evaporation (at AMEGO-X/e-ASTROGAM).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spontaneously broken boosts in CFTs

Conformal Field Theories (CFTs) have rich dynamics in heavy states. We describe the constraints due to spontaneously broken boost and dilatation symmetries in such states. The spontaneously broken boost symmetries require the existence of new low-lying primaries whose scaling dimension gap, we argue, scales as O(1). We demonstrate these ideas in various states, including fluid, superfluid, mean field theory, and Fermi surface states. We end with some remarks about the large charge limit in 2d and discuss a theory of a single compact boson with an arbitrary conformal anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Giant Wilson loops and AdS 2 /dCFT 1

The 1/2-BPS Wilson loop in N = 4 supersymmetric Yang-Mills theory is an important and well-studied example of conformal defect. In particular, much work has been done for the correlation functions of operator insertions on the Wilson loop in the fundamental representation. In this paper, we extend such analyses to Wilson loops in the large-rank symmetric and antisymmetric representations, which correspond to probe D3 and D5 branes with AdS 2 × S 2 and AdS 2 × S 4 worldvolume geometries, ending at the AdS 5 boundary along a one-dimensional contour. We first compute the correlation functions of protected scalar insertions from supersymmetric localization, and obtain a representation in terms of multiple integrals that are similar to the eigenvalue integrals of the random matrix, but with important differences. Using ideas from the Fermi Gas formalism and the Clustering method, we evaluate their large N limit exactly as a function of the ’t Hooft coupling. The results are given by simple integrals of polynomials that resemble the Q-functions of the Quantum Spectral Curve, with integration measures depending on the number of insertions. Next, we study the correlation functions of fluctuations on the probe D3 and D5 branes in AdS. We compute a selection of three- and four-point functions from perturbation theory on the D-branes, and show that they agree with the results of localization when restricted to supersymmetric kinematics. We also explain how the difference of the internal geometries of the D3 and D5 branes manifests itself in the localization computation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Resolving the ($\mathscr{g}$-2)$_μ$ discrepancy with $\mathcal{F}$–SU(5) intersecting D-branes

A discrepancy between the measured anomalous magnetic moment of the muon (g - 2) μ and computed Standard Model value now stands at a combined 4.2σ following experiments at Brookhaven National Lab (BNL) and the Fermi National Accelerator Laboratory (FNAL). A solution to the disagreement is uncovered in flipped SU(5) with additional TeV-Scale vector-like 10 +$\bar{10}$ multiplets and charged singlet derived from local F-Theory, collectively referred to as $\mathcal {F}$-SU(5). Here we engage general No-Scale supersymmetry (SUSY) breaking in $\mathcal {F}$-SU(5) D-brane model building to alleviate the (g-2)μ. tension between the Standard Model and observations. A robust Δa μ (SUSY) is realized via mixing of M 5 and M 1X at the secondary SU(5) x U(1) X unification scale in $\mathcal {F}$-SU(5) emanating from SU(5) breaking and U(1) X flux effects. Calculations unveil Δa μ (SUSY) = 19.0-22.3 x 10 -10 for gluino masses of M($\tilde{g}$ = 2.25-2.56 TeV nd higgsino dark matter, aptly residing within the BNL+FNAL 1σ mean. This (g – 2)μ favorable region of the model space also generates the correct light Higgs boson mass and branching ratios of companion rare decay processes, and is further consistent with all LHC Run 2 constraints. Finally, we also examine the heavy SUSY Higgs boson in light of recent LHC searches for an extended Higgs sector.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The large- N partition function for non-parity-invariant Chern-Simons-matter theories

We extend the Fermi gas approach to a class of ABJM-like necklace quiver theories without parity invariance. The resulting partition function on S 3 retains the form of an Airy function, but now includes a phase that scales as Nk in the large- N limit where k is an overall Chern-Simons level. We demonstrate the presence of this phase both analytically and numerically in the case of a three node quiver.

