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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Investigation of microorganisms in cannabis after heating in a commercial vaporizer

There are concerns about microorganisms present on cannabis materials used in clinical settings by individuals whose health status is already compromised and are likely more susceptible to opportunistic infections from microbial populations present on the materials. Most concerning is administration by inhalation where cannabis plant material is heated in a vaporizer, aerosolized, and inhaled to receive the bioactive ingredients. Heating to high temperatures is known to kill microorganisms including bacteria and fungi; however, microbial death is dependent upon exposure time and temperature. It is unknown whether the heating of cannabis at temperatures and times designated by a commercial vaporizer utilized in clinical settings will significantly decrease the microbial loads in cannabis plant material. To assess this question, bulk cannabis plant material supplied by National Institute on Drug Abuse (NIDA) was used to assess the impact of heating by a commercial vaporizer. Initial method development studies using a cannabis placebo spiked with Escherichia coli were performed to optimize culture and recovery parameters. Subsequent studies were carried out using the cannabis placebo, low delta-9 tetrahydrocannabinol (THC) potency and high THC potency cannabis materials exposed to either no heat or heating for 30 or 70 seconds at 190°C. Phosphate-buffered saline was added to the samples and the samples agitated to suspend the microorganism. Microbial growth after no heat or heating was evaluated by plating on growth media and determining the total aerobic microbial counts and total yeast and mold counts. Overall, while there were trends of reductions in microbial counts with heating, these reductions were not statistically significant, indicating that heating using standard vaporization parameters of 70 seconds at 190°C may not eliminate the existing microbial bioburden, including any opportunistic pathogens. When cultured organisms were identified by DNA sequence analyses, several fungal and bacterial taxa were detected in the different products that have been associated with opportunistic infections or allergic reactions including Enterobacteriaceae, Staphylococcus, Pseudomonas, and Aspergillus.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1975

Interdisciplinary application and interpretation of EREP data within the Susquehanna River Basin

The author has identified the following significant results. It has become that lineaments seen on Skylab and ERTS images are not equally well defined, and that the clarity of definition of a particular lineament is recorded somewhat differently by different interpreters. In an effort to determine the extent of these variations, a semi-quantitative classification scheme was devised. In the field, along the crest of Bald Eagle Mountain in central Pennsylvania, statistical techniques borrowed from sedimentary petrography (point counting) were used to determine the existence and location of intensely fractured float rock. Verification of Skylab and ERTS detected lineaments on aerial photography at different scales indicated that the brecciated zones appear to occur at one margin of the 1 km zone of brecciation defined as a lineament. In the Lock Haven area, comparison of the film types from the SL4 S190A sensor revealed the black and white Pan X photography to be superior in quality for general interpretation to the black and white IR film. Also, the color positive film is better for interpretation than the color IR film.

Mcmurtry, G. J.↗
NASA NTRS1993

A petabyte size electronic library using the N-Gram memory engine

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

Bugajski, Joseph M.↗
NASA NTRS1993

Testing the frozen flow approximation

We investigate the accuracy of the frozen-flow approximation (FFA), recently proposed by Matarrese, et al. (1992), for following the nonlinear evolution of cosmological density fluctuations under gravitational instability. We compare a number of statistics between results of the FFA and n-body simulations, including those used by Melott, Pellman & Shandarin (1993) to test the Zel'dovich approximation. The FFA performs reasonably well in a statistical sense, e.g. in reproducing the counts-in-cell distribution, at small scales, but it does poorly in the crosscorrelation with n-body which means it is generally not moving mass to the right place, especially in models with high small-scale power.

