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At least 199 records · Page 11

Phonons in complex twisted crystals: Angular momenta, interactions, and topology

We report phonons and their interactions are critically important for a variety of energy-relevant applications ranging from low thermal resistance substrates to thermal barrier coatings. Fundamental insights into the nature of phonons and allowed interactions are governed by the underlying symmetries of the crystal lattice. In this paper, we provide a comprehensive and detailed description of lattice dynamics derived from twist symmetries of chiral and achiral crystals—twist dynamics. Phonon bands naturally carry quantized crystal angular momentum derived from rotational phases, which give insights into the nature of band crossings and avoided crossings, selection rules for phonon interactions, and topological band crossing behaviors. Twist dynamics is demonstrated for a variety of materials covering a range of space groups, symmetry operations, twist axis orientations, and constituent elements. Furthermore, twist symmetry offers insights into peculiar features observed in scattering measurements. In this context, we present inelastic neutron scattering measurements for rutile TiO 2 and explain them using twist dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations.

97 MATHEMATICS AND COMPUTING↗

The recovery of the HEAO-2 observatory

In August 1980, the Second High Energy Astronomy Observatory suffered the simultaneous double failure of two gyros, leaving the observatory with one gyro less than what is required for operation. The function of the missing gyro was replaced to allow restoration of spacecraft operation by reprogramming the on-board computer to derive rate from star and sun sensors, and by utilizing complex procedures. Large sun sensor quantization, jump characteristics of the star tracker, and extremely limited computer memory capacity further complicated the problem. Recovery attempts continued for over three months, during which time a suitable rate algorithm was derived. Final verification of the technique was never completed, however, due to the unexpected revival of one of the failed gyros.

Rose, R. E.↗

Quantization of the band at the surface of charge density wave material 2H-TaSe 2

By using angle-resolved photoemission spectroscopy combined with the first-principles electronics atructure calculations, we report the quantum well states at the surface of a single crystal 2H-TaSe 2 . We observed sub-bands at the three-dimensional Brillouin zone center forming the quantized states due to its highly dispersive nature and light effective mass along k z direction. The quantized sub-bands shift upward towards E F with the decrease of temperature across TCDW. The band shift could not be explained by two-dimensional Fermi-surface nesting-driven charge density waves(CDW), nor by purely strong electron-phonon coupling only. The CDW in 2H-TaSe 2 is likely related to the bands at higher binding energy, and the CDW mechanism could be explained by the excitons, and our observation gives support to this scenario.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spontaneous Exciton Collapse in a Strongly Flattened Ellipsoidal InSb Quantum Dot

Abstract Electronic and excitonic states in an InSb strongly flattened ellipsoidal quantum dot (QD) with complicated dispersion law are theoretically investigated within the framework of the geometric adiabatic approximation in the strong, intermediate, and weak quantum confinement regimes. For the lower levels of the spectrum, the square root dependence of energy on QD sizes is revealed in the case of Kane’s dispersion law. The obtained results are compared to the case of a parabolic (standard) dispersion law of charge carriers. The possibility of the accidental exciton instability is revealed for the intermediate quantum confinement regime. For the weak quantum confinement regime, the motion of the exciton's center-of-gravity is quantized, which leads to the appearance of additional Coulomb-like sub-levels. It is revealed that in the case of the Kane dispersion law, the Coulomb levels shift into the depth of the forbidden band gap, moving away from the quantum confined level, whereas in the case of the parabolic dispersion law, the opposite picture is observed. The corresponding selection rules of quantum transitions for the interband absorption of light are obtained. New selection rules of quantum transitions between levels conditioned by 2D exciton center of mass vertical motion quantization in a QD are revealed. The absorption threshold behavior characteristics depending on the QDs geometrical sizes are also revealed.

97 MATHEMATICS AND COMPUTING↗

Polariton Condensation in Gap-Confined States of Photonic Crystal Waveguides

Here, the development of patterned multiquantum well heterostructures in GaAs/AlGaAs waveguides has recently made it possible to achieve exciton-polariton condensation in a topologically protected bound state in the continuum (BIC). Polariton condensation was shown to occur above a saddle point of the two-dimensional polariton dispersion in a one-dimensional photonic crystal waveguide. A rigorous analysis of the condensation phenomenon in these systems, as well as the role of the BIC, is still missing. In the present Letter, we theoretically and experimentally fill this gap by showing that polariton confinement resulting from the negative effective mass and the photonic energy gap in the dispersion play a key role in enhancing the relaxation toward the condensed state. In fact, our results show that low-threshold polariton condensation is achieved within the effective trap created by the exciting laser spot, regardless of whether the resulting confined mode is long-lived (polariton BIC) or short-lived (lossy mode). In both cases, the spatial quantization of the polariton condensate and the threshold differences associated to the corresponding state lifetime are measured and characterized. For a given negative mass, a slightly lower condensation threshold from the polariton BIC mode is found and associated to its reduced radiative losses, as compared to the lossy one.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pythia8 Quark and Gluon Jets (float8 e4m3FN)