Supersymmetric Gauge Theory↗

Two-loop electroweak corrections to the Top-Quark Contribution to ϵ K

The parameter ϵ K measures CP violation in the neutral kaon system. It is a sensitive probe of new physics and plays a prominent role in the global fit of the Cabibbo-Kobabyashi-Maskawa matrix. The perturbative theory uncertainty is currently dominated by the top-quark contribution. Here, we present the calculation of the full two-loop electroweak corrections to the top-quark contribution to ϵ K , including the resummation of QED-QCD logarithms. We discuss different renormalization prescriptions for the electroweak input parameters. In the traditional normalization of the weak Hamiltonian with two powers of the Fermi constant G F , the top-quark contribution is shifted by –1%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A simple introduction to the SiMPL method for density-based topology optimization

We introduce a novel method for solving density-based topology optimization problems: Sigmoidal Mirror descent with a Projected Latent variable (SiMPL). The SiMPL method (pronounced as “the simple method”) optimizes a design using only first-order derivative information of the objective function. The bound constraints on the density field are enforced with the help of the (negative) Fermi–Dirac entropy, which is also used to define a non-symmetric distance function called a Bregman divergence on the set of admissible designs. This Bregman divergence leads to a simple update rule that is further simplified with the help of a so-called latent variable. Because the SiMPL method involves discretizing the latent variable, it produces a sequence of pointwise-feasible iterates, even when high-order finite elements are used in the discretization. Numerical experiments demonstrate that the method outperforms other popular first-order optimization algorithms. In conclusion, to outline the general applicability of the technique, we include examples with (self-load) compliance minimization and compliant mechanism optimization problems.

Calculus of Variations and Optimization↗

ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks (40/100G) across distributed sites for processing, storage, and analysis. Like general purpose networks, research networks experience intrusions. However, monitoring anomalies in such high-speed network traffics is challenging given current cyber-infrastructure. Moreover, traditional network intrusion detection systems (NIDS) are signature based. However, anomaly patterns are difficult to define and that rulesets are often not updated frequently enough to reflect the changes of attack behaviors. We present ThunderSecure, a high-throughput, unsupervised learning-based intrusions detection system for 100G research networks. ThunderSecure implements an efficient packet processing and detection pipeline using multi-cores and GPUs. It extracts statistical and temporal features from real-time network data streams and feeds them to a one-class anomaly detection network. A baseline of normal distribution will be created based on the training observation. Testing traffic deviated from the learned profile will be marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets mirrored from two 100G network connections at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. Results show that ThunderSecure can recognize science data traffic captured long after the training and made nearly certain detection on the segment of the streams where anomalous flows were injected.

100G research network↗

Significantly increased Raman enhancement on defect-rich O-incorporated 1T-MoS 2 nanosheets

Improving charge transfer is the key to the performance of non-noble metal semiconductor-based surface enhanced Raman scattering (SERS) substrates. In this work, the O-incorporated 1T-MoS 2 nanosheets with rich sulfur defects (ID-MoS 2 ) are obtained by simple calcination of 1T-MoS 2 nanosheets in air atmosphere. Using rhodamine 6G (R6G) as typical probe molecules, ID-MoS 2 nanosheets show ultrahigh Raman enhancement effects with an enhancement factor of 1.24 × 10 7 due to sulfur defects and O incorporation in the 1T-MoS 2 lattice. First-principle density functional theory calculations suggest that the existence of sulfur defects and O incorporation significantly increase the Fermi energy level (E f ) and electronic density of states of ID-MoS 2 . Furthermore, O incorporation can enhance the interactions between the substrate and the adsorbed molecules through electrostatic and hydrogen bonding. All these improve the charge transfer resonance and result in the remarkable SERS activity of ID-MoS 2 nanosheets. This is the first study on the increasing SERS performance of semiconductor substrates by simultaneously employing defect and dopant incorporation. This study provides an approach to optimize the performance of semiconductor-based SERS substrates.

36 MATERIALS SCIENCE↗

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗

Particle Acceleration by Magnetic Reconnection in Geospace

Particles are accelerated to very high, non-thermal energies during explosive energy-release phenomena in space, solar, and astrophysical plasma environments. While it has been established that magnetic reconnection plays an important role in the dynamics of Earth’s magnetosphere, it remains unclear how magnetic reconnection can further explain particle acceleration to non-thermal energies. Here we review recent progress in our understanding of particle acceleration by magnetic reconnection in Earth’s magnetosphere. With improved resolutions, recent spacecraft missions have enabled detailed studies of particle acceleration at various structures such as the diffusion region, separatrix, jets, magnetic islands (flux ropes), and dipolarization front. With the guiding-center approximation of particle motion, many studies have discussed the relative importance of the parallel electric field as well as the Fermi and betatron effects. However, in order to fully understand the particle acceleration mechanism and further compare with particle acceleration in solar and astrophysical plasma environments, there is a need for further investigation of, for example, energy partition and the precise role of turbulence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Itinerant to relocalized transition of f electrons in the Kondo insulator CeRu 4 Sn 6

