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At least 595 records · Page 33

Synchrotron infrared nano-spectroscopy and -imaging

Infrared (IR) spectroscopy has evolved into a powerful analytical technique to probe molecular and lattice vibrations, low-energy electronic excitations and correlations, and related collective surface plasmon, phonon, or other polaritonic resonances. In combination with scanning probe microscopy, near-field infrared nano-spectroscopy and -imaging techniques have recently emerged as a frontier in imaging science, enabling the study of complex heterogeneous materials with simultaneous nanoscale spatial resolution and chemical and quantum state spectroscopic specificity. Here, we describe synchrotron infrared nano-spectroscopy (SINS), which takes advantage of the low-noise, broadband, high spectral irradiance, and coherence of synchrotron infrared radiation for near-field infrared measurements across the mid- to far-infrared with nanometer spatial resolution. This powerful combination provides a qualitatively new form of broadband spatio-spectral analysis of nanoscale, mesoscale, and surface phenomena that were previously difficult to study with IR techniques, or even any form of micro-spectroscopy in general. We review the development of SINS, describe its technical implementations, and highlight selected examples representative of the rapidly growing range of applications in physics, chemistry, biology, materials science, geology, and atmospheric and space sciences.

47 OTHER INSTRUMENTATION↗

Rapid design of top-performing metal-organic frameworks with qualitative representations of building blocks

Abstract Data-driven materials design often encounters challenges where systems possess qualitative (categorical) information. Specifically, representing Metal-organic frameworks (MOFs) through different building blocks poses a challenge for designers to incorporate qualitative information into design optimization, and leads to a combinatorial challenge, with large number of MOFs that could be explored. In this work, we integrated Latent Variable Gaussian Process (LVGP) and Multi-Objective Batch-Bayesian Optimization (MOBBO) to identify top-performing MOFs adaptively, autonomously, and efficiently. We showcased that our method (i) requires no specific physical descriptors and only uses building blocks that construct the MOFs for global optimization through qualitative representations, (ii) is application and property independent, and (iii) provides an interpretable model of building blocks with physical justification. By searching only ~1% of the design space, LVGP-MOBBO identified all MOFs on the Pareto front and 97% of the 50 top-performing designs for the CO 2 working capacity and CO 2 /N 2 selectivity properties.

36 MATERIALS SCIENCE↗

Proximity ferroelectricity in wurtzite heterostructures

Proximity ferroelectricity is an interface-associated phenomenon in electric-field-driven polarization reversal in a non-ferroelectric polar material induced by one or more adjacent ferroelectric materials. Here, in this paper, we report proximity ferroelectricity in wurtzite ferroelectric heterostructures. In the present case, the non-ferroelectric layers are AlN and ZnO, whereas the ferroelectric layers are Al 1−x B x N, Al 1−x Sc x N and Zn 1−x Mg x O. The layered structures include nitride–nitride, oxide–oxide and nitride–oxide stacks that feature two-layer (asymmetric) and three-layer (symmetric) configurations. Ferroelectric switching in both layers is validated by multimodal characterization methods, including polarization hysteresis, anisotropic chemical etching, second harmonic generation, piezo response force microscopy, electromechanical testing and atomic resolution polarization orientation imaging in real space by scanning transmission electron microscopy. We present a physical switching model in which antipolar nuclei originate in the ferroelectric layer and propagate towards the internal non-ferroelectric interface. The domain wall leading edge produces elastic and electric fields that extend beyond the interface at close proximity, reducing the switching barrier in the non-ferroelectric layer, and allowing complete domain propagation without breakdown. Density functional theory calculations of polymorph energies, reversal barriers and domain wall energies support this model. Proximity ferroelectricity enables polarization reversal in wurtzites without the chemical or structural disorder that accompanies elemental substitution, opening new questions and opportunities regarding interface-based ferroelectricity.

