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

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At least 19 records

InSAR Time Series Analysis of L-Band Wide-Swath SAR Data Acquired by ALOS-2

We present that operating at L-band (24 cm wavelength) in wide-swath modes is one of the characteristics of the new and next generation satellite synthetic aperture radar (SAR) missions. After 3 years of operation, the Japan Aerospace Exploration Agency Advanced Land Observing Satellite-2 (ALOS-2) satellite has acquired a wealth of L-band wide-swath SAR data over many areas using its ScanSAR mode. We present interferometry SAR (InSAR) time series analysis results from ALOS-2 ScanSAR data. We analyze the possible error sources in the InSAR and correct them if possible. We present different time series analysis results including azimuth frequency modulation rate error, line of sight (LOS) ionospheric phase, azimuth shift caused by the ionosphere, and LOS displacement processed using both full-aperture and burst-by -burst workflows. The final InSAR LOS displacement time series result reveals both large-scale tectonic and small-scale anthropogenic deformation components. In conclusion, the results demonstrate the potential for measuring continental or even global-scale tectonic deformation and illustrate the promise of upcoming L-band wide-swath SAR missions, such as the NASA-ISRO SAR mission.

47 OTHER INSTRUMENTATION↗

Stellar Parameters for Pulsating B-star Candidates in the Kepler Field

The field of asteroseismology has enjoyed a large swath of data coming from recent missions (e.g., CoRoT, Kepler, K2). This wealth of new data has allowed the field to expand beyond the previous limitation of a few extremely bright and evolved stars. Asteroseismology relies on accurate surface measurements for boundary conditions, but the predicted physical parameters in the Kepler Input Catalog (KIC) are unreliable for hot stars. We present stellar parameters of 25 candidate pulsating B-star candidates in the Kepler field. We use blue optical spectra to measure the projected rotational velocity (Vsin i), effective temperature (T {sub eff}), and surface gravity (logg) using TLUSTY and Kurucz ATLAS9 model atmospheres. We find a large discrepancy between our spectroscopically derived parameters and those derived from photometry in the KIC and Gaia Data Release 2 (DR2). Using spectral energy distributions, we also measure the radii of these stars and later calculate the luminosities and masses. We find the extinctions (A {sub V}) of these stars to be consistent with zero, which is expected for stars of high Galactic latitude.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantitatively Monitoring Bubble-Flow at a Seep Site Offshore Oregon: Field Trials and Methodological Advances for Parallel Optical and Hydroacoustical Measurements

Two lander-based devices, the Bubble-Box and GasQuant-II, were used to investigate the spatial and temporal variability and total gas flow rates of a seep area offshore Oregon, United States. The Bubble-Box is a stereo camera–equipped lander that records bubbles inside a rising corridor with 80 Hz, allowing for automated image analyses of bubble size distributions and rising speeds. GasQuant is a hydroacoustic lander using a horizontally oriented multibeam swath to record the backscatter intensity of bubble streams passing the swath plain. The experimental set up at the Astoria Canyon site at a water depth of about 500 m aimed at calibrating the hydroacoustic GasQuant data with the visual Bubble-Box data for a spatial and temporal flow rate quantification of the site. For about 90 h in total, both systems were deployed simultaneously and pressure and temperature data were recorded using a CTD as well. Detailed image analyses show a Gaussian-like bubble size distribution of bubbles with a radius of 0.6–6 mm (mean 2.5 mm, std. dev. 0.25 mm); this is very similar to other measurements reported in the literature. Rising speeds ranged from 15 to 37 cm/s between 1- and 5-mm bubble sizes and are thus, in parts, slightly faster than reported elsewhere. Bubble sizes and calculated flow rates are rather constant over time at the two monitored bubble streams. Flow rates of these individual bubble streams are in the range of 544–1,278 mm 3 /s. One Bubble-Box data set was used to calibrate the acoustic backscatter response of the GasQuant data, enabling us to calculate a flow rate of the ensonified seep area (~1,700 m 2 ) that ranged from 4.98 to 8.33 L/min (5.38 × 10 6 to 9.01 × 10 6 CH 4 mol/year). Such flow rates are common for seep areas of similar size, and as such, this location is classified as a normally active seep area. For deriving these acoustically based flow rates, the detailed data pre-processing considered echogram gridding methods of the swath data and bubble responses at the respective water depth. The described method uses the inverse gas flow quantification approach and gives an in-depth example of the benefits of using acoustic and optical methods in tandem.