A float8 (e4m3FN) quantized version of the quark and gluon jet dataset originally published by Komiske, Metodiev, and Thaler (Zenodo record 3164691). Only the 20-file subset without charm and bottom quark jets is included here. All simulation parameters and jet selection criteria are identical to the original: Pythia 8.226, √s = 14 TeV Quarks from WeakBosonAndParton:qg2gmZq, gluons from WeakBosonAndParton:qqbar2gmZg with the Z decaying to neutrinos FastJet 3.3.0, anti-k_t jets with R = 0.4 p_T^jet ∈ [500, 550] GeV, |y^jet| < 1.7 There are 20 files, each in compressed NumPy format (QG_jets_fp8e4m3fn_0.npz through QG_jets_fp8e4m3fn_19.npz). Each file contains two arrays: X: (100000, M, 4) — 50k quark and 50k gluon jets, randomly sorted, padded to max multiplicity M, with particle features (pt, rapidity, azimuthal angle, pdgid) y: (100000,) — jet labels, gluon = 0, quark = 1 Since NumPy has no native fp8 dtype, X is stored as float32, but the values have been quantized through TensorFlow's float8_e4m3fn type and carry only fp8 precision. The quantization procedure is as follows: a global per-channel scale factor is computed from the absolute maximum value across all 20 chunks (with FP8_MAX = 448.0, the maximum representable value of e4m3FN). Each chunk is then scaled into the fp8 dynamic range, round-tripped through tf.experimental.float8_e4m3fn, and scaled back. This global scaling ensures a consistent quantization grid across the full dataset. The y labels are unchanged. Users should be aware that e4m3FN has limited dynamic range and precision. We recommend verifying this format is appropriate for your application; for a less aggressive reduction see the float16 and float32 versions linked below. If you use this dataset, please cite the original Zenodo record and its associated paper: Komiske, Metodiev, Thaler, Energy Flow Networks: Deep Sets for Particle Jets, JHEP 01 (2019) 121, arXiv:1810.05165

DiLullo, Nicholas [Brown University] (ORCID:000000↗

The accuracies of effective interactions in downfolding coupled-cluster approaches for small-dimensionality active spaces

Here, this paper evaluates the accuracy of the Hermitian form of the downfolding procedure using the double unitary coupled cluster (DUCC) ansatz on the benchmark systems of linear chains of hydrogen atoms, H6 and H8. The computational infrastructure employs the occupation-number-representation codes to construct the matrix representation of arbitrary second-quantized operators, allowing for the exact representation of exponentials of various operators. The tests demonstrate that external amplitudes from standard single-reference coupled cluster methods that sufficiently describe external (out-of-active-space) correlations reliably parameterize the Hermitian downfolded effective Hamiltonians in the DUCC formalism. The results show that this approach can overcome the problems associated with losing the variational character of corresponding energies in the corresponding SR-CC theories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Positronium on the light front

Basis Light-front Quantization (BLFQ) is a newly developed nonperturbative approach, aiming at solving relativistic bound systems based on the Hamiltonian formalism of light-front dynamics. Here, in this work, we introduce its application to the positronium system at strong coupling, α = 0.3, with a dynamical photon mediating the interaction between the positron and the electron. Non-perturbative mass renormalization is needed to cancel the fermion self-energy divergence. Finally, we present the resulting mass spectrum, light-front wave functions (LFWFs), and the photon distribution inside positronium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Reply to: Low-frequency quantum oscillations in LaRhIn 5 : Dirac point or nodal line?

We thank G.P. Mikitik and Yu.V. Sharlai for contributing this note and the cordial exchange about it. First and foremost, we note that the aim of our paper is to report a methodology to diagnose topological (semi)metals using magnetic quantum oscillations. Thus far, such diagnosis has been based on the phase offset of quantum oscillations, which is extracted from a “Landau fan plot”. A thorough analysis of the Onsager–Lifshitz–Roth quantization rules has shown that the famous π-phase shift can equally well arise from orbital or spin magnetic moments in topologically trivial systems with strong spin-orbit coupling or small effective masses. Therefore, the “Landau fan plot” does not by itself constitute a proof of a topologically nontrivial Fermi surface. In the paper at hand, we report an improved analysis method that exploits the strong energy dependence of the effective mass in linearly dispersing bands. This leads to a characteristic temperature dependence of the oscillation frequency which is a strong indicator of nontrivial topology, even for multi-band metals with complex Fermi surfaces. Three materials, Cd 3 As 2 , Bi 2 O 2 Se and LaRhIn5 served as test cases for this method. Linear band dispersions were detected for Cd 3 As 2 , as well as the F ≈ 7 T pocket in LaRhIn 5 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic photocurrents in multifold Weyl fermions

