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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Out of one, many: distinguishing time delays from lensed supernovae

ABSTRACT Gravitationally lensed Type Ia supernovae are an emerging probe with great potential for constraining dark energy, spatial curvature, and the Hubble constant. The multiple images and their time delayed and magnified fluxes may be unresolved, however, blended into a single light curve. We demonstrate methods without a fixed source template matching for extracting the individual images, determining whether there are one (no lensing) or two or four (lensed) images, and measuring the time delays between them that are valuable cosmological probes. We find 100 per cent success for determining the number of images for time delays greater than ∼10 d.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Leveraging graph clustering techniques for cyber‐physical system analysis to enhance disturbance characterisation

Abstract Cyber‐physical systems have behaviour that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber‐physical systems requires improved understanding of the combined cyber‐physical system behaviour and methods for holistic analysis. Therefore, the authors propose leveraging clustering techniques on cyber‐physical data from smart grid systems to analyse differences and similarities in behaviour during cyber‐, physical‐, and cyber‐physical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber‐physical systems. Through this analysis, deeper insights can be shared with decision‐makers on what cyber and physical components are strongly or weakly linked, what cyber‐physical pathways are most traversed, and the criticality of certain cyber‐physical nodes or edges. This paper presents several types of clustering methods for cyber‐physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber‐physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber‐physical graph interdependency analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Indra: a public computationally accessible suite of cosmological N -body simulations

ABSTRACT Indra is a suite of large-volume cosmological N-body simulations with the goal of providing excellent statistics of the large-scale features of the distribution of dark matter. Each of the 384 simulations is computed with the same cosmological parameters and different initial phases, with 10243 dark matter particles in a box of length 1 h−1 Gpc, 64 snapshots of particle data and halo catalogues, and 505 time-steps of the Fourier modes of the density field, amounting to almost a petabyte of data. All of the Indra data are immediately available for analysis via the SciServer science platform, which provides interactive and batch computing modes, personal data storage, and other hosted data sets such as the Millennium simulations and many astronomical surveys. We present the Indra simulations, describe the data products and how to access them, and measure ensemble averages, variances, and covariances of the matter power spectrum, the matter correlation function, and the halo mass function to demonstrate the types of computations that Indra enables. We hope that Indra will be both a resource for large-scale structure research and a demonstration of how to make very large data sets public and computationally accessible.

Falck, Bridget↗
DOE OSTI2023

Genomic variation across Chinook salmon populations reveals effects of a duplication on migration alleles and supports fine scale structure

Abstract The distribution of ecotypic variation in natural populations is influenced by neutral and adaptive evolutionary forces that are challenging to disentangle. This study provides a high‐resolution portrait of genomic variation in Chinook salmon ( Oncorhynchus tshawytscha ) with emphasis on a region of major effect for ecotypic variation in migration timing. With a filtered data set of ~13 million single nucleotide polymorphisms (SNPs) from low‐coverage whole genome resequencing of 53 populations (3566 barcoded individuals), we contrasted patterns of genomic structure within and among major lineages and examined the extent of a selective sweep at a major effect region underlying migration timing (GREB1L/ROCK1). Neutral variation provided support for fine‐scale structure of populations, while allele frequency variation in GREB1L/ROCK1 was highly correlated with mean return timing for early and late migrating populations within each of the lineages ( r 2 = .58–.95; p < .001). However, the extent of selection within the genomic region controlling migration timing was much narrower in one lineage (interior stream‐type) compared to the other two major lineages, which corresponded to the breadth of phenotypic variation in migration timing observed among lineages. Evidence of a duplicated block within GREB1L/ROCK1 may be responsible for reduced recombination in this portion of the genome and contributes to phenotypic variation within and across lineages. Lastly, SNP positions across GREB1L/ROCK1 were assessed for their utility in discriminating migration timing among lineages, and we recommend multiple markers nearest the duplication to provide highest accuracy in conservation applications such as those that aim to protect early migrating Chinook salmon. These results highlight the need to investigate variation throughout the genome and the effects of structural variants on ecologically relevant phenotypic variation in natural species.

