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At least 1,675 records · Page 93

Fast and accurate algorithm for calculating long-baseline neutrino oscillation probabilities with matter effects

Neutrino oscillation experiments will be entering the precision era in the next decade with the advent of high statistics experiments like DUNE, HK, and JUNO. Correctly estimating the confidence intervals from data for the oscillation parameters requires very large Monte Carlo datasets involving calculating the oscillation probabilities in matter many, many times. In this paper, we leverage past work to present a new, fast, precise technique for calculating neutrino oscillation probabilities in matter optimized for long-baseline neutrino oscillations in the Earth’s crust including both accelerator and reactor experiments. For ease of use by theorists and experimentalists, we provide fast ++ and codes . Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Long-Lived and Bright Biexcitons in Quantum Dots with Parabolic Band Potentials

Multiple exciton physics in semiconductor nanocrystals play an important role in optoelectronic devices. Here, this work investigates radially alloyed CdZnSe/CdS nanocrystals with suppressed Auger recombination due to the spatial separation of carriers, which also underpins their performance in optical gain and scintillation experiments. Due to suppressed Auger recombination, the biexciton lifetime is greater than 10 ns, much longer than most nanocrystals. The samples show optical gain, amplified spontaneous emission, and lasing at thresholds <2 excitons per particle. They also show broad gain bandwidth (>500 meV) encompassing 4 amplified spontaneous emission bands. Similarly enabled by slowed multiple exciton relaxation, the samples display strong performance in scintillating films under X-ray illumination. The CdZnSe/CdS samples have fast radioluminescence rise (<80 ps) and decay times (<5 ns), light yields up to 6700 photonsMeV -1 , and the demonstrated capacity for incorporation into large area films for scintillation imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microcalorimetry: The First Two Decades

Our group at GSFC began experimental and theoretical work on microcalorimetry almost twenty years ago, in August of 1982. Over the next 10 months, we completed the initial demonstration of a Si impurity thermometer-based calorimeter as an X-ray spectrometer. This successful demonstration resulted in the development by many investigators of scientific applications for microcalorimeters, ranging from optical spectroscopy to dark matter detection to particle physics applications. Many new technical approaches for cryogenic detectors were proposed by investigators and have been developed. In this presentation, I will describe the early development of microcalorimeters at GSFC and University of Wisconsin and the subsequent rapid growth of this work around the world The key milestones in the early development were the initial spectroscopy demonstrations and the selection of XRS, our microlcalorimeter-based instrument for the Advanced X-ray Astrophysics Facility (AXAF) and ultimately for ASTRO-E. An additional key event was the development of the direct detection of dark matter experiment and the formation of the Center for Particle Astrophysics. Both of these programs provided long term support for this technology in its precarious early days. A major additional technical step in the development of detectors was the demonstration of devices based on superconducting transition edge sensors (TES). These detectors promised (and have delivered) improved energy resolution and higher event rate capabilities. They couple naturally to SQUIDS, which operate well at the low temperatures where the detectors must operate. The past two decades have taken microcalorimeters from their infancy to applications in real experiments. I will provide an overview of the early development of the devices and review the breadth of the present technology and applications.

Moseley, Harvey↗

Autoencoders for semivisible jet detection

The production of dark matter particles from confining dark sectors may lead to many novel experimental signatures. Depending on the details of the theory, dark quark production in proton-proton collisions could result in semivisible jets of particles: collimated sprays of dark hadrons of which only some are detectable by particle collider experiments. The experimental signature is characterised by the presence of reconstructed missing momentum collinear with the visible components of the jets. This complex topology is sensitive to detector inefficiencies and mis-reconstruction that generate artificial missing momentum. With this work, we propose a signal-agnostic strategy to reject ordinary jets and identify semivisible jets via anomaly detection techniques. A deep neural autoencoder network with jet substructure variables as input proves highly useful for analyzing anomalous jets. The study focuses on the semivisible jet signature; however, the technique can apply to any new physics model that predicts signatures with anomalous jets from non-SM particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Flavor-changing light bosons with accidental longevity

We consider a model with a complex scalar field that couples to (e, μ) or (μ, τ) within the “longevity” window: [|m l 1 – m l 2 |, m l 1 + m l 2 ] in which l 1 and l 2 are the two different charged leptons. Within such a mass window, even a relatively large coupling (e.g. of the size commensurate with the current accuracy/discrepancy in the muon g – 2 experiment) leads to long lifetimes and macroscopic propagation distance between production and decay points. We propose to exploit several existing neutrino experiments and one future experiment to probe the parameter space of this model. For the μ – e sector, we exploit the muonium decay branching ratio and the production and decay sequence at the LSND experiment, excluding the parametric region suggested by g μ – 2 anomaly. For the τ – μ sector, we analyze three main production mechanisms of scalars at beam dump experiments: the Drell-Yan process, the heavy meson decay, and the muon scattering. We explore the constraints from the past CHARM and NuTeV experiments, and evaluate sensitivity for the proposed beam dump experiment, SHiP. The latter can thoroughly probe the parameter space relevant for the g μ – 2 anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Characterising the Higgs boson with ATLAS data from the LHC Run-2

