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NASA NTRS2018

Life Beyond the Solar System: Remotely Detectable Biosignatures

For the first time in human history, we will soon be able to apply to the scientific method to the question "Are We Alone?" The rapid advance of exoplanet discovery, planetary systems science, and telescope technology will soon allow scientists to search for life beyond our Solar System through direct observation of extrasolar planets. This endeavor will occur alongside searches for habitable environments and signs of life within our Solar System. While these searches are thematically related and will inform each other, they will require separate observational techniques. The search for life on exoplanets holds potential through the great diversity of worlds to be explored beyond our Solar System. However, there are also unique challenges related to the relatively limited data this search will obtain on any individual world.

Domagal-Goldman, Shawn↗

DOE OSTI2023

Snowmass2021 Cosmic Frontier White Paper: Primordial black hole dark matter

Primordial Black Holes (PBHs) are a viable candidate to comprise some or all of the dark matter and provide a unique window into the high-energy physics of the early universe. This white paper discusses the scientific motivation, current status, and future reach of observational searches for PBHs. Future observational facilities supported by DOE, NSF, and NASA will provide unprecedented sensitivity to PBHs. However, devoted analysis pipelines and theoretical modeling are required to fully leverage these novel data. The search for PBHs constitutes a low-cost, high-reward science case with significant impact on the high energy physics community.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Developing a Vision for Heliophysics Infrastructure: The LIKED Resource and the DIARieS Ecosystem

Heliophysics data and computational infrastracture are not equipped for 21st science, suffering from holes in the know-how to build better systems. Without a clear vision, efforts to improve the infrastructure have been incremental and incoherent. This poster presents both the vision and the technology required: an online LIbrary KnowledgE and Discovery (LIKED) resource for discovering and implementing knowledge, data, and infrastructure resources; and an online analysis ecosystem to simplify Discovery, Implementation, Analysis, Reproducibility, and Sharing (DIARieS) of scientific results and environments. The LIKED and DIARieS solutions adopt FAIR data principles and the best practices from the budding field of open science. The proposed new infrastructure components will close many of the current gaps in heliophysics’ infrastructure, such as the ability to search for data and knowledge by phenomenon across domains, and to find software and examples relevant to the desired data set (including model data). Further, these components will enable community members to more efficiently use the resources already present and improve upon the content via a community-curated and trusted library. Combining these solutions lowers the barriers to heliophysics resources for all, increasing the return on our investments. Finally, the structure behind these ideas are topic-agnostic, so they are fully extensible to other fields, leading to invaluable connections to other disciplines. Just as with the development and construction of a long-term satellite mission, we must work together as a community to build a vision of the infrastructure that will most benefit the community, and then collaborate to construct, assemble, and test all the necessary pieces individually and as a unit. Our purpose in presenting this work is to not only describe the proposed vision, but also to gather feedback from the community on this topic.

infrastructure↗

DOE OSTI2023

A Search for Heavy Neutral Leptons Decaying to Electron-Positron Pairs and Neutral Pions in the MicroBooNE Detector

This thesis presents a search for heavy neutral leptons (HNLs) decaying inside the MicroBooNE detector. The MicroBooNE detector is a liquid-argon time projection chamber located at Fermilab that receives flux from two neutrino beams; the booster neutrino beam (BNB) and the neutrinos at the main injector (NuMI) beam. The search uses data taken when the NuMI beam was on, with a total exposure of $7.01\times10^{20}$ protons on target. HNLs would be produced in kaon decays, and the source of HNLs targeted in this search is kaons decaying at rest in the NuMI hadron absorber. The kinematics of the HNLs produced in this way allow their decays to be distinguished from the majority of beam-neutrino interactions and cosmic-ray activity that constitute the background. Two HNL decay channels are studied, $\nu$\ee and \vpi. Boosted decision trees (BDTs) are trained to separate the simulated HNL decays from the expected background events. The BDT score distributions are used to calculate upper limits on the mixing angle \umusq in the mass range $10\le m_{\rm HNL}\le 245$~MeV. This is the first direct search for HNL decays to the \vpi channel, and the limits provide the most stringent constraints on \umusq in the mass range $35<\mhnl<175$~MeV.