Horn, Rebekah L.↗
DOE OSTI2022

Thermoelastic properties of zircon: Implications for geothermobarometry

Abstract A thermal-pressure equation of state has been determined for zircon (ZrSiO4) that characterizes its thermoelastic behavior at metamorphic conditions. New pressure-volume (P-V) data from a “Mud Tank” zircon have been collected from 1 bar to 8.47(1) GPa using X-ray diffraction, and elastic moduli were measured from room temperature up to 1172 K by resonance ultrasound spectroscopy. These data were fitted simultaneously with temperature-volume (T-V) data from the literature in EosFit7c using a new scaling technique. The parameters of a third-order Birch-Murnaghan EoS with a Mie-Grüneisen-Debye model for thermal pressure have compressional EoS parameters K0T = 224.5(1.2) GPa, K0T' = 4.90(31) with a fixed initial molar volume V0 = 39.26 cm3/mol and thermal parameters γ0 = 0.868(15), q = 2.37(80), and ΘD = 848(38) K. EoS parameters that describe the variation of unit-cell parameters with pressure and temperature were determined using an isothermal-type EoS. This new EoS confirms that zircons are stiffer than garnets and exhibit a much lower thermal expansion. This results in steep isomekes between zircon and garnets, which makes zircon trapped as inclusions in garnets at metamorphic conditions a good piezothermometer.

Geochemistry & Geophysics↗
NASA NTRS2003

The Achromatic Light Curve of the Optical Afterglow of GRB 030226 at a Redshift of z Approximately 2

Abstract. We report on optical and near-infrared (NIR) follow-up observations of the afterglow of GRB 030226, mainly performed with the telescopes at ESO La Silla and Paranal, with additional data obtained at other places. Our first observations started 0.2 days after the burst when the afterglow was at a magnitude of R approximately equal to 19 . One week later the magnitude of the afterglow had fallen to R=25, and at two weeks after the burst it could no longer be detected (R > 26). Our VLT blueband spectra show two absorption line systems at redshifts z = 1.962 +/- 0.001 and at z = 1.986 +/- 0.001, placing the redshift of the burster close to 2. Within our measurement errors no evidence for variations in the line strengths has been found between 0.2 and 1.2 days after the burst. An overabundance of alpha-group elements might indicate that the burst occurred in a chemically young interstellar region shaped by the nucleosynthesis from type II supernovae. The spectral slope of the afterglow shows no signs for cosmic dust along the line of sight in the GRB host galaxy, which itself remained undetected (R > 26.2). At the given redshift no supernova component affected the light from the GRB afterglow, so that the optical transient was essentially only powered by the radiation from the GRB fireball, allowing for a detailed investigation of the color evolution of the afterglow light. In our data set no obvious evidence for color changes has been found before, during, or after the smooth break in the light curve approximately 1 day after the burst. In comparison with investigations by others, our data favor the interpretation that the afterglow began to develop into a homogeneous interstellar medium before the break in the light curve became apparent.

Klose, S.↗
DOE OSTI2020

Quantum anomalous Hall effect in two-dimensional magnetic insulator heterojunctions

Abstract Recent years have witnessed tremendous success in the discovery of topological states of matter. Particularly, sophisticated theoretical methods in time-reversal-invariant topological phases have been developed, leading to the comprehensive search of crystal database and the prediction of thousands of topological materials. In contrast, the discovery of magnetic topological phases that break time reversal is still limited to several exemplary materials because the coexistence of magnetism and topological electronic band structure is rare in a single compound. To overcome this challenge, we propose an alternative approach to realize the quantum anomalous Hall (QAH) effect, a typical example of magnetic topological phase, via engineering two-dimensional (2D) magnetic van der Waals heterojunctions. Instead of a single magnetic topological material, we search for the combinations of two 2D (typically trivial) magnetic insulator compounds with specific band alignment so that they can together form a type-III broken-gap heterojunction with topologically non-trivial band structure. By combining the data-driven materials search, first-principles calculations, and the symmetry-based analytical models, we identify eight type-III broken-gap heterojunctions consisting of 2D ferromagnetic insulators in the MXY compound family as a set of candidates for the QAH effect. In particular, we directly calculate the topological invariant (Chern number) and chiral edge states in the MnNF/MnNCl heterojunction with ferromagnetic stacking. This work illustrates how data-driven material science can be combined with symmetry-based physical principles to guide the search for heterojunction-based quantum materials hosting the QAH effect and other exotic quantum states in general.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey

ABSTRACT Recent analyses have found intriguing correlations between the colour (c) of type Ia supernovae (SNe Ia) and the size of their ‘mass-step’, the relationship between SN Ia host galaxy stellar mass (Mstellar) and SN Ia Hubble residual, and suggest that the cause of this relationship is dust. Using 675 photometrically classified SNe Ia from the Dark Energy Survey 5-yr sample, we study the differences in Hubble residual for a variety of global host galaxy and local environmental properties for SN Ia subsamples split by their colour. We find a 3σ difference in the mass-step when comparing blue (c < 0) and red (c > 0) SNe. We observe the lowest r.m.s. scatter (∼0.14 mag) in the Hubble residual for blue SNe in low mass/blue environments, suggesting that this is the most homogeneous sample for cosmological analyses. By fitting for c-dependent relationships between Hubble residuals and Mstellar, approximating existing dust models, we remove the mass-step from the data and find tentative ∼2σ residual steps in rest-frame galaxy U − R colour. This indicates that dust modelling based on Mstellar may not fully explain the remaining dispersion in SN Ia luminosity. Instead, accounting for a c-dependent relationship between Hubble residuals and global U − R, results in ≤1σ residual steps in Mstellar and local U − R, suggesting that U − R provides different information about the environment of SNe Ia compared to Mstellar, and motivating the inclusion of galaxy U − R colour in SN Ia distance bias correction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A new redback pulsar candidate 4FGL J2054.2+6904

ABSTRACT The Fermi catalogue contains about 2000 unassociated γ-ray sources. Some of them were recently identified as pulsars, including so-called redbacks and black widows, which are millisecond pulsars in tight binary systems with non- and partially-degenerate low-mass stellar companions irradiated by the pulsar wind. We study a likely optical and X-ray counterpart of the Fermi source 4FGL J2054.2+6904 proposed earlier as a pulsar candidate. We use archival optical data as well as Swift/XRT and SRG/eROSITA X-ray data to clarify its nature. Using Zwicky Transient Facility data in g and r bands spanning over 4.7 yr, we find a period of ≈7.5 h. The folded light curve has a smooth sinusoidal shape with the peak-to-peak amplitude of ≈0.4 mag. The spectral fit to the optical spectral energy distribution of the counterpart candidate gives the star radius of 0.5 ± 0.1 R⊙ and temperature of 5500 ± 300 K implying a G2–G9-type star. Its X-ray spectrum is well fitted by an absorbed power law with the photon index of 1.0 ± 0.3 and unabsorbed flux of ≈2 × 10−13 erg s−1 cm−2. All the properties of 4FGL J2054.2+6904 and its presumed counterpart suggest that it is a member of the redback family.

Karpova, A. V. (ORCID:0000000242115856)↗
DOE OSTI2021

A model-independent data assimilation (MIDA) module and its applications in ecology

Abstract. Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.

58 GEOSCIENCES↗
DOE OSTI2022

iMaNGA: mock MaNGA galaxies based on IllustrisTNG and MaStar SSPs – I. Construction and analysis of the mock data cubes

ABSTRACT Galaxy formation and evolution simulations are essential tools to probe poorly known astrophysics processes, but particular care is needed to compare simulations with galaxy observations, as observed data need to be modelled as well. We present a method to generate mock galaxies from the hydro-dynamical IllustrisTNG simulations which are suited to compare with integral field spectroscopic observation of galaxies from the SDSS-IV/Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. First, we include the same instrumental effects and procedures as adopted in the acquisition and analysis of real data. Furthermore, we generate the galaxy spectra from the simulations using new stellar population models based on the MaNGA stellar library (MaStar). In this way, our mock data cubes have the same spatial sampling, cover the same wavelength range (3600–10 300 Å), and share the same spectral resolution (R ≈ 1800) and flux calibration of real MaNGA galaxy spectra. In this first paper, we demonstrate the method over an early- and a late-type simulated galaxy from TNG50. We analyse the correspondent mock MaNGA-like data cubes with the same full spectral fitting code, firefly, which was used for the observed spectra. We find that the intrinsic and recovered age and metallicity gradients are consistent within 1σ, with residuals over all tassels consistent with 0 at the 68 ${{\ \rm per\ cent}}$ confidence level. We also perform the challenging test at comparing intrinsic and recovered star formation histories, finding a close resemblance between input and output. In follow-up papers, we will present a full simulated MaNGA-like catalogue (≈10 000 galaxies) with a comprehensive comparison of TNG50 simulations to MaNGA observational results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Flaring Stars in a Non-targeted mm-wave Survey with SPT-3G