The Higgs boson was discovered by the ATLAS and CMS Collaborations in 2012 using data from Run 1 of the Large Hadron Collider (2010 2012). In Run 2 (2015 2018), about 140 fb -1 of proton–proton collisions at a centre-of-mass energy of 13 TeV were collected by the ATLAS experiment. This review presents the most important Run 2 results obtained by the ATLAS Collaboration regarding the properties of the Higgs boson and its interactions with other particles. The performed studies significantly enhance the understanding of the Higgs boson, while hunting for deviations from the predictions of the Standard Model of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Extending Rucio with modern cloud storage support

Rucio is a software framework designed to facilitate scientific collaborations in efficiently organising, managing, and accessing extensive volumes of data through customizable policies. The framework enables data distribution across globally distributed locations and heterogeneous data centres, integrating various storage and network technologies into a unified federated entity. Rucio offers advanced features like distributed data recovery and adaptive replication, and it exhibits high scalability, modularity, and extensibility. Originally developed to meet the requirements of the high-energy physics experiment ATLAS, Rucio has been continuously expanded to support LHC experiments and diverse scientific communities. Recent R&D projects within these communities have evaluated the integration of both private and commercially-provided cloud storage systems, leading to the development of additional functionalities for seamless integration within Rucio. Furthermore, the underlying systems, FTS and GFAL/Davix, have been extended to cater to specific use cases. This contribution focuses on the technical aspects of this work, particularly the challenges encountered in building a generic interface for self-hosted cloud storage, such as MinIO or CEPH S3 Gateway, and established providers like Google Cloud Storage and Amazon Simple Storage Service. Additionally, the integration of decentralised clouds like SEAL is explored. Key aspects, including authentication and authorisation, direct and remote access, throughput and cost estimation, are highlighted, along with shared experiences in daily operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Intense gamma-ray source based on focused electron beams from a laser wakefield accelerator

Laser wakefield accelerators generate ultrashort electron bunches with the capability to produce γ-rays. Here, we produce focused laser wakefield acceleration electron beams using three quadrupole magnets. Electron beams are then focused into a 3 mm lead converter to generate intense, focused bremsstrahlung γ beams. Experimental results demonstrate the generation and propagation of focused γ beams to a best focus spot size of 2.3 ± 0.1 × 2.7 ± 0.2 mm 2 using a copper stack calorimeter. Monte Carlo simulations conducted using GEANT4 are in good agreement with experimental results and enable detailed examination of γ-ray generation. Simulations indicate that the focused γ beams contained 2.6 × 10 9 photons in the range of 100 keV to 33 MeV with an average energy of 6.4 MeV. A γ-ray intensity of 7 × 10 10 W/cm 2 was estimated from simulations. In conclusion, the generation of focused bremsstrahlung γ-ray sources can have important applications in medical imaging applications and laboratory astrophysics experiments.

43 PARTICLE ACCELERATORS↗

Evolution of intermittent filaments in the scrape-off layer of NSTX

Filamentary structures naturally arise from background turbulence in the scrape-off layer (SOL) of plasmas, leading to significant particle and heat transport that can degrade overall plasma confinement. This enhanced transport can contribute to unacceptably high heat loads on plasma-facing components. As such, understanding the physics of SOL plasma filaments is critical for predicting and mitigating their effects in future fusion devices. On the National Spherical Torus Experiment (NSTX), plasma filaments—commonly referred to as “blobs”—were investigated using the gas-puff imaging (GPI) diagnostic in the edge and SOL regions. The analysis involved identifying, segmenting, and tracking the characteristic contours of the blobs in each frame of the GPI video sequences. Their evolution was characterized through shape descriptors, velocity, and angular velocity derived from their contour coordinates. The results indicate that as the blob area increases, their shapes become more concave and less circular, suggesting reduced structural stability in larger blobs. This result aligns with previous theoretical results where it was shown that larger blobs are more susceptible to instabilities [Krasheninnikov et al., J. Plasma Phys. 74, 679–717 (2008) and D'Ippolito et al., Phys. Plasmas 18, 060501 (2011)]. A positive correlation was observed between radial velocity and radial position, suggesting radially outward acceleration of the filaments, potentially driven by decreasing viscous drag toward the far SOL. Interestingly, blobs in background SOL turbulence exhibited minimal spinning in contrast to filaments originating from edge localized modes, which show substantial rotation during their paths [Lampert et al., Phys. Plasmas 29, 102502 (2022)]. Statistical analysis of the solidity and total curvature shape descriptors, along with their temporal evolution, revealed relatively broad, near-Gaussian distributions. This suggests that blob morphology is strongly influenced by stochastic turbulent processes in the surrounding plasma environment. Blob parameters were also compared with bulk plasma and radial profile measurements. Notable trends were found between blob rotation and poloidal velocity with collisionality and line-integrated density. These findings contribute to a deeper understanding of blob dynamics and provide valuable insights for refining SOL turbulence models.