54 ENVIRONMENTAL SCIENCES↗

C-FOG: Life of Coastal Fog

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp . An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

58 GEOSCIENCES↗

Quantifying the effect of 3D models on moment tensor results using synthetic data

Moment tensors provide vital information on seismic source properties for seismic events. Moment tensors require seismic wavespeed models to compute Green’s functions, which measure the impulse response between a given source and receiver. Traditionally, researchers have used one-dimensional velocity models to calculate Green’s functions since 1D Green’s functions are computationally cheap to compute. Local 1D velocity models can also accurately model waveforms at short distances (< 500 km). However, 1D velocity models do not account for lateral heterogeneity, which can cause significant misfit in tectonically complex regions such as the Middle East (Covellone and Savage, 2012). Green’s functions calculated using 3D seismic wavespeed models have been shown to perform better in tectonically complex regions (Covellone and Savage, 2012; Kintner and Modrak, 2022), so we are interested in quantifying the effect of considering 3D structure on moment tensor inversion results. The Middle East is an ideal study area for a synthetic moment tensor test for two reasons. Firstly, the Middle East is a tectonically complex region that has been heavily studied. Secondly, the Middle East has significant seismic activity throughout the region, but imperfect station coverage due to limited open data through large swaths of the domain. The tectonic complexity and uneven station coverage will test real-world performance even in a synthetic experiment.

58 GEOSCIENCES↗

Moisture‐Budget Drivers of Global Projections of Meteorological Drought From Multiple GCM Large Ensembles

Future projections of global meteorological drought are evaluated in the Multi‐Model Large Ensemble Archive, including an evaluation of the atmospheric moisture budget, conditioned on drought years. Drought is defined as 5‐year running‐mean annual precipitation below some threshold, for example, 10th percentile. Drought increases in frequency over the subtropics, in addition to certain tropical regions, consistent with previous studies. Here, the moisture‐budget decomposition allows drought to be defined as mean‐flow, eddy, or feedback droughts, depending on which term in the equation contributes the largest negative interannual anomaly. In the historical climate, mean‐flow droughts constitute most droughts at low latitudes; eddy droughts are equally common at higher latitudes; feedback droughts (i.e., droughts exacerbated by land–atmosphere feedbacks) constitute almost all droughts in water‐limited subtropical/Mediterranean regions. The future drought increases are predominantly due to increases in feedback droughts in regions where these droughts are common historically but also over the Amazon. However, over most Mediterranean‐type regions mean‐flow droughts are also large contributors, resulting from dynamics. Eddy droughts also contribute to future increases along the equatorward flanks of historical eddy‐driven jets, likely reflecting poleward shifts therein. Model uncertainty is particularly large over the Amazon and Australia, a reflection of model diversity in processes associated with land‐atmosphere interaction. Based on these results, an availability of 3‐D atmospheric data from a wider swath of global climate model large ensembles could help constrain global drought projections based on the representation of drought mechanisms in the historical climate.

54 ENVIRONMENTAL SCIENCES↗

Solvent effects on differentiation of mouse brain tissue using laser microdissection ‘cut and drop’ sampling with direct mass spectral analysis

