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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

En echelon faults reactivated by wastewater disposal near Musreau Lake, Alberta

We use machine-learning and cross-correlation techniques to enhance earthquake detectability by two magnitude units for the earthquake sequence near Musreau Lake, Alberta, which is induced by wastewater disposal. This deep catalogue reveals a series of en echelon ~N–S oriented strike-slip faults that are favourably oriented for reactivation. These faults require only ~0.6 MPa overpressure for triggering to occur. Earthquake activity occurs in bursts, or episodes; episodes restricted to the largest fault tend to have earthquakes starting near the southern end (distant from injectors) and progressing northwards (towards the injectors). While most events are concentrated along these ~N–S oriented faults, we also delineate smaller faults. Together, these findings suggest pore pressure as the triggering mechanism, where a time-dependent increase in pore pressure likely caused these faults to progressively reawaken. Analysis of the ‘next record-breaking event’, a statistical model that forecasts the sequencing of earthquake magnitudes, suggests that the next largest event would be M L ~4.3. The seismically illuminated length of the largest fault indicates potential magnitudes as large as M w 5.3.

58 GEOSCIENCES↗
DOE OSTI2024

Enhanced PDV waveform search and analysis method using parallel circular-convolution / cross-correlation for improved dynamic surface velocity extraction [Poster]

Previous work on exhaustive search methodologies for extracting best-match parameters pertaining to dynamic surface quantities from PDV was done by cross-correlating synthetically generated PDV waveforms with observed counterparts using the circular-convolution theorem. This work was further developed into an open-source PDV analysis toolkit called CCPDVANALYSIS which expands upon and enhances the previously tested methods by parallelizing serial algorithmic components and incorporating a comprehensive script library for different flavors of instantaneous frequency functions utilized in generating synthetic PDV waveforms. Results of these enhancements have been shown to markedly decrease execution times of exhaustive search and extraction algorithms and produce improved velocity recoveries for low-velocity and dynamically varying velocity signals. The CCPDVANALYSIS script library demonstrates an advanced method for extracting velocities from low-velocity and non-constant velocity signals further extending and improving the methods beyond capabilities of traditional frequency domain tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Synthesis‐Related Nanoscale Defects in Mo‐Based Janus Monolayers Revealed by Cross‐Correlated AFM and TERS Imaging

2D Janus transition metal dichalcogenides (TMDs) are promising candidates for various applications including non-linear optics, energy harvesting, and catalysis. These materials are usually synthesized via chemical conversion of pristine TMDs. Nanometer-scale characterization of the obtained Janus materials’ morphology and local composition is crucial for both the synthesis optimization and the future device applications. In this work, we present the results of cross-correlated atomic force microscopy (AFM) and tip-enhanced Raman spectroscopy (TERS) study of Janus monolayers synthesized by the hydrogen plasma-assisted chemical conversion of MoSe 2 and MoS 2 . We demonstrate that the choice of both the growth substrate and the starting TMD influences the residual strain, thereby shaping the nanoscale morphology of the resulting Janus material. Furthermore, by employing TERS imaging, we show the presence of nanoscale islands (≈20 nm across) of MoSe 2 - ${\mathrm{Mo}}_{{\mathrm{Se}}}^{\mathrm{S}}$ (MoS 2 -${\mathrm{Mo}}_{\mathrm{S}}^{{\mathrm{Se}}}$) vertical heterostructures originating from the bilayer nanoislands in the precursor monolayer crystals. The understanding of the origins of nanoscale defects in Janus TMDs revealed in this study can help with further optimization of the Janus conversion process towards uniform and wrinkle-/crack-free Janus materials. Moreover, this work shows that cross-correlated AFM and TERS imaging is a powerful and accessible method for studying nanoscale composition and defects in Janus TMD monolayers.