We present a flare star catalog from four years of non-targeted millimeter-wave survey data from the South Pole Telescope (SPT). The data were taken with the SPT-3G camera and cover a 1500-square-degree region of the sky from $20^{h}40^{m}0^{s}$ to $3^{h}20^{m}0^{s}$ in right ascension and $-42^{\circ}$ to $-70^{\circ}$ in declination. This region was observed on a nearly daily cadence from 2019-2022 and chosen to avoid the plane of the galaxy. A short-duration transient search of this survey yields 111 flaring events from 66 stars, increasing the number of both flaring events and detected flare stars by an order of magnitude from the previous SPT-3G data release. We provide cross-matching to Gaia DR3, as well as matches to X-ray point sources found in the second ROSAT all-sky survey. We have detected flaring stars across the main sequence, from early-type A stars to M dwarfs, as well as a large population of evolved stars. These stars are mostly nearby, spanning 10 to 1000 parsecs in distance. Most of the flare spectral indices are constant or gently rising as a function of frequency at 95/150/220 GHz. The timescale of these events can range from minutes to hours, and the peak $\nu L_{\nu}$ luminosities range from $10^{27}$ to $10^{31}$ erg s$^{-1}$ in the SPT-3G frequency bands.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Nothing to see here: failed supernovae are faint or rare

ABSTRACT The absence of Type IIP core-collapse supernovae arising from progenitors above 17 solar masses suggests the existence of another evolutionary path by which massive stars end their lives. The direct collapse of a stellar core to a black hole without the production of a bright, explosive transient is expected to produce a long-lived, dim, red transient known as a failed supernova. Despite the detection of a number of candidates for disappearing massive stars in recent years, conclusive observational evidence for failed supernovae remains elusive. A custom-built pipeline designed for the detection of faint transients is used to re-analyse 10 yr of observations of 231 nearby galaxies from the PTF/ZTF surveys. This analysis recovers known supernovae, and yields a number of interesting transients. However, none of these are consistent with a failed supernova. Through Monte Carlo tests the recovery efficiency of our pipeline is quantified. By assuming failed supernovae occur as a Poissonian process with zero detections in the data set, 95 per cent upper limits to the rate of failed supernovae are calculated as a function of failed supernova absolute magnitude. We estimate failed supernovae to be less than 0.61, 0.33, 0.26, or 0.23 of the core-collapse SN rate for absolute magnitudes of −11, −12, −13, and −14, respectively. Finally, we show that if they exist, the Vera C. Rubin Observatory will find 1.7–3.7 failed SNe per year for an absolute bolometric luminosity of ∼6 × 1039 erg s−1 out to distances of 33–43 Mpc, depending on their assumed spectral energy distribution.

Byrne, R. A. (ORCID:0000000177661737)↗
DOE OSTI2021

Measurements from mobile surface vehicles during the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE)

Abstract. Between 14 and 20 July 2018, small unmanned aircraft systems (UASs) were deployed to the San Luis Valley of Colorado (USA) alongside surface-based remote sensors, in situ sensors, and radiosonde systems as part of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). The measurements collected as part of LAPSE-RATE targeted quantities related to enhancing our understanding of boundary layer structure, cloud and aerosol properties and surface–atmosphere exchange and provide detailed information to support model evaluation and improvement work. Additionally, intensive intercomparison between the different unmanned aircraft platforms was completed. The current paper describes the observations obtained using three different types of surface-based mobile observing vehicles. These included the University of Colorado Mobile UAS Research Collaboratory (MURC), the National Oceanic and Atmospheric Administration National Severe Storms Laboratory Mobile Mesonet, and two University of Nebraska Combined Mesonet and Tracker (CoMeT) vehicles. Over the 1-week campaign, a total of 143 h of data were collected using this combination of vehicles. The data from these coordinated activities provide detailed perspectives on the spatial variability of atmospheric state parameters (air temperature, humidity, pressure, and wind) throughout the northern half of the San Luis Valley. These datasets have been checked for quality and published to the Zenodo data archive under a specific “community” setup for LAPSE-RATE (https://zenodo.org/communities/lapse-rate/, last access: 21 January 2021) and are accessible at no cost by all registered users. The primary dataset DOIs are https://doi.org/10.5281/zenodo.3814765 (CU MURC measurements; de Boer et al., 2020d), https://doi.org/10.5281/zenodo.3738175 (NSSL MM measurements; Waugh, 2020), and https://doi.org/10.5281/zenodo.3838724 (UNL CoMeT measurements; Houston and Erwin, 2020).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surface science insight note: A linear algebraic approach to elucidate native films on Fe 3 O 4 surface

