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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data

Spectral induced polarization (SIP) is a non-intrusive geophysical method that collects chargeability information (the ability of a material to retain charge) in the time domain or its phase shift in the frequency domain. Although SIP is a temporal method, it cannot measure the dynamics of flow and solute/species transport in the subsurface over long times (i.e., 10–100 s of years). Data collected with the SIP technique need to be coupled with fluid flow and reactive-transport models in order to capture long-term dynamics. To address this challenge, PFLOTRAN-SIP was built to couple SIP data to fluid flow and solute transport processes. Specifically, this framework couples the subsurface flow and transport simulator PFLOTRAN and geoelectrical simulator E4D without sacrificing computational performance. PFLOTRAN solves the coupled flow and solute-transport process models in order to estimate solute concentrations, which were used in Archie’s model to compute bulk electrical conductivities at near-zero frequency. These bulk electrical conductivities were modified while using the Cole–Cole model to account for frequency dependence. Using the estimated frequency-dependent bulk conductivities, E4D simulated the real and complex electrical potential signals for selected frequencies for SIP. These frequency-dependent bulk conductivities contain information that is relevant to geochemical changes in the system. This study demonstrated that the PFLOTRAN-SIP framework is able to detect the presence of a tracer in the subsurface. SIP offers a significant benefit over ERT in the form of greater information content. It provided multiple datasets at different frequencies that better constrained the tracer distribution in the subsurface. Consequently, this framework allows for practitioners of environmental hydrogeophysics and biogeophysics to monitor the subsurface with improved resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Classifying photonic topology using the spectral localizer and numerical K -theory

Recently, the spectral localizer framework has emerged as an efficient approach for classifying topology in photonic systems featuring local nonlinearities and radiative environments. In nonlinear systems, this framework provides rigorous definitions for concepts such as topological solitons and topological dynamics, where a system’s occupation induces a local change in its topology due to nonlinearity. For systems embedded in radiative environments that do not possess a shared bulk spectral gap, this framework enables the identification of local topology and shows that local topological protection is preserved despite the lack of a common gap. However, as the spectral localizer framework is rooted in the mathematics of C*-algebras, and not vector bundles, understanding and using this framework requires developing intuition for a somewhat different set of underlying concepts than those that appear in traditional approaches for classifying material topology. In this tutorial, we introduce the spectral localizer framework from a ground-up perspective and provide physically motivated arguments for understanding its local topological markers and associated local measure of topological protection. In doing so, we provide numerous examples of the framework’s application to a variety of topological classes, including crystalline and higher-order topology. We then show how Maxwell’s equations can be reformulated to be compatible with the spectral localizer framework, including the possibility of radiative boundary conditions. To aid in this introduction, we also provide a physics-oriented introduction to multi-operator pseudospectral methods and numerical K-theory, two mathematical concepts that form the foundation for the spectral localizer framework. Finally, we provide some mathematically oriented comments on the C*-algebraic origins of this framework, including a discussion of real C*-algebras and graded C*-algebras that are necessary for incorporating physical symmetries. Looking forward, we hope that this tutorial will serve as an approachable starting point for learning the foundations of the spectral localizer framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Beyond traditional diagnostics: Identifying active galactic nuclei using spectral energy distribution fitting in DESI data

Active galactic nuclei (AGN) are typically identified through their distinctive X-ray or radio emissions, mid-infrared (MIR) colors, or emission lines. However, each method captures different subsets of AGN due to signal-to-noise (S/N) limitations, redshift coverage, and extinction effects, underscoring the necessity for a multiwavelength approach for comprehensive AGN samples. This study explores the effectiveness of spectral energy distribution (SED) fitting as a robust method for AGN identification. Using CIGALE optical-MIR SED fits on DESI Early Data Release galaxies, we compare SED-based AGN selection (AGNFRAC ≥ 0.1) with traditional methods including BPT diagrams, WISE colors, X-ray, and radio diagnostics. The SED fitting identifies ∼70% of narrow- and broad-line AGN and 87% of WISE-selected AGN. Incorporating high S/N WISE photometry reduces star-forming galaxy contamination from 62% to 15%. Initially, ∼50% of SED-AGN candidates are undetected by standard methods, but additional diagnostics classify ∼85% of these sources, revealing low-ionization nuclear emission-line regions and retired galaxies potentially representing evolved systems with weak AGN activity. Further spectroscopic and multiwavelength analysis will be essential to determine the true AGN nature of these sources. SED fitting provides complementary AGN identification, unifying multiwavelength AGN selections. This approach enables more complete – albeit somewhat contaminated – AGN samples, which are essential for upcoming large-scale surveys where spectroscopic diagnostics may be limited.