Lucchin, Francesco↗
NASA NTRS2007

An IEEE 1451.1 Architecture for ISHM Applications

The IEEE 1451.1 Standard for a Smart Transducer Interface defines a common network information model for connecting and managing smart elements in control and data acquisition networks using network-capable application processors (NCAPs). The Standard is a network-neutral design model that is easily ported across operating systems and physical networks for implementing complex acquisition and control applications by simply plugging in the appropriate network level drivers. To simplify configuration and tracking of transducer and actuator details, the family of 1451 standards defines a Transducer Electronic Data Sheet (TEDS) that is associated with each physical element. The TEDS contains all of the pertinent information about the physical operations of a transducer (such as operating regions, calibration tables, and manufacturer information), which the NCAP uses to configure the system to support a specific transducer. The Integrated Systems Health Management (ISHM) group at NASA's John C. Stennis Space Center (SSC) has been developing an ISHM architecture that utilizes IEEE 1451.1 as the primary configuration and data acquisition mechanism for managing and collecting information from a network of distributed intelligent sensing elements. This work has involved collaboration with other NASA centers, universities and aerospace industries to develop IEEE 1451.1 compliant sensors and interfaces tailored to support health assessment of complex systems. This paper and presentation describe the development and implementation of an interface for the configuration, management and communication of data, information and knowledge generated by a distributed system of IEEE 1451.1 intelligent elements monitoring a rocket engine test system. In this context, an intelligent element is defined as one incorporating support for the IEEE 1451.x standards and additional ISHM functions. Our implementation supports real-time collection of both measurement data (raw ADC counts and converted engineering units) and health statistics produced by each intelligent element. The handling of configuration, calibration and health information is automated by using the TEDS in combination with other electronic data sheets extensions to convey health parameters. By integrating the IEEE 1451.1 Standard for a Smart Transducer Interface with ISHM technologies, each element within a complex system becomes a highly flexible computation engine capable of self-validation and performing other measures of the quality of information it is producing.

Morris, Jon A.↗
NASA NTRS1994

ROSAT all-sky survey observations of X-ray variability in cool giant stars

We have identified 24 active late-type giant stars, including 11 RS CVn systems, with soft X-ray count rates high enough to allow the detection of statistically significant variability on a Roentgen Satellite (ROSAT) orbital timescale (96 minutes) as observed by the Position Sensitive Proportional Counter (PSPC) during the all-sky survey. Our sensitivity typically lies in the range of 10% - 25%, depending on the source count rate. Comparison is made to the daily, nonflare solar soft X-ray variability as observed by the Solrad satellites during solar minimum in 1969 and solar maximum in 1975. Seven of the 24 stars show significant variability; in two of these cases (HR 3922 and HR 8448) major flares were observed in which the peak count rate is enhanced by at least a factor of 3 above quiescent. While HR 3922 (G5 III) is not (yet) classified as an RS CVn star, its flare is more energetic (3 x 10(exp 31) ergs/s) than previously observed RS CVn flares. The apparently single giant HR 8167 (G8 III) also shows two flares. While one might expect to find an anticorrelation between saturated coronae and variability, we find no evidence of this: the two stars in our sample with the highest ratio of f(sub x)/f(sub v) both show variability. We also point out that Capella (G6 III + F9 III) is one of the stars manifesting variability.

Haisch, Bernhard↗
DOE OSTI2021

Preliminary clustering properties of the DESI BGS bright targets using DR9 Legacy Imaging Surveys

ABSTRACT We characterize the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy Imaging Surveys (DR9). We describe changes in the DR9 selection compared to the DR8 one and we also compare the DR9 selection in three distinct regions: BASS/MzLS in the north Galactic Cap (NGC), DECaLS in the NGC, and DECaLS in the south Galactic Cap (SGC). We investigate the systematics associated with the selection and assess its completeness by matching the BGS targets with the Galaxy and Mass Assembly (GAMA) survey. We measure the angular clustering for the overall bright sample (rmag ≤ 19.5) and as function of apparent magnitude and colour. This enables to determine the clustering strength r0 and slope γ by fitting a power-law model that can be used to generate accurate mock catalogues for this tracer. We use a counts-in-cells technique to explore higher order statistics and cross-correlations with external spectroscopic data sets in order to check the evolution of the clustering with redshift and the redshift distribution of the BGS targets using clustering redshifts. While this work validates the properties of the BGS bright targets, the final target selection pipeline and clustering properties of the entire DESI BGS will be fully characterized and validated with the spectroscopic data of Survey Validation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

An analysis of new techniqes for radiometric correction of LANDSAT-4 Thematic Mapper images

The utility of methods for generating TM RLUTS which can improve the quality of the resultant images was investigated. The TM-CCT-ADDS tape was changed to account for a different collection window for the calibration data. Several scenes of Terrebonne Bay, Louisiana and the Grand Bahamas were analyzed to evaluate the radiometric corrections operationally applied to the image data and to investigate several techniques for reducing striping in the images. Printer plots for the TM shutter data were produced and detector statistics were compiled and plotted. These statistics included various combinations of the average shutter counts for each scan before and after DC restore for forward and reverse scans. Results show that striping is caused by the detectors becoming saturated when they view a bright cloud and depress the DC restore level.

