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At least 739 records · Page 41

Disoriented isospin condensates in heavy-ion collisions

Anomalous neutral to charged kaon correlations measured by the ALICE collaboration have defied usual explanations. We propose that the large fluctuations could arise because of a disoriented isospin condensate where there is an imbalance between up and down condensates at the time kaons hadronize. This could happen in heavy-ion collisions when the quark condensate re-forms as the system cools and the approximate chiral symmetry of QCD is broken. Within the linear sigma model, we show that the energy cost of forming a disoriented isospin condensate is small making it very plausible.

Kapusta, Joseph [University of Minnesota, Minneapo↗

Electrical conductivity of multilayered Cu/Nb composites fabricated by accumulative roll bonding

The electrical conductivity of nanolayered copper/niobium composites fabricated using accumulative roll bonding was investigated as a function of layer thickness. Cu/Nb was used as a model system to evaluate the processing-structure–property relationship stemming from the accumulative roll bonding process. The physical properties were compared against samples of individual average layer heights ranging from 193 to 25 nm. The electrical resistivity was measured over a temperature range of ~3–300 K. Analysis on the role of interfaces on temperature dependence is conducted including the residual resistivity ratio and temperature coefficient of resistivity. It was found that electrical resistivity increases with decreasing layer height.

36 MATERIALS SCIENCE↗

An information-matching approach to optimal experimental design and active learning

The efficacy of mathematical models heavily depends on the quality of the training data, yet collecting sufficient data is often expensive and challenging. Many modeling applications require inferring parameters only as a means to predict other quantities of interest (QoI). Because models often contain many unidentifiable (sloppy) parameters, QoIs often depend on a relatively small number of parameter combinations. Therefore, we introduce an information-matching criterion based on the Fisher information matrix to select the most informative training data from a candidate pool. This method ensures that the selected data contain sufficient information to learn only those parameters that are needed to constrain downstream QoIs. It is formulated as a convex optimization problem, making it scalable to large models and datasets. Here, we demonstrate the effectiveness of this approach across various modeling problems in diverse scientific fields, including power systems and underwater acoustics. Finally, we use information-matching as a query function within an active learning (AL) loop for materials science applications. In all these applications, we find that a relatively small set of optimal training data can provide the necessary information for achieving precise predictions. These results are encouraging for diverse future applications, particularly AL in large machine-learning models.

Materials science↗

Quantifying the relationship between electric field enhancement and plasmon-driven electron transfer

Plasmonic materials interact strongly with light to create localized, out-of-equilibrium environments with intense electromagnetic fields known as hotspots. After forming, hotspots dissipate energy into their surroundings and can transfer energy and charge carriers to nearby molecules, giving plasmonic materials the potential to drive reactions with sunlight. However, the field needs a better mechanistic understanding of plasmon–molecule interactions and how the local plasmon environment, specifically the electromagnetic field enhancement and spatial distribution of hotspots, impacts the reaction yield. Here, in this work, we mapped plasmon-driven charge transfer across ordered plasmonic substrates using diffraction-limited surface-enhanced Raman spectroscopy (SERS) microscopy to understand the relationship between the average local electric field enhancement and charge transfer reaction yield. We tracked the plasmon-induced electron transfer to buckminsterfullerene (C 60 ) and found that areas with the greatest SERS intensity were not the areas with the greatest ensemble-averaged reduction of C 60 , suggesting that areas with higher electric field enhancement—or “hotter,” more enhancing hotspots—do not improve the charge transfer reaction yield. This work shows that efforts to improve plasmon-driven charge transfer should not merely focus on creating substrates with extremely enhancing regions but also consider how other factors could optimize photoreduction yields.

Koble, MaKenna M. [Univ. of Minnesota, Minneapolis↗

Experimental electronic structures of the Fe IV =O bond in S=1 heme vs. nonheme sites: Effect of the porphyrin ligand

