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At least 307 records · Page 17

Continuum of magnetic excitations in the Kitaev honeycomb iridate D 3 LiIr 2 O 6

Inelastic neutron scattering (INS) measurements of powder D 3 ( 7 Li)( 193 Ir) 2 O 6 reveal low energy magnetic excitations with a scattering cross-section that is broad in ∣Q∣ and energy transfer. The magnetic nature of the excitation spectrum is demonstrated by longitudinally polarized neutron scattering. The total magnetic moment of 1.8(4)μ B /Ir inferred from the observed magnetic scattering cross-section is consistent with the effective moment inferred from magnetic susceptibility data and expectations for the J eff = 1/2 single ion state. The rise in the dynamic correlation function $\mathcal{S}(Q,w)$ for ℏω < 5 meV can be described by a simple model assuming nearest-neighbor anisotropic spin exchange, such as that found in the Kitaev model. Exchange disorder associated with the D site likely plays an important role in stabilizing the low T quantum fluctuating state.

Halloran, Thomas [Johns Hopkins Univ., Baltimore, ↗

FilDReaMS: II. Application to the analysis of the relative orientations between filaments and the magnetic field in four Herschel fields

Context. Both simulations and observations of the interstellar medium show that the study of the relative orientations between filamentary structures and the magnetic field can bring new insight into the role played by magnetic fields in the formation and evolution of filaments and in the process of star formation. Aims. We provide a first application of FilDReaMS, the new method presented in the companion paper to detect and analyze filaments in a given image. The method relies on a template that has the shape of a rectangular bar with variable width. Our goal is to investigate the relative orientations between the detected filaments and the magnetic field. Methods. We apply FilDReaMS to a small sample of four Herschel fields (G210, G300, G82, G202) characterized by different Galactic environments and different evolutionary stages. First, we look for the most prevalent bar widths, and we examine the networks formed by filaments of different bar widths as well as their hierarchical organization. Second, we compare the filament orientations to the magnetic field orientation inferred from Planck polarization data and, for the first time, we study the statistics of the relative orientation angle as functions of both spatial scale and H2 column density. Results. We find preferential relative orientations in the four Herschel fields: small filaments with low column densities tend to be slightly more parallel than perpendicular to the magnetic field; in contrast, large filaments, which all have higher column densities, are oriented nearly perpendicular (or, in the case of G202, more nearly parallel) to the magnetic field. In the two nearby fields (G210 and G300), we observe a transition from mostly parallel to mostly perpendicular relative orientations at an H 2 column density ≃ 1.1 × 10 21 cm -2 and 1.4 × 10 21 cm -2 , respectively, consistent with the results of previous studies. Conclusions. Our results confirm the existence of a coupling between magnetic fields at cloud scales and filaments at smaller scale. They also illustrate the potential of combining Herschel and Planck observations, and they call for further statistical analyses with our dedicated method.

79 ASTRONOMY AND ASTROPHYSICS↗

The trailing edge is everywhere: tree rings reveal the transient risk of extinction hidden inside climate envelope forecasts

Given the importance of climate in shaping species’ geographic distributions, climate change poses an existential threat to biodiversity. Climate envelope modeling, the predominant approach used to quantify this threat, presumes that individuals in populations respond to climate variability and change according to species-level responses inferred from spatial occurrence data—such that individuals at the cool edge of a species’ distribution should benefit from warming (the “leading edge”), whereas individuals at the warm edge should suffer (the “trailing edge”). Using 1,558 tree-ring time series of an aridland pine (Pinus edulis) collected at 977 locations across the species’ distribution, we found that trees everywhere grow less in warmer-than-average and drier-than-average years. Ubiquitous negative temperature sensitivity indicates that individuals across the entire distribution should suffer with warming—the entire distribution is a trailing edge. Species-level responses to spatial climate variation are opposite in sign to individual-scale responses to time-varying climate for approximately half the species’ distribution with respect to temperature and the majority of the species’ distribution with respect to precipitation. These findings, added to evidence from the literature for scale-dependent climate responses in hundreds of species, suggest that correlative, equilibrium-based range forecasts may fail to accurately represent how individuals in populations will be impacted by changing climate. A scale-dependent view of the impact of climate change on biodiversity highlights the transient risk of extinction hidden inside climate envelope forecasts and the importance of evolution in rescuing species from extinction whenever local climate variability and change exceeds individual-scale climate tolerances.