36 MATERIALS SCIENCE↗

A detailed study of interpretability of deep neural network based top taggers

Abstract Recent developments in the methods of explainable artificial intelligence (XAI) allow researchers to explore the inner workings of deep neural networks (DNNs), revealing crucial information about input–output relationships and realizing how data connects with machine learning models. In this paper we explore interpretability of DNN models designed to identify jets coming from top quark decay in high energy proton–proton collisions at the Large Hadron Collider. We review a subset of existing top tagger models and explore different quantitative methods to identify which features play the most important roles in identifying the top jets. We also investigate how and why feature importance varies across different XAI metrics, how correlations among features impact their explainability, and how latent space representations encode information as well as correlate with physically meaningful quantities. Our studies uncover some major pitfalls of existing XAI methods and illustrate how they can be overcome to obtain consistent and meaningful interpretation of these models. We additionally illustrate the activity of hidden layers as neural activation pattern diagrams and demonstrate how they can be used to understand how DNNs relay information across the layers and how this understanding can help to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. These studies not only facilitate a methodological approach to interpreting models but also unveil new insights about what these models learn. Incorporating these observations into augmented model design, we propose the particle flow interaction network model and demonstrate how interpretability-inspired model augmentation can improve top tagging performance.

97 MATHEMATICS AND COMPUTING↗

Assessing the sources of reionization: a spectroscopic case study of a 30× lensed galaxy at z ~ 5 with Ly α , C IV, Mg ιι, and [Ne ιιι]

We present a detailed spectroscopic analysis of a galaxy at z ≃ 4.88 that is, by chance, magnified ~30× by gravitational lensing. Only three sources at z ≳ 5 are known with such high magnification. This particular source has been shown to exhibit widespread, high equivalent width ${{\rm C\, \small {IV}}}\ \lambda 1549\, \mathring{\rm A}$ emission, implying it is a unique example of a metal-poor galaxy with a hard radiation field, likely representing the galaxy population responsible for cosmic reionization. Using ultraviolet (UV) nebular line ratio diagnostics, Very Large Telescope (VLT)/X-shooter observations rule out strong active galactic nuclei (AGN) activity, indicating a stellar origin of the hard radiation field instead. We present a new detection of ${[{\rm Ne\, \small {III}}]}\ \lambda 3870\, \mathring{\rm A}$ and use the [${\rm Ne\, \small {III}}$]/[${\rm O\, \small {II}}$] line ratio to constrain the ionization parameter and gas-phase metallicity. Closely related to the commonly used [${\rm O\, \small {III}}$]/[${\rm O\, \small {II}}$] ratio, our [${\rm Ne\, \small {III}}$]/[${\rm O\, \small {II}}$] measurement shows this source is similar to local ‘Green Pea’ galaxies and Lyman-continuum leakers. It furthermore suggests this galaxy is more metal poor than expected from the fundamental metallicity relation, possibly as a consequence of excess gas accretion diluting the metallicity. Finally, we present the highest redshift detection of ${{\rm Mg\, \small {II}}}\ \lambda 2796\, \mathring{\rm A}$, observed at high equivalent width in emission, in contrast to more evolved systems predominantly exhibiting ${\rm Mg\, \small {II}}$ absorption. Strong ${\rm Mg\, \small {II}}$ emission has been observed in most z ~ 0 Lyman-continuum leakers known and has recently been proposed as an indirect tracer of escaping ionizing radiation. In conclusion, this strongly lensed galaxy, observed just $300\, \mathrm{Myr}$ after reionization ends, enables testing of observational diagnostics proposed to constrain the physical properties of distant galaxies in the James Webb Space Telescope (JWST)/Extremely Large Telescope (ELT) era.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine learning surrogate for charged particle beam dynamics with space charge based on a recurrent neural network with aleatoric uncertainty

In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through a lattice of 22 quadrupole magnets. Our ML model is developed based on data generated by a Kapchinsky–Vladimirsky (KV) envelope model of beam transport. We show that a recurrent neural network can be used as a dynamical surrogate model for fast prediction of the LEBT beam envelope. Furthermore, we endow the model with the prediction of aleatoric uncertainty and compare three different approaches. We demonstrate that the ML-based uncertainty quantification models are well calibrated and produce good estimates of the regions where the model is less certain about its predictions. This ML framework is a necessary step in the development of a real-time virtual diagnostic tool with uncertainty quantification that can be integrated into more complex downstream tasks (e.g., adaptive control or learning flexible control policies via reinforcement learning) for improved efficiency in beam operations. In future work, we plan to expand on this preliminary study by considering more realistic envelope models that include longitudinal momentum spread and dispersive effects in bending magnets, as well as particle tracking codes with 3D space charge (such as and ). Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Equivalence of EFTs and timelike extra dimensions