Seyfert↗
DOE OSTI2023

Daily and Seasonal Variations of Shallow Seismic Velocities in Southern California From Joint Analysis of H/V Ratios and Autocorrelations of Seismic Waveforms

Establishing a baseline of ongoing secular velocity variations at the subsurface can improve the accuracy of detecting and interpreting short-term velocity changes, and advance the understanding of observed seismic motions and the behavior of subsurface materials. Toward these goals, we develop and apply a deconvolved autocorrelation (DA) method to estimate regional daily and seasonal changes of seismic velocities in southern California. The DA method combines advantages of traditional autocorrelation and Horizontal-to-Vertical Spectral Ratio, and is used to analyze over 10 years of data recorded by 50 stations. The results indicate widespread daily and seasonal changes of up to 10% and 4%, respectively, in the top tens of meters of the crust. The thickness of the surface layer, distance from the coast, and topographic variations are important factors controlling the amplitudes of the resolved velocity variations. The results suggest that changes of soil moisture and thermoelastic strain are likely dominant factors affecting the daily and seasonal variations, respectively. The developed DA method can improve the accuracy and robustness of estimated changes of subsurface materials at other locations.

58 GEOSCIENCES↗
DOE OSTI2022

Spectral evidence of solar neighborhood analogs in CALIFA galaxies

We introduce a novel nonparametric method to find solar neighborhood analogs (SNAs) in extragalactic integral field spectroscopic surveys. The main ansatz is that the physical properties of the solar neighborhood (SN) should be encoded in its optical stellar spectrum. We assume that our best estimate of such a spectrum is the one extracted from the analysis performed by the Code for Stellar properties Heuristic Assignment (CoSHA) from the MaStar stellar library. It follows that finding SNAs in other galaxies consist in matching, in a χ 2 sense, the SN reference spectrum across the optical extent of the observed galaxies. We applied this procedure to a selection of CALIFA galaxies, by requiring a close to face-on projection, relative isolation, and non-active galactic nucleus. We explore how the local and global properties of the SNAs (stellar age, metallicity, dust extinction, mass-to-light ratio, stellar surface mass density, star-formation density, and galactocentric distance) and their corresponding host galaxies (morphological type, total stellar mass, star-formation rate, and effective radius) compared with those of the SN and the Milky Way (MW). We find that SNAs are located preferentially in S(B)a–S(B)c galaxies, in a ring-like structure, which radii seem to scale with the galaxy size. Despite the known sources of systematics and errors, most properties present a considerable agreement with the literature on the SN. We conclude that the solar neighborhood is relatively common in our sample of SNAs. Our results warrant a systematic exploration of correlations among the physical properties of the SNAs and their host galaxies. We reckon that our method should inform current models of the galactic habitable zone in our MW and other galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Semi-Implicit Computation of Fast Modes in a Scheme Integrating Slow Modes by a Leapfrog Method Based on a Selective Implicit Time Filter