Kogut, J.↗
NASA NTRS1985

Enhancing effects of gamma interferon on phagocytic cell association with and killing of Trypanosoma cruzi

Results are reported from a study of the influence gamma interferon (GIFN) and interleukin 2 (IL2) have on the capability of P388D1 cells and mouse resident peritoneal macrophages (MPM) to attach to the blood-resident parasites Trypanosoma cruzi and kill them. Cultures of trypomastigote forms of the Tulahuen strain of T. cruzi grown in bovine serum were introduced into peritoneal cells of mice, along with P388D1 cells incubated with GIFN, IL2 and both. Control cells were also maintained. Statistical analysis were then performed on data on counts of the number of dead T. Cruzi cells. The GIFN enhanced the interaction of MPM and P388D1 cells with the surface of T. Cruzi, provided the interaction was given over 12 hr to take place. A depression of the cytotoxicity of P388D1 cells was attributed to mediation by H2O2, an effect partially offset by incubation with the lymphokine GIFN.

Wirth, J. J.↗
NASA NTRS1994

The first Extreme Ultraviolet Explorer source catalog

The Extreme Ultraviolet Explorer (EUVE) has conducted an all-sky survey to locate and identify point sources of emission in four extreme ultraviolet wavelength bands centered at approximately 100, 200, 400, and 600 A. A companion deep survey of a strip along half the ecliptic plane was simultaneously conducted. In this catalog we report the sources found in these surveys using rigorously defined criteria uniformly applied to the data set. These are the first surveys to be made in the three longer wavelength bands, and a substantial number of sources were detected in these bands. We present a number of statistical diagnostics of the surveys, including their source counts, their sensitivites, and their positional error distributions. We provide a separate list of those sources reported in the EUVE Bright Source List which did not meet our criteria for inclusion in our primary list. We also provide improved count rate and position estimates for a majority of these sources based on the improved methodology used in this paper. In total, this catalog lists a total of 410 point sources, of which 372 have plausible optical ultraviolet, or X-ray identifications, which are also listed.

Bowyer, S.↗
NASA NTRS2006

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

Liu, Zhaoyan↗
NASA NTRS2014

Clustering Days with Similar Airport Weather Conditions

On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between the aircraft demand and the weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traffic data to identify patterns and past decisions that can ultimately inform day-of-operations decision-making. More specifically, this study identified similar weather impacted days at select U.S. airports, and analyzed the traffic management initiatives implemented on these representative days. The identification of the similar days was accomplished by applying a decision tree algorithm to the hourly Localized Aviation Model Output Statistics Program observations and the arrival delays for Newark Liberty International Airport. The branches from the trained decision tree were subsequently pruned to identify four weather conditions that resulted in medium to high delays for the arrivals scheduled to Newark in 2012. Using these weather conditions, four, daily airport-level Weather Impacted Traffic Index values were calculated using the Localized Aviation Model Output Statistics Program observations and the 2012 scheduled arrival counts from the FAAs Aviation System Performance Metric system. The four, daily Weather Impacted Traffic Index values for 2012 were subsequently clustered using an Expectation Maximization clustering algorithm, and nine unique types of weather days at Newark were identified. By far the most prominent type of day at Newark was a day associated with relatively good weather conditions, where there was little convective activity, winds were low, ceilings and visibility were high and there was little precipitation. Moderate levels of convective activity characterized the next most prominent type of day. Days with persistently high winds or low ceiling and visibility levels were relatively rare in 2012. Lastly, the frequency at which Ground Delay Programs, Ground Stops and Miles-in-Trail restrictions were implemented on each of the typical types of days at Newark were analyzed. Based on the results, it does appear as if the usage of Miles-in-Trail, Ground Delay Program and Ground Stop restrictions correlates well with the severity of the weather associated with each unique type of weather impacted day at Newark. Furthermore, the results demonstrate that it is feasible to use historical weather and air traffic archives to provide guidance on the types of traffic management restrictions to implement in response to the weather conditions impacting an airport.