Standard materials are often used to obtain spectra that can be compared to those from unknown samples. Spectra measured from these known substances are also used as a means of computing sensitivity factors to allow quantification by X-ray photoelectron spectroscopy (XPS) of less well-defined materials. Spectra from known materials also provide line shapes suitable for inclusion in spectral models which, when fitted to spectra, permit the chemical state for a sample to be assessed. Both types of information depend on isolating photoemission signals from the inelastically scattered signal. In this Insight note, technical issues associated with the use of XPS of as received Fe 3 O 4 powder sample surface are discussed. The Insight note is designed to show how linear algebraic techniques applied to data collected from a sample marketed as pure Fe 3 O 4 powder are used to verify that XPS has been performed on chemistry representative of the sample. The methods described in this Insight note can further be utilized in elucidating complex XPS data obtained from thin films formed or evolved during cyclic/non-steady use of complex (electro)catalyst surfaces, especially in the presence of contaminants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Tree crown damage and its effects on forest carbon cycling in a tropical forest

Abstract Crown damage can account for over 23% of canopy biomass turnover in tropical forests and is a strong predictor of tree mortality; yet, it is not typically represented in vegetation models. We incorporate crown damage into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to evaluate how lags between damage and tree recovery or death alter demographic rates and patterns of carbon turnover. We represent crown damage as a reduction in a tree's crown area and leaf and branch biomass, and allow associated variation in the ratio of aboveground to belowground plant tissue. We compare simulations with crown damage to simulations with equivalent instant increases in mortality and benchmark results against data from Barro Colorado Island (BCI), Panama. In FATES, crown damage causes decreases in growth rates that match observations from BCI. Crown damage leads to increases in carbon starvation mortality in FATES, but only in configurations with high root respiration and decreases in carbon storage following damage. Crown damage also alters competitive dynamics, as plant functional types that can recover from crown damage outcompete those that cannot. This is a first exploration of the trade‐off between the additional complexity of the novel crown damage module and improved predictive capabilities. At BCI, a tropical forest that does not experience high levels of disturbance, both the crown damage simulations and simulations with equivalent increases in mortality does a reasonable job of capturing observations. The crown damage module provides functionality for exploring dynamics in forests with more extreme disturbances such as cyclones and for capturing the synergistic effects of disturbances that overlap in space and time.

Needham, Jessica F.↗
DOE OSTI2021

Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography *

Abstract Neutron computed tomography (NCT), a 3D non-destructive characterization technique, is carried out at nuclear reactor or spallation neutron source-based user facilities. Because neutrons are not severely attenuated by heavy elements and are sensitive to light elements like hydrogen, neutron radiography and computed tomography offer a complementary contrast to x-ray CT conducted at a synchrotron user facility. However, compared to synchrotron x-ray CT, the acquisition time for an NCT scan can be orders of magnitude higher due to lower source flux, low detector efficiency and the need to collect a large number of projection images for a high-quality reconstruction when using conventional algorithms. As a result of the long scan times for NCT, the number and type of experiments that can be conducted at a user facility is severely restricted. Recently, several deep convolutional neural network (DCNN) based algorithms have been introduced in the context of accelerating CT scans that can enable high quality reconstructions from sparse-view data. In this paper, we introduce DCNN algorithms to obtain high-quality reconstructions from sparse-view and low signal-to-noise ratio NCT data-sets thereby enabling accelerated scans. Our method is based on the supervised learning strategy of training a DCNN to map a low-quality reconstruction from sparse-view data to a higher quality reconstruction. Specifically, we evaluate the performance of two popular DCNN architectures—one based on using patches for training and the other on using the full images for training. We observe that both the DCNN architectures offer improvements in performance over classical multi-layer perceptron as well as conventional CT reconstruction algorithms. Our results illustrate that the DCNN can be a powerful tool to obtain high-quality NCT reconstructions from sparse-view data thereby enabling accelerated NCT scans for increasing user-facility throughput or enabling high-resolution time-resolved NCT scans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A novel CMB component separation method: hierarchical generalized morphological component analysis

ABSTRACT We present a novel technique for cosmic microwave background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to generalized morphological component analysis (GMCA), we introduce hierarchical GMCA (HGMCA), a Bayesian hierarchical graphical model for source separation. We test our method on Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25{{\ \rm per\ cent}}$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the 0.02–0.03 per cent level at ℓ > 200 (and $\lt 0.26{{\ \rm per\ cent}}$ for all ℓ), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art internal linear combination type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.

79 ASTRONOMY AND ASTROPHYSICS↗