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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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NASA NTRS1993

Successive X-ray bursts from accreting neutron stars

The evolution of a neutron star undergoing a series of thermonuclear flashes in its accreted hydrogen-rich layer has been numerically followed to determine the effects of the history of the neutron star's thermal and compositional structure on the properties of the emitted X-ray bursts. Burst characteristics are studied for a range of mass accretion rates, CNO abundances in the accreted matter, and initial thermal states of the underlying neutron star core; the bursts exhibit erratic behavior for low CNO metal abundances and cool neutron star cores, with the burst recurrence time scales varying by 1-2 orders of magnitude. There is typically a continued presence of a substantial amount of unburnt hydrogen in the accreted layer throughout the series of the X-ray burst events. Convective mixing during the quiescent phase leads to the inward transport of helium to high densities and eventually to the initiation of the next outburst. The resulting bursts can be weak and, in such cases, are characterized by short recurrence time scales (1-2 hr), low peak luminosities (0.1-0.2 times the Eddington value), and low alpha-values (about 20).

Taam, Ronald E.↗

DOE OSTI2026

Dark Energy Survey Year 3 results: Simulation-based 𝑤CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. Here, this work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the CosmoGridV1 suite of N-body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological 𝑤CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent Buzzard galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving 2−3× higher figures of merit in the 𝛺 𝑚 − 𝑆 8 plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming Stage-IV wide-field imaging surveys.

Thomsen, A. [Zurich, ETH] (ORCID:0000000203099021)↗

DOE OSTI2023

The cosmic web of X-ray active galactic nuclei seen through the eROSITA Final Equatorial Depth Survey (eFEDS)

Which galaxies in the general population turn into active galactic nuclei (AGNs) is a keystone of galaxy formation and evolution. Thanks to SRG/eROSITA’s contiguous 140 square degree pilot survey field, we constructed a large, complete, and unbiased soft X-ray flux-limited (FX > 6.5 × 10 -15 erg s -1 cm -2 ) AGN sample at low redshift, 0.05 < z < 0.55. Two summary statistics, the clustering using spectra from SDSS-V and galaxy-galaxy lensing with imaging from HSC, are measured and interpreted with halo occupation distribution and abundance matching models. Both models successfully account for the observations. We obtain an exceptionally complete view of the AGN halo occupation distribution. The population of AGNs is broadly distributed among halos with a mean mass of 3.9 -2.4 +2.0 × 10 12 M ⊙ . This corresponds to a large-scale halo bias of b(z = 0.34) = 0.99 -0.10 +0.08 . The central occupation has a large transition parameter, σ log 10 (M) = 1.28 ± 0.2. The satellite occupation distribution is characterized by a shallow slope, α sat = 0.73 ± 0.38. We find that AGNs in satellites are rare, with f sat < 20%. Most soft X-ray-selected AGNs are hosted by central galaxies in their dark matter halo. A weak correlation between soft X-ray luminosity and large-scale halo bias is confirmed (3.3σ). We discuss the implications of environmental-dependent AGN triggering. This study paves the way toward fully charting, in the coming decade, the coevolution of X-ray AGNs, their host galaxies, and dark matter halos by combining eROSITA with SDSS-V, 4MOST, DESI, LSST, and Euclid data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Joint X-Ray, Kinetic Sunyaev–Zeldovich, and Weak Lensing Measurements: Toward a Consensus Picture of Efficient Gas Expulsion from Groups and Clusters