Rationale: Laser microdissection-liquid vortex capture/electrospray ionization mass spectrometry (LMD-LVC/ESI-MS) has potential for on-line classification of tissue but an investigation into what analytical conditions provide best spectral differentiation has not been conducted. The effects of solvent, ionization polarity, and spectral acquisition parameters on differentiation of mouse brain tissue regions are described.Methods: Individual 40 × 40 μm microdissections from cortex, white, grey, granular, and nucleus regions of mouse brain tissue were analyzed using different capture/ESI solvents, in positive and negative ion mode ESI, using time-of-flight (TOF)-MS and sequential window acquisitions of all theoretical spectra (SWATH)-MS (a permutation of tandem-MS), and combinations thereof. Principal component analysis-linear discriminant analysis (PCA-LDA), applied to each mass spectral dataset, was used to determine the accuracy of differentiation of mouse brain tissue regions. Results: Mass spectral differences associated with capture/ESI solvent composition manifested as altered relative distributions of ions rather than the presence or absence of unique ions. In negative ion mode ESI, 80/20 (v/v) methanol/water yielded spectra with low signal/noise ratios relative to other solvents. PCA-LDA models acquired using 90/10 (v/v) methanol/chloroform differentiated tissue regions with 100% accuracy while data collected using methanol misclassified some samples. The combination of SWATH-MS and TOF-MS data improved differentiation accuracy.Conclusions: Combined TOF-MS and SWATH-MS data differentiated white, grey, granular, and nucleus mouse tissue regions with greater accuracy than when solely using TOF-MS data. Using 90/10 (v/v) methanol/chloroform, tissue regions were perfectly differentiated. Lastly, these results will guide future studies looking to utilize the potential of LMD-LVC/ESI-MS for tissue and disease differentiation.

47 OTHER INSTRUMENTATION↗

Data Science in Chemical Engineering: Applications to Molecular Science

Chemical engineering is being rapidly transformed by the tools of data science. On the horizon, artificial intelligence (AI) applications will impact a huge swath of our work, ranging from the discovery and design of new molecules to operations and manufacturing and many areas in between. Early adoption of data science, machine learning, and early examples of AI in chemical engineering has been rich with examples of molecular data science—the application tools for molecular discovery and property optimization at the atomic scale. Here, we summarize key advances in this nascent subfield while introducing molecular data science for a broad chemical engineering readership. We introduce the field through the concept of a molecular data science life cycle and discuss relevant aspects of five distinct phases of this process: creation of curated data sets, molecular representations, data-driven property prediction, generation of new molecules, and feasibility and synthesizability considerations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Waffle Homes: Utilizing Aerial Imagery of Unfinished Buildings to Determine Average Room Size

A primary function of the Population Density Tables Project (PDT) at Oak Ridge National Laboratory is to produce residential population densities per 1000 sq. ft. for each country and their associated first-level administrative units. This is accomplished by utilizing the average size of different types of dwelling areas (urban, rural, single-family, multi-family, etc.) and the average household size provided by a country’s Census or statistical bureau records. This data is available for the majority of Europe, North America, and large swathes of Asia, but is less easily found in Africa and South America. In these regions, Censuses generally report dwelling area by number of rooms, which poses the challenging question of how we can translate number of rooms to dwelling size when no dwelling size areas are available with which to compare. Using sub-meter resolution satellite imagery of Accra, Ghana, this challenge can be tackled using imagery of roofless buildings currently under construction that show the interior floor plan of the dwelling. A sample of buildings from the different neighborhoods of Accra can be digitized to provide an estimate and range of average room sizes of dwellings. This average room size can then be translated to a total dwelling area using the "number of rooms occupied by a household" variable from the Ghanaian Census. This intermediate step between average dwelling size and number of rooms occupied, fills the missing link that prevents PDT from continually producing new population densities for countries where dwelling size is unavailable through any official means.

Woody, Carson↗

AlgoSCR: an algorithm for solar contamination removal from radio interferometric data

Hydrogen intensity mapping is a new field in astronomy that promises to make three-dimensional maps of the matter distribution of the Universe using the redshifted 21cm line of neutral hydrogen gas (HI). Several ongoing and upcoming radio interferometers, such as Tianlai, CHIME, HERA, HIRAX, etc., are using this technique. These instruments are designed to map large swaths of the sky by drift scanning over periods of many months. One of the challenges of the observations is that the daytime data are contaminated by strong radio signals from the Sun. In the case of Tianlai, this results in almost half of the measured data being unusable. We try to address this issue by developing an algorithm for solar contamination removal (AlgoSCR) from the radio data. The algorithm is based on an eigenvalue analysis of the visibility matrix and hence is applicable only to interferometers. We apply AlgoSCR to simulated visibilities, as well as real daytime data from the Tianlai dish array. The algorithm can reduce strong solar contamination by about 95 per cent without seriously affecting other weaker sky signals and thus makes the data usable for certain applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NEAMS-Multiphysics MOOSE End Year Framework Activities FY20

