Search NASA⌕ Search

SEARCH · Search NASA

Results for “Background Estimation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Isolating Unisolated Upsilons with Anomaly Detection in CMS Open Data

We present the first study of anti-isolated Upsilon decays to two muons (ϒ→𝜇⁺⁢𝜇⁻) in proton-proton collisions at the Large Hadron Collider. Using a machine learning (ML)-based anomaly detection strategy, we “rediscover” the ϒ in 13 TeV CMS Open Data from 2016, despite overwhelming anti-isolated backgrounds. We elevate the signal significance to 6.4⁢𝜎 using these methods, starting from 1.6⁢𝜎 using the dimuon mass spectrum alone. Moreover, we demonstrate improved sensitivity from using an ML-based estimate of the multifeature likelihood compared to traditional “cut-and-count” methods. This is the first ever detection of anti-isolated Upsilons, which can be useful in the study of heavy-flavor fragmentation in quantum chromodynamics. Our Letter demonstrates that it is possible and practical to find real signals in experimental collider data using ML-based anomaly detection, and we distill a readily accessible benchmark dataset from the CMS Open Data to facilitate future anomaly detection developments.

machine learning↗
DOE OSTI2024

Measurement and calibration of non-linear shear terms in galaxy cluster fields

Introduction Galaxy cluster lensing is a powerful tool for measuring the mass of galaxy clusters, but accurate shear measurement and calibration are critical to obtaining reliable results. This study focuses on the measurement and calibration of weak lensing shears to improve mass estimates in cluster lensing. To deal with the problem, we first developed an image simulation pipeline, jedisim, which utilizes galaxy images extracted from the Hubble Space Telescope (HST) Ultra Deep Field (UDF) and the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS). Methods The simulations represent realistic galaxy distributions and morphologies as input sources. The foreground halo with a Navarro–Frenk–White (NFW) profile is constructed such that the lensing signals of background galaxies can be measured by the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) Science Pipelines. By comparing the measured reduced shear g meas and the true reduced shear g true , we observe non-linearity up to g ≲ 0.6 . We fit polynomials to the data with quadratic correction adequate to g ≲ 0.4 . Meanwhile, we conduct mass estimates using the pzmassfitter code on four different clusters. Results The mass estimate results are significantly improved after applying the shear calibration derived from the present work—from 4.954 ± 0.504 × 1 0 14 M ⊙ to 10.507 ± 0.498 × 1 0 14 M ⊙ after calibration for a simulated cluster with the mass of 10 × 1 0 14 M ⊙ . In multiple cases of validation, the estimated results are all consistent with true cluster mass. Discussion This study yields the first relationship between reality and shape measurement of the LSST Science Pipelines and serves as the first step toward the overall goal of mass calibration in cluster lensing. By addressing the challenges in shear measurement and calibration, we aim to enhance the accuracy and reliability of mass estimates in galaxy cluster lensing studies.

Astronomy & Astrophysics↗
DOE OSTI2024

Searching for cosmological stochastic backgrounds by notching out resolvable compact binary foregrounds with next-generation gravitational-wave detectors

Stochastic gravitational-wave backgrounds can be of either cosmological or astrophysical origin. The detection of an astrophysical stochastic gravitational-wave background with ground-based interferometers is expected in the near future. Perhaps even more excitingly, the detection of stochastic backgrounds of cosmological origin by future ground-based interferometers could reveal invaluable information about the early Universe. From this perspective, the astrophysical background is a foreground that can prevent the extraction of this information from the data. In this paper, we revisit a time-frequency domain notching procedure previously proposed to remove the astrophysical foreground in the context of next-generation ground-based detectors, but we consider the more realistic scenario where we remove individually detectable signals by taking into account the uncertainty in the estimation of their parameters. We find that time-frequency domain masks can still efficiently remove the astrophysical foreground and suppress it to about 5% of its original level. Further removal of the foreground formed by unresolvable events (in particular, unresolvable binary neutron stars), which is about 10 times larger than the residual foreground from realistic notching, would require detector sensitivity improvements. Therefore, the main limitation in the search for a cosmological background is the unresolvable foreground itself, and not the residual of the notching procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

