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At least 649 records · Page 36

Spectroscopic signatures of time-reversal symmetry breaking superconductivity

The collective mode spectrum of a symmetry-breaking state, such as a superconductor, provides crucial insight into the nature of the order parameter. In this work, we study two collective modes which are unique to unconventional superconductors that spontaneously break time reversal symmetry. We show that these modes are coherent and underdamped for a wide variety of time-reversal symmetry breaking superconducting states. By further demonstrating that these modes can be detected using a number of existing experimental techniques, we propose that our work can be leveraged as a form of “collective mode spectroscopy” that drastically expands the number of experimental probes capable of detecting time-reversal symmetry breaking in unconventional superconductors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hunting for Polluted White Dwarfs and Other Treasures with Gaia XP Spectra and Unsupervised Machine Learning

White dwarfs (WDs) polluted by exoplanetary material provide the unprecedented opportunity to directly observe the interiors of exoplanets. However, spectroscopic surveys are often limited by brightness constraints, and WDs tend to be very faint, making detections of large populations of polluted WDs difficult. In this paper, we aim to increase considerably the number of WDs with multiple metals in their atmospheres. Using 96,134 WDs with Gaia DR3 BP/RP (XP) spectra, we constructed a 2D map using an unsupervised machine-learning technique called Uniform Manifold Approximation and Projection (UMAP) to organize the WDs into identifiable spectral regions. The polluted WDs are among the distinct spectral groups identified in our map. We have shown that this selection method could potentially increase the number of known WDs with five or more metal species in their atmospheres by an order of magnitude. Such systems are essential for characterizing exoplanet diversity and geology.

79 ASTRONOMY AND ASTROPHYSICS↗

Into the UV: A Precise Transmission Spectrum of HAT-P-41b Using Hubble’s WFC3/UVIS G280 Grism

The ultraviolet–visible wavelength range holds critical spectral diagnostics for the chemistry and physics at work in planetary atmospheres. To date, time-series studies of exoplanets to characterize their atmospheres have relied on several combinations of modes on the Hubble Space Telescope’s STIS/COS instruments to access this wavelength regime. Here for the first time, we apply the Hubble WFC3/UVIS G280 grism mode to obtain exoplanet spectroscopy from 200 to 800 nm in a single observation. We test the G280 grism mode on the hot Jupiter HAT-P-41b over two consecutive transits to determine its viability for the characterization of exoplanet atmospheres. We obtain a broadband transit depth precision of 29–33 ppm and a precision of on average 200 ppm in 10 nm spectroscopic bins. Spectral information from the G280 grism can be extracted from both the positive and negative first-order spectra, resulting in a 60% increase in the measurable flux. Additionally, the first Hubble Space Telescope orbit can be fully utilized in the time-series analysis. We present detailed extraction and reduction methods for use by future investigations with this mode, testing multiple techniques. We find the results to be fully consistent with STIS measurements of HAT-P-41b from 310 to 800 nm, with the G280 results representing a more observationally efficient and precise spectrum. HAT-P-41b’s transmission spectrum is best fit with a model with T {sub eq} = 2091 K, high metallicity, and significant scattering and cloud opacity. With these first-of-their-kind observations, we demonstrate that WFC3/UVIS G280 is a powerful new tool to obtain UV–optical spectra of exoplanet atmospheres, adding to the UV legacy of Hubble and complementing future observations with the James Webb Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

Reward based optimization of resonance-enhanced piezoresponse spectroscopy

Dynamic spectroscopies in scanning probe microscopy (SPM) are critical for probing material properties, such as force interactions, mechanical properties, polarization switching, electrochemical reactions, and ionic dynamics. However, the practical implementation of these measurements is constrained by the need to balance imaging time and data quality. Signal to noise requirements favor long acquisition times and high frequencies to improve signal fidelity. However, these are limited on the low end by contact resonant frequency and photodiode sensitivity and on the high end by the time needed to acquire high-resolution spectra or the propensity for sample degradation under high field excitation over long times. The interdependence of key parameters such as instrument settings, acquisition times, and sampling rates makes manual tuning labor-intensive and highly dependent on user expertise, often yielding operator-dependent results. These limitations are prominent in techniques like dual amplitude resonance tracking in piezoresponse force microscopy that utilize multiple concurrent feedback loops for topography and resonance frequency tracking. Here, a reward-driven workflow is proposed that automates the tuning process, adapting experimental conditions in real time to optimize data quality. Furthermore, this approach significantly reduces the complexity and time required for manual adjustments and can be extended to other SPM spectroscopic methods, enhancing overall efficiency and reproducibility.