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a general finite element package meant for high performance solution of multiphysics problems in science and engineering. In this report, we present additions and enhancements to MOOSE funded by the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program. NEAMS-funded MOOSE framework library improvements include: expansion of support for multi-level multi-application restart; enhancement of coupling between native MOOSE applications and external libraries; addition of a sparse automatic differentiation (AD) container enabling non-local degree of freedom coupling; block-specific quadrature rules; further development of an eigenvalue executioner; faster setup of periodic boundary conditions; and creation of a mesh meta-data system streamlining simulation startup. Besides developing the framework library, NEAMS funds were used to overhaul a swath of important MOOSE infrastructure in order to substantially improve user experience. These critical infrastructure changes included adapting MOOSE to python 3, improving the test harness to catch race conditions, and most importantly transitioning MOOSE to use Conda, a globally known packaging system, that greatly eases software adoption.

97 MATHEMATICS AND COMPUTING↗

Elucidating the Dynamics of Electroweak Symmetry Breaking through Study of High-Multiplicity Boson Final States at the LHC

To understand the full story of the electroweak symmetry breaking (EWSB) and how the universe arrived at today’s universe, the structure of the Higgs potential needs to be probed. We must carefully select and study processes at the LHC that are sensitive to the Higgs potential. In this context, longitudinal vector boson scattering (VBS) processes, V L V L →V L V L , and di-Higgs production, including V L V L →HH at the LHC have been studied for any potential deviation from SM prediction. However, many classes of models beyond the Standard Model (BSM) may result in the 2→2 process being perfectly well-behaved and SM-like but show interesting deviations in 2→3, 2→4, or 2→n(3) processes. If we are to complete the mission objectives the P5 laid out, then a large swath of 2→n(3) must be thoroughly searched and checked. The research supported by this award used data collected at the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) to explore VBS produced VVH process in the semi-merged channel. In addition, in the electroweak sector, there are open questions in the multi-gauge boson couplings and the Higgs couplings to the gauge bosons. The research supported by the award also studied the triboson production WWZ process at the LHC, which is a crossed diagram of a VBS process. During the funded period of 9 months, the analysis designs have been finalized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Detection and classification capabilities of two multibeam sonars

Multibeam sonars can be used to detect and classify marine fauna under conditions when optical sensors are ineffective. In this work, we compare the detection and classification capabilities of two multibeam sonars with different operating frequencies, the Tritech Gemini 720is (720 kHz) and the Teledyne BlueView M900-2250 (2250 kHz). The two sonars were deployed with overlapping swaths in a narrow tidal channel with peak currents of approximately 2 m/s where seals, schools of fish, and diving birds were intermittently present. In comparing data concurrently acquired by both sonars, we observe differences in the appearance of detected targets and detection capabilities. The detected target tracks are classified using a random forest model as either individual biological targets (flora and fauna, including fish, diving birds, seals, and plant matter), fish schools, or nonbiological targets (including entrained air and sonar artifacts). Despite the observed differences in detection capabilities for the two sonars, automatic classification distinguishes between target classes with precision and recall above 0.7 and 0.9, respectively. Furthermore, these results suggest that while similar methodologies can be used for data analysis, some outcomes from environmental studies using multibeam sonars may be instrument-specific.