On the detectability of the moving lens signal in CMB experiments

Abstract Upcoming cosmic microwave background (CMB) experiments are expected to detect new signals probing interaction of CMB photons with intervening large-scale structure. Among these the moving-lens effect, the CMB temperature anisotropy induced by cosmological structures moving transverse to our line of sight, is anticipated to be measured to high significance in the near future. In this paper, we investigate two possible strategies for the detection of this signal: pairwise transverse-velocity estimation and oriented stacking. We expand on previous studies by including in the analysis realistic simulations of competing signals and foregrounds. We confirm that the moving lens effect can be detected at ≥ 10σlevel by a combination of CMB-S4 and LSST surveys. We show that the limiting factors in the detection depend on the strategy: for the stacking analysis, correlated extragalactic foregrounds, namely the cosmic infrared background and thermal Sunyaev Zel'dovich effect, play the most important role. The addition of foregrounds make the signal-to-noise ratio be most influenced by large and nearby objects. As for the pairwise detection, halo lensing and pair number counts are the main issues. In light of our findings, we elaborate on possible strategies to improve the analysis approach for the moving lens detection with upcoming experiments. We also deliver to the community all the simulations and tools we developed for this study.

Astronomy & Astrophysics↗
DOE OSTI2024

Searching for cosmological stochastic backgrounds by notching out resolvable compact binary foregrounds with next-generation gravitational-wave detectors

Stochastic gravitational-wave backgrounds can be of either cosmological or astrophysical origin. The detection of an astrophysical stochastic gravitational-wave background with ground-based interferometers is expected in the near future. Perhaps even more excitingly, the detection of stochastic backgrounds of cosmological origin by future ground-based interferometers could reveal invaluable information about the early Universe. From this perspective, the astrophysical background is a {\it foreground} that can prevent the extraction of this information from the data. In this paper, we revisit a time-frequency domain notching procedure previously proposed to remove the astrophysical foreground in the context of next-generation ground-based detectors, but we consider the more realistic scenario where we remove individually detectable signals by taking into account the uncertainty in the estimation of their parameters. We find that time-frequency domain masks can still efficiently remove the astrophysical foreground and suppress it to about $5\%$ of its original level. Further removal of the foreground formed by unresolvable events (in particular, unresolvable binary neutron stars), which is about $10$ times larger than the residual foreground from realistic notching, would require detector sensitivity improvements. Therefore, the main limitation in the search for a cosmological background is the unresolvable foreground itself, and not the residual of the notching procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Natural isotopic compositions of titanium, iron, and nickel observed in commercial fuel pellets – Promising candidate elements for stable isotope tagging

Stable isotope taggants would constitute unique identifiers for nuclear fuel cycle materials, resulting in expedited timelines and high confidence provenance assessments for nuclear forensics investigations. However, reliably identifying and interpreting stable isotope taggants in nuclear materials recovered from outside of regulatory control will largely be predicated on the assumption that the taggant element intrinsic to the untagged nuclear material exhibits natural isotopic ratios. Here, we present high-precision Ti, Fe, and Ni isotope compositions in 13 commercial low-enriched uranium (LEU) fuel pellets to assess the suitability of these transition metals as stable isotope taggants. Our investigations reveal limited isotope variations among the fuel pellets in all three elements, which are consistent with small mass-dependent isotope fractionations, comparable to variations previously reported for natural samples. In practice, isotopically tagged nuclear materials are expected to fall along isotopic mixing lines, since intrinsic background levels of taggant elements dilute the taggant towards natural isotope compositions. Furthermore, the observation that Ti, Fe, and Ni isotope compositions in a suite of LEU fuel pellets are close to or indistinguishable from estimates for the Bulk Silicate Earth demonstrates that a two end-member mixing assumption would be valid for these transition metals, indicating that all three are promising candidate elements for stable isotope tagging. Finally, we present mass balance calculations to quantify isotopic perturbations expected from admixing isotopically anomalous Ti, Fe, and Ni taggants to assess the interplay between elemental and taggant concentrations and find favorable compromises for facilitating successful taggant identification with current analytical methods.