2D materials↗
DOE OSTI2026

Emulating galaxy and peculiar velocity clustering on non-linear scales

We explore the potential of cross-correlating galaxies and peculiar velocities on non-linear scales to enhance cosmological constraints. Leveraging the ABACUSSUMMIT simulation suite and the halo occupation distribution (HOD) formalism, we trained emulator models to describe the non-linear clustering of galaxies and velocities in redshift space. Our analysis demonstrates that combining galaxy and peculiar velocity clustering provides tighter constraints on both HOD and cosmological parameters, particularly on σ8 and w0. We further applied our models to realistic mock catalogues, reproducing the expected density and peculiar velocity errors of type-Ia supernovae, Tully-Fisher and fundamental plane measurements for the combined ZTF and DESI measurements. While systematic biases arise in the HOD parameters, the cosmological constraints remain unbiased, yielding a 3.8% precision measurement on fσ 8 compared to 4.7% when using galaxy clustering alone. We demonstrate that while combining tracers with realistic velocity measurements still yields an improvement, the gains are diminished, highlighting the need for further efforts to reduce velocity measurement uncertainties and correct observational systematics on small scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Dark Energy Survey Year 6 results: Clustering redshifts and importance sampling of self-organized-maps 𝑛⁡(𝑧) realizations for 3 × 2 ⁢pt samples

This work is part of a series establishing the redshift framework for the 3 × 2 ⁢pt analysis of the Dark Energy Survey Year 6 (DES Y6). For DES Y6, photometric redshift distributions are estimated using self-organizing maps (SOMs), calibrated with spectroscopic and many-band photometric data. To overcome limitations from color-redshift degeneracies and incomplete spectroscopic coverage, we enhance this approach by incorporating clustering-based redshift constraints (clustering-z, or WZ) from angular cross-correlations with BOSS and eBOSS galaxies and eBOSS quasar samples. We define a WZ likelihood and apply importance sampling to a large ensemble of SOM-derived 𝑛⁡(𝑧) realizations, selecting those consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales corresponding to 1.5–5 Mpc to optimize signal-to-noise ratio while mitigating modeling uncertainties and marginalizes over redshift-dependent galaxy bias and other systematics informed by the N-body simulation CARDINAL . While a sparser spectroscopic reference sample limits WZ constraining power at 𝑧 >1.1, particularly for source bins, we demonstrate that combining SOM with WZ improves redshift accuracy and enhances the overall cosmological constraining power of DES Y6. As a result, we estimate an improvement in 𝑆 8 of approximately 10% for cosmic shear and 3 ×2⁢pt analysis, primarily due to the WZ calibration of the source samples.

Cosmological parameters↗
DOE OSTI2025

Boosting H I -Galaxy Cross-Clustering Signal through Higher-Order Cross-Correlations

After reionization, neutral hydrogen (${\rm H\, \small {I}}$) traces the large-scale structure (LSS) of the Universe, enabling ${\rm H\, \small {I}}$ intensity mapping (IM) to capture the LSS in 3D and constrain key cosmological parameters. We present a new framework utilizing higher-order cross-correlations to study ${\rm H\, \small {I}}$ clustering around galaxies, tested using real-space data from the IllustrisTNG300 simulation. This approach computes the joint distributions of k-nearest neighbor (kNN) optical galaxies and the ${\rm H\, \small {I}}$ brightness temperature field smoothed at relevant scales (the kNN-field framework), providing sensitivity to all higher-order cross-correlations, unlike two-point statistics. To simulate ${\rm H\, \small {I}}$ data from actual surveys, we add random thermal noise and apply a simple foreground cleaning model, filtering out Fourier modes of the brightness temperature field with k ∥ < k min,∥ . Under current levels of thermal noise and foreground cleaning, typical of a Canadian Hydrogen Intensity Mapping Experiment (CHIME)-like survey, the ${\rm H\, \small {I}}$-galaxy cross-correlation signal in our simulations, using the kNN-field framework, is detectable at >30σ across r = [3, 12] h –1 Mpc. In contrast, the detectability of the standard two-point correlation function (2PCF) over the same scales depends strongly on the foreground filter: a sharp k ∥ filter can spuriously boost detection to 8σ due to position-space ringing, whereas a less sharp filter yields no detection. Nonetheless, we conclude that kNN-field cross-correlations are robustly detectable across a broad range of foreground filtering and thermal noise conditions, suggesting their potential for enhanced constraining power over 2PCFs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Constraints on cosmology and baryonic feedback with joint analysis of Dark Energy Survey Year 3 lensing data and ACT DR6 thermal Sunyaev-Zel'dovich effect observations