A flat 3-brane probing a five-dimensional anti–de Sitter space has the same symmetries and symmetry breaking pattern as one probing a five-dimensional de Sitter space with two time directions. Despite the seemingly different physical setups, we show that the effective field theory of the brane bending mode is identical in both cases. In particular, despite “wrong” signs in the Dirac-Born-Infeld (DBI) action for the two-time de Sitter case, the theories have the same S -matrix. This is consistent with the expectation that effective field theories are determined solely by their degrees of freedom and pattern of symmetry breaking, even in the case of spacetime symmetries. We comment further on the equivalence between the Weyl/dilaton and DBI representations of the EFT of broken conformal symmetry. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Streamlining latent spaces in machine learning using moment pooling

Many machine learning applications involve learning a latent representation of data, which is often high-dimensional and difficult to directly interpret. In this work, we propose “moment pooling,” a natural extension of deep sets networks which drastically decreases the latent space dimensionality of these networks while maintaining or even improving performance. Moment pooling generalizes the summation in deep sets to arbitrary multivariate moments, which enables the model to achieve a much higher effective latent dimensionality for a fixed learned latent space dimension. We demonstrate moment pooling on the collider physics task of quark/gluon jet classification by extending energy flow networks (EFNs) to moment EFNs. We find that moment EFNs with latent dimensions as small as 1 perform similarly to ordinary EFNs with higher latent dimension. This small latent dimension allows for the internal representation to be directly visualized and interpreted, which in turn enables the learned internal jet representation to be extracted in closed form. Published by the American Physical Society 2024

Gambhir, Rikab (ORCID:0000000251080448)↗

GALILEO: Galactic Axion Laser Interferometer Leveraging Electro-Optics

We propose a novel experimental method for probing light dark matter candidates. We show that an electro-optical material’s refractive index is modified in the presence of a coherently oscillating dark matter background. A high-precision resonant Michelson interferometer can be used to read out this signal. The proposed detection scheme allows for the exploration of an uncharted parameter space of dark matter candidates over a wide range of masses—including masses exceeding a few tens of microelectronvolts, which is a challenging parameter space for microwave cavity haloscopes. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Microbiome dynamics in the congregate environment of U.S. Army Infantry training

Within military training and operational environments, individuals from diverse backgrounds share common spaces, follow structured routines and diets, and engage in physically demanding tasks. While there has been interest in leveraging microbiome features to predict and improve military health and performance, the longitudinal convergence of microbiomes in such constrained environments has not been established. To assess the degree of microbiome convergence, we performed shotgun metagenomic sequencing on swab samples from a military trainee cohort. Samples were taken across four different body sites, three timepoints, and two spatially distinct platoons. We observed evidence of convergence in one platoon, whereby similarity in microbiome composition increased over time, with numerous differentially abundant species. We found no indication of strain transfer between individuals, suggesting that convergence was influenced by external environmental factors, diet, and lifestyle. Microbial shifts observed in the convergence process included a decrease in fungal species, such as Malassezia restricta in nasal cavities, and a decrease in Prevotella species at inguinal regions across time. Shifts in multiple Corynebacterium species were also observed with varying magnitudes depending on the body site. Overall, we provide preliminary evidence of convergence of host microbial communities in military-associated environments that were distinguishable using shotgun metagenomic sequencing approaches. The data presented here on microbiome convergence, dynamics, and stability may inform risk-based mitigation in congregate military settings facilitating development of targeted microbial, dietary, or other interventions to optimize health and performance of military populations.

Biological and medical sciences↗

A Succession of Cloud, Precipitation, Aerosol and Air Quality Field Experiments in the Coastal Urban Environment

The interactions and feedbacks among clouds, aerosols, pollutants, and the thermodynamic and kinematic environment remains an area of active research with important implications for our understanding of climate, weather and air quality. These linkages are further complicated in coastal and urban environments where local circulations and anthropogenic influences impact each of these components and their interactions. Within this context, fundamental questions regarding the lifecycle of convective clouds, aerosols and pollutants have brought together a diverse, integrated, and interagency collaboration of scientists to collect and analyze measurements, in the Houston, Texas, area, from the summer of 2021 through the summer of 2022, with subsequent modeling studies to address these important research objectives. Herein, the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility and Atmospheric System Research (ASR) Program, the National Science Foundation’s (NSF) Physical and Dynamic Meteorology Program, the National Aeronautic and Space Administration’s (NASA’s) Tropospheric Composition Research and Health and Air Quality Applied Sciences Programs and the Texas Commission on Environmental Quality (TCEQ) are collaborating on a joint set of field campaigns to study the interactions of cloud, aerosol, and pollutants within the coastal, urban environment. In the Houston area, onshore flow from the Gulf of Mexico and the associated sea breeze circulation generates numerous isolated convective cells, particularly in the summer months, that interact with a variety of urban and industrial emissions.