16 TIDAL AND WAVE POWER↗

Geothermal Deep Direct Use for Turbine Inlet Cooling in East Texas

The National Renewable Energy Laboratory (NREL), the Southern Methodist University Geothermal Laboratory (SMU), Eastman Chemical (Longview, TX), and TAS (Houston, TX) evaluated the feasibility of using geothermal heat to improve the performance of a natural-gas power plant in East Texas. The area of interest is the Eastman Chemical plant in Longview, Texas, which is on the northwestern margin of a geologic region known as the Sabine Uplift. The feasibility study focused on determining the potential for accessing a subsurface hot-water geothermal resource within a 10-km radius of the site to provide thermal energy for absorption chillers. Wells within a 20-km radius are included for broader geological comparison to determine the heat flow, temperature-at-depth, field porosity and permeability. The lithologies of most interest are the Lower Cretaceous Trinity Group and Upper Jurassic Cotton Valley Group. The deeper Cotton Valley formations are hotter (averaging 117 to 130°C), yet permeability and porosity are low. The shallower Trinity Group contains more variability in permeability and porosity and lower temperatures averaging about 98 to 117°C. The shallower formations are considered despite the lower temperature because of increased ability to produce larger volumes of water and extract enough heat before reinjection. The complete SMU analysis is available in the National Geothermal Data System (NGDS). Tapping such deep geothermal sources for direct heating (as opposed to power generation) is known as geothermal deep direct use (DDU). Geothermal DDU has potential across a wide swath of the United States but is underutilized due to challenging project economics associated with developing a deep geothermal resource for what are typically small-scale, variable-demand projects. This project examines the feasibility of geothermal energy integration in a natural-gas combined cycle power station in East Texas. The DDU resource is tapped to drive absorption chillers (24/7) for production of chilled water at 5-10°C (41-50°F). This chilled water is stored until needed, which allows for continuous operation with a relatively small-capacity geothermal/absorption chiller system. When conditions are favorable, the chilled water is dispatched to cool the air entering the compressor stage of a gas combustion turbine. This process, known as turbine inlet cooling (TIC), boosts power production during periods of high temperature and high-power demand. Such systems can enhance grid reliability and reduce the cost for peak-demand power. A simulation model of the power plant was developed in IPSEpro software and validated against operational data from the plant. This model allowed the team to estimate the additional power that could be produced by applying TIC under different operating and ambient conditions. Absorption chiller performance was estimated from vendor sources to determine the production rate of chilled water from the geothermal resource. Geothermal drilling and development costs were estimated using NREL's GEOPHIRES 2.0. The expected lower drilling costs in this region led to an estimated cost of geothermal heat of about $4/MMBtu (1.4 cents/kWh t ). The estimated cost for the absorption chillers and TIC hardware were obtained from literature sources and project partners. Hourly data were obtained for weather, natural gas and electricity prices, and plant operating state for 2017, which served as a representative year. NREL estimated the capital cost, operating cost, and additional electricity production and revenue for different combinations of geothermal capacity, chiller capacity, and water storage-tank size. The analysis drove toward smaller geothermal and chiller systems to reduce equipment cost. A relatively low-cost water storage tank accumulated the near-continuous chilled water output for later use when TIC was most valued.

15 GEOTHERMAL ENERGY↗

Oddities in Lightning Measurements from Space Reveal Extreme Flashes and Thunderstorms [Slides]

Space-based sensors are well-suited for detecting intracloud (IC) and Cloud to Ground (CG) lightning over large swaths of the Earth. Current sensors also measure the signals generated by lightning that contain information about the physical discharge process and the radiative transfer effects they experience on their path to orbit. Long records of orbital lightning data reveal rare and exceptional lightning signals push the boundaries of what the sensors are designed to measure and our understanding of what lightning and thunderstorms are capable of. Space-based sensors have revealed long-horizontal “megaflashes,” highly radiant “superbolts,” extremely high flash rate thunderstorms, and more.

58 GEOSCIENCES↗

Enhancing Energy Systems Cybersecurity using Blockchain (SBIR Final Phase I Report)