There is no consensus on how baryon feedback shapes the underlying matter distribution from either simulations or observations. We confront the uncertain landscape by jointly analyzing new measurements of the gas distribution around groups and clusters—DESI+ACT kinetic Sunyaev–Zel’dovich (kSZ) effect profiles and eROSITA X-ray gas masses—with mean halo masses characterized by galaxy–galaxy lensing. Across a wide range of halo masses ( M 500 = 10 13−14 M ⊙ ) and redshifts (0 < z < 1), we find evidence of more efficient gas expulsion beyond several R 500 than predicted by most state-of-the-art simulations. A like-with-like comparison reveals all kSZ and X-ray observations are inconsistent with the fiducial 1 Gpc 3 hydrodynamical FLAMINGO simulation, which was calibrated to reproduce pre-eROSITA X-ray gas fractions: eROSITA X-ray gas fractions are 2 × lower than the simulation, and the kSZ measurements are combined >8σ discrepant. The FLAMINGO simulation variant with the most gas expulsion, and therefore the most suppression of the matter power spectrum relative to a dark-matter-only simulation, provides a good description of how much gas is expelled and how far it extends; the enhanced gas depletion is achieved by more powerful but less frequent AGN outbursts. Joint kSZ, X-ray, and lensing measurements form a consistent picture of gas expulsion beyond several R 500 , implying a more suppressed matter power spectrum than predicted by most recent simulations. Complementary observables (e.g., thermal Sunyaev–Zel’dovich effect and fast radio bursts) and next-generation simulations are critical to understanding the physical mechanism behind this extreme gas expulsion and mapping its impact on the large-scale matter distribution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Identifying Different Classes of Seismic Noise Signals Using Unsupervised Learning

Abstract Proper classification of nontectonic seismic signals is critical for detecting microearthquakes and developing an improved understanding of ongoing weak ground motions. We use unsupervised machine learning to label five classes of nonstationary seismic noise common in continuous waveforms. Temporal and spectral features describing the data are clustered to identify separable types of emergent and impulsive waveforms. The trained clustering model is used to classify every 1 s of continuous seismic records from a dense seismic array with 10–30 m station spacing. We show that dominate noise signals can be highly localized and vary on length scales of hundreds of meters. The methodology demonstrates the complexity of weak ground motions and improves the standard of analyzing seismic waveforms with a low signal‐to‐noise ratio. Application of this technique will improve the ability to detect genuine microseismic events in noisy environments where seismic sensors record earthquake‐like signals originating from nontectonic sources.

Johnson, Christopher W.↗

DOE OSTI2020

Stellar and weak lensing profiles of massive galaxies in the Hyper-Suprime Cam survey and in hydrodynamic simulations

ABSTRACT We perform a consistent comparison of the mass and mass profiles of massive (M⋆ > 1011.4 M⊙) central galaxies at z ∼ 0.4 from deep Hyper Suprime-Cam (HSC) observations and from the Illustris, TNG100, and Ponos simulations. Weak lensing measurements from HSC enable measurements at fixed halo mass and provide constraints on the strength and impact of feedback at different halo mass scales. We compare the stellar mass function (SMF) and the Stellar-to-Halo Mass Relation (SHMR) at various radii and show that the radius at which the comparison is performed is important. In general, Illustris and TNG100 display steeper values of α where $M_{\star } \propto M_{\rm vir}^{\alpha }$. These differences are more pronounced for Illustris than for TNG100 and in the inner rather than outer regions of galaxies. Differences in the inner regions may suggest that TNG100 is too efficient at quenching in situ star formation at Mvir ≃ 1013 M⊙ but not efficient enough at Mvir ≃ 1014 M⊙. The outer stellar masses are in excellent agreement with our observations at Mvir ≃ 1013 M⊙, but both Illustris and TNG100 display excess outer mass as Mvir ≃ 1014 M⊙ (by ∼0.25 and ∼0.12 dex, respectively). We argue that reducing stellar growth at early times in $M_\star \sim 10^{9-10} \, \mathrm{M}_{\odot }$ galaxies would help to prevent excess ex-situ growth at this mass scale. The Ponos simulations do not implement AGN feedback and display an excess mass of ∼0.5 dex at r < 30 kpc compared to HSC which is indicative of overcooling and excess star formation in the central regions. The comparison of the inner profiles of Ponos and HSC suggests that the physical scale over which the central AGN limits star formation is r ≲ 20 kpc. Joint comparisons between weak lensing and galaxy stellar profiles are a direct test of whether simulations build and deposit galaxy mass in the correct dark matter haloes and thereby provide powerful constraints on the physics of feedback and galaxy growth. Our galaxy and weak lensing profiles are publicly available to facilitate comparisons with other simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Cosmology from cross-correlation of ACT-DR4 CMB lensing and DES-Y3 cosmic shear