In this study, the three-dimensional electronic structure and the nature of Ce 4 f electrons of the Kondo insulator CeRu 4 Sn 6 are investigated by angle-resolved photoemission spectroscopy, utilizing tunable photon energies. Our results reveal (i) the three-dimensional k -space nature of the Fermi surface, (ii) the localized-to-itinerant transition of f electrons occurs at a much high temperature than the hybridization gap opening temperature, and (iii) the "relocalization" of itinerant f electrons below 25 K, which could be the precursor to the establishment of magnetic order.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quaternary i-MAX Phases (Mo 2/3 RE 1/3 ) 2 AlC (RE: Dy, Tb, Er): Experimental Characterization and First-Principles Insights into their Fundamental Properties

Rare earth (RE)-based materials have unique electronic, magnetic, and optical properties, leading to the recent discovery of atomically layered solids with the chemical formula (M' 2/3 RE 1/3 ) 2 AlC, which have since garnered significant attention in the scientific community. This study aims to synthesize, characterize, and investigate the structural and thermal stability of the RE i-MAX phases. We prepared i-MAX phases using molybdenum (Mo) as M′ and RE elements as Dy, Tb, and Er, namely (Mo 2/3 Dy 1/3 ) 2 AlC, (Mo 2/3 Tb 1/3 ) 2 AlC, and (Mo 2/3 Er 1/3 ) 2 AlC. Structural characterization through x-ray diffraction (XRD) and Raman spectroscopy confirms the formation of the RE-based i-MAX phase, along with the presence of minor impurity phases in the alloys. Thermogravimetric analysis (TGA) conducted up to 1000°C under ambient conditions reveals that the i-MAX phases remain thermally stable up to approximately 450°C, beyond which oxidation leads to a noticeable weight gain in all samples. Differential scanning calorimetry (DSC) measurements during heating and cooling cycles show endothermic and exothermic peaks for (Mo 2/3 Dy 1/3 ) 2 AlC i-MAX in the 410–420°C range, indicating a temperature-induced minor atomic arrangement. In contrast, these peaks are absent in the Tb- and Er-based i-MAX phases. These findings offer valuable insights into the thermal behavior and stability of these i-MAX phases under thermal stress, contributing to a deeper understanding of their unique properties. Furthermore, first-principles density functional theory (DFT) calculations were performed to investigate the electronic and optical properties of the i-MAX phases. The results reveal their metallic nature, with pronounced contributions from Mo and RE elements near the Fermi level and within the conduction band.

Rare earth↗

Defect Thermodynamics and Transport Properties of Proton Conducting Oxide BaZr 1–x Y x O 3–δ (x ≤ 0.1) Guided by Density Functional Theory Modeling

Density functional theory-based thermodynamic modeling was performed to determine the effect of humidity and H 2 /O 2 gas pressure on the defect chemistry and transport properties of proton conducting oxide BaZr 1-x Y x O 3-δ (x ≤ 0.1) in the temperature range of 800–1200K, relevant for solid oxide fuel/electrolysis cell applications. The first-principles charge defect analysis was carried out to obtain the defect energetic ensembles as a function of Fermi level as well as the dependence of the hydration and oxidation reaction energies on complex defect-dopant configurations. It is shown that oxygen vacancies introduced to compensate for the extra Ba vacancies may cause a slight increase in the concentration of hydroxyl and proton species upon hydration of Ba deficient BaZr 1-x Y x O 3-δ , while the overall proton diffusivity is predicted to decrease with increased proton hopping barriers upon trapping near the Ba vacancies. The developed defect model is further demonstrated to be able to describe the bulk defect chemistry and transport properties of BaZr 0.9 Y 0.1 O 3-δ under the solid oxide cell operating conditions. Finally, the theoretical framework developed in this work further allows the inclusion of configurational, energetic and electronic characteristics of the defects that can be used as a complementary tool to experimental measurements for testing various mechanistic pathways or to provide essential mechanistic data.

36 MATERIALS SCIENCE↗

Evidence for strong electronic correlations in the bulk state of grey arsenic

Here, we investigate the electron band structure of grey arsenic, whose (111) face hosts the topological Shockley state. Interestingly, the bulk band close to the touching point with the surface state exhibits the characteristics of inelastic scattering. Moreover, the band structure analysis reveals linearity in the imaginary part of electron self-energy. These features are analogous to those observed in high-temperature superconductors and marginal Fermi liquid systems, respectively, where strong electronic correlations exist. Our results suggest that correlated many-body states can be connected by non-interacting topological states, providing a viable playground to explore the coupling between topological and correlated states via grey arsenic surface.