Intentional forensics↗
DOE OSTI2026

Space Mission Options for Reconnaissance and Mitigation of Asteroid 2024 YR4

Near-Earth asteroid 2024 YR 4 was discovered on 2024-12-27 and its probability of Earth impact in December 2032 peaked at ~3% on 2025-02-18. Additional observations ruled out Earth impact by 2025-02-23. However, the probability of lunar impact in December 2032 then rose, reaching ~4% by the end of the apparition in May 2025. James Webb Space Telescope (JWST) observations on 2025-03-26 estimated the asteroid’s diameter at 60 ± 7 m. Studies of 2024 YR 4 ’s potential lunar impact effects suggest lunar ejecta could increase micrometeoroid debris flux in low Earth orbit up to 1000 times above background levels over just a few days, possibly threatening astronauts and spacecraft. In this work, we present options for space missions to 2024 YR 4 that could be utilized if lunar impact is confirmed. Here, we cover flyby & rendezvous reconnaissance, deflection, and robust disruption of the asteroid. We examine both rapid-response and delayed launch options through 2032. We evaluate chemical and solar electric propulsion, various launch vehicles, optimized deep space maneuvers, and gravity assists. Re-tasking extant spacecraft and using built spacecraft not yet launched are also considered. The best reconnaissance mission options launch in late 2028, leaving only approximately three years for development at the time of this writing in August 2025. Deflection missions were assessed and appear impractical. However, kinetic robust disruption missions are available with launches between April 2030 and April 2032. Nuclear robust disruption missions are also available with launches between late 2029 and late 2031. Finally, even if lunar impact is ruled out there is significant potential utility in deploying a reconnaissance mission to characterize the asteroid.

Asteroid deflection↗
DOE OSTI2026

Mass dependence of halo baryon fractions from the kinetic Sunyaev–Zeldovich effect

ABSTRACT We detect the kinetic Sunyaev–Zeldovich imprint of peculiar motions of galaxy groups and clusters, using the photometric Dark Energy Spectroscopic Instrument Legacy Surveys together with cosmic microwave background (CMB) maps from the Atacama Cosmology Telescope (ACT). We develop a comprehensive forward model based on the AbacusSummit cosmological simulations: Mock galaxy group catalogues and synthetic kinetic Sunyaev–Zeldovich (kSZ) maps are generated, together with a reconstructed peculiar velocity field that allows for photo-z errors, redshift-space distortions, and survey masks. We investigate possible contamination from the cosmic infrared background (CIB), finding that CIB effects are subdominant to the kSZ signal in the relevant ACT frequency channel. We then predict the kSZ signal expected when stacking CMB temperature maps around groups, taking account of their estimated radial velocities. Comparing the model with observations, we are able to constrain the total baryon fraction within haloes, as well as their internal gas profiles. We find evidence for mass dependence of the halo baryon fraction within the virial radius. The gas fraction in massive groups is consistent with the universal baryon fraction, but low-mass groups ($10^{12.5} \lesssim M\, /\, h^{-1}\, \mathrm{M}_\odot \lesssim 10^{14}$) are depleted to $0.38 \pm 0.11$ times the universal baryon fraction. We find this low virial baryon fraction to be consistent with an extended gas profile, for which the total baryon content reaches the universal value well beyond the virial radius. This conclusion is consistent with previous analyses using X-ray, kSZ, and weak lensing, and plausibly reflects energetic feedback processes from the galaxies in these haloes.

Roper, Finn A [Institute for Astronomy, University↗
DOE OSTI2025

Estimation of intensity, footprint, and capacity of surface urban heat islands using a direction-enhanced adaptive synchronous extraction (DEASE) method

Here, the surface urban heat island (SUHI) effect, assessed through remotely sensed land surface temperature (LST), remains a focal point in urban climate research. Conventional indicators like SUHI intensity (SUHII) and footprint (SUHIF) capture peak values and spatial extent but fail to account for the cumulative thermal load—a critical dimension reflecting the total heat exposure imposed by spatially continuous warming, which directly limits a holistic assessment of ecological and societal impacts of the SUHI effect. Therefore, this study introduces an indicator termed SUHI capacity (SUHIC), designed to quantify the aggregated SUHI effect by integrating the magnitude of the warming signal across all affected areas, thereby enabling a more comprehensive evaluation of urban thermal environments. Furthermore, a direction-enhanced adaptive synchronous extraction (DEASE) method is proposed for the quantification of SUHIC. This method can dynamically identify the optimal background reference area based on the urban-rural LST gradients in various directions within the city, without relying on predefined mathematical models as previously. The results from 102 European cities first confirm that the directional variations in urban-rural LST gradients, and the DEASE method can effectively capture these distinctions for the simultaneous estimation of SUHII, SUHIF, and SUHIC. Secondly, the spatial patterns of absolute SUHIC values show strong associations with those of SUHIF (R2>0.86), while its relative values (normalized by the area of urban) align more closely with SUHII (R2 > 0.64). More importantly, SUHIC can serve as a crucial reference for assessing the urban thermal signal when SUHII and SUHIF diverge. The proposed method and framework contribute to standardizing the quantification of the SUHI effect.