47 OTHER INSTRUMENTATION↗

The completed SDSS-IV extended baryon oscillation spectroscopic survey: pairwise-inverse probability and angular correction for fibre collisions in clustering measurements

ABSTRACT The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344 080 quasars at 0.8 < z < 2.2, 174 816 luminous red galaxies between 0.6 < z < 1.0, and 173 736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These ‘fibre collisions’ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected $\rm {\mathit{ w}_p}\left(\mathit{ r}_p\right)$ and the redshift-space multipole ξ(ℓ = 0, 2, 4)(s) correlation functions down to $0.1\, h^{-1}{\rm Mpc}$, regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales $s\gtrsim 20\, h^{-1}{\rm Mpc}$ for ξℓ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to $\sim 0.1\, h^{-1}{\rm Mpc}$ scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.

79 ASTRONOMY AND ASTROPHYSICS↗

CLASS Survey Description: Coronal-line Needles in the SDSS Haystack

Coronal lines are a powerful, yet poorly understood, tool to identify and characterize active galactic nuclei. There have been few large-scale surveys of coronal lines in the general galaxy population in the literature so far. Using a novel preselection technique with a flux-to-rms ratio $\mathcal{F}$, followed by Markov Chain Monte Carlo fitting, we searched for the full suite of 20 coronal lines in the optical spectra of almost 1 million galaxies from the Sloan Digital Sky Survey Data Release 8. We present a catalog of the emission-line parameters for the resulting 258 galaxies with detections. The Coronal Line Activity Spectroscopic Survey includes line properties, host-galaxy properties, and selection criteria for all galaxies in which at least one line is detected. This comprehensive study reveals that a significant fraction of coronal-line activity is missed in past surveys based on a more limited set of coronal lines; ~60% of our sample do not display the more widely surveyed [Fe x] λ6374. In addition, we discover a strong correlation between coronal-line and Wide-field Infrared Survey Explorer W2 luminosities, suggesting that the mid-infrared flux can be used to predict coronal-line fluxes. For each line we also provide a confidence level that the line is present, generated by a novel neural network, trained on fully simulated data. We find that after training the network to detect individual lines using 100,000 simulated spectra, we achieve an overall true-positive rate of 75.49% and a false-positive rate of only 3.96%.

79 ASTRONOMY AND ASTROPHYSICS↗

Spin-phonon resonances in nearly polar metals with spin-orbit coupling

In metals in the vicinity of a polar transition, interactions between electrons and soft phonon modes remain to be determined. Here we explore the consequences of spin-orbit assisted electron-phonon coupling on the collective modes of such nearly polar metals in the presence of magnetic field. We find that the soft polar phonon hybridizes with spin-flip electronic excitations of the Zeeman-split bands leading to an anticrossing. The associated energy splitting allows for an unambiguous determination of the strength of the spin-orbit mediated coupling to soft modes in polar metals by spectroscopic experiments. Here, the approach to the polar transition is reflected by the softening of the effective g factor of the hybridized spin-flip mode. Analyzing the static limit, we find that the polar order parameter can be oriented by magnetic field. This provides possibilities for alternative switching protocols in polar metallic materials. We demonstrate that the effects we predict can be observed with current experimental techniques and discuss promising material candidates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Time-Resolved Optical Pump-Resonant X-ray Probe Spectroscopy of 4-Thiouracil: A Simulation Study