The goal of this SBIR research has been to investigate blockchain technology and its applications in the fossil fuel sector - with a focus on how this technology could be leveraged to improve the cybersecurity of these systems. The primary tasks that we carried out involved evaluating existing blockchain technology, identifying relevant and compelling use cases, researching the integration of blockchain technology into industrial systems, and the design and implementation of a proof of concept system. A key finding is that within industrial systems where many parties are involved, trust can be lacking. By providing technology that assures verifiable trust in the data, many processes may be able to be automated. We believe that verifiable trust in the data can only be provided if we trust the data from "cradle to grave." This means that we need to secure the systems that are creating the data, moving the data, and storing the data. The last of these is provided by blockchain. Blockchain technology will not only improve security and trust within these systems, in some cases it will also be able increase the operational tempo of some processes significantly. We are vendors of commercial communications software that is based upon the Open Management Group (OMG) data distribution service (DDS) standard; it secures data in motion. In addition to many defense, transportation, and medical systems, it is running in oil, gas, and coal systems. Over the course of this effort we have come to believe that blockchain technology could be an important enabler for this sector: we have engaged with a number of our customers and identified several compelling use cases beyond cryptocurrencies, which we document further within this report. Furthermore, as it turns out, we believe that many of these use cases are relevant across a wide swath of industries. This analysis provides necessary and important foundational work that could lead to new ways of securing oil and gas processing, and coal mining infrastructure against cyber threats.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Uncovering New Physics in the Cosmic Microwave Background: Developing Novel Theoretical Models and Machine-Learning-Powered Constraints

The search for evidence of new physics via its signatures in the cosmos is a cornerstone goal of the Office of High Energy Physics in the DOE Office of Science. Indeed, the current concordance cosmological model provides intriguing hints for beyond-the-standard-model (BSM) physics, such as dark matter and dark energy. Recently, a potential breakdown has appeared in this model, which could be initial evidence toward a further important revision in our fundamental theoretical understanding of cosmology. This breakdown is reflected in disagreements between inferences of the current expansion rate of the universe, H 0 (the Hubble constant), based on indirect, cosmological data (e.g., from the early universe) and based on direct, local measurements. Despite significant effort, a compelling new concordance cosmological model has yet to be found; achieving significant progress on this front was the first major focus of the project. Theoretical considerations indicate that if the observational discrepancies are not due to systematic errors, they strongly suggest new physics operating in the redshift range just prior to recombination, when cosmic microwave background (CMB) photons last scattered. Crucially, almost all such models produce unique signatures in the CMB temperature and polarization power spectra, which will be measured with unprecedented precision by ongoing and upcoming experiments, including the DOE-supported CMB-S4 project. However, these subtle hints of new physics must be uncovered from beneath a swath of Galactic and extragalactic foreground contamination. Current CMB analysis methods, although powerful, do not optimally infer the CMB power spectrum in the presence of non-Gaussian foregrounds. There is thus scope for theoretical improvement in this foundational challenge of cosmological inference, which formed the second major focus of the project. The primary objectives of the project were two-fold: (1) to develop new theoretical models in cosmology that can restore concordance amongst the full suite of cosmological data sets, thereby potentially providing evidence of novel BSM physics; (2) to develop new theoretical machinery to enable significant sensitivity improvements in searches for new physics in cosmology, particularly via the CMB power spectrum. The two objectives are intertwined, as the analysis methodology improvements in (2) will enable the tightest possible constraints on the signatures of new physics predicted by the novel scenarios in (1). The theoretical approaches to restore concordance focused on models involving novel scalar field dynamics in the pre-recombination universe (the “early dark energy” scenario and modifications thereof), as well as couplings between this field and other components in the standard cosmological model, such as dark matter. We also studied a model featuring a generalization of the decaying dark matter scenario, in which a sub-component of dark matter converts into dark radiation at late times in cosmic history. While these ideas are mostly driven by phenomenological considerations, this tactic has proven extremely successful in cosmology throughout the past few decades, including in the early history of evidence for dark matter and dark energy. The new theoretical machinery envisioned in (2) is undergirded by developments in signal processing and machine learning, which will enable improvements in CMB power spectrum estimation in the presence of non-Gaussian foreground contaminants. In turn, this will yield optimal sensitivity in searches for new physics in the CMB, by maximizing the cosmological information that is extracted from this observable. The most ambitious outcome of this work would be the construction of a new cosmological model that restores concordance amongst data sets. Although the individual models studied here did not fully achieve that goal, significant progress in narrowing down the model space was made, as described below. Moreover, the outcome of the methodological improvements in (2) will significantly impact a wide range of theoretical cosmology, by enabling the tightest possible constraints on any model that leaves novel signatures in the CMB temperature and polarization power spectra.

79 ASTRONOMY AND ASTROPHYSICS↗