Indicator↗
DOE OSTI2025

Impact of host climate model on contrail cirrus effective radiative forcing estimates

Estimates of aviation effective radiative forcing (ERF) indicate that contrail cirrus is currently its largest contributor, although with a substantial associated uncertainty of ∼ 70 %. Here, we implement the contrail parameterisation developed for the Community Atmosphere Model (CAM) in the UK Met Office Unified Model (UM), allowing us to compare, for the first time, the impact of key features of the host climate model on contrail cirrus ERF. We find that differences in background humidity between the models result in the UM-simulated contrail fractions being 2 to 3 times larger than in CAM. Additionally, the models show contrasting responses in overall global cloud fraction, with contrails increasing the total cloud fraction in the UM and decreasing it in CAM. Differences in the complexity of the cloud microphysics schemes lead to significant differences in simulated changes to cloud ice water content due to aviation. After compensating for the unrealistically low contrail optical depth in the UM, we estimate the 2018 contrail cirrus ERF to be 40.8 mW m−2 in the UM, compared to 60.1 mW m−2 in CAM. These values highlight the substantial uncertainty in contrail cirrus ERF due to differences in microphysics and radiation schemes between the two models. We also find a factor-of-8 uncertainty in contrail cirrus ERF due to existing uncertainty in contrail cirrus optical depth. Future research should focus on better representing microphysical and radiative contrail characteristics in climate models and on improved observational constraints.

Zhang, Weiyu [University of Leeds (United Kingdom)↗
DOE OSTI2026

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗
DOE OSTI2025

A statistical approach to screening isotopic signatures in monitoring for underground nuclear explosions

The ability to differentiate between atmospheric radionuclide signatures from underground nuclear explosions (UNEs) and signals from other sources, such as medical isotope-production facilities and nuclear reactors, can be critical to the detection and monitoring of unannounced, low-yield nuclear events. Signatures having anomalously high amplitudes, compared to background levels, remain the best indicator in screening for a UNE. However, isotopic composition can further validate a suspected UNE signature, but separation from any atmospheric background composition is first necessary. To date, evaluating the challenges of performing this separation has typically involved comparing an observed background with a highly idealized deterministic model of radioxenon signature production by a UNE that does not consider the influence of post-detonation chemical/physical processes in the detonation cavity or the subsequent gas transport mechanisms that can also affect the isotopic composition of the detected gas signature. In addition, purely deterministic models, as previously employed, overlook the uncertainty inherent in estimating critical parameters characterizing the UNE and its detonation environment. In this paper, we create detailed, multi-parameter models of radionuclide evolution using the widely accepted England and Rider post-detonation radionuclide decay-chain network coupled to detailed models simulating physical production and transport processes affecting the gas signature. Because these models are governed by uncertain parameters including barometric fluctuations, realistic ranges of variation for each of the parameters influencing isotopic composition are then defined. A Latin-Hypercube sampling approach is used to obtain a random distribution of isotopic production and gas transport results associated with a given value of each parameter. We apply these results to background histories of two stations, one providing 4-isotope background measurements and the other providing two-isotope measurements associated with the 2013 DPRK announced UNE.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Scintillation of liquid nitrogen