We theoretically monitor the photoinduced ππ* → nπ* internal conversion process in 4-thiouracil (4TU), triggered by an optical pump. The element-sensitive spectroscopic signatures are recorded by a resonant X-ray probe tuned to the sulfur, oxygen, or nitrogen K-edge. We employ high-level electronic structure methods optimized for core-excited electronic structure calculation combined with quantum nuclear wavepacket dynamics computed on two relevant nuclear modes, fully accounting for their quantum nature of nuclear motions. We critically discuss the capabilities and limitations of the resonant technique. For sulfur and nitrogen, we document a pre-edge spectral window free from ground-state background and rich with ππ* and nπ* absorption features. The lowest sulfur K-edge shows strong absorption for both ππ* and nπ*. In the lowest nitrogen K-edge window, we resolve a state-specific fingerprint of the ππ* and an approximate timing of the conical intersection via its depletion. A spectral signature of the nπ* transition, not accessible by UV–vis spectroscopy, is identified. The oxygen K-edge is not sensitive to molecular deformations and gives steady transient absorption features without spectral dynamics. Here, the ππ*/nπ* coherence information is masked by more intense contributions from populations. Altogether, element-specific time-resolved resonant X-ray spectroscopy provides a detailed picture of the electronic excited-state dynamics and therefore a sensitive window into the photophysics of thiobases.

97 MATHEMATICS AND COMPUTING↗

Generating synthetic cosmological data with GalSampler

As part of the effort to meet the needs of the Large Synoptic Survey Telescope Dark Energy Science Collaboration (LSST DESC) for accurate, realistically complex mock galaxy catalogues, in this work we have developed galsampler, an open-source python package that assists in generating large volumes of synthetic cosmological data. The key idea behind galsampler is to recast hydrodynamical simulations and semi-analytic models as physically motivated galaxy libraries. galsampler populates a new, larger volume halo catalogue with galaxies drawn from the baseline library; by using weighted sampling guided by empirical modelling techniques, galsampler inherits statistical accuracy from the empirical model and physically motivated complexity from the baseline library. We have recently used galsampler to produce the cosmoDC 2 extragalactic catalogue made for the LSST DESC Data Challenge 2 . Using cosmoDC 2 as a guiding example, we outline how galsampler can continue to support ongoing and near-future galaxy surveys such as the Dark Energy Survey, the Dark Energy Spectroscopic Instrument, WFIRST, and Euclid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Code interoperability extends the scope of quantum simulations

The functionality of many materials is critically dependent on the integration of dissimilar components and on the interfaces that arise between them. The description of such heterogeneous components requires the development and deployment of first principles methods, coupled to appropriate dynamical descriptions of matter and advanced sampling techniques, in order to capture all the relevant length and time scales of importance to the materials’ performance. It is thus essential to build simple, streamlined computational schemes for the prediction and design of multiple properties of broad classes of materials, by developing interoperable codes which can be efficiently coupled to each other to perform complex tasks. We discuss the use of interoperable codes to simulate the structural and spectroscopic characterization of materials, including chemical reactions for catalysis, the description of defects for quantum information science, and heat and charge transport.

36 MATERIALS SCIENCE↗

The Dark Energy Spectroscopic Instrument: one-dimensional power spectrum from first Ly α forest samples with Fast Fourier Transform

ABSTRACT We present the one-dimensional Ly α forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises 26 330 quasar spectra, at redshift z > 2.1, contained in the DESI Early Data Release and the first 2 months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated with the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on lognormal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Ly α forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement.

79 ASTRONOMY AND ASTROPHYSICS↗

Reaction Discovery Using Spectroscopic Insights from an Enzymatic C–H Amination Intermediate