54 ENVIRONMENTAL SCIENCES↗

Information and Statistics in Nuclear Experiment and Theory (ISNET)

As with all empirical sciences, nuclear physics operates in the virtuous cycle of the scientific method: observations inspire theoretical models; models lead to new predictions; predictions are tested in experiments; experiments lead to new observations; and so on. Evaluating what we are inferring, and how certain we are of it, is key to this process. These requirements, and a general interest in applying novel statistical, mathematical, and computational techniques, led to the formation of a dedicated research community entitled “Information and Statistics in Nuclear Experiment and Theory (ISNET)” (https://isnet-series.github.io/), which now includes more than 300 members. While the community’s interests lean toward nuclear theory, the unifying theme for this group is the inference of knowledge from data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analysis of Design Alternatives of Actively Cooled RF Window for MPEX

The Materials Plasma Exposure eXperiment (MPEX) has been designed as a linear plasma divertor simulator in order to address plasma material interaction (PMI) science for next-generation fusion devices. It will have the capability to test neutron irradiated samples with plasma fluxes of greater than 10 24 m -2 s -1 . It is expected to operate steady state for up to 10 6 s to consider PMI affects through reactor end of life. The conceptual design of MPEX was completed in 2019, with preliminary design having begun in 2020. The plasma source for MPEX is a helicon antenna, where the energized helical antenna sits outside of the vacuum in order to minimize impurities in the plasma. It is expected to receive up to 200 kW of continuous power, and so the antenna and the window must be actively cooled. The water-cooled copper antenna has been operated at full power on the Proto-MPEX device (which is a test facility to demonstrate the plasma source and heating systems). The water-cooled window, however, is a novel component that must meet numerous competing requirements. It requires a low dielectric loss to allow the Radio Frequency (RF) power to create the plasma within the vacuum boundary. It must be structurally robust to handle the significant heat flux from the plasma and any heat from dielectric coupling. It must be compatible with the coolant (preferably water). It requires a vacuum seal that minimizes impurities into the plasma and does not compromise the structural integrity of the window. Two window designs have been tested. Results from these tests, where temperatures are measured and heat fluxes inferred from infrared camera data, have been correlated with thermal-structural simulations. When these simulations are extrapolated to the full power steady-state heat fluxes that are expected in MPEX, the designs do not appear to have the necessary structural robustness. This study explores design alternatives for the MPEX helicon antenna window, presents analysis results for several of the alternatives, and shows a viable solution that satisfies the requirements for MPEX operation.

Tipton Jr, Joseph↗

Numerical methods and hypoexponential approximations for gamma distributed delay differential equations

Abstract Gamma distributed delay differential equations (DDEs) arise naturally in many modelling applications. However, appropriate numerical methods for generic gamma distributed DDEs have not previously been implemented. Modellers have therefore resorted to approximating the gamma distribution with an Erlang distribution and using the linear chain technique to derive an equivalent system of ordinary differential equations (ODEs). In this work, we address the lack of appropriate numerical tools for gamma distributed DDEs in two ways. First, we develop a functional continuous Runge–Kutta (FCRK) method to numerically integrate the gamma distributed DDE without resorting to Erlang approximation. We prove the fourth-order convergence of the FCRK method and perform numerical tests to demonstrate the accuracy of the new numerical method. Nevertheless, FCRK methods for infinite delay DDEs are not widely available in existing scientific software packages. As an alternative approach to solving gamma distributed DDEs, we also derive a hypoexponential approximation of the gamma distributed DDE. This hypoexponential approach is a more accurate approximation of the true gamma distributed DDE than the common Erlang approximation but, like the Erlang approximation, can be formulated as a system of ODEs and solved numerically using standard ODE software. Using our FCRK method to provide reference solutions, we show that the common Erlang approximation may produce solutions that are qualitatively different from the underlying gamma distributed DDE. However, the proposed hypoexponential approximations do not have this limitation. Finally, we apply our hypoexponential approximations to perform statistical inference on synthetic epidemiological data to illustrate the utility of the hypoexponential approximation.