Cross-correlation between weak lensing of the Cosmic Microwave Background (CMB) and weak lensing of galaxies offers a way to place robust constraints on cosmological and astrophysical parameters with reduced sensitivity to certain systematic effects affecting individual surveys. We measure the angular cross-power spectrum between the Atacama Cosmology Telescope (ACT) DR4 CMB lensing and the galaxy weak lensing measured by the Dark Energy Survey (DES) Y3 data. Our baseline analysis uses the CMB convergence map derived from ACT-DR4 and Planck data, where most of the contamination due to the thermal Sunyaev Zel’dovich effect is removed, thus avoiding important systematics in the cross-correlation. In our modelling, we consider the nuisance parameters of the photometric uncertainty, multiplicative shear bias and intrinsic alignment of galaxies. The resulting cross-power spectrum has a signal-to-noise ratio = 7.1 and passes a set of null tests. We use it to infer the amplitude of the fluctuations in the matter distribution (S_8 ≡ σ_8(Ω_m/0.3)^0.5 = 0.782 ± 0.059) with informative but well-motivated priors on the nuisance parameters. We also investigate the validity of these priors by significantly relaxing them and checking the consistency of the resulting posteriors, finding them consistent, albeit only with relatively weak constraints. This cross-correlation measurement will improve significantly with the new ACT-DR6 lensing map and form a key component of the joint 6×2pt analysis between DES and ACT.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

The growth of density perturbations in the last ~10 billion years from tomographic large-scale structure data

In order to investigate the origin of the ongoing tension between the amplitude of matter fluctuations measured by weak lensing experiments at low redshifts and the value inferred from the cosmic microwave background anisotropies, we reconstruct the evolution of this amplitude from z ~ 2 using existing large-scale structure data. To do so, we decouple the linear growth of density inhomogeneities from the background expansion, and constrain its redshift dependence making use of a combination of 6 different data sets, including cosmic shear, galaxy clustering and CMB lensing. We analyze these data under a consistent harmonic-space angular power spectrum-based pipeline. We show that current data constrain the amplitude of fluctuations mostly in the range 0.2 < z < 0.7, where it is lower than predicted by . This difference is mostly driven by current cosmic shear data, although the growth histories reconstructed from different data combinations are consistent with each other, and we find no evidence of systematic deviations in any particular experiment. In spite of the tension with , the data are well-described by the model, albeit with a lower value of S 8 ≡ σ 8 (Ω m /0.3) 0.5 . As part of our analysis, we find constraints on this parameter of S 8 = 0.7781 ± 0.0094 (68% confidence level), reaching almost percent-level errors comparable with CMB measurements, and 3.4σ away from the value found by .