Abstract A scheme for integration of atmospheric equations containing terms with differing time scales is developed. The method employs a filtered leapfrog scheme utilizing a fourth-order implicit time filter with one function evaluation per time step to compute slow-propagating phenomena such as advection and rotation. The terms involving fast-propagating modes are handled implicitly with an unconditionally stable method that permits application of larger time steps and faster computations compared to fully explicit treatment. Implementation using explicit and recurrent formulation is provided. Stability analysis demonstrates that the method is conditionally stable for any combination of frequencies involved in the slow and fast terms as they approach the origin. The implicit filter used in the method damps the computational modes without noticeably sacrificing the accuracy of the physical mode. TheO[(Δt 4 )] accuracy for amplitude errors achieved by the implicitly filtered leapfrog is preserved in applications where terms responsible for fast propagation are integrated with a semi-implicit method. Detailed formulation of the method for soundproof nonhydrostatic anelastic equations is provided. Procedures for implementation in global spectral shallow-water models are also given. Examples comparing numerical and analytical solutions for linear gravity waves demonstrate the accuracy of the scheme. The performance is also shown in more practical nonlinear applications, where numerical solutions accomplished by the method are evaluated against those computed from a scheme where the slow terms are handled by the third-order Runge–Kutta scheme. It demonstrates that the method is able to accurately resolve fine-scale dynamics of Kelvin–Helmholtz shear instabilities, the evolution of density current, and nonlinear drifts of twin tropical cyclones.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Characterizing extreme laser intensities by ponderomotive acceleration of protons from rarified gas

Abstract A new method to diagnose extreme laser intensities through measurement of angular and spectral distributions of protons directly accelerated by the laser focused into a rarefied gas is proposed. We simulated a laser pulse focused by an off-axis parabolic mirror by Stratton–Chu integrals, that enables description of laser pulse with different spatial-temporal profiles focusing in a focal spot down to the diffraction limit, that makes our theoretical predictions be a basis for experimental realization. The relationship between characteristics of the proton distributions and parameters of the laser pulse have been analyzed. The analytical and numerical results obtained justify the new method of laser diagnostics. The proposed scheme should be valuable for the commissioning of new extreme intensity laser facilities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Fragment-based initialization for quantum subspace methods

Here, we present a novel quantum-classical algorithm called LAS-QKSD for multireference systems, by combining a classical localized active space (LAS) fragment-based multireference algorithm with the quantum Krylov subspace diagonalization (QKSD) method for quantum computers. The algorithm uses wave function information from a LAS self-consistent field (LASSCF) calculation to prepare an initial state with better overlap with the target ground state than the Hartree-Fock state. This is coupled with the use of QKSD to ultimately converge to the exact energy, providing faster convergence than starting from the Hartree-Fock state. Fragmentation has the two-fold benefit of fewer configurations on the classical side of the algorithm as well as fewer state preparation gates on the quantum side. First, we compare the LAS-QKSD method to the classical LASSCF method and to QKSD with a Hartree-Fock initial state. We then examine ways to load the LASSCF wave function using direct initialization and a QKSD-motivated spectral filtering approach. Finally, using a bimetallic complex, we show that the LAS-QKSD method is an efficient alternative to highly expensive complete active space SCF (CASSCF) calculations on strongly correlated systems.

D'Cunha, Ruhee↗
DOE OSTI2021

Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hysteresis

Multi-dimensional spectral-imaging is a mainstay of the scanning probe and electron microscopies, micro-Raman, and various forms of chemical imaging. In many cases, individual spectra can be fit to a specific functional form, with the model parameter maps, providing direct insight into material properties. Since spectra are often acquired across a spatial grid of points, spatially adjacent spectra are likely to be similar to one another; yet, this fact is almost never used when considering parameter estimation for functional fits. On datasets tried here, we show that by utilizing proximal information, whether it be in the spatial or spectral domains, it is possible to improve the reliability and increase the speed of such functional fits by ~2-3x, as compared to random priors. We explore and compare three distinct new methods: (1) spatially averaging neighborhood spectra, and propagating priors based on functional fits to the averaged case, (2) hierarchical clustering-based methods where spectra are grouped hierarchically based on response, with the priors propagated progressively down the hierarchy, and (3) regular clustering without hierarchical methods with priors propagated from fits to cluster means. Our results highlight that utilizing spatial and spectral neighborhood information is often critical for accurate parameter estimation in noisy environments, which we show for ferroelectric hysteresis loops acquired on a prototypical PbTiO3 thin film with piezoresponse spectroscopy. This method is general and applicable to any spatially measured spectra where functional forms are available. Examples include exploring the superconducting gap with tunneling spectroscopy, using the Dynes formula, or current-voltage curve fits in conductive atomic force microscopy mapping. Here we explore the problem for ferroelectric hysteresis, which, given its large parameter space, constitutes a more difficult task than, for example, fitting current-voltage curves with a Schottky emission formula.