97 MATHEMATICS AND COMPUTING↗

Mass calibration of distant SPT galaxy clusters through expanded weak-lensing follow-up observations with HST, VLT, & Gemini-South

Expanding from previous work, we present weak-lensing (WL) measurements for a total sample of 30 distant (z median = 0.93) massive galaxy clusters from the South Pole Telescope Sunyaev–Zel’dovich (SPT-SZ) Survey, measuring galaxy shapes in Hubble Space Telescope (HST) Advanced Camera for Surveys images. We remove cluster members and preferentially select z ≳ 1.4 background galaxies via V - I colour, employing deep photometry from VLT/FORS2 and Gemini-South/GMOS. We apply revised calibrations for the WL shape measurements and the source redshift distribution to estimate the cluster masses. In combination with earlier Magellan/Megacam results for lower-redshifts clusters, we infer refined constraints on the scaling relation between the SZ detection significance and the cluster mass, in particular regarding its redshift evolution. The mass scale inferred from the WL data is lower by a factor $0.76^{+0.10}_{-0.14}$ (at our pivot redshift z = 0.6) compared to what would be needed to reconcile a flat Planck νΛCDM cosmology (in which the sum of the neutrino masses is a free parameter) with the observed SPT-SZ cluster counts. In order to sensitively test the level of (dis-)agreement between SPT clusters and Planck, further expanded WL follow-up samples are needed.

79 ASTRONOMY AND ASTROPHYSICS↗

The distribution of [α/Fe] in the Milky Way disc

ABSTRACT Using a sample of red giant stars from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) Data Release 16, we infer the conditional distribution $p([\alpha /{\rm Fe}]\, |\, [{\rm Fe}/{\rm H}])$ in the Milky Way disk for the α-elements Mg, O, Si, S, and Ca. In each bin of [Fe/H] and Galactocentric radius R, we model p([α/Fe]) as a sum of two Gaussians, representing ‘low-α’ and ‘high-α’ populations with scale heights $z_1=0.45\, {\rm kpc}$ and $z_2=0.95\, {\rm kpc}$, respectively. By accounting for age-dependent and z-dependent selection effects in APOGEE, we infer the [α/Fe] distributions that would be found for a fair sample of long-lived stars covering all z. Near the Solar circle, this distribution is bimodal at sub-solar [Fe/H], with the low-α and high-α peaks clearly separated by a minimum at intermediate [α/Fe]. In agreement with previous results, we find that the high-α population is more prominent at smaller R, lower [Fe/H], and larger |z|, and that the sequence separation is smaller for Si and Ca than for Mg, O, and S. We find significant intrinsic scatter in [α/Fe] at fixed [Fe/H] for both the low-α and high-α populations, typically ∼0.04-dex. The means, dispersions, and relative amplitudes of this two-Gaussian description, and the dependence of these parameters on R, [Fe/H], and α-element, provide a quantitative target for chemical evolution models and a test for hydrodynamic simulations of disk galaxy formation. We argue that explaining the observed bimodality will probably require one or more sharp transitions in the disk’s gas accretion, star formation, or outflow history in addition to radial mixing of stellar populations.