traffic flow management↗
NASA NTRS2014

Clustering Days with Similar Airport Weather Conditions

On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between the aircraft demand and the weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traffic data to identify patterns and past decisions that can ultimately inform day-of-operations decision-making. More specifically, this study identified similar weather impacted days at select U.S. airports, and analyzed the traffic management initiatives implemented on these representative days. The identification of the similar days was accomplished by applying a decision tree algorithm to the hourly Localized Aviation Model Output Statistics Program observations and the arrival delays for Newark Liberty International Airport. The branches from the trained decision tree were subsequently pruned to identify four weather conditions that resulted in medium to high delays for the arrivals scheduled to Newark in 2012. Using these weather conditions, four, daily airport-level Weather Impacted Traffic Index values were calculated using the Localized Aviation Model Output Statistics Program observations and the 2012 scheduled arrival counts from the FAAs Aviation System Performance Metric system. The four, daily Weather Impacted Traffic Index values for 2012 were subsequently clustered using an Expectation Maximization clustering algorithm, and nine unique types of weather days at Newark were identified. By far the most prominent type of day at Newark was a day associated with relatively good weather conditions, where there was little convective activity, winds were low, ceilings and visibility were high and there was little precipitation. Moderate levels of convective activity characterized the next most prominent type of day. Days with persistently high winds or low ceiling and visibility levels were relatively rare in 2012. Lastly, the frequency at which Ground Delay Programs, Ground Stops and Miles-in-Trail restrictions were implemented on each of the typical types of days at Newark were analyzed. Based on the results, it does appear as if the usage of Miles-in-Trail, Ground Delay Program and Ground Stop restrictions correlates well with the severity of the weather associated with each unique type of weather impacted day at Newark. Furthermore, the results demonstrate that it is feasible to use historical weather and air traffic archives to provide guidance on the types of traffic management restrictions to implement in response to the weather conditions impacting an airport.

weather↗
NASA NTRS1994

A spaceflight study of synaptic plasticity in adult rat vestibular maculas

Behavioral signs of vestibular perturbation in altered gravity have not been well correlated with structural modifications in neurovestibular centers. This ultrastructural research investigated synaptic plasticity in hair cells of adult rat utricular maculas exposed to microgravity for nine days on a space shuttle. The hypothesis was that synaptic plasticity would be more evident in type II hair cells because they are part of a distributed modifying macular circuitry. All rats were shared with other investigators and were subjected to treatments unrelated to this experiment. Maculas were obtained from flight and control rats after shuttle return (R + 0) and nine days post-flight (R + 9). R + 9 rats had chromodacryorrhea, a sign of acute stress. Tissues were prepared for ultrastructural study by conventional methods. Ribbon synapses were counted in fifty serial sections from medial utricular macular regions of three rats of each flight and control group. Counts in fifty additional consecutive sections from one sample in each group established method reliability. All synapses were photographed and located to specific cells on mosaics of entire sections. Pooled data were analyzed statistically. Flown rats showed abnormal posture and movement at R + 0. They had statistically significant increases in total ribbon synapses and in sphere-like ribbons in both kinds of hair cells; in type II cells, pairs of synapses nearly doubled and clusters of 3 to 6 synapses increased twelve-fold. At R + 9, behavioral signs were normal. However, synapse counts remained high in both kinds of hair cells of flight maculas and were elevated in control type II cells. Only counts in type I cells showed statistically significant differences at R + 9. High synaptic counts at R + 9 may have resulted from stress due to experimental treatments. The results nevertheless demonstrate that adult maculas retain the potential for synaptic plasticity. Type II cells exhibited more synaptic plasticity, but space flight induced synaptic plasticity in type I cells.

Weightlessness↗
DOE OSTI2026

Historic climate, cosmogenic 10Be, denudation-rate, and geospatial datasets from the Pikes Peak region, Colorado, USA