High-valent Fe IV =O species are common intermediates in biological and artificial catalysts. Heme and nonheme S=1 Fe IV =O sites have been synthesized and studied for decades but little quantitative experimental comparison of their electronic structures has been available, due to the lack of direct methods focused on the iron. This study allows a rigorous determination of the electronic structure of a nonheme Fe IV =O center and its comparison to an Fe IV =O heme site using 1s2p resonant inelastic X-ray scattering (RIXS) and Fe L-edge X-ray absorption spectroscopy (XAS). Further, variable temperature magnetic circular dichroism (VT-MCD) of the ligand field transitions, combined with nuclear resonance vibrational spectroscopy of the two S=1 Fe IV =O systems show that the equatorial ligand field decreases from a nonheme to a heme Fe IV =O site. Alternatively, RIXS and Fe L-edge XAS combined with MCD show that the Fe dπ orbitals are unperturbed in the Fe IV =O heme relative to the nonheme site because the strong axial Fe-O bond uncouples the Fe dπ orbitals from the porphyrin π-system. As a consequence, the thermodynamics and kinetics of the H-atom abstraction reactions are actually very similar for heme compound II and nonheme Fe IV =O active sites.

bioinorganic chemistry↗

Elastocaloric evidence for a multicomponent superconductor stabilized within the nematic state in Ba(Fe 1− x Co x ) 2 As 2

The iron-based high-$T_c$ superconductors (SCs) exhibit rich phase diagrams with intertwined phases, including magnetism, nematicity, and superconductivity. The superconducting $T_c$ in many of these materials is maximized in the regime of strong nematic fluctuations, making the role of nematicity in influencing the superconductivity a topic of intense research. Here, in this study, we use the AC elastocaloric effect (ECE) to map out the phase diagram of Ba(Fe 1− x Co x ) 2 As 2 near optimal doping. The ECE signature at $T_c$ on the overdoped side, where superconductivity condenses without any nematic order, is quantitatively consistent with other thermodynamic probes that indicate a single-component superconducting state. In contrast, on the slightly underdoped side, where superconductivity condenses within the nematic phase, ECE reveals a second thermodynamic transition proximate to and below $T_c$. We rule out magnetism and reentrant tetragonality as the origin of this transition and find that our observations strongly suggest a phase transition into a multicomponent superconducting state. This implies the existence of a subdominant pairing instability that competes strongly with the dominant $s^±$ instability. Our results highlight the significant role of nematic order in determining the pairing symmetry close to optimal doping in this extensively studied iron-based SC, while also demonstrating the power of ECE in uncovering strain-tuned phase diagrams of quantum materials.

Ghosh, Sayak [Stanford University, CA (United Stat↗

Quasiclassical sampling and Wigner sampling of initial vibrational coordinates and momenta for polyatomic molecules in Monte Carlo molecular dynamics simulations

In a quasiclassical trajectory simulation, the vibrational modes are initialised with quantised vibrational energies, but vibrational phases are sampled by Monte Carlo. This requires an algorithm to assign coordinates and momenta to the various atoms. In this work, we present two methods for implementing this for nonrotating polyatomic molecules, namely, fixed-energy vibrational-state-selected initial conditions and thermal initial conditions. We also present a method for initiating classical trajectories with a ground-state Wigner distribution. These vibrational treatments are sufficient to initialise trajectories for unimolecular processes, and we also show how they can be applied to simulate bimolecular collision processes. The treatments of unimolecular and bimolecular collision processes are available in two Python codes called wigner_state_selected.py and bimolecular_collision.py, respectively, which will generate initial condition files that are recognisable by the SHARC and SHARC-MN computer programs for dynamics calculations. Both codes are available as standalone programs, as well as being included in SHARC-MN, and they will be included in future versions of SHARC. Here, the methods implemented in these codes are mostly also available in the ANT computer program, and those that are not available in ANT will be incorporated in future versions of ANT.

Wigner distribution↗

Baryon number violation: from nuclear matrix elements to BSM physics

Processes that violate baryon number, most notably proton decay and $n\bar{n}$ transitions, are promising probes of physics beyond the Standard Model (BSM) needed to understand the lack of antimatter in the Universe. To interpret current and forthcoming experimental limits, theory input from nuclear matrix elements to UV complete models enters. Thus, an interplay of experiment, effective field theory, lattice QCD, and BSM model building is required to develop strategies to accurately extract information from current and future data and maximize the impact and sensitivity of next-generation experiments. Here, we briefly summarize the main results and discussions from the workshop ‘INT-25-91W: Baryon Number Violation: From Nuclear Matrix Elements to BSM Physics,’ held at the Institute for Nuclear Theory, University of Washington, Seattle, WA, 13–17 January 2025.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Inferring Neutron Star Merger Ejecta Morphology with Kilonovae