ARPES↗

Physical, numerical, and computational challenges of modeling neutrino transport in core-collapse supernovae

The proposal that core collapse supernovae are neutrino driven is still the subject of active investigation more than 50 years after the seminal paper by Colgate and White. The modern version of this paradigm, which we owe to Wilson, proposes that the supernova shock wave is powered by neutrino heating, mediated by the absorption of electron-flavor neutrinos and antineutrinos emanating from the proto-neutron star surface, or neutrinosphere. Neutrino weak interactions with the stellar core fluid, the theory of which is still evolving, are flavor and energy dependent. The associated neutrino mean free paths extend over many orders of magnitude and are never always small relative to the stellar core radius. Thus, neutrinos are never always fluid like. Instead, a kinetic description of them in terms of distribution functions that determine the number density of neutrinos in the six-dimensional phase space of position, direction, and energy, for both neutrinos and antineutrinos of each flavor, or in terms of angular moments of these neutrino distributions that instead provide neutrino number densities in the four-dimensional phase-space subspace of position and energy, is needed. In turn, the computational challenge is twofold: (i) to map the kinetic equations governing the evolution of these distributions or moments onto discrete representations that are stable, accurate, and, perhaps most important, respect physical laws such as conservation of lepton number and energy and the Fermi–Dirac nature of neutrinos and (ii) to develop efficient, supercomputer-architecture-aware solution methods for the resultant nonlinear algebraic equations. In this review, we present the current state of the art in attempts to meet this challenge.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server

Abstract With machine learning applications now spanning a variety of computational tasks, multi-user shared computing facilities are devoting a rapidly increasing proportion of their resources to such algorithms. Graph neural networks (GNNs), for example, have provided astounding improvements in extracting complex signatures from data and are now widely used in a variety of applications, such as particle jet classification in high energy physics (HEP). However, GNNs also come with an enormous computational penalty that requires the use of GPUs to maintain reasonable throughput. At shared computing facilities, such as those used by physicists at Fermi National Accelerator Laboratory (Fermilab), methodical resource allocation and high throughput at the many-user scale are key to ensuring that resources are being used as efficiently as possible. These facilities, however, primarily provide CPU-only nodes, which proves detrimental to time-to-insight and computational throughput for workflows that include machine learning inference. In this work, we describe how a shared computing facility can use the NVIDIA Triton Inference Server to optimize its resource allocation and computing structure, recovering high throughput while scaling out to multiple users by massively parallelizing their machine learning inference. To demonstrate the effectiveness of this system in a realistic multi-user environment, we use the Fermilab Elastic Analysis Facility augmented with the Triton Inference Server to provide scalable and high-throughput access to a HEP-specific GNN and report on the outcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Electronic structural and lattice thermodynamic properties of MAlO2 and M5AlO4 (M = Li, Na, K) sorbents for CO2 capture applications

Abstract The electronic properties and thermal stabilities of MAlO 2 and M 5 AlO 4 (M = Li, Na, K) are investigated by density functional theory and lattice phonon dynamics. Based on the calculated electronic and lattice thermodynamic properties, their abilities to capture CO 2 as solid sorbents are analyzed. The calculated electronic structural properties of MAlO 2 and M 5 AlO 4 indicate that all these alkali aluminates are semiconductors with a bandgap range of 2.4 ~ 6.4 eV. The 1st valence bands of these alkali aluminates are located 0 ~ − 6 eV under Fermi levels and are mainly contributed by p orbitals of O, s and p orbitals of Al and M. The phonon vibrational frequencies of M 5 AlO 4 spread at a lower frequency range compared to their MAlO 2 phases. With increasing temperature, the calculated phonon free energies of M 5 AlO 4 decrease faster than their corresponding MAlO 2 while their entropies have opposite trends. The reaction 2MAlO 2 + CO 2 = M 2 CO 3 + Al 2 O 3 has higher reaction heat and Gibbs free energy change than those of corresponding reaction 2 / 5 M 5 AlO 4 + CO 2 = M 2 CO 3 + 1 / 5 Al 2 O 3 , which shows the former reaction possesses lower turnover temperature. Among the alkali aluminates studied, the β-NaAlO 2 , lt-KAlO 2 , and γ-LiAlO 2 are better candidates that could be applied for CO 2 capture technologies. Graphical Abstract

36 MATERIALS SCIENCE↗