Engineered hemoproteins can selectively incorporate nitrogen from nitrene precursors like hydroxylamine, O-substituted hydroxylamines, and organic azides into organic molecules. Although iron-nitrenoids are often invoked as the reactive intermediates in these reactions, their innate reactivity and transient nature have made their characterization challenging. Here we characterize an iron-nitrosyl intermediate generated from NH 2 OH within a protoglobin active site that can undergo nitrogen-group transfer catalysis, using UV–vis, electron paramagnetic resonance (EPR) spectroscopy, and high-resolution electrospray ionization mass spectrometry (HR-ESI-MS) techniques. The mechanistic insights gained led to the discovery of aminating reagents—nitrite (NO 2 – ), nitric oxide (NO), and nitroxyl (HNO)—that are new to both nature and synthetic chemistry. Based on the findings, we propose a catalytic cycle for C–H amination inspired by the nitrite reductase pathway. Furthermore, this study highlights the potential of engineered hemoproteins to access natural nitrogen sources for sustainable chemical synthesis and offers a new perspective on the use of biological nitrogen cycle intermediates in biocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra

Abstract Transit spectroscopy is a powerful tool for decoding the chemical compositions of the atmospheres of extrasolar planets. In this paper, we focus on unsupervised techniques for analyzing spectral data from transiting exoplanets. After cleaning and validating the data, we demonstrate methods for: (i) initial exploratory data analysis, based on summary statistics (estimates of location and variability); (ii) exploring and quantifying the existing correlations in the data; (iii) preprocessing and linearly transforming the data to its principal components; (iv) dimensionality reduction and manifold learning; (v) clustering and anomaly detection; and (vi) visualization and interpretation of the data. To illustrate the proposed unsupervised methodology, we use a well-known public benchmark data set of synthetic transit spectra. We show that there is a high degree of correlation in the spectral data, which calls for appropriate low-dimensional representations. We explore a number of different techniques for such dimensionality reduction and identify several suitable options in terms of summary statistics, principal components, etc. We uncover interesting structures in the principal component basis, namely well-defined branches corresponding to different chemical regimes of the underlying atmospheres. We demonstrate that those branches can be successfully recovered with a K-means clustering algorithm in a fully unsupervised fashion. We advocate for lower-dimensional representations of the spectroscopic data in terms of the main principal components, in order to reveal the existing structure in the data and quickly characterize the chemical class of a planet.

Matchev, Konstantin T. (ORCID:0000000341829096)↗

In-plane thermal conductivity and the applicability of the Wiedemann–Franz law in dilute AlCu thin films

The Wiedemann–Franz (WF) law correlates heat and charge transport in metals. However, the validity of this correlation remains an open-ended question, especially in the context of inelastic scattering at room temperature. To address this gap in knowledge, we perform independent measurements of the in-plane thermal and electrical conductivities across four AlCu (0.5% Cu) films [thickness (⁠h⁠) ≈ 174, 98, 53, and 24 nm] using optical pump–probe metrologies and four-point probe techniques, respectively. For in-plane thermal conductivity measurements, we utilize time-domain thermoreflectance, in both concentric and beam-offset configurations, and the time-resolved magneto-optic Kerr effect. Our results show that the WF law overpredicts the thermal conductivity by at least ∼10% in all films, thus demonstrating modest deviations in predicted thermal conductivity when applying the WF law to dilute AlCu films. Using infrared variable angle spectroscopic ellipsometry, we demonstrate increased electron scattering rates in the thinnest film (⁠⁠h⁠ ≈ 24 nm), indicating electron-boundary scattering drives the reduction in in-plane thermal conductivity. Furthermore, this is generally an elastic scattering process, which is supported by our thermal conductivity measurements and analysis.

Electrical conductivity↗

Enzymes and Models. In: XAFS Techniques for Catalysts, Nanomaterials, and Surfaces

Many important redox-active metalloenzymes consist of 3d transition metals in their active sites. They catalyze multi-electron reactions in aqueous solution, under ambient temperature and pressure. To understand the functionality of the catalytic sites of these enzymes, X-ray spectroscopy methods provide important information of the electronic structure of the metal of interest and its local structural information, as well as their changes during the catalysis. Studying model compounds, that mimic enzyme catalytic site structures or their functional mimics, is as critical as studying enzymes themselves, in order to interpret X-ray spectroscopic data. In this chapter, various X-ray spectroscopic methods that are useful for structural and electronic structural studies of enzymes and model compounds are described.