42 ENGINEERING↗
DOE OSTI2025

Bias‐Dependent Quantum Efficiency Reveals Recombination Pathways in Thin Film Solar Cells

Identifying where recombination predominantly occurs—whether at the front interface, back interface, or throughout the bulk—is crucial for optimizing CdSeTe solar cells and many other photovoltaic device architectures. Here, a simple and effective diagnostic is demonstrated: measuring external quantum efficiency (QE) under varying forward biases. The drift–diffusion simulations reveal that each recombination pathway leaves a distinct bias-induced signature in the normalized QE: a progressive drop at long wavelengths for back-limited devices, a short-wavelength decline for front-limited devices, and a relatively uniform decrease across all wavelengths for bulk-limited devices. These predictions are validated with experiments on As-doped and Cu-doped CdSeTe devices, with and without passivation layers or different front buffers. In each case, the observed bias-dependent QE spectral changes align with the simulated recombination map. Because this method uses standard QE instrumentation, it offers a broadly accessible and cost-efficient means to diagnose recombination pathways—extending beyond CdSeTe to other thin-film and emerging solar cell technologies. By pinpointing recombination bottlenecks, researchers and manufacturers can strategically refine doping profiles, passivation schemes, and interface designs to further improve device performance.

CdTe↗
DOE OSTI2020

Spectral emittance measurements of micro/nanostructures in energy conversion: a review

Micro/nanostructures play a key role in tuning the radiative properties of materials and have been applied to the high-temperature energy conversion systems for improved performance. Among the various radiative properties, spectral emittance is of integral importance for the design and analysis of materials that function as radiative absorbers or emitters. This article presents an overview of the spectral emittance measurement techniques using both the direct and indirect methods. Several micro/nanostructures are also introduced, and a special emphasis is placed on the emissometers developed for characterizing engineered micro/nanostructures in high-temperature applications (e.g., solar energy conversion and thermophotovoltaic devices). Both experimental facilities and measured results for different materials are summarized. Future prospects in developing instrumentation and micro/nanostructured surfaces for practical applications are also outlined. This study provides a comprehensive source of information for the application of micro/nanostructures in high-temperature energy conversion engineering.

14 SOLAR ENERGY↗
DOE OSTI2024

Training custom light curve models of SN Ia subpopulations selected according to host galaxy properties

ABSTRACT Type Ia supernova (SN Ia) cosmology analyses include a luminosity step function in their distance standardization process to account for an observed yet unexplained difference in the post-standardization luminosities of SNe Ia originating from different host galaxy populations [e.g. high-mass ($M \gtrsim 10^{10} \, {\rm M}_{\odot }$) versus low-mass galaxies]. We present a novel method for including host-mass correlations in the SALT3 (Spectral Adaptive Light curve Template 3) light curve model used for standardizing SN Ia distances. We split the SALT3 training sample according to host-mass, training independent models for the low- and high-host-mass samples. Our models indicate that there are different average Si ii spectral feature strengths between the two populations, and that the average spectral energy distribution of SNe from low-mass galaxies is bluer than the high-mass counterpart. We then use our trained models to perform an SN cosmology analysis on the 3-yr spectroscopically confirmed Dark Energy Survey SN sample, treating SNe from low- and high-mass host galaxies as separate populations throughout. We find that our mass-split models reduce the Hubble residual scatter in the sample, albeit at a low statistical significance. We do find a reduction in the mass-correlated luminosity step but conclude that this arises from the model-dependent re-definition of the fiducial SN absolute magnitude rather than the models themselves. Our results stress the importance of adopting a standard definition of the SN parameters (x0, x1, c) in order to extract the most value out of the light curve modelling tools that are currently available and to correctly interpret results that are fit with different models.