We present a joint analysis of weak gravitational lensing (shear) data obtained from the first three years of observations by the Dark Energy Survey and thermal Sunyaev-Zel'dovich (tSZ) effect measurements from a combination of Atacama Cosmology Telescope (ACT) and Planck data. A combined analysis of shear (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) can jointly probe both the distribution of matter and the thermodynamic state of the gas, accounting for the correlated effects of baryonic feedback on both observables. We detect the shear$~\times~$tSZ cross-correlation at a 21$\sigma$ significance, the highest to date, after minimizing the bias from cosmic infrared background leakage in the tSZ map. By jointly modeling the small-scale shear auto-correlation and the shear$~\times~$tSZ cross-correlation, we obtain $S_8 = 0.811^{+0.015}_{-0.012}$ and $\Omega_{\rm m} = 0.263^{+0.023}_{-0.030}$, results consistent with primary CMB analyses from Planck and P-ACT. We find evidence for reduced thermal gas pressure in dark matter halos with masses $M < 10^{14} \, M_{\odot}/h$, supporting predictions of enhanced feedback from active galactic nuclei on gas thermodynamics. A comparison of the inferred matter power suppression reveals a $2-4\sigma$ tension with hydrodynamical simulations that implement mild baryonic feedback, as our constraints prefer a stronger suppression. Finally, we investigate biases from cosmic infrared background leakage in the tSZ-shear cross-correlation measurements, employing mitigation techniques to ensure a robust inference. Our code is publicly available on GitHub.

Pandey, S. [Johns Hopkins U.; Columbia U.] (ORCID:↗
DOE OSTI2026

A Pulsar-Inspired Timing Framework for Power System: Optimization and Performance Evaluation

Due to their excellent stability, neutron pulsar stars are considered promising candidate timing sources for power system applications. However, the complexity of pulsar signals necessitates advanced processing algorithms to provide accurate timing references. This paper presents the foundational framework for pulsar signal processing, serving as the basis for further optimization. To enhance the timing accuracy and computation efficiency in pulsar period searches, three algorithms are proposed as the initial optimization step: wavelet de-noising, fast folding, and cross-correlation for profile evaluation. Wavelet de-noising improves signal-to-noise ratio (SNR) by 36%–70%. Fast folding reduces computation time from hundreds of seconds to mere milliseconds. Cross-correlation works better than traditional SNR-based methods by effectively identifying the optimal period. The performance of the proposed algorithms is evaluated using observation data from telescopes. Together, these algorithms significantly improve pulsar timing performance, reducing the error of the Pulse Per Second (PPS) signal from hundreds to tens of microseconds.

Wu, Ori [ORNL] (ORCID:0000000326723410)↗
DOE OSTI2025

Plasma modification through boron particulate injection in the full tungsten environment of WEST

Recent experiments have confirmed the compatibility of extended boron particulate injections with high performance plasma discharges in the full tungsten (W) environment of WEST. Utilizing an impurity powder dropper (IPD) equipped with boron (B) powders a series of extended experimental programs providing controlled injections have quantified plasma response to varying levels of injection rate and total injection quantity. Calibration of injection quantities confirmed through post-situ testing of the IPD and cross-correlated with both high-speed camera illumination and spectroscopic measurement have allowed for the first time a fine scale determination of the effects of powder introduction on plasma performance. Plasma enhancement, consistent with turbulence reduction through profile modification, has been observed with sustained increases in the stored energy (WMHD), by 18%, electron temperature (T e ) by 35%, and neutron rate (N n ) by up to 200%, all of which scale positively with increasing powder injection rates. These injections have also resulted in both prompt and extended reductions in native impurity content, decreases in post injection radiated power, and strong decreases in divertor deuterium signatures signifying a reduction in recycling suggesting enhanced boron layer formation which provides a reduction of source terms and leads to enhanced gettering of main ion and impurity sources.

Lunsford, R. [Princeton Plasma Physics Laboratory ↗
DOE OSTI2024

Multi-Tiered Estimation for Correlation Spectroscopy in 3D (MTECS3D) v0.1

This innovative software estimates rotational diffusion coefficients of particles from X-ray photon correlation spectroscopy (XPCS) data of monodispersed particle systems. It is the first method capable of extracting rotational diffusion information from three-dimensional particle systems using XPCS. Using the angular-temporal cross-correlation of the XPCS images, this software is able to estimate the rotational diffusion coefficients with only a few percent relative errors while requiring minimal prior knowledge of particle structures. This software enhances XPCS analysis capabilities, allowing researchers to study translational and rotational Brownian dynamics of particles in suspension across various temporal and spatial scales.