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of elevation-dependent denudation rates on Pikes Peak in the Front Range of the Rocky Mountains, Colorado, USA. The package includes GIS layers used to produce the study-area map, including sample locations, sample watershed boundaries, the Pikes Peak batholith, Pleistocene glacier extent, weather station locations, and elevation and hillshade rasters, together with comma-separated value (CSV) tables and matching CSV data dictionaries. These mapped layers provide the geographic framework for interpreting denudation patterns across the Pikes Peak region and for relating sample locations to watershed geometry, bedrock setting, glacial history, and nearby climate stations. The first group of tables reports climate and geospatial context for the study area. These files include station-based temperature and precipitation data used to characterize elevational gradients in mean annual climate and monthly climate seasonality, sample locations, denudation-rate and topographic metrics, fixed frost-cracking model parameters, frost-cracking intensity and precipitation-frequency metrics, and stream-power inversion results. Together, these data provide the basis for evaluating how denudation varies with elevation, climate, and landscape form across sampled catchments on Pikes Peak. The second group of tables reports cosmogenic nuclide and erosion-model results used in the denudation analysis. Included files contain accelerator mass spectrometry (AMS) measurements for in situ-produced cosmogenic beryllium-10 (10Be), including sample identifiers, measured 10Be:9Be ratios, analytical uncertainties, carrier mass, quartz mass, blank corrections, blank-group statistics, and calculated 10Be concentrations and uncertainties. Additional tables summarize stream-power-law inversion results for sampled catchments, including optimized model parameters, predicted erosion rates, residual metrics, channel-pixel counts, and convergence status, as well as regression equations and summary statistics used to evaluate relationships among elevation, climate, frost cracking, precipitation forcing, and denudation rate. The package contains GIS files, comma-separated value files (.csv), Microsoft Excel files (.xlsx), CSV data dictionaries, a file-level metadata table, and a readme text file.

10Be cosmogenic nuclides↗
NASA NTRS2021

Probabilistic Processing of Asynchronous Geiger-Mode Avalanche Photodiode Arrays for Background Rate Measurements

A system-level performance evaluation of Geiger-mode avalanche photodiode (GmAPD) arrays requires accurate measurement and prediction of the background rate of the device due to dark counts and other spurious detection events. Since a GmAPD detector reports only a binary value and timestamp associated with an avalanche event, dark count rates are typically measured by averaging thousands of frames to support a statistically significant measurement. For both synchronous and asynchronous detector, the Poisson distributed background rates are referenced to the time each pixel is armed. Unlike for synchronous GmAPD imagers where all the pixels are armed to an array-wide arm signal, an asynchronous pixel operates independently from its neighboring pixels; requiring the background rates to be calculated using an interarrival histogram. For both types of imagers, the background rate is typically evaluated by fitting an exponential distribution to a fixed window within a measured histogram of time intervals between detection events However, if the statistics of the background rate are insufficient – whether that is due to low population sizes, saturation, or a large dynamic range of population size across the array, the pixel, or array-wide, performance metrics may report results with varying accuracy. This paper reports on an implementation of an algorithm that evaluates GmAPD background rates based on statistical metrics rather than fixed windows. The algorithm functions by determining the appropriate integration window within the interarrival time histogram based on a per-pixel count rate set by a predetermined tolerable measurement error. The implementation of the algorithm allows us to characterize GmAPD arrays with orders of magnitude spread in background rates across the detector using common statistical parameters.

Mumolo, J.↗
DOE OSTI2025

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the 300 deg 2 DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3σ on scales below approximately 10', but large scales are unaffected. We fit Ω m and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Exploring Randomly Wired Neural Networks for Climate Model Emulation

Exploring the climate impacts of various anthropogenic emissions scenarios is key to making informed decisions for climate change mitigation and adaptation. State-of-the-art Earth system models can provide detailed insight into these impacts but have a large associated computational cost on a per-scenario basis. This large computational burden has driven recent interest in developing cheap machine learning models for the task of climate model emulation. In this paper, we explore the efficacy of randomly wired neural networks for this task. We describe how they can be constructed and compare them with their standard feedforward counterparts using the ClimateBench dataset. Specifically, we replace the serially connected dense layers in multilayer perceptrons, convolutional neural networks, and convolutional long short-term memory networks with randomly wired dense layers and assess the impact on model performance for models with 1 million and 10 million parameters. We find that models with less-complex architectures see the greatest performance improvement with the addition of random wiring (up to 30.4% for multilayer perceptrons). Furthermore, of 24 different model architecture, parameter count, and prediction task combinations, only one had a statistically significant performance deficit in randomly wired networks relative to their standard counterparts, with 14 cases showing statistically significant improvement. We also find no significant difference in prediction speed between networks with standard feedforward dense layers and those with randomly wired layers. These findings indicate that randomly wired neural networks may be suitable direct replacements for traditional dense layers in many standard models.

54 ENVIRONMENTAL SCIENCES↗