43 PARTICLE ACCELERATORS↗

NASA NTRS1993

A tool for manual endmember selection and spectral unmixing

Sampling a continuous radiance spectrum in many narrow contiguous spectral bands results in a high covariance between the bands. Hence, the true dimensionality of imaging spectrometer data is not determined by the number of spectral bands, but by the number of spectrally unique signatures whose mixtures reproduce the spectral variance observed in an image. Methods to unmix high dimensional multispectral data use principal components analysis to reduce the dimensionality. The variance of the spectral data is modeled as a linear combination of a finite set of endmembers in the space of the eigen-vectors that account for most of the variance. The number and characteristics of these endmembers are determined not only by the number and characteristics of the spectrally unique materials on the surface but also by processes (e.g., illumination, atmospheric scattering and absorption) affecting the signal received by the sensor. Selection of endmember spectra has typically been from a library. However, since most libraries are incomplete and do not account for the processes mentioned above, we have devised a computer display that allows researchers to explore interactively the eigenvector space of a representative and mean-corrected subset of the image data in search of extreme spectra to designate as endmembers. This display, which is based on parallel coordinates, is unique in the area of multidimensional visualization in that it includes not only a passive view of higher dimensional data but also the capability to interact and move geometrical objects in higher dimensional spaces.

Bateson, C. Ann↗

DOE OSTI2024

Search for a heavy neutral lepton that mixes predominantly with the tau neutrino

We report a search for a heavy neutral lepton (HNL) that mixes predominantly with ν τ . The search utilizes data collected with the Belle detector at the KEKB asymmetric energy e + e − collider. The data sample was collected at and just below the center-of-mass energies of the ϒ ( 4 S ) and ϒ ( 5 S ) resonances and has an integrated luminosity of 915 fb − 1 , corresponding to ( 836 ± 12 ) × 10 6 e + e − → τ + τ − events. We search for production of the HNL (denoted N ) in the decay τ − → π − N followed by its decay via N → μ + μ − ν τ . The search focuses on the parameter-space region in which the HNL is long-lived, so that the μ + μ − originate from a common vertex that is significantly displaced from the collision point of the KEKB beams. Consistent with the expected background yield, one event is observed in the data sample after application of all the event-selection criteria. We report limits on the mixing parameter of the HNL with the τ neutrino as a function of the HNL mass. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

NASA NTRS1976

A search of the SAS-2 data for pulsed gamma-ray emission from radio pulsars

Data from the SAS-2 high energy gamma ray experiment were examined for pulsed emission from each of 75 radio pulsars which were viewed by the instrument and which have sufficiently well defined period and period derivative information from radio observations to allow for gamma ray periodicity searches. When gamma ray arrival times were converted to pulsar phase using the radio reference timing information, two pulsars, PSR 1747-46 and PSR 1818-04, showed positive effects, each with a probability less than 0.0001 of being a random fluctuation in the data for that pulsar. These are in addition to PSR 0531+21 and PSR 0833-45, previously reported. The results of this study suggest that gamma-ray astronomy has reached the detection threshold for gamma ray pulsars and that work in the near future should give important information on the nature of pulsars.

Ogelman, H. B.↗

NASA NTRS1990

Orthogonal stack of global tide gauge sea level data

Yearly and monthly tide gauge sea level data from around the globe are fitted to numerically generated equilibrium tidal data to search for the 18.6 year lunar tide and 14 month pole tide. Both tides are clearly evident in the results, and their amplitudes and phases are found to be consistent with a global equilibrium response. Global, monthly sea level data from outside the Baltic sea and Gulf of Bothnia are fitted to global atmospheric pressure data to study the response of the ocean to pressure fluctuations. The response is found to be inverted barometer at periods greater than two months. Global averages of tide gauge data, after correcting for the effects of post glacial rebound on individual station records, reveal an increase in sea level over the last 80 years of between 1.1 mm/yr and 1.9 mm/yr.

Trupin, A.↗

NASA NTRS2019

An X-Ray Spectroscopic Search For Dark Matter And Unidentified Line Signatures In The Perseus Cluster With Hitomi