Taylor, G. (ORCID:0000000157563259)↗
DOE OSTI2023

Fiber Optic Temperature Sensor Using Dual Air- Filled Fabry-Pérot Cavities With Variable Pressure

We present an approach for high temperature measurement using a pair of fiber-optic Fabry–Pérot (FP) cavities filled with gas of identical but variable pressure. One of the FPs (reference FP) is placed in the cold zone with a known temperature. The temperature of the measuring FP can be deduced by the spectral fringe shift vs. pressure of the two FPs. This method does not require measurement of the pressure or the knowledge of the optical properties of the gas. The use of gas as the sensing material and the measurement mechanism also implies long-term stability and eliminates the cross-sensitivity to strain. We fabricated the sensors and tested them for measuring temperature up to 800 °C. Here, the sensor shows good linearity in the range. Long-term test conducted at 800 °C exhibited the stability of the sensor with fluctuations of ≤0.3% over a duration exceeding 100 hours.

42 ENGINEERING↗
DOE OSTI2022

Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm

Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales $\textit{O}$ (10 0–6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions $\textit{O}$ (10 0–2 years) precisely within longer $\textit{O}$ (10 3–6 years) simulations. The standard forward sea-level modelling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for 1D pseudo-spectral sea-level models based on the normal mode method that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution $\textit{O}$ (10 0–2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution $\textit{O}$ (10 3–6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model temporal resolution and show how this sensitivity feeds back onto ice-sheet dynamics in coupled modelling. We apply the new algorithm to simulate sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries and provide appropriate time window profiles for each application. The time window algorithm reduces the total CPU time by ~ 50 % in each of these examples and changes the trend of the total CPU time increase from quadratic to linear. This improvement would increase with longer simulations than those considered here. Our algorithm also allows for coupling time intervals of annual temporal scale for coupled ice-sheet–sea-level modelling of regions such as West Antarctica that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Frequency domain assurance criterion for defect detection in additively manufactured parts

Additive manufacturing (AM) is a very desirable manufacturing method for industries such as aerospace and automotive due to its ability to create internal features and complex geometries, however, these characteristics also present challenges for nondestructive evaluation (NDE) and defect detection. Dynamic analysis and modal analysis have shown promise for NDE and identifying flaws in AM parts. Frequency Domain Assurance Criterion (FDAC) is a method of dynamic evaluation that represents the degree of correlation between two sets of operational deflection shapes (ODS) at each spectral line. Using colormaps to display the results allows for quick and easy interpretation of parts’ similarities and differences. This method appears to show promise in identifying parts with minor defects and can be used to differentiate nominal and defective parts. This paper explores the use of FDAC on various AM parts with and without intentional defects.

Deonarain, G↗
DOE OSTI2021

Spectral Induced Polarization-Biogeochemical Relationships for Remediation Amendment Monitoring

Geophysical tools such as electrical resistivity (ER) can indirectly monitor subsurface changes in response to remedial injections. These methods exhibit relatively low spatial resolution compared to sediment core characterization but are advantageous due to the ability to collect measurements non-intrusively over time across large volumes of the subsurface. Moreover, along with confirmatory groundwater or core sampling, geophysical methods can be used during active biogeochemical remedies to monitor short-term contaminant transformations and mobility, as well as part of an overall strategy for long-term monitoring of subsurface contaminated sites. The use of alternating current spectral induced polarization (SIP) provides significantly more information than conventional geophysical methods like direct current ER. SIP allows for monitoring changes in both solution and surface conductivity by separation of real and imaginary conductivity, respectively, as well as surface capacitance. In principle, SIP can measure indicators of remedy progression such as precipitation reactions that sequester contaminants, potentially providing a better indication of amendment delivery and reactivity as compared to conventional ER methods. However, multiple processes and material properties have overlapping (interacting) electrical responses across a range of frequencies. Hence, the purpose of this scoping study was to evaluate if SIP can be used to monitor (a) amendment delivery and (b) precipitation and reactivity of amendments under consideration at Hanford. SIP measurements were collected in fully saturated columns packed with sand and Hanford formation sediments containing (a) amendments that were highly conductive with significant capacitance (zero valent iron – ZVI, sulfur modified iron – SMI) and (b) amendments that exhibited low electrical conductivity with a small capacitance (calcite, apatite, bismuth). The sand was a quartz material with homogenous particle size that exhibited a relatively low surface conductivity. It was used as a control for comparison with the sediments from the Hanford Site, which have a greater surface conductivity because of their complex mineralogy and heterogeneous particle size distribution and may have complex interactions with amendments. The amendment mass fraction was varied to represent the different stages and subsurface locations associated with the delivery of a remedy. The primary objective was to identify the solution and solid surface changes associated with the delivery amendments and their secondary reactions within the subsurface. The figure below summarizes results for the amendments tested through this project. The SIP phase shift or imaginary conductivity change for the high conductivity amendments was more than 10 times that of the low conductivity amendments, highlighting the relative ease of detection of ZVI and SMI independent of the background signal from sand or Hanford sediments. The ZVI phase shift and imaginary conductivity changes occur primarily at high frequency (> 100 Hz) whereas SMI changes were at low frequency (0.01 to 10 Hz). SIP signals of SMI also increased over time and the maximum shifted to lower frequencies. The low conductivity amendments (calcite, abiotic and biotic apatite, bismuth subnitrate) exhibited relatively small phase and imaginary conductivity changes when added to sediments. The changes were above minimum detection limits (0.5 mrad for phase shift, 0.03 µS/cm for imaginary conductivity) for the highest concentration except for the commercial bismuth material. The lowest amendment concentration that can be detected is likely sediment specific, as minerals in sediments (clays, magnetite, Fe-oxides) have some capacitance and, therefore, exhibit a variable phase shift.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

