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NASA NTRS2011

Cross Calibration of SeaWiFS and MODIS Using On-Orbit Observations of the Moon

Observations of the Moon provide a primary technique for the on-orbit cross calibration of Earth remote sensing instruments. Monthly lunar observations are major components of the on-orbit calibration strategies of SeaWiFS and MODIS. SeaWiFS has collected more than 132 low phase angle and 59 high phase angle lunar observations over 12 years, Terra MODIS has collected more than 82 scheduled and 297 unscheduled lunar observations over 9 years, and Aqua MODIS has collected more than 61 scheduled and 171 unscheduled lunar observations over 7 years. The NASA Ocean Biology Processing Group s Calibration and Validation Team and the NASA MODIS Characterization Support Team use the USGS RObotic Lunar Observatory (ROLO) photometric model of the Moon to compare these time series of lunar observations over time and varying observing geometries. The cross calibration results show that Terra MODIS and Aqua MODIS agree, band-to-band, at the 1-3% level, while SeaWiFS and either MODIS instrument agree at the 3-8% level. The combined uncertainties of these comparisons are 1.3% for Terra and Aqua MODIS, 1.4% for SeaWiFS and Terra MODIS, and 1.3% for SeaWiFS and Aqua MODIS. Any residual phase dependence in the ROLO model, based on these observations, is less than 1.7% over the phase angle range of -80deg to -6deg and +5deg to +82deg . The lunar cross calibration of SeaWiFS, Terra MODIS, and Aqua MODIS is consistent with the vicarious calibration of ocean color products for these instruments, with the vicarious gains mitigating the calibration biases for the ocean color bands.

Eplee, Robert E., Jr.↗

DOE OSTI2022

How to Obtain the Redshift Distribution from Probabilistic Redshift Estimates

Abstract A reliable estimate of the redshift distribution n ( z ) is crucial for using weak gravitational lensing and large-scale structures of galaxy catalogs to study cosmology. Spectroscopic redshifts for the dim and numerous galaxies of next-generation weak-lensing surveys are expected to be unavailable, making photometric redshift (photo- z ) probability density functions (PDFs) the next best alternative for comprehensively encapsulating the nontrivial systematics affecting photo- z point estimation. The established stacked estimator of n ( z ) avoids reducing photo- z PDFs to point estimates but yields a systematically biased estimate of n ( z ) that worsens with a decreasing signal-to-noise ratio, the very regime where photo- z PDFs are most necessary. We introduce Cosmological Hierarchical Inference with Probabilistic Photometric Redshifts ( CHIPPR ), a statistically rigorous probabilistic graphical model of redshift-dependent photometry that correctly propagates the redshift uncertainty information beyond the best-fit estimator of n ( z ) produced by traditional procedures and is provably the only self-consistent way to recover n ( z ) from photo- z PDFs. We present the chippr prototype code, noting that the mathematically justifiable approach incurs computational cost. The CHIPPR approach is applicable to any one-point statistic of any random variable, provided the prior probability density used to produce the posteriors is explicitly known; if the prior is implicit, as may be the case for popular photo- z techniques, then the resulting posterior PDFs cannot be used for scientific inference. We therefore recommend that the photo- z community focus on developing methodologies that enable the recovery of photo- z likelihoods with support over all redshifts, either directly or via a known prior probability density.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Disentangling the Black Hole Mass Spectrum with Photometric Microlensing Surveys

Abstract From the formation mechanisms of stars and compact objects to nuclear physics, modern astronomy frequently leverages surveys to understand populations of objects to answer fundamental questions. The population of dark and isolated compact objects in the Galaxy contains critical information related to many of these topics, but is only practically accessible via gravitational microlensing. However, photometric microlensing observables are degenerate for different types of lenses, and one can seldom classify an event as involving either a compact object or stellar lens on its own. To address this difficulty, we apply a Bayesian framework that treats lens type probabilistically and jointly with a lens population model. This method allows lens population characteristics to be inferred despite intrinsic uncertainty in the lens class of any single event. We investigate this method’s effectiveness on a simulated ground-based photometric survey in the context of characterizing a hypothetical population of primordial black holes (PBHs) with an average mass of 30 M ⊙ . On simulated data, our method outperforms current black hole (BH) lens identification pipelines and characterizes different subpopulations of lenses while jointly constraining the PBH contribution to dark matter to ≈25%. Key to robust inference, our method can marginalize over population model uncertainty. We find the lower mass cutoff for stellar origin BHs, a key observable in understanding the BH mass gap, particularly difficult to infer in our simulations. This work lays the foundation for cutting-edge PBH abundance constraints to be extracted from current photometric microlensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1991