Covariance and correlation↗

Newton, entanglement, and the graviton

Many experiments have recently been proposed to test whether nonrelativistic gravitational interactions can generate entanglement. In this paper, I consider the extent to which these experiments can test if the graviton exists. Assuming unitarity and Lorentz invariance of the S-matrix, I demonstrate that this "Newtonian entanglement" requires the existence of massless bosons, universally coupled to mass, in the Hilbert space of low-energy scattering states. These bosons could be the usual spin-2 gravitons, but in principle there are other possibilities like spin-0 scalar gravitons. I suggest a concept for a more refined experiment to rule these out. The special role of d=3+1 spacetime dimensions and the possibility that unitarity is violated by gravity are highlighted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Observations and theory of the solar semidiurnal tide in the mesosphere of Venus

The 1978 Pioneer Venus mission, in addition to producing strong IR radiometer experiment evidence for the existence of a semidiurnal solar tide in the Venus mesosphere, has yielded radiative flux and cloud particle distribution data about the structure of solar heating and IR cooling which facilitate calculations of tidal forcing functions and estimates of radiative dissipation rates. It is presently shown that a physically reasonable mean flow can be found which leads to theoretically predicted tides that are in excellent agreement with those observed. The zonal mean flow obtained exhibits a maximum velocity of about 130 m/sec at 70 km altitude, decreasing to about zero at 88 km, together with a jet-like meridional structure that strongly deviates from solid body rotation.

Fels, S. B.↗

Investigating the Martian Environment with the Mars Global Surveyor Thermal Emission Spectrometer

The Thermal Emission Spectrometer (TES) onboard Mars Global Surveyor (MGS) is being used to investigate the surface and atmosphere of Mars and the martian moons Phobos and Deimos. As such, it builds upon infrared observations obtained by previous spacecraft, e.g.. Mariner 9 and Viking Orbiters. The objectives of the TES experiment are: (1) determine and map surface minerals. rocks. and ices; (2) study the atmospheric dust composition. particle size, and spatial and temporal distribution; (3) investigate condensate clouds, CO2 and H2O, location. temperature, and height; (4) investigate polar cap deposits, e.g., growth, retreat, and energy balance; (5) measure the thermo-physical properties of surface materials; and (6) characterize the atmospheric structure and dynamics. The TES instrument is based upon a Michelson interferometer and collects data in the 1700-200 per cm region (about 6-50 micron at 5 or 10 per cm resolution. There are also broad-band bolometric (4.5100 microns and solar reflectance (0.3-2.7 microns) channels. The TES was designed to have a noise equivalent spectral radiance of 1.2 x l0(exp -8) per W per square cm per sr per cm corresponding to a signal-to-noise ratio of 490 at 1000 per cm (10 mm) for a 270 K scene and preflight data suggest a radiometric accuracy of about 1.2 x 10(exp -8) per W per square cm per sr per cm. In-flight observations indicate a small systematic calibration offset of about 1.2 x 10(exp -7) per W per square cm per sr per cm is present in the TES data. MGS achieved Mars orbital insertion September 11, 1997, and entered the initial aerobraking phase. MGS should have reached a circular orbit by early 1998. However, structural damage to one solar panel occurred during its deployment in the cruise phase and ultimately required an assessment of the extent of the damage and a much slower aerobraking period. This has delayed reaching the final circular orbit until March 1999. TES and the other MGS science instruments began operating just after orbital insertion and continued to obtain data until November 1998 when the TES was turned off to reduce power consumption on the spacecraft. TES data obtained during orbits 2 to 53 have previously been published and clearly illustrate the variety of scientific questions that can be addressed with them.