The reported detection of a 3.5 keV emission signal in the Perseus cluster core by Bulbulet al. (2014, ApJ, 789, 13) was ruled out at high confidence in analysis conducted by Aharonian et al. (2017, ApJ, 837, L15) of X-ray spectra at 5 eV energy resolution obtained with the Hitomi observatory Soft X-ray Spectrometer (SXS). Using the same data, we search the full 2–12 keV SXS energy band for previously unidentified emission and absorption features. No significant unidentified line emission or absorption is found. Line flux upper limits (1σper resolution element) vary with photon energy and assumed intrinsic width, decreasing from∼100 at 2 keV to<10 photons cm−2s−1sr−1over most of the 5–10 keV energy range for a Gaussian line with Doppler broadening of 640 kms−1. Limits for narrower and broader lines have a similar energy dependence and are systematically smaller and larger, respectively. These line flux limits are used to constrain the decay rate of hypothetical dark matter candidates. For the sterile neutrino decay rate, we place new constraints over the mass range of 4–24 keV with mass resolution better than any previous X-ray analysis. Additionally, the accuracy of relevant thermal spectral models and atomic data are evaluated. The Perseus cluster spectra may be described by a composite of multi-temperature thermal and active galactic nuclei (AGN) power-law continua. Superposed on these, a few line emission signals possibly originating from unmodeled atomic processes (including SiXIV and FeXXV)are marginally detected and tabulated. Comparisons with previous X-ray upper limits and future prospects for dark matter searches using high-energy resolution spectroscopy are discussed.

Takayuki Tamura↗

DOE OSTI2024

Fast mass spectrometry search and clustering of untargeted metabolomics data

The throughput of mass spectrometers and the amount of publicly available metabolomics data are growing rapidly, but analysis tools such as molecular networking and Mass Spectrometry Search Tool do not scale to searching and clustering billions of mass spectral data in metabolomics repositories. To address this limitation, we designed MASST+ and Networking+, which can process datasets that are up to three orders of magnitude larger than those processed by state-of-the-art tools.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1976

A search of the SAS-2 data for pulsed gamma-ray emission from radio pulsars

Data from the SAS-2 high-energy (above 35 MeV) gamma-ray experiment have been examined for pulsed emission from each of 75 radio pulsars which were viewed by the instrument and which have sufficiently well-defined period and period-derivative information from radio observations to allow for gamma-ray periodicity searches. When gamma-ray arrival times were converted to pulsar phase using the radio reference timing information, two pulsars, PSR 1747-46 and PSR 1818-04, showed positive effects, each with a probability of less than 1 part in 10,000 of being a random fluctuation in the data for that pulsar. These are in addition to PSR 0531+21 and PSR 0833-45, previously reported. The results of this study suggest that gamma-ray astronomy has reached the detection threshold for gamma-ray pulsars and that work in the near future should give important new information on the nature of pulsars.

Ogelman, H.↗

NASA NTRSDate not supplied

Usage-Based Discovery of Earth Observations

Most providers of Earth Observation data enable search via dataset characteristics, (e.g., quantity being measured, instrument, location, and time). However, the Earth Science Information Partners Federation (ESIP) is attempting to improve dataset discovery by capturing information on how datasets are used. At a usage-based discovery hackfest at the July 2020 ESIP Summer Meeting, participants pooled their collective skills to implement a prototype based on the connections between datasets and data usage, which can reveal unanticipated patterns in dataset connectivity that are not apparent through traditional approaches. A survey of natural hazards websites, focusing on hydrology-related hazards such as floods and hydrology datasets such as rainfall, illustrated the difficulty of gleaning which dataset was actually used and how it was accessed. This difficulty highlights the need for greater transparency on dataset usage in website design. An application wireframe for a usage-based discovery database was conceptualized as a tool to help applications data specialists rapidly assemble a fit-for-purpose website as part of a disaster response, where customer feedback was integral to the manner in which the website would be developed and delivered. Capturing connections among datasets and instances of usage, either for research or applications, could help users identify datasets with a proven track record of utility or those that have been supplanted by more accurate and(or) precise representations. It may also help Earth Observation providers maximize returns on investments in data services. Social discovery, i.e, following discovery paths laid down by previous users of the data, could be a critical tool for improving the timeliness and applicability of dataset delivery at times and in circumstances where practitioners don’t have the capacity to evaluate the deluge of datasets that are returned by today’s search tools.

search↗

DOE OSTI2022

Investigating the effect of Milky Way dwarf spheroidal galaxies extension on dark matter searches with Fermi-LAT data

Satellite galaxies of the Milky Way with high mass-to-light ratios and little baryon content, i.e., dwarf spheroidal galaxies (dSphs), are among the most promising targets to detect or constrain the nature of dark matter (DM) through its final annihilation products into high-energy photons. Previously, the assumption that DM emission from dSphs is pointlike has been used to set strong constraints on DM candidates using data from the Fermi Large Area Telescope (LAT). However, due to their high DM densities and proximity, dSphs actually have sufficient angular extension to be detected by the Fermi-LAT. Here, we perform a comprehensive analysis about the impact of accounting for angular extension in the search for gamma-ray DM signals toward known dSphs with Fermi-LAT. Further, we show that, depending on the dSph under consideration, limits on the DM cross section can be weakened by up to a factor of 2–2.5, while the impact on the stacked, i.e., combined, limits is at most 1.5–1.8 depending on the annihilation channel. This result is of relevance when comparing dSph limits to other multimessenger DM constraints and for testing the DM interpretation of anomalous “excesses.”