Here, we examine the magneto-optical response of chiral multifold fermions. Specifically, we show that they are ideal candidates for observing the helical magnetic effect (HME) previously predicted for simple Weyl fermions. Unlike Weyl fermions, the HME is present in multifold fermions even in the simplest case where the low-energy dispersion is linear and spherically symmetric. In this ideal case, we derive an analytical expression for the HME and find it is proportional to the circular photogalvanic effect; for realistic parameters and accounting for the geometry of the setup, the HME photocurrent could be roughly the same order of magnitude as the circular photogalvanic effect observed in multifold fermions. Additional nonlinear and symmetry-breaking terms will ruin the quantization but not hurt the observation of the HME.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Conductance of Carbon Nanotubes

The recent report of quantized conductance in a 4 m long multiwalled nanotube (MWNT) raises the exciting possibility of ballistic transport at room temperature over relatively long distances. We argue that this is made possible by the special symmetry of the eigenstates of the lowest propagating modes in metallic nanotubes which suppresses backscattering. This unusual effect is absent for the higher propagating modes so that transport is not ballistic once the bias exceeds the cut-off energy for the higher modes, which is estimated to be approximately 75 meV for nanotubes of diameter approximately 15 nm. Also, we show that the symmetry of the eigenstates can significantly affect their coupling to the reservoir and hence the contact resistance. A simple model is presented that can be used to understand the observed conductance-voltage characteristics.

Datta, Supriyo↗

Mechanical cosmology: Simulating scalar fluctuations in expanding universes using synthetic mechanical lattices

Inspired by recent advances in observational astrophysics and continued explorations in the field of analog gravity, we discuss the prospect of simulating models of cosmology within the context of synthetic mechanical lattice experiments. We focus on the physics of expanding universe scenarios described by the Friedmann-Lemaître-Robertson-Walker (FLRW) metric. Specifically, quantizing scalar fluctuations in a background FLRW spacetime leads to a quadratic bosonic Hamiltonian with temporally varying pair production terms. Here we present a mapping that provides a one-to-one correspondence between these classes of cosmology models and feedback-coupled mechanical oscillators. As proof of principle, we then perform experiments on a synthetic mechanical lattice composed of such oscillators. We simulate two different FLRW expansion scenarios with universes dominated by vacuum energy and matter and discuss our experimental results. Published by the American Physical Society 2025

Rhyno, Brendan (ORCID:0000000235266998)↗

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

The statistical mechanics of near-BPS black holes

Due to the failure of thermodynamics for low temperature near-extremal black holes, it has long been conjectured that a 'thermodynamic mass gap' exists between an extremal black hole and the lightest near-extremal state. For non-supersymmetric near-extremal black holes in Einstein gravity with an AdS2 throat, no such gap was found. Rather, at that energy scale, the spectrum exhibits a continuum of states, up to non-perturbative corrections. In this paper, we compute the partition function of near-BPS black holes in supergravity where the emergent, broken, symmetry is PSU(1, 1|2). To reliably compute this partition function, we show that the gravitational path integral can be reduced to that of a $\mathcal{N}=4$ supersymmetric extension of the Schwarzian theory, which we define and exactly quantize. In contrast to the non-supersymmetric case, we find that black holes in supergravity have a mass gap and a large extremal black hole degeneracy consistent with the Bekenstein–Hawking area. Furthermore, our results verify a plethora of string theory conjectures, concerning the scale of the mass gap and the counting of extremal micro-states.

79 ASTRONOMY AND ASTROPHYSICS↗

Asynchronous Ballistic Reversible Computing using Superconducting elements

Computing uses energy. At the bare minimum, erasing information in a computer increases the entropy. Landauer has calculated %7E k B T log(2) Joules is dissipated per bit of energy erased. While the success of Moores law has allowed increasing computing power and efficiency for many years, these improvements are coming to an end. This project asks if there is a way to continue those gains by circumventing Landauer through reversible computing. We explore a new reversible computing paradigm, asynchronous ballistic reversible computing or ABRC. The ballistic nature of data in ABRC matches well with superconductivity which provides a low-loss environment and a quantized bit encoding the fluxon. We discuss both these and our development of a superconducting fabrication process at Sandia. We describe a fully reversible 1-bit memory cell based on fluxon dynamics. Building on this model, we propose several other gates which may also offer reversible operation.

97 MATHEMATICS AND COMPUTING↗