In this study we incorporate a new grid of kilonova simulations produced by the Monte Carlo radiative transfer code SuperNu in an inference pipeline for astrophysical transients and evaluate their performance. These simulations contain four different two-component ejecta morphology classes. We analyze follow-up observational strategies by Vera Rubin Observatory in optical and James Webb Space Telescope (JWST) in mid-infrared (MIR). Our analysis suggests that, within these strategies, it is possible to discriminate between the four different morphologies only when late-time JWST observations in MIR are available. We conclude that follow-ups by the new Vera Rubin Observatory alone are not sufficient to determine ejecta morphology. Additionally, we make comparisons between surrogate models based on radiative transfer simulation grids by SuperNu and POSSIS, by analyzing the historic kilonova AT2017gfo that accompanied the gravitational wave event GW170817. We show that both SuperNu and POSSIS models provide similar fits to photometric observations but their qualitative interpretations differ.

79 ASTRONOMY AND ASTROPHYSICS↗

Pre-training Vision Models for the Classification of Alerts from Wide-field Time-domain Surveys

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.

79 ASTRONOMY AND ASTROPHYSICS↗

N 2 Onet: a global collaborative network facilitating advances in measurement, modeling, and mitigation of agricultural soil nitrous oxide emissions

Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identified in a workshop of N 2 O emissions experts include poor process-based understanding of controls on soil N 2 O emissions in the field; insufficient data to reduce uncertainty in N 2 O budgets from the field to regional scales, including N 2 O emission measurements and importantly, field-scale N balances; and high uncertainty in model predictions of soil N 2 O emissions across environmental and management conditions. To reduce these uncertainties, we present the concept of N 2 Onet, a global collaborative initiative to accelerate advances in N 2 O measurement, analyses, and mitigation. N 2 Onet will serve as an observational network of supersites with multi-scale measurements; a database hub for N 2 O flux and ancillary data; and a catalyst for community building, information sharing, and training. By coalescing and coordinating the global community of researchers, N 2 Onet will provide a roadmap for reducing N 2 O emissions from agriculture worldwide.

54 ENVIRONMENTAL SCIENCES↗

An atomic cluster expansion potential for twisted multilayer graphene

Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning interatomic potentials (MLIPs) are a promising approach to model such systems. Our work develops a method to generate training and test datasets for fitting MLIPs that capture all possible misalignments but remain small-scale to facilitate efficient data generation and parameter estimation. To achieve this, we generate configurations with periodic boundary conditions suitable for density functional theory calculations, and then introduce an internal twist and shift within those supercell structures. Using this technique, supplemented with an active learning workflow, we fit an Atomic Cluster Expansion potential for simulating twisted multilayer graphene and test it for accuracy and robustness on a range of simulation tasks.

2D materials↗

Scaling relations in the phase-space structure of dark matter haloes

We present new scaling relations for the isotropic phase-space distribution functions (DFs) and energy distributions of simulated dark matter haloes. These relations are inspired by those for the singular isothermal sphere with density profile $\rho (r)\propto r^{-2}$, for which the DF satisfies $f(E) \propto r_{\mathrm{max}}^{-2}(E)$ and the energy distribution satisfies $\mathrm{ d}M/\mathrm{ d}E \propto r_{\mathrm{max}}(E)$, with $r_{\mathrm{max}}(E)$ being the radius where the gravitational potential equals energy $E$. For the simulated haloes, we find $f(E)\propto r_{\mathrm{max}}^{-2.08}(E)$ and $\mathrm{ d}M/\mathrm{ d}E \propto r_{\mathrm{max}}(E)$ across broad energy ranges. In addition, the proportionality coefficients depend on the gravitational constant and the parameters of the best-fitting Navarro–Frenk–White density profile. These scaling relations are satisfied by haloes over a wide mass range and provide an efficient method to approximate their DFs and energy distributions. Understanding the origin of these relations may shed more light on halo formation.

galaxies: haloes↗

Interplay between aging and rejuvenation in spin glasses

Aging in a single-crystal spin glass (Cu 0.92 ⁢Mn 0.08 ) has been measured using ac susceptibility techniques over a temperature range of 0.3–0.8𝑇 𝑔 . In these studies, traditional aging experiments (or “quench” aging protocols) are compared to aging curves constructed from finite-cooling-rate curves. By comparing the growth rates of spin glass order between the two types of aging curves, it is determined that quantitative comparisons between protocols that are taken by quenching and protocols using a finite cooling rate are not possible without a deeper understanding of the interplay between aging and rejuvenation. Finally, we then demonstrate that the data presented indicate that rejuvenation, rather than cumulative aging, is the cause of the discrepancies between the two growth rates.