SDSS-IV MaStar: [α/Fe] for the MaNGA Stellar Library from synthetic model spectra

ABSTRACT We calculate the α-enhancement ratio [α/Fe] for the Mapping Nearby Galaxies at APO (MaNGA) Stellar Library (MaStar) while also fitting for the fundamental atmospheric parameters effective temperature, surface gravity, and metallicity – Teff, log g, [Fe/H]. This approach builds upon a previous catalogue of stellar parameters, whereby only the fundamental atmospheric parameters are fit with solar-scaled models. Here, we use the same Markov Chain Monte Carlo method with the additional free parameter [α/Fe]. Using the full spectral fitting code pPXF, we are able to fit multiple lines sensitive to [α/Fe] for a more robust measurement. Quality flags based on the convergence of the sampler, errors in [α/Fe] and a cut in the χ2 of the model fit are used to clean the final catalogue, returning 17 214 spectra and values in the range of −0.25 < [α/Fe] < 0.48. Comparing our calculated [α/Fe] with literature values reveals a degeneracy in cool stars with log g ≥ ∼4; this comparison is then used to create an alternative and calibrated parameter set. We also plot the final catalogue in an [Fe/H] versus [α/Fe] diagram and recover the expected result of increasing [α/Fe] with decreasing [Fe/H] for Milky Way disc-halo stars. We apply our method to a subsample of spectra of uniform resolution and higher signal to noise that finds that our results are independent of this higher signal to noise. In the context of stellar population models, we are able to cover a parameter space for the creation of intermediate to old age models at solar-scaled [α/Fe], high [Fe/H] and enhanced [α/Fe], low [Fe/H].

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Harmonic analysis of discrete tracers of large-scale structure

It is commonplace in cosmology to analyze fields projected onto the celestial sphere, and in particular density fields that are defined by a set of points e.g. galaxies. When performing an harmonic-space analysis of such data (e.g. an angular power spectrum) using a pixelized map one has to deal with aliasing of small-scale power and pixel window functions. We compare and contrast the approaches to this problem taken in the cosmic microwave background and large-scale structure communities, and advocate for a direct approach that avoids pixelization. We describe a method for performing a pseudo-spectrum analysis of a galaxy data set and show that it can be implemented efficiently using well-known algorithms for special functions that are suited to acceleration by graphics processing units (GPUs). The method returns the same spectra as the more traditional map-based approach if in the latter the number of pixels is taken to be sufficiently large and the mask is well sampled. The method is readily generalizable to cross-spectra and higher-order functions. It also provides a convenient route for distributing the information in a galaxy catalog directly in harmonic space, as a complement to releasing the configuration-space positions and weights, and a route to spectral apodization. Finally, we make public a code enabling the application of our method to existing and upcoming datasets.

79 ASTRONOMY AND ASTROPHYSICS↗