Liquid nitrogen is commonly used in cryogenic applications and is a promising medium for the direct immersion cooling of sensors used for nuclear and particle physics experiments. The scintillation properties of gaseous nitrogen are well-documented, but little is known about the scintillation of liquid nitrogen. If present, scintillation light from interactions of ambient radioactivity could produce backgrounds for rare event searches such as the direct detection of dark matter. Using a coincidence-tagged alpha decay, we demonstrate that liquid nitrogen exhibits measurable, albeit very faint, scintillation. Assuming the same scintillation wavelengths as gaseous nitrogen, we estimate a relative scintillation yield of $Y_{\liquidn}/Y^{\STP}_{\gasn} =$ \num[uncertainty-descriptors={stat,sys}]{0.0142(0.0005)(0.0030)} with respect to gaseous nitrogen at standard temperature and pressure. Considering the average scintillation yield from alpha decays in gaseous nitrogen, this implies a scintillation yield for alpha decays in liquid nitrogen of $Y_{\liquidn} = \qty[]{2.39(0.56)}{photons~per~MeV}$. To our knowledge this is the first measurement of scintillation in liquid nitrogen.

Pagani, Luca (ORCID:0000000234692581)↗
DOE OSTI2025

HIV drug resistance during antiretroviral therapy scale-up in Uganda, 2012–19: a population-based, longitudinal study

Background With scale-up of antiretroviral therapy (ART) in sub-Saharan Africa, increasing pretreatment HIV drug resistance has been reported; however, the broader effect of ART expansion on population-level resistance patterns remains insufficiently quantified. We aimed to estimate the longitudinal prevalence of drug resistance and resistance-conferring mutations. Methods This study used data collected as part of the Rakai Community Cohort Study (RCCS), an open population-based census and cohort study conducted in southern Uganda. At each survey round, residents aged 15–49 years are invited to participate and receive a structured questionnaire that obtains sociodemographic, behavioural, and health information, including self-reported past and current ART use. Voluntary HIV testing is conducted using a rapid test algorithm and a venous blood sample. People with HIV provide samples for viral load quantification and deep sequencing. We analysed RCCS survey, HIV viral load, and deep sequencing (which was used to predict resistance) data from five survey rounds. The key outcomes were the population prevalence of viraemic people with HIV with non-nucleoside reverse transcriptase inhibitor (NNRTI), nucleoside reverse transcriptase inhibitor (NRTI), protease inhibitor, or multiclass resistance among all participants (regardless of HIV serostatus) in the 2015 and 2017 surveys. Prevalence of class-specific resistance and resistance-conferring substitutions were estimated using robust log-Poisson regression. Findings Between Aug 10, 2011, and Nov 4, 2020, there were 43 361 participants in the RCCS and 7923 (18·27%) people with HIV. Over five survey rounds, 93 622 participant visits occurred, among which 17 460 (18·65%) were from people with HIV. Over the analysis period, the median age of study participants remained similar (28 years [22–35] in 2012 and 29 years [21–38] in 2019). Sufficient data were available to reliably genotype 4072 (90·03%) of 4523 participant visits from 3407 people with HIV for at least one drug. Overall population prevalence of resistance contributed by viraemic pretreatment people with HIV decreased between 2012 and 2017 from 0·56% (95% CI 0·42–0·75) to 0·25% (0·18–0·33) for NNRTI and from 0·24% (0·15–0·37) to 0·05% (0·02–0·10) for NRTI (prevalence ratio 0·44 [0·29–0·68] for NNRTI and 0·21 [0·09–0·47] for NRTI). Between 2012 and 2017, NNRTI resistance among viraemic pretreatment people with HIV increased from 4·86% (3·69–6·42) to 9·61% (7·27–12·7; prevalence ratio 1·98 [1·34–2·91]). The prevalence of NNRTI and NRTI resistance was substantially higher among viraemic treatment-experienced people with HIV (51·49% [46·24–57·34] for NNRTI and 36·46% [30·06–44·22] for NRTI in 2017) than among pretreatment people with HIV. NNRTI and NRTI resistance was predominantly attributable to rtK103N and rtM184V. inT97A was observed at a similar prevalence among viraemic treatment-experienced (9·96% [6·41–15·48]) and viraemic pretreatment (10·56% [8·01–13·93]) people with HIV; no major dolutegravir resistance mutations were observed. Interpretation Despite rising NNRTI resistance among pretreatment people with HIV, overall population prevalence of pretreatment HIV drug-resistant viraemia decreased due to increasing ART uptake and viral suppression. This finding underscores the crucial role of achieving and maintaining high ART coverage in reducing transmission of drug-resistant HIV. The high prevalence of mutations conferring resistance to components of first-line ART regimens among viraemic people with HIV is potentially concerning. Funding National Institutes of Health, Johns Hopkins University Center for AIDS Research, Bill & Melinda Gates Foundation, and the US Centers for Disease Control and Prevention.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Electromagnetic Shower Reconstruction and Identification in FASER's Emulsion Detector for LHC Forward Neutrino Measurements