Roush, T. L.↗

Machine learning assisted phase and size-controlled synthesis of iron oxide particles

Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in various fields, including materials science, energy storage, biomedical applications, environmental science, and earth science. However, despite significant advances in this area, much of the current palette of particle outcomes has been based on time-consuming trial-and-error exploration of synthesis conditions. The present study was designed to explore a very different approach to 1) predict the outcome of synthesis from specified reaction parameters based on using machine learning (ML) techniques, and 2) correlate sets of parameters to obtain products with desired outcomes by a newly designed recommendation algorithm. To achieve this, four ML algorithms were tested, namely random forest, logistic regression, support vector machine, and k-nearest neighbor. Among the models, random forest outperformed the others, attaining 96% and 81% accuracy when predicting the phase and size of iron oxide particles in the test dataset. Surprisingly, the permutation feature importance analysis revealed that volume, which may strongly relate to pressure, was one of the important features, along with precursor concentration, pH, temperature, and time, influencing the phase and size of iron oxide particles during synthesis. To verify the robustness of the random forest models, prediction and experimental results were compared based on 24 randomly generated methods in additive and non-additive systems not included in the datasets. The predictions of product phase and particle size from the models agreed well with the experimental results. Furthermore, a searching and ranking algorithm was developed to recommend potential synthesis parameters for obtaining iron oxide products with the desired phase and particle size from previous studies in the dataset. Furthermore, this study lays the foundation for a closed-loop approach in materials synthesis and preparation, beginning with suggesting potential reaction parameters from the dataset and predicting potential outcomes, followed by conducting experiments and analyses, and ultimately enriching the dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

In this paper, we developed a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of multiphase computational fluid dynamics (MCFD) simulations for bubbly flows. The proposed approach is supported by high-resolution two-phase flow measurements, including those by double-sensor conductivity probes, high-speed imaging, and particle image velocimetry. Local distributions of key physical quantities of interest (QoIs), including the void fraction and phasic velocities, are obtained to support the Bayesian inference. In the process, the epistemic uncertainties of the closure relations are inversely quantified while the aleatory uncertainties from stochastic fluctuations of the system are evaluated based on experimental uncertainty analysis. The combined uncertainties are then propagated through the MCFD solver to obtain uncertainties of the QoIs, based on which probability-boxes are constructed for validation. The proposed approach relies on three machine learning methods: feedforward neural networks and principal component analysis for surrogate modeling, and Gaussian processes for model form uncertainty modeling. The whole process is implemented within the framework of an open-source deep learning library PyTorch with graphics processing unit (GPU) acceleration, thus ensuring the efficiency of the computation. The results demonstrate that with the support of high-resolution data, the uncertainties of MCFD simulations can be significantly reduced. The proposed approach has the potential for other applications that involve numerical models with empirical parameters.

42 ENGINEERING↗

Quantum enhanced metrology in the search for fundamental physical phenomena

These notes summarize lectures given at the 2019 Les Houches summer school on Quantum Information Machines. They describe and review an application of quantum metrology concepts to searches for ultralight dark matter. In particular, for ultralight dark matter that couples as a weak classical force to a laboratory harmonic oscillator, quantum squeezing benefits experiments in which the mass of the dark matter particle is unknown. This benefit is present even if the oscillatory dark matter signal is much more coherent than the harmonic oscillator that it couples to, as is the case for microwave frequency searches for dark matter axion particles.

Lehnert, Konrad↗

Comprehensive Review of DPF-based Flash Neutron Radiography Viability

MJOLNIR (MegaJOule Neutron Imaging Radiography) is a Dense Plasma Focus (DPF) being developed by LLNL as a prototype to assess the viability of a DPF as a flash neutron radiography source. To date, MJOLNIR has discharged up to 1.3 MJ of stored energy into a deuterium plasma load and achieved yields up to 1.2 × 10 12 neutrons per discharge. The MJOLNIR pulse length already meets the preliminary requirements for flash neutron radiography and we demonstrate in this report plausible paths forward to meet the yield requirement in a deuterium plasma. MJOLNIR’s neutron spot size has been characterized to be a factor of two greater than radiography requirements and presents the greatest challenge. A path forward to sufficiently shrinking spot size is outlined in this report, using a combination of gas dopants and a smaller anode implosion radius. A DPF is a plasma device with coaxial electrodes whose discharge ends with a stagnated hot and dense plasma column on-axis, at the tip of the central anode. Inside the MJOLNIR DPF plasma column, both thermal and beam target processes generate neutrons. To understand the underlying physics of neutron generation inside the DPF, we model the experiment using a combination of kinetic, fluid, and reduced-order models we have been developing for over ten years at LLNL. Our numerical tools are also pivotal to charting the path forward because they allow us to numerically test out which modifications would improve the DPF’s characteristic output.

42 ENGINEERING↗