dynamical phase transitions↗

Conventional superconductivity in single-crystalline BiPt

Binary Bi-Pd/Pt systems have attracted a lot of interest because of their topologically nontrivial nature along with superconductivity. We report the structural and superconducting properties of high-quality single-crystalline BiPt using a comprehensive range of experimental techniques, including X-ray diffraction, electron microscopy, muon spin rotation/relaxation (𝜇⁢SR), magnetization, resistivity, and heat capacity. Our findings establish that BiPt is a weak type-II superconductor with a transition temperature (𝑇 𝑐 ) of 1.2 K which exhibits pronounced anisotropic superconducting characteristics attributed to its hexagonal crystal structure. Magnetization and electronic transport studies reveal that BiPt lies within the dirty limit, while 𝜇⁢SR and heat capacity data indicate conventional 𝑠-wave superconductivity that maintains time-reversal symmetry. Here, this work provides valuable insights into the pairing symmetry and superconducting mechanism of topologically trivial BiPt, a sound comparison system for other Bi-based topologically nontrivial superconductors.

Demagnetization↗

Sampling off-axis neutrino fluxes with the short-baseline near detector

The short-baseline near detector (SBND), the near detector in the short-baseline neutrino program at Fermi National Accelerator Laboratory, is located just 110 m from the booster neutrino beam target. Thanks to this close proximity, relative to its 4 m × 4 m front face, neutrinos enter SBND over a range of angles from 0° to approximately 1.6°, enabling the detector to sample variations in the neutrino flux as a function of the angle—a technique known as precision reaction-independent spectrum measurement (PRISM), referred to here as SBND-PRISM. In this paper, we show how muon- and electron-neutrino fluxes vary as a function of the neutrino beam axis angle and how this can be exploited to expand the physics potential of SBND. We make use of a model that predicts an angle-dependent electron-neutrino excess signal to illustrate this effect, such as 𝜈 𝜇 → 𝜈 𝑒 oscillations. We present how SBND-PRISM provides a method to add robustness against uncertainties in cross-section modeling and, more generally, uncertainties that do not depend on the spatial position of neutrino interaction inside the detector. The fluxes, along with their associated covariance matrices, are made publicly available with this publication.

Abratenko, P. [Tufts University]↗

First Limits on Light Dark Matter Interactions in a Low Threshold Two-Channel Athermal Phonon Detector from the TESSERACT Collaboration

We present results of a search for spin-independent dark matter-nucleus interactions in a 1 cm 2 by 1 mm thick (0.233 g) high-resolution silicon athermal phonon detector operated above ground. For interactions in the substrate, this detector achieves an rms baseline energy resolution of 361.5⁢(4) m⁢ eV (statistical error), the best for any athermal phonon detector to date. With an exposure of 0.233 g ×12 hours, we place the most stringent constraints on dark matter masses between 44 and 87 M⁢ eV/c 2 , with the lowest unexplored cross section of 4⁢ × 10 −32 c⁢m 2 at 87 M⁢ eV/c 2 . We employ a conservative salting technique to reach the lowest dark matter mass ever probed via direct detection experiment. This constraint is enabled by two-channel rejection of low energy backgrounds that are coupled to individual sensors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Two-Step Procedure to Detect Cosmological Gravitational Wave Backgrounds with Next-Generation Terrestrial Gravitational-Wave Detectors

Cosmological gravitational-wave backgrounds are an exciting science target for next-generation ground-based detectors, as they encode invaluable information about the primordial Universe. However, any such background is expected to be obscured by the astrophysical foreground from compact-binary coalescences. We propose a novel framework to detect a cosmological gravitational-wave background in the presence of binary black holes and binary neutron star signals with next-generation ground-based detectors, including Cosmic Explorer and the Einstein Telescope. Our procedure involves first removing all the individually resolved binary black hole signals by notching them out in the time-frequency domain. Then, we perform joint Bayesian inference on the individually resolved binary neutron star signals, the unresolved binary neutron star foreground, and the cosmological background. For a flat cosmological background, we find that we can claim detection at 5⁢𝜎 level when Ω ref ≥ 2.7 × 10 −12 /$\sqrt{𝑇_{obs}/yr}$, where 𝑇 obs is the observation time (in years), which is within a factor of ≲ 2 from the sensitivity reached in the absence of these astrophysical foregrounds.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