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2015

The I4 Online Query Tool for Earth Observations Data

The NASA Earth Observation System Data and Information System (EOSDIS) delivers an average of 22 terabytes per day of data collected by orbital and airborne sensor systems to end users through an integrated online search environment (the Reverb/ECHO system). Earth observations data collected by sensors on the International Space Station (ISS) are not currently included in the EOSDIS system, and are only accessible through various individual online locations. This increases the effort required by end users to query multiple datasets, and limits the opportunity for data discovery and innovations in analysis. The Earth Science and Remote Sensing Unit of the Exploration Integration and Science Directorate at NASA Johnson Space Center has collaborated with the School of Earth and Space Exploration at Arizona State University (ASU) to develop the ISS Instrument Integration Implementation (I4) data query tool to provide end users a clean, simple online interface for querying both current and historical ISS Earth Observations data. The I4 interface is based on the Lunaserv and Lunaserv Global Explorer (LGE) open-source software packages developed at ASU for query of lunar datasets. In order to avoid mirroring existing databases - and the need to continually sync/update those mirrors - our design philosophy is for the I4 tool to be a pure query engine only. Once an end user identifies a specific scene or scenes of interest, I4 transparently takes the user to the appropriate online location to download the data. The tool consists of two public-facing web interfaces. The Map Tool provides a graphic geobrowser environment where the end user can navigate to an area of interest and select single or multiple datasets to query. The Map Tool displays active image footprints for the selected datasets (Figure 1). Selecting a footprint will open a pop-up window that includes a browse image and a link to available image metadata, along with a link to the online location to order or download the actual data. Search results are either delivered in the form of browse images linked to the appropriate online database, similar to the Map Tool, or they may be transferred within the I4 environment for display as footprints in the Map Tool. Datasets searchable through I4 (http://eol.jsc.nasa.gov/I4_tool) currently include: Crew Earth Observations (CEO) cataloged and uncataloged handheld astronaut photography; Sally Ride EarthKAM; Hyperspectral Imager for the Coastal Ocean (HICO); and the ISS SERVIR Environmental Research and Visualization System (ISERV). The ISS is a unique platform in that it will have multiple users over its lifetime, and that no single remote sensing system has a permanent internal or external berth. The open source I4 tool is designed to enable straightforward addition of new datasets as they become available such as ISS-RapidSCAT, Cloud Aerosol Transport System (CATS), and the High Definition Earth Viewing (HDEV) system. Data from other sensor systems, such as those operated by the ISS International Partners or under the auspices of the US National Laboratory program, can also be added to I4 provided sufficient access to enable searching of data or metadata is available. Commercial providers of remotely sensed data from the ISS may be particularly interested in I4 as an additional means of directing potential customers and clients to their products.

Stefanov, William L.↗

NASA NTRS1974

Study of the characteristics of seismic signals generated by natural and cultural phenomena

Seismic data recorded at the Tonto Forest Seismological Observatory in Arizona and the Uinta Basin Seismological Observatory in Utah were used to compare the frequency of occurrence, severity, and spectral content of ground motions resulting from earthquakes, and other natural and man-made sources with the motions generated by sonic booms. A search of data recorded at the two observatories yielded a classification of over 180,000 earthquake phase arrivals on the basis of frequency of occurrence versus maximum ground velocity. The majority of the large ground velocities were produced by seismic surface waves from moderate to large earthquakes in the western United States, and particularly along the Pacific Coast of the United States and northern Mexico. A visual analysis of raw film seismogram data over a 3-year period indicates that local and regional seismic events, including quarry blasts, are frequent in occurrence, but do not produce ground motions at the observatories comparable to either the large western United States earthquakes or to sonic booms. Seismic data from the Nevada Test Site nuclear blasts were used to derive magnitude-distance-sonic boom overpressure relations.

Goforth, T. T.↗

DOE OSTI2023

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Detection of Anomalies in Gamma Background Radiation Data with K-Means and Self-Organizing Map Clustering Algorithms (Consortium on Nuclear Security Technologies (CONNECT) Q1 Report)

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. The challenge is that spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

61 RADIATION PROTECTION AND DOSIMETRY↗