79 ASTRONOMY AND ASTROPHYSICS↗

Resonant scattering at the center of the galaxy cluster PKS 0745-191 with XRISM

We report evidence of the resonant scattering effect at the center of the galaxy cluster PKS 0745-191 with XRISM. We analyzed XRISM/Resolve commissioning-phase observations of the distant cluster PKS 0745-191 ($z = 0.103$) with a $54$ ks exposure. The gain drift was corrected using the onboard modulated X-ray source (MXS), and spectra were extracted from all the pixels that were well illuminated by MXS, the core region (four central pixels, $\sim$100 kpc), and the surrounding region. A single-temperature collisional ionization equilibrium (CIE) model fits the full field-of-view spectrum with $kT \approx 6$ keV and a turbulent velocity of ${\approx}120$ km s$^{-1}$. From the core ($r < 50$ kpc) spectrum, we detected a ${\approx}22\%$ suppression of the Fe xxv He$\alpha$ resonance (w) line relative to the CIE prediction. We performed a Monte Carlo simulation to calculate the resonant scattering (RS) effect using radial profiles from Chandra data. The RS-inferred turbulence agrees with that by Resolve line-broadening, demonstrating that RS provides an independent and consistent constraint on ICM turbulence. These results highlight XRISM/Resolve’s potential for turbulence studies in galaxy clusters.

Astronomy and AstroPhysics↗

Recombination smooths the time-signal disrupted by latency in within-host HIV phylogenies

Within-host HIV evolution involves several features that may disrupt standard phylogenetic reconstruction. One important feature is re-activation of latently integrated provirus, which has the potential to disrupt the temporal signal, leading to variation in the branch lengths and apparent evolutionary rates in a tree. Yet, real within-host HIV phylogenies tend to show clear, ladder-like trees structured by the time of sampling. Another important feature is recombination, which violates the fundamental assumption that evolutionary history can be represented by a single bifurcating tree. Thus, recombination complicates the within-host HIV dynamic by mixing genomes and creating evolutionary loop structures that cannot be represented in bifurcating trees. In this paper, we develop a coalescent-based simulator of within-host HIV evolution that includes latency, recombination, and effective population size dynamics that allows us to study the relationship between the true, complex genealogy of within-host HIV evolution, encoded as an Ancestral Recombination Graph (ARG), and the observed phylogenetic tree. To compare our ARG results to the familiar phylogeny format, we calculate the expected bifurcating tree after decomposing the ARG into all unique site trees, their combined distance matrix, and the overall corresponding bifurcating tree. While latency and recombination separately disrupt the phylogenetic signal, remarkably, we find that recombination recovers the temporal signal of within-host HIV evolution caused by latency by mixing fragments of old, latent genomes into the contemporary population. In effect, recombination averages over extant heterogeneity, whether it stems from mixed time-signals or population bottlenecks. Further, we establish that the signals of latency and recombination can be observed in phylogenetic trees despite being an incorrect representation of the true evolutionary history. Using an Approximate Bayesian Computation method, we develop a set of statistical probes to tune our simulation model to nine longitudinally-sampled within-host HIV phylogenies. Because ARGs are exceedingly difficult to infer from real HIV data, our simulation system allows investigating effects of latency, recombination, and population size bottlenecks by matching decomposed ARGs to real data as observed in standard phylogenies.

59 BASIC BIOLOGICAL SCIENCES↗

Bayesian uncertainty quantification for nuclear matter incompressibility

Within a Bayesian statistical framework using the standard Skyrme-Hartree-Fock model, the maximum a posteriori (MAP) values and uncertainties of nuclear matter incompressibility and isovector interaction parameters are inferred from the experimental data of giant resonances and neutron-skin thicknesses of typical heavy nuclei. Furthermore, with the uncertainties of the isovector interaction parameters constrained by the data of the isovector giant dipole resonance and the neutron-skin thickness, we have obtained K 0 = 223$^{+7}_{–8}$ MeV at 68% confidence level using the data of the isoscalar giant monopole resonance in 208 Pb measured at the Research Center for Nuclear Physics (RCNP), Japan, and at the Texas A&M University, USA. Although the corresponding 120 Sn data gives a MAP value for K 0 about 5 MeV smaller than the 208 Pb data, there are significant overlaps in their posterior probability distribution functions.