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1999

A TRMM Rainfall Estimation Method Applicable to Land Areas

Methods developed to estimate rain rate on a footprint scale over land with the satellite-borne multispectral dual-polarization Special Sensor Microwave Imager (SSM/1) radiometer have met with limited success. Variability of surface emissivity on land and beam filling are commonly cited as the weaknesses of these methods. On the contrary, we contend a more significant reason for this lack of success is that the information content of spectral and polarization measurements of the SSM/I is limited. because of significant redundancy. As a result, the complex nature and vertical distribution C, of frozen and melting ice particles of different densities, sizes, and shapes cannot resolved satisfactorily. Extinction in the microwave region due to these complex particles can mask the extinction due to rain drops. Because of these reasons, theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. To illustrate the weakness of these models, as an example we can consider the brightness temperature measurement made by the radiometer in the 85 GHz channel (T85). Models indicate that T85 should be inversely related to the rain rate, because of scattering. However, rain rate derived from 15-minute rain gauges on land indicate that this is not true in a majority of footprints. This is also supported by the ship-borne radar observations of rain in the Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) region over the ocean. Based on these observations. we infer that theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. We do not follow the above path of rain retrieval on a footprint scale. Instead, we depend on the limited ability of the microwave radiometer to detect the presence of rain. This capability is useful to determine the rain area in a mesoscale region. We find in a given rain event that this rain area is closely related to the mesoscale-average rain rate. Based on this observation, in this study we have developed a method to estimate the mesoscale-average rain rate over land utilizing microwave radiometer data. Because of the high degree of geographic and seasonal variability in the nature and intensity of rain, this method requires some tuning with 15-minute rain gauge data on land. After tuning the method, it can be applied to an independent set of rain events that are close in time and space. We find that the mesoscale rain rates retrieved over the period of a month on land with this method shows a correlation of about 0.85 with respect to the surface rain-gauge observations. This mesoscale-average rain rate estimation method can be useful to extend the spatial and temporal coverage of the rainfall data provided by the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM) satellite.

Prabhakara, C.↗

DOE OSTI2022

Bridging the Bondi and Event Horizon Scales: 3D GRMHD Simulations Reveal X-shaped Radio Galaxy Morphology

X-shaped radio galaxies (XRGs) produce misaligned X-shaped jet pairs and make up ≲10% of radio galaxies. XRGs are thought to emerge in galaxies featuring a binary supermassive black hole (SMBH), SMBH merger, or large-scale ambient medium asymmetry. We demonstrate that XRG morphology can naturally form without such special, preexisting conditions. Our 3D general-relativistic magnetohydrodynamic (GRMHD) simulation for the first time follows magnetized rotating gas from outside the SMBH sphere of influence of radius RB to the SMBH of gravitational radius Rg at the largest scale separation, RB/Rg = 103, to date. Initially, our axisymmetric system of constant-density hot gas contains a weak vertical magnetic field and rotates in the equatorial plane of a rapidly spinning SMBH. We seed the gas with small-scale 2% level pressure perturbations. Infalling gas forms an accretion disk, and the SMBH launches relativistically magnetized collimated jets reaching well outside RB. Under the pressure of the infalling gas, the jets intermittently turn on and off, erratically wobble, and inflate pairs of cavities in different directions, resembling an X-shaped jet morphology. Synthetic X-ray images reveal multiple pairs of jet-powered shocks and cavities. Large-scale magnetic flux accumulates on the SMBH, becomes dynamically important, and leads to a magnetically arrested disk state. The SMBH accretes at 2% of the Bondi rate ($\dot{M}\simeq 2.4\times {10}^{-3}{M}_{\odot }\,{\mathrm{yr}}^{-1}$ for M87*) and launches twin jets at η = 150% efficiency. These jets are powerful enough (P jets ≃ 2 × 10 44 erg s -1 ) to escape along the SMBH spin axis and end the short-lived intermittent jet state, whose transient nature can account for the rarity of XRGs.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2011

The Atacama Cosmology Telescope: A Measurement of the Primordial Power Spectrum

We present constraints on the primordial power spectrum of adiabatic fluctuations using data from the 2008 Southern Survey of the Atacama Cosmology Telescope (ACT). The angular resolution of ACT provides sensitivity to scales beyond l = 1000 for resolution of multiple peaks in the primordial temperature power spectrum, which enables us to probe the primordial power spectrum of adiabatic scalar perturbations with wavenumbers up to k approx. = 0.2 Mp/c. We find no evidence for deviation from power-law fluctuations over two decades in scale. Matter fluctuations inferred from the primordial temperature power spectrum evolve over cosmic time and can be used to predict the matter power spectrum at late times; we illustrate the overlap of the matter power inferred from CMB measurements (which probe the power spectrum in thc linear regime) with existing probes of galaxy clustering, cluster abundances and weak lensing constraints on the primordial power. This highlights the range of scales probed by current measurement.s of the matter power spectrum.