54 ENVIRONMENTAL SCIENCES↗

EXPLAINABLE AND TRUSTWORTHY DIAGNOSTICS ACHIEVABLE THROUGH PROCESS-BASED AUTOMATED REASONING

An approach has been developed that incorporates domain knowledge to obtain a more explainable and trustworthy equipment health monitoring diagnosis than might otherwise be obtained from a purely data-driven method. Physics-based models serve to constrain the realizable solution space and render a more trusted diagnosis. An automated reasoning algorithm performs backward chaining to infer a diagnosis that is consistent with logic statements that have been evaluated as true. This diagnosis is made explainable to an operator by providing the forward chaining path that elucidates for inspection and validity testing those truths implied by the diagnosis.

automated reasoning↗

13 TeV pp collisions, Exotics type, PYTHIA8 generator: tev13pp_pythia8_gkk2radion2gg

Production of Gkk (with different masses) decaying to a radion and Z boson. The radion decays to 2 gluons. Z boson decays to leptons. The events are designed to study kinematics of events. Each file is created with a fixed mass of Gkk and radion, assuming that the mass of M(Gkk)>M(radion)+M(Z0). The mass for Gkk and radion is included as pythia8_gkk2radion2gg_g[M1]_r[M2] where M1 is the mass of Gkk (in GeV), and M2 is the mass of radion (in GeV). 5000 events generated per file. Event record is slimmed to reduce the disk space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Laboratory Study of the Torus Instability Threshold in Solar-relevant, Line-tied Magnetic Flux Ropes

Coronal mass ejections (CMEs) occur when long-lived magnetic flux ropes (MFRs) anchored to the solar surface destabilize and erupt away from the Sun. This destabilization is often described in terms of an ideal magnetohydrodynamic instability called the torus instability. It occurs when the external magnetic field decreases sufficiently fast such that its decay index, ${n}_{}=-z\,\partial (\mathrm{ln}{B}_{})/\partial z$, is larger than a critical value, $n\gt {n}_{\mathrm{cr}}^{}$, where ${n}_{\mathrm{cr}}^{}=1.5$ for a full, large aspect ratio torus. However, when this is applied to solar MFRs, a range of conflicting values for ${n}_{\mathrm{cr}}^{}$ is found in the literature. To investigate this discrepancy, we have conducted laboratory experiments on arched, line-tied flux ropes and applied a theoretical model of the torus instability. Our model describes an MFR as a partial torus with foot points anchored in a conducting surface and numerically calculates various magnetic forces on it. This calculation yields better predictions of ${n}_{\mathrm{cr}}^{}$ that take into account the specific parameters of the MFR. Here, we describe a systematic methodology to properly translate laboratory results to their solar counterparts, provided that the MFRs have a sufficiently small edge safety factor or, equivalently, a large enough twist. After this translation, our model predicts that ${n}_{\mathrm{cr}}^{}$ in solar conditions falls near ${n}_{\mathrm{cr}}^{\mathrm{solar}}\sim 0.9$ and within a larger range of ${n}_{\mathrm{cr}}^{\mathrm{solar}}\sim (0.7,1.2)$, depending on the parameters. The methodology of translating laboratory MFRs to their solar counterparts enables quantitative investigations of CME initiation through laboratory experiments. These experiments allow for new physics insights that are required for better predictions of space weather events but are difficult to obtain otherwise.

79 ASTRONOMY AND ASTROPHYSICS↗

Forecasts for Galaxy Formation and Dark Matter Constraints from Dwarf Galaxy Surveys