190 ≤ A ≤ 219↗

Role of the likelihood for elastic scattering uncertainty quantification

In the last decade, uncertainty quantification (UQ) for optical model potentials (OMPs) has become a focal point for nuclear reaction theory, and several competing approaches for OMP UQ have recently been developed. Here, we clarify recent efforts to compare frequentist and Bayesian approaches in the context of OMP UQ [G. B. King et al., Phys. Rev. Lett. 122, 232502 (2019)]. We replicate a portion of that OMP UQ study but use independent statistical tools. Specifically, we compare two methods for OMP parameter inference from elastic scattering data: the Levenberg-Marquardt algorithm for χ 2 minimization on one hand and Markov chain Monte Carlo (MCMC) sampling on the other. Separately, we assess the common practice of using a renormalized likelihood (χ 2 /N), N being the number of data points, instead of the canonical weighted-least-squares likelihood (χ 2 ), as a way of accounting for unknown data correlations. Here, we show that for a generic linear model and for a five-parameter OMP analysis, frequentist and uniform-prior Bayesian approaches recover the same optimum and uncertainty estimates—not systematically larger uncertainties for the Bayesian approach, as was concluded in G. B. King et al., Phys. Rev. Lett. 122, 232502 (2019). Further, we show that if an additional, near-degenerate parameter is introduced into the same OMP analysis such that the parameter posterior becomes non-Gaussian, then covariance-based estimates of uncertainty become unreliable. Finally, we show that regardless of optimization approach, if χ 2 /N is used for the likelihood, the resulting parametric uncertainties increase by $\sqrt{N}$, and that this is responsible for the conclusions drawn in the revisited study. Based on our replication results, we find that a fortuitous cancellation of unreported errors and the renormalization factor can lead to improvement in empirical coverages, as was the case in the original comparative study. We emphasize that developing and applying a realistic likelihood function is an essential task in a UQ analysis, and that several recent UQ studies that employed a renormalized likelihood (i.e., including a 1/N factor) may have yielded unrealistically large uncertainties for elastic-scattering observables. If the parameter posterior deviates from multivariate-normal, a sampling-based approach like MCMC has a clear advantage over methods that assume the Laplace approximation holds. We note that empirical coverage can serve as an important internal check for the analyst whose model or data may have additional, unaccounted-for uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Signature of hadron-quark crossover in binary-neutron-star mergers

Here, we study observational signatures of the hadron-quark crossover in binary-neutron-star mergers by numerical-relativity simulations with various mass configurations. We employ two equations of state (EoSs) for matter consistent with inference from the observational data. In the crossover scenario the EoS is softened in a density realized in binary-neutron-star mergers and is smoothly continued to quark matter. In the phase transition scenario without crossover, the EoS remains stiff and a first-order phase transition takes place in a density out of reach of mergers. A GW170817-like system forms a remnant massive neutron star in both scenarios, and it collapses into a black hole only in the crossover scenario due to the softening while gravitational-wave emission is strong. This difference is clearly reflected in the sudden shutdown of gravitational waves. For a given EoS, the lifetime of the merger remnant is determined primarily by the total mass of the system. Identifying these features in a variety of future events with the next generation of ground-based gravitational-wave detectors will enable us to clarify details of hadron-quark transition. The mass of the accretion disk surrounding the remnant black hole is affected not only by the lifetime of the remnant but also by the mass ratio of the system. Electromagnetic emission associated with the disk outflow will also be useful for detailed investigation of the hadron-quark transition.