Hlozek, Renee↗

DOE OSTI2026

Prospects for exploring non-standard neutrino properties with argon-based CEvNS experiments

Coherent elastic neutrino-nucleus scattering (CEvNS) provides a powerful frame-work for testing the Standard Model (SM) and searching for new physics at low energies. In this work, we examine the prospects for argon-based CEvNS experiments at stopped-pion sources to perform precision measurements of weak interactions and probe non-standard neutrino properties. Our study focused on the CENNS-10 and CENNS-750 detectors at the Spallation Neutron Source at Oak Ridge National Laboratory, the Coherent Captain Mills (CCM) detector at Los Alamos National Laboratory, and the proposed PIP2-BD detector at Fermilab’s Facility for Dark Matter Discovery (F2D2). Using realistic neutrino fluxes and detector configurations corresponding to these facilities, we evaluate event rates and sensitivities to a range of observables. Within the SM, argon-based CEvNS detectors enable precision tests of electroweak parameters, including the weak mixing angle, at momentum transfers well below the electroweak scale. We also investigate the sensitivity of these experiments to neutrino electromagnetic properties, such as the magnetic moment and effective charge radius, as well as to possible non-standard neutrino interactions with quarks. Together, these studies highlight the potential of argon-based CEvNS experiments as a clean and versatile platform for precision exploration of non-standard neutrino properties.

Carey, Sam [Wayne State U.] (ORCID:000900029607531↗

DOE OSTI2021

Kinetically Controlled Formation of Semi-crystalline Conjugated Polymer Nanostructures

Conjugated polymer (CP) materials that are considered as an attractive choice for various electronic and optoelectronic applications possess highly heterogeneous complex structures that can span several orders of magnitude in length scale. This is due to the intricate coupling effects of weak secondary interactions and entropic forces that determine molecular organization in bulk polymer materials. Understanding the influence of molecular interactions on the emergence and evolution of nano- and microscale structures is of paramount importance to the guided design and development of condensed CP materials. Such understanding is even more critical for the rational design of hierarchical systems away from equilibrium, where weak molecular interactions can guide the system along competing kinetic pathways toward local energy minima and metastable architectures. In this work, we studied a promising concept for accessing various kinetically stabilized semi-crystalline CP nanostructures that are formed in the process of controlled chain-growth Kumada catalyst-transfer polymerization initiated by a small-molecule catalytic species which can exist in equilibrium between free and aggregated states. Specifically, we chose a small-molecule perylenedicarboximide (PDCI) polymerization catalytic initiator which has a strong tendency toward reversible supramolecular assembly–disassembly that can be controlled by temperature. Addition of a thiophene monomer to a solution of the PDCI initiator starts the chain-growth polymerization process, which produces distinct nanoscale semi-crystalline polythiophene structures formed under predominant kinetic control. Furthermore, we demonstrated that, depending on the reaction temperature (which affects the fine balance between the position of PDCI assembly–disassembly equilibrium, rate of polymerization, and solvent–solute interactions for the growing polythiophene chains), a range of kinetically trapped hierarchically organized semi-crystalline CP systems with substantially varying optoelectronic properties could be obtained. In addition to spectroscopic and electron microscopic studies, in order to better reveal the structural aspects of the generated polymer nanoscale systems, we carried out a series of X-ray diffraction and neutron scattering experiments which indicated complex hierarchical organization in these kinetically stabilized CP assembled materials. We expect that this in situ polymerization-based approach can lead to a general way to expand access to various semi-crystalline CP nanostructured materials with broadly tunable electronic and optical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗

DOE OSTI2022

Map-based cosmology inference with lognormal cosmic shear maps

ABSTRACT Most cosmic shear analyses to date have relied on summary statistics (e.g. ξ+ and ξ−). These types of analyses are necessarily suboptimal, as the use of summary statistics is lossy. In this paper, we forward-model the convergence field of the Universe as a lognormal random field conditioned on the observed shear data. This new map-based inference framework enables us to recover the joint posterior of the cosmological parameters and the convergence field of the Universe. Our analysis properly accounts for the covariance in the mass maps across tomographic bins, which significantly improves the fidelity of the maps relative to single-bin reconstructions. We verify that applying our inference pipeline to Gaussian random fields recovers posteriors that are in excellent agreement with their analytical counterparts. At the resolution of our maps – and to the extent that the convergence field can be described by the lognormal model – our map posteriors allow us to reconstruct all summary statistics (including non-Gaussian statistics). We forecast that a map-based inference analysis of LSST-Y10 data can improve cosmological constraints in the σ8–Ωm plane by $\approx\!{30}{{\ \rm per\ cent}}$ relative to the currently standard cosmic shear analysis. This improvement happens almost entirely along the $S_8=\sigma _8\Omega _{\rm m}^{1/2}$ directions, meaning map-based inference fails to significantly improve constraints on S8.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The Simons Observatory: Combining cross-spectral foreground cleaning with multitracer B -mode delensing for improved constraints on inflation

The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio r from measurements of cosmic microwave background (CMB) polarization B-modes. Its nominal design including three small-aperture telescopes (SATs) targets a precision σ⁡(r = 0) ≤ 0.003 without delensing. Achieving this goal and further reducing uncertainties requires a thorough understanding and mitigation of other large-scale B-mode sources such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate r by including delensing within a cross-spectral likelihood, and demonstrate it for the first time on SO-like simulations accounting for various levels of foreground complexity, inhomogeneous noise and partial sky coverage. As introduced in an earlier SO delensing paper, lensing B-modes are synthesized using internal CMB lensing reconstructions as well as Planck-like cosmic infrared background maps and LSST-like galaxy density maps. We then extend SO’s power-spectrum-based foreground-cleaning algorithm to include all auto- and cross-spectra between the lensing template and the SAT B-modes in the likelihood function. This allows us to constrain r and the parameters of our foreground model simultaneously. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions. In the absence of primordial B-modes, we find that the 1⁢σ statistical uncertainty on r, σ⁡(r), decreases by 37% as a result of delensing. Tensor modes at the level of r = 0.01 are successfully detected by our pipeline. Even when using more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of r both with and without delensing by employing the moment-expansion method. In this case, uncertainties are increased due to the higher number of model parameters, and delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO’s nominal sensitivity level.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Multiplication of Freestanding Compound Semiconductor Membranes from a Single Wafer by Alternating Growth with 2D Materials

Single-crystal compound semiconductors, such as III-N and III-V, are important building blocks for functional devices due to their high electron mobilities, wide range of bandgaps, and excellent optoelectronic properties. However, current methods to produce their freestanding membranes for heterointegration suffer from slow processes or poor material quality. Here, we demonstrate an approach to grow and harvest multiple wafer-scale single-crystal membranes with high throughput by introducing weak van der Waals interfaces between epitaxial layers. This is achieved by directly growing two-dimensional (2D) materials on compound semiconductors in their native deposition systems, which enables alternating growth of 2D material and compound semiconductor epitaxial layers in a single run. Each epilayer in the multi-stack structure is then sequentially harvested by mechanical exfoliation, producing multiple freestanding single-crystal membranes with extremely high throughput from a single wafer, primed for integration in mixed-dimensional heterostructures.

Han, Ne Myo↗

DOE OSTI2022

Multiplication of Freestanding Compound Semiconductor Membranes from a Single Wafer by Alternating Growth with 2D Materials

Han, Ne Myo↗