We present methods for electromagnetic shower reconstruction and identification in the FASERnu emulsion detector using 100 GeV and 200 GeV electron test-beam data from the CERN SPS H4 beamline. The reconstruction employs a clustering-based algorithm without energy-dependent tuning to determine shower axes. A multi-level identification chain comprising track pre-selection, a cut-based selection, and a BDT classifier achieves combined background rejection rates of 99.99% (100 GeV) and 99.94% (200 GeV). The method reaches total reconstruction and identification efficiencies of 58.9% (100 GeV) and 70.8% (200 GeV) evaluated from simulated samples. Energy reconstruction using the total number of reconstructed segments as the calorimetric estimator yields relative biases of +0.6% (100 GeV) and -0.8% (200 GeV), with resolutions of 25.4% and 22.6%, respectively. Systematic uncertainties on the energy reconstruction are dominated by variations in emulsion film detection efficiency, contributing (+10.9%/-8.2%) at 100 GeV and (+10.3%/-6.9%) at 200 GeV. The methodology provides a validated framework for electron neutrino identification with the FASERnu detector at the LHC.

Mammen Abraham, Roshan [UC, Irvine]↗
DOE OSTI2026

SPT-3G D1: Foreground-Robust Lensing Templates for Primordial Gravitational Wave Searches

Gravitational lensing of the cosmic microwave background (CMB) generates B-mode polarization that acts as a source of contamination to searches for B modes generated by primordial gravitational waves (PGWs). The strongest constraint on PGW B modes is already significantly limited by lensing B modes, as shown in the most recent BICEP result. In this work, we present CMB lensing B-mode templates constructed using SPT-3G and Planck data, which characterize the lensing B modes and can be used to improve PGW B-mode searches. We use SPT-3G data from the 2019 and 2020 observing seasons for the E modes and the CMB-reconstructed lensing potential, and a cosmic infrared background (CIB) map from Planck as an external lensing tracer. To test for extragalactic foreground biases in the lensing template, we consider CMB lensing reconstruction variants with different levels of foreground immunity: the standard and profile-hardened global minimum variance (GMV) quadratic estimators, and a polarization-only quadratic estimator. We validate the template construction using Gaussian simulations and Agora simulations with realistic non-Gaussian foregrounds. From simulations, we find that foreground-induced biases are strongly suppressed for the template constructed with the profile-hardened GMV + CIB tracer, with residual bias below 10% of the statistical uncertainty on the template power spectrum. Data difference tests on this template similarly show no evidence for significant foreground contamination. This foreground-immune lensing template achieves delensed residual BB power of $A_{\rm lens}^{\rm res} \simeq 0.48$ averaged over $20 \leq \ell \leq 200$, the highest delensing efficiency lensing template to date. These results demonstrate and validate a method to construct foreground-robust lensing templates which will be used in upcoming delensed PGW B-mode analyses of BICEP data.

Nakato, Y. [Stanford U.]↗
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

Induced seismicity and geothermal energy production in the Salton Sea Geothermal Field, California

We analyze the relationship between geothermal energy production and seismic hazards in the Salton Sea Geothermal Field (SSGF) between 1972 and 2022. A clear increase in seismic activity accompanies geothermal energy production and is greatest to the east of the Brawley fault, where the amount of injection exceeds the amount of production. We estimate that, whereas there was a 2% chance of a M6.07 earthquake nucleating inside the SSGF within a fifty-year period prior to energy production (pre-production), there is an equal probability that a M6.70 earthquake nucleates there in a fifty-year period during which historically average energy production conditions persist (syn-production). Similarly, we estimate a 2% chance of a M7.15 and M6.92 occurring in the broader Brawley Seismic Zone (excluding the SSGF) within a fifty-year period during the pre- and syn-production eras, respectively. We find that linear regression models fail to reliably forecast the background seismicity rate as a function of fluid production and injection.

15 GEOTHERMAL ENERGY↗