QCD phase transitions↗

Hydroxyl radical mediated damage of proteins in low oxygen solution investigated using X-ray footprinting mass spectrometry

In the method of X-ray footprinting mass spectrometry (XFMS), proteins at micromolar concentration in solution are irradiated with a broadband X-ray source, and the resulting hydroxyl radical modifications are characterized using liquid chromatography mass spectrometry to determine sites of solvent accessibility. These data are used to infer structural changes in proteins upon interaction with other proteins, folding, or ligand binding. XFMS is typically performed under aerobic conditions; dissolved molecular oxygen in solution is necessary in many, if not all, the hydroxyl radical modifications that are generally reported. In this study we investigated the result of X-ray induced modifications to three different proteins under aerobic versus low oxygen conditions, and correlated the extent of damage with dose calculations. We observed a concentration-dependent protecting effect at higher protein concentration for a given X-ray dose. For the typical doses used in XFMS experiments there was minimal X-ray induced aggregation and fragmentation, but for higher doses we observed formation of covalent higher molecular weight oligomers, as well as fragmentation, which was affected by the amount of dissolved oxygen in solution. The higher molecular weight products in the form of dimers, trimers, and tetramers were present in all sample preparations, and, upon X-ray irradiation, these oligomers became non-reducible as seen in SDS-PAGE. The results provide an important contribution to the large body of X-ray radiation damage literature in structural biology research, and will specifically help inform the future planning of XFMS, and well as X-ray crystallography and small-angle X-ray scattering experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DriveSense: A Noise-Resilient Framework for Driving Mode Identification

Accurate drive mode classification is essential for enhancing the reliability and predictive maintenance of heavy-duty electric trucks. This study proposes a novel fuzzy logic-based framework, DriveSense, for real-time drive mode classification, addressing key challenges such as sensor noise, transitional behaviors, and computational efficiency. The proposed approach integrates a two-stage filtering pipeline, combining adaptive outlier removal and a dynamic Kalman filter to enhance data quality. A fuzzy inference system with smoothened trapezoidal membership functions is then applied to classify driving modes into standstill, constant speed, acceleration, and deceleration while mitigating the effects of noise and edge cases. Performance evaluation using real-world and simulated drive cycles demonstrates significant improvements in classification accuracy (up to 97.8%), F1-score (up to 0.97), and robustness against noise, while reducing false positives. Comparative analysis against baseline models, demonstrates DriveSense’s superior accuracy and generalizability across diverse driving patterns. The framework’s lightweight and interpretable fuzzy inference engine operates with low computational latency, ensuring compatibility with real-time embedded systems typical of heavy-duty electric trucks. Moreover, DriveSense models transitional behaviors through overlapping fuzzy sets and adaptive borderline classification logic, enabling smooth identification of subtle shifts such as rolling stops or gradual deceleration. These results highlight DriveSense’s potential to enhance predictive maintenance strategies, reduce downtime, and support scalable, fleet-wide diagnostics.

Kumar, Praveen [Oak Ridge National Laboratory (ORN↗

Analyzing Data Privacy for Edge Systems

Internet-of-Things (IoT)-based streaming applications are all around us. Currently, we are transitioning from IoT processing being performed on the cloud to the edge. While moving to the edge provides significant networking efficiency benefits, IoT edge computing creates significant data privacy concerns. We propose a methodology that can successfully privacy protect the continual data streams generated by sensors on the edge device. We implement local differential privacy on streaming data and incorporate Bayesian inference and Gaussian process to evaluate the privacy policy. We demonstrate our methodology on a real-world smart meter testbed and identify the optimal privacy protection settings.

Kotevska, Olivera↗

Bayesian quantum state reconstruction with a learning-based tuned prior

We demonstrate machine-learning-enhanced Bayesian quantum state tomography on near-term intermediate-scale quantum hardware. Our approach to selecting prior distributions leverages pre-trained neural networks incorporating measurement data and enables improved inference times over standard prior distributions.

Regmi, Sangita↗

UQTk User Manual (V.3.1.0)

The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.1.0 offers intrusive and non-intrusive methods for propagating input uncertainties through computational models, tools for sensitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters from experimental data. This manual discusses the download and installation process for UQTk, provides pointers to the UQ methods used in the toolkit, and describes some of the examples provided with the toolkit.

97 MATHEMATICS AND COMPUTING↗