Abstract The abundance of faint dwarf galaxies is determined by the underlying population of low-mass dark matter (DM) halos and the efficiency of galaxy formation in these systems. Here, we quantify potential galaxy formation and DM constraints from future dwarf satellite galaxy surveys. We generate satellite populations using a suite of Milky Way (MW)–mass cosmological zoom-in simulations and an empirical galaxy–halo connection model, and assess sensitivity to galaxy formation and DM signals when marginalizing over galaxy–halo connection uncertainties. We find that a survey of all satellites around one MW-mass host can constrain a galaxy formation cutoff at peak virial masses of M 50 = 10 8 M ⊙ at the 1 σ level; however, a tail toward low M 50 prevents a 2 σ measurement. In this scenario, combining hosts with differing bright satellite abundances significantly reduces uncertainties on M 50 at the 1 σ level, but the 2 σ tail toward low M 50 persists. We project that observations of one (two) complete satellite populations can constrain warm DM models with m WDM ≈ 10 keV (20 keV). Subhalo mass function (SHMF) suppression can be constrained to ≈70%, 60%, and 50% that in cold dark matter (CDM) at peak virial masses of 10 8 , 10 9 , and 10 10 M ⊙ , respectively; SHMF enhancement constraints are weaker (≈20, 4, and 2 times that in CDM, respectively) due to galaxy–halo connection degeneracies. These results motivate searches for faint dwarf galaxies beyond the MW and indicate that ongoing missions like Euclid and upcoming facilities including the Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope will probe new galaxy formation and DM physics.

79 ASTRONOMY AND ASTROPHYSICS↗

A Material Frame: Hard Recoils from Slow Force Carriers

We modify the Standard Model by making the longitudinal component of the photon physical, propagating with small speed $c_L \ll 1$. This modification breaks gauge invariance and Lorentz symmetry, defining a preferred reference frame. No new fields or scales are introduced, and the photon mass is protected by a Galilean higher-form symmetry. The theory has a smooth $c_L\to0$ limit: the new modes decouple from standard matter and ordinary gauge theory predictions are recovered. Experimental constraints are severe. Charged particles Cherenkov-emit these slow modes, experiencing hard recoils against the preferred frame. The recoil rate decreases with $c_L$, but the momentum transfer remains of the order of the particle's momentum. Dark matter detectors, sensitive to keV-scale nuclear recoils, imply an order-of-magnitude bound $c_L \lesssim 10^{-60}$, tens of orders of magnitude stronger than speed-difference bounds. At such values, $c_L$ is better understood as a recoil-rate factor rather than a physically relevant speed. The slow modes, practically fixed in space, make the reference frame a material medium capable of absorbing momentum from charged particles.

Serra, Francesco [Johns Hopkins U.]↗

Ab initio multishell valence-space Hamiltonians and the island of inversion

In the shell-model framework, valence-space Hamiltonians connecting multiple major-oscillator shells are of key interest for investigating the physics of neutron-rich nuclei, which have been the subject of intense experimental activity for decades. Here we present an extension of the ab initio valence-space in-medium similarity renormalization group, which allows the derivation of such Hamiltonians nonperturbatively. Starting from initial two- and three-nucleon forces from chiral effective field theory, we then calculate properties of nuclei in the important island-of-inversion region above oxygen, so far unexplored with ab initio methods. In this work, our results in the neon and magnesium isotopes indicate the importance of neutron excitation from the $\textit{sd}$ to $\textit{pf}$ shells and ground states dominated by intruder configurations around $\textit{N}$ = 20, consistent with the conclusions from phenomenological studies. We also benchmark the excitation spectrum of 16 O with coupled-cluster theory, finding generally good agreement, and discuss implications for ground-state energies and charge radii in oxygen and calcium isotopes. Finally we outline the proper procedure for treating the longstanding issue of center-of-mass contamination, and show that with a particular choice of valence space, these spurious states can be removed successfully.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

CAS without SCF—Why to use CASCI and where to get the orbitals

The complete active space self-consistent field (CASSCF) method has seen broad adoption due to its ability to describe the electronic structure of both the ground and excited states of molecules over a broader swath of the potential energy surface than is possible with the simpler Hartree–Fock approximation. However, it also has a reputation for being unwieldy, computationally costly, and un-black-box. Here, we discuss a class of alternatives, complete active space configuration interaction (CASCI) methods, paying particular attention to their application to electronic excited states. The goal of this Perspective is fourfold. First, we argue that CASCI is not merely an approximation to CASSCF, in that it can be designed to have important qualitative advantages over CASSCF. Second, we present several insights drawn from our experience experimenting with different schemes for computing orbitals to be employed in CASCI. Third, we argue that CASCI is well suited for application to nanomaterials. Lastly, we reason that, with the rise in new low-scaling approaches for describing multireference systems, there is a greater need than ever to develop new methods for defining orbitals that provide an efficient and accurate description of both static correlation and electronic excitations in a limited active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