Hu, Zixi↗
DOE OSTI2025

Constraints on Local Primordial Non-Gaussianity with 3D Velocity Reconstruction from the Kinetic Sunyaev-Zeldovich Effect

The cosmic velocity field is an unbiased probe of the total matter distribution but is challenging to measure directly at intermediate and high redshifts. The large-scale velocity field imprints a signal in the cosmic microwave background (CMB) through the kinetic Sunyaev-Zeldovich (kSZ) effect. We perform the first 3D reconstruction of the large-scale velocity field from the kSZ effect by applying a quadratic estimator to CMB temperature maps and the 3D positions of galaxies. We do so by combining CMB data from the fifth data release of the Atacama Cosmology Telescope (in combination with Planck) and a spectroscopic galaxy sample from the Sloan Digital Sky Survey. We then measure the galaxy-velocity cross-power spectrum and detect the presence of the kSZ signal at a signal-to-noise ratio of 7.2⁢𝜎. Using this galaxy-velocity cross-correlation alone, we constrain the amplitude of local primordial non-Gaussianity finding 𝑓 NL =−9⁢0$^{+210}_{−350}$. In conclusion, this pathfinder measurement sets the stage for joint galaxy-CMB kSZ constraints to significantly enhance the 𝑓 NL information obtained from galaxy surveys through sample variance cancellation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

How to detect lensing rotation

Gravitational lensing rotation of images is predicted to be negligible at linear order in density perturbations, but can be produced by the post-Born lens-lens coupling at second order. This rotation is somewhat enhanced for Cosmic Microwave Background (CMB) lensing due to the large source path length, but remains small and very challenging to detect directly by CMB lensing reconstruction alone. We show the rotation may be detectable at high significance as a cross-correlation signal between the curl reconstructed with Simons Observatory (SO) or CMB-S4 data, and a template constructed from quadratic combinations of large-scale structure (LSS) tracers. Equivalently, the lensing rotation-tracer-tracer bispectrum can also be detected, where LSS tracers considered include the CMB lensing convergence, galaxy density, and the Cosmic Infrared Background (CIB), or optimal combinations thereof. We forecast that an optimal combination of these tracers can probe post-Born rotation at the level of 5.7σ–6.1σ with SO and 13.6σ–14.7σ for CMB-S4, depending on whether standard quadratic estimators or maximum a posteriori iterative methods are deployed. We also show possible improvement up to 21.3σ using a CMB-S4 deep patch observation with polarization-only iterative lensing reconstruction. However, these cross-correlation signals have non-zero bias because the rotation template is quadratic in the tracers, and exists even if the lensing is rotation free. We estimate this bias analytically, and test it using simple null-hypothesis simulations to confirm that the bias remains subdominant to the rotation signal of interest. Detection and then measurement of the lensing rotation cross-spectrum is therefore a realistic target for future observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Sequential Fracture Activation and Stress Evolution During EGS Stimulation at Utah FORGE Revealed by Waveform Cross‐Correlation

Mapping fracture networks in Enhanced Geothermal Systems (EGS) is essential for optimizing reservoir performance, yet complex fracture evolution during stimulation remains difficult to resolve. This study examines the evolution of microseismicity and fracture networks during stage 3 of the 2022 EGS stimulation at the Utah Frontier Observatory for Research in Geothermal Energy site. We map the fracture network represented by 20 clusters of seismic events identified by waveform similarities with cross-correlation. We characterize their geometric properties such as strike, dip, length, and width, and analyze the time evolution of activated fractures. The results reveal a systematic fracture evolution: early activation of pre-existing natural fractures, complex network development during peak injection, and continued activation of less favorably oriented fractures post-injection. Magnitude calibration using the Principal Component Analysis of cross-correlated waveforms improves relative amplitude measurements, refining estimations of the Gutenberg-Richter b-values with spatial variations in b-values suggesting stress re-distribution across the stimulated area. Analysis of the stress state of selected fractures further shows that fractures requiring higher excess pore pressure primarily activate at the end of injection and post-injection, highlighting stress transfer due to pore pressure as a dominant triggering mechanism. These findings provide insights into fracture propagation, stress evolution, and seismic hazard assessment in EGS reservoirs.