Yachandra, VK↗

Applying deep learning methods to develop new models of molecular charge transfer, nonadiabatic dynamics, and nonlinear spectroscopy in the condensed phase

Photon- and field-induced charge transfer has central importance in the generation and storage of electricity, the novel properties of materials, photo-induced catalysis, and electro-optic activity (e.g., photovoltaic cells, fuel cells, and organic chromophores for use in optical fibers and light-emission diodes). These non-equilibrium electronic and chemical transformations are probed by ultrafast, nonlinear spectroscopies. Accurate simulations play a crucial role in our ability to understand, optimize, and control these transformations. This project applies modern deep learning and machine learning (ML) methods to dramatically improve models of electronic dynamics, electronic-nuclear dynamics, and spectroscopic measurements for improved simulations of chemistry in complex environments, far from equilibrium phenomena, and processes in extreme environments, such as materials exposed to strong or resonant fields. This project develops accurate neural net models that go beyond predictive capability to also provide new insight into the fundamental physics underlying electron and nuclear dynamics. To achieve its objectives, this project explores and develops customized versions of high-capacity deep learning algorithms/models. These techniques are developed with an emphasis on fundamental chemical insight, not just predictive accuracy, to assist the development of the next generation of quantum simulation methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Studying Type II supernovae as cosmological standard candles using the Dark Energy Survey

ABSTRACT Despite vast improvements in the measurement of the cosmological parameters, the nature of dark energy and an accurate value of the Hubble constant (H0) in the Hubble–Lemaître law remain unknown. To break the current impasse, it is necessary to develop as many independent techniques as possible, such as the use of Type II supernovae (SNe II). The goal of this paper is to demonstrate the utility of SNe II for deriving accurate extragalactic distances, which will be an asset for the next generation of telescopes where more-distant SNe II will be discovered. More specifically, we present a sample from the Dark Energy Survey Supernova Program (DES-SN) consisting of 15 SNe II with photometric and spectroscopic information spanning a redshift range up to 0.35. Combining our DES SNe with publicly available samples, and using the standard candle method (SCM), we construct the largest available Hubble diagram with SNe II in the Hubble flow (70 SNe II) and find an observed dispersion of 0.27 mag. We demonstrate that adding a colour term to the SN II standardization does not reduce the scatter in the Hubble diagram. Although SNe II are viable as distance indicators, this work points out important issues for improving their utility as independent extragalactic beacons: find new correlations, define a more standard subclass of SNe II, construct new SN II templates, and dedicate more observing time to high-redshift SNe II. Finally, for the first time, we perform simulations to estimate the redshift-dependent distance-modulus bias due to selection effects.

79 ASTRONOMY AND ASTROPHYSICS↗

In Situ/Operando (Soft) X-ray Spectroscopy Study of Beyond Lithium-ion Batteries

The lightweight, rechargeable lithium-ion battery is one of the dominant energy storage devices globally in portable electronics due to its high energy density, no memory effect, wide operating voltage, lightweight, and good charge efficiency. However, due to safety concerns, the depletion of lithium reserves, and the corresponding increase of cost, an alternative battery system becomes more and more desirable. To develop alternative battery systems with low cost and high material abundance, for example, sodium, magnesium, zinc, and calcium, it is important to understand the chemical and electronic structure of materials. Additionally, soft X-ray spectroscopy, for example, X-ray absorption spectroscopy (XAS), X-ray emission spectroscopy (XES), and resonant inelastic soft X-ray scattering (RIXS), is an element-specific technique with sensitivity to the local chemical environment and structural order of the element of interest. Modern soft X-ray systems enable operando experiments that can be applied to amorphous and crystalline samples, making it a powerful tool for studying the electronic and structural changes in electrode and electrolyte species. In this article, the application of in situ/operando (soft) X-ray spectroscopy in beyond lithium-ion batteries is reviewed to demonstrate how such spectroscopic characterizations could facilitate the interpretation of interfacial phenomena under in situ/operando condition and subsequent development of the beyond lithium-ion batteries.

(soft) X-ray spectroscopy↗