Asirifi, Richard [Texas A & M Univ., College Stati↗
DOE OSTI2025

STILGAR End-of-Project Report

The Subsurface Tunnel Imaging LeveraGed by Analysis of Rayleigh wave ellipticity (STILGAR) project demonstrated an integrated geophysical approach for detecting, locating, and characterizing underground structural changes using dense seismic arrays and advanced inversion techniques. Field campaigns were conducted at two operational mines—the Redmond salt mine (Utah) and Graymont Pleasant Gap limestone mine (Pennsylvania)—providing real-world testbeds for monitoring anthropogenic subsurface activity. At the Redmond salt mine, seismic interferometry combined with back-projection inversion successfully identified continuous, low-amplitude signals from mining operations. The approach differentiated stationary from migrating anthropogenic sources, captured daily operational cycles, and validated the potential of passive seismic monitoring for remote detection of underground activity. At the Graymont Pleasant Gap mine, two dense seismic deployments in the spring and fall of 2023 generated over 4 TB of high-resolution data. Key outcomes included the relocation of 199 underground and 8 surface explosions with accuracies within tens of meters and the development of a 3D P-wave velocity model using the triple-difference tomography algorithm (tomoTD) that resolved major structural features such as the mine entrance, low-velocity tunnels, and roof-collapse areas. Ambient noise cross-correlation and back-projection analyses revealed persistent sources linked to ongoing mining activity, whereas horizontal-to-vertical spectral ratio (HVSR) and ellipticity studies confirmed stable site responses across seasons and identified soil thickness trends consistent with regional erosional and depositional processes. Checkerboard and sensitivity tests further validated the robustness of the tomographic results. Overall, the findings emphasize that although significant progress has been made in subsurface imaging, further work is needed to enhance the detection and localization of underground structures. Accurate imaging requires higher frequencies, yet anthropogenic sources tend to dominate the seismic record at those frequencies, and high-frequency surface waves are affected by higher modes that complicate interpretation. The improved detection and localization of human-induced signals enabled detailed temporal and spatial mapping of daily mine operations, demonstrating the feasibility of continuous anthropogenic source monitoring. Sensitivity to signals from nontraditional sources, such as fan operations, highlights the broader applicability of this approach to other industrial environments in which continuous and impulsive signals are present. The field campaigns produced a substantial volume of high-quality seismic data, supporting the development and testing of new methods for seismic source characterization and subsurface imaging. Future deployments should include sensors capable of recording lower frequencies to probe deeper structures, increase bandwidth to enhance resolution and sensitivity to both shallow and deep targets, and collect additional large-scale datasets to refine imaging and source characterization techniques. Moreover, conducting 3D modeling studies of seismic wavefields at higher frequencies will provide a better understanding of wave scattering and cavity–wavefield interactions in complex underground environments. In conclusion, the STILGAR project demonstrated that integrated seismic monitoring can effectively characterize underground operations, capturing both natural and anthropogenic signals. The approaches developed provide a foundation for improved detection, localization, and imaging of subsurface structures and are directly transferable to broader industrial monitoring applications.

58 GEOSCIENCES↗
DOE OSTI2025

The Lyman- α forest from LBGs: First 3D correlation measurement with DESI and prospects for cosmology

The Lyman-α (Lyα) forest is a key tracer of large-scale structure at redshifts z > 2, traditionally studied using the spectra of luminous but relatively rare quasars. In this work, we explore the viability of using the fainter yet significantly more abundant Lyman Break Galaxies (LBGs) as alternative background sources for Lyα forest studies. We analyze 4,151 Lyα forest skewers extracted from LBG spectra obtained in the DESI pilot surveys conducted in the COSMOS and XMM-LSS fields. From this dataset, we present the first measurement of the Lyα forest auto-correlation function derived exclusively from LBG spectra, probing comoving separations up to 48 h -1 Mpc at an effective redshift of z eff = 2.70. The measured LBG Lyα forest auto-correlation is consistent with that derived from DESI DR2 quasar Lyα forest spectra at a comparable redshift, validating the use of LBGs as reliable background sources for Lyα forest analyses. In addition, we measure the cross-correlation between the LBG Lyα forest and the positions of 13,362 galaxies, demonstrating that this observable serves as a sensitive diagnostic for assessing the precision and accuracy of galaxy redshift estimates, and for identifying and correcting systematic offsets. Finally, using both synthetic LBG spectra and Fisher matrix forecasts, we show that a future wide-area survey covering ∼5,000 deg 2 , targeting 1,000 LBGs per square degree at signal-to-noise levels comparable to our sample, could enable LBG-based Lyα forest baryon acoustic oscillation (BAO) measurements with expected uncertainties of σ α ISO = 0.4% (isotropic) and σ α AP = 1.3% (Alcock-Paczynski). This performance is further enhanced when combining the BAO analysis with a Lyα forest Full Shape (FS) approach, yielding a predicted uncertainty of σ α ISO FS = 0.6%. These results open a new avenue for precision cosmology at high redshift using the Lyα forest in dense LBG samples.

Lyman alpha forest↗
DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗
DOE OSTI2025

The imprint of cosmic voids from the DESI Legacy Survey DR9 Luminous Red Galaxies in the Planck 2018 lensing map through spectroscopically calibrated mocks

The cross-correlation of cosmic voids with the lensing convergence (κ) map of the Cosmic Microwave Background (CMB) fluctuations provides a powerful tool to refine our understanding of the current cosmological model. However, several studies have reported a moderate tension (up to ∼2σ) between the lensing imprint of cosmic voids on the observed CMB and the ΛCDM signal predicted by simulations. To address this “lensing-is-low” tension and to obtain new, precise measurements of the signal, we exploit the large DESI Legacy Survey Luminous Red Galaxy (LRG) data set, covering approximately 19 500 deg 2 of the sky and including about 10 million LRGs at z < 1.05. Our ΛCDM template was created using the Buzzard mocks, which we specifically calibrated to match the clustering properties of the observed galaxy sample by exploiting more than one million DESI spectra. We identified our catalogs of 3D voids in the range 0.35 < z < 0.95 and cross-correlated them through a stacking methodology, dividing the sample into bins according to the redshift and λv values of the voids. For the full void sample, we report a 14σ detection of the lensing signal, with A κ = 1.016 ± 0.054, which increases to 17σ when considering the void-in-void (A κ = 0.944 ± 0.064) and the void-in-cloud (A κ = 0.975 ± 0.060) populations individually, the highest detection significance for studies of this kind. We observe a full agreement between observations and ΛCDM mocks across all redshift bins, sky regions, and void populations considered. In addition to these findings, our analysis highlights the importance of accurately matching sparseness and redshift error distributions between mocks and observations, as well as the role of λ v in enhancing the signal-to-noise ratio through void population discrimination.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Fast baryonic field painting for Sunyaev-Zel’dovich analyses: Transfer function vs hybrid effective field theory

Here, we present two approaches for “painting” baryonic properties relevant to the Sunyaev-Zel’dovich (SZ) effect—optical depth and Compton-y—onto three-dimensional N-body simulations, using the MillenniumTNG suite as a benchmark. The goal of these methods is to produce fast and accurate reconstruction methods to aid future analyses of baryonic feedback using the SZ effect. The first approach employs a Gaussian process emulator to model the SZ quantities via a transfer function, while the second utilizes hybrid effective field theory (HEFT) to reproduce these quantities within the simulation. Our analysis involves comparing both methods to the true MillenniumTNG optical depth and Compton-y fields using several metrics, including the cross-correlation coefficient, power spectrum, and power spectrum error. Additionally, we assess how well the reconstructed fields correlate with dark matter haloes across various mass thresholds. The results indicate that the transfer function method yields more accurate reconstructions for fields with initially high correlations (r ≈ 1), such as between the optical depth and dark matter fields. Conversely, the HEFT-based approach proves more effective in enhancing correlations for fields with weaker initial correlations (r ∼ 0.5), such as between the Compton-y and dark matter fields. Lastly, we discuss extensions of our methods to improve the reconstruction performance at the field level.

Liu, R. Henry [University of California, Berkeley,↗