Digital cartography of Io

A high resolution controlled mosaic of the hemisphere of Io centered on longitude 310 degrees is produced. Digital cartographic techniques were employed. Approximately 80 Voyager 1 clear and blue filter frames were utilized. This mosaic was merged with low-resolution color images. This dataset is compared to the geologic map of this region. Passage of the Voyager spacecraft through the Io plasma torus during acquisition of the highest resolution images exposed the vidicon detectors to ionized radiation, resulting in dark-current buildup on the vidicon. Because the vidicon is scanned from top to bottom, more charge accumulated toward the bottom of the frames, and the additive error increases from top to bottom as a ramp function. This ramp function was removed by using a model. Photometric normalizations were applied using the Minnaert function. An attempt to use Hapke's photometric function revealed that this function does not adequately describe Io's limb darkening at emission angles greater than 80 degrees. In contrast, the Minnaert function accurately describes the limb darkening up to emission angles of about 89 degrees. The improved set of discrete camera angles derived from this effort will be used in conjunction with the space telemetry pointing history file (the IPPS file), corrected on 4 or 12 second intervals to derive a revised time history for the pointing of the Infrared Interferometric Spectrometer (IRIS). For IRIS observations acquired between camera shutterings, the IPPS file can be corrected by linear interpolation, provided that the spacecraft motions were continuous. Image areas corresponding to the fields of view of IRIS spectra acquired between camera shutterings will be extracted from the mosaic to place the IRIS observations and hotspot models into geologic context.

Mcewen, Alfred S.↗

NASA NTRS1993

An intercomparison of instrumentation for tropospheric measurements of dimethyl sulfide: Aircraft results for concentrations at the parts-per-trillion level

This paper reports results from NASA's Chemical Instrumentation and Test Evaluation (CITE 3) during which airborne measurements of dimethyl sulfide (DMS) from six instruments were intercompared. Represented by the six instruments are three fundamentally different detection principles (flame photometric, mass spectrometric, and electron capture after fluorination); three collection/preconcentration methods (cryogenic, gold wool absorption, and polymer absorbent); and three types of oxidant scrubbers (solid phase alkaline, aqueous reactor, and cotton). The measurements were made over the Atlantic Ocean in August/September 1989 during flights from NASA's Wallops Flight Center, Virginia, and Natal, Brazil. The majority of the intercomparisons are at DMS mixing ratios less than 50 pptv. Results show that instrument agreement is of the order of a few pptv for mixing ratios less than 50 pptv and to within about 15% above 50 pptv. Statistically significant (95% confidence) measurement biases were noted among some of the techniques. However, in all cases, any bias is small and within the accuracy of the measurements and prepared DMS standards. Thus, we conclude that the techniques intercompared during CITE 3 provide equally valid measurements of DMS in the range of a few pptv to 100 pptv (upper range of the intercomparisons).

Gregory, Gerald L.↗

DOE OSTI2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

Aubourg, Eric [APC, Paris] (ORCID:000000025592023X↗

DOE OSTI2025

Forecasting Dark Matter Subhalo Constraints from Stellar Streams using Implicit Likelihood Inference

The evidence for dark matter (DM) remains compelling, although attempts to understand its particle nature remain inconclusive. One promising method to study DM is detecting DM subhalos through their gravitational interactions with stellar streams. In this study, we apply Neural Posterior Estimation (NPE) to constrain subhalo interaction parameters, including mass, scale radius, velocity, and encounter geometry, from stellar stream kinematics. We generate particle spray simulations based on the Lagrange Cloud stripping technique, focusing on the ATLAS-Aliqa Uma stream as a test case. We train multiple NPE models across multiple observational scenarios, quantifying how kinematic completeness affects inference and forecasting constraints from upcoming surveys including LSST, 4MOST, and 10-year Gaia data. Our results demonstrate that NPE can produce accurate and well-calibrated posteriors. In the idealized case with full 6D coordinates, we achieve subhalo mass uncertainties of 15-20% for a $10^7 \, \mathrm{M_\odot}$ subhalo, with 5D coordinates (excluding radial velocities) achieving similar performance. Under realistic observational conditions, mass uncertainties range from 50% (present-day) to 20-40% (future scenarios), with comparable performance between the photometric-only LSST sample and a smaller sample that includes Gaia proper motions and 4MOST radial velocities. Most notably, we find that velocity bimodality emerges when phase space is poorly sampled, whether due to missing kinematic information or limited stellar tracers. Combining large photometric samples with targeted spectroscopic follow-up can effectively resolves this degeneracy. These results demonstrate the power of implicit likelihood inference for optimizing stellar stream observational strategies and forecasting DM subhalo constraints from upcoming surveys.

Nguyen, Tri [Northwestern U. (main); SkAI, Chicago↗

NASA NTRS2021

The Effect of Missing Groups in the Calculation of the Solar Irradiance Deficit: Analysis of the Sunspot Areas from the SOON Network

Sunspot areas are one of the most important indices of solar activity. To obtain an extended time series covering multiple solar cycles one must combine data from different observatories after a proper comparison and calibration of the individual data sets. We compare the daily and group values of sunspot areas provided by the different stations from the Solar Optical Observing Network, SOON, which are determined using similar instruments and techniques. We investigate if there are systematic differences among the stations and whether the differences in the daily values can be attributed to missing groups in the records or errors in the measurements. We find significant differences among the stations of the SOON network in terms of sizes (average daily and group values), quality of observations and coverage (considering number of missing groups and data gaps). Our results indicate that calibration factors for daily values can be used with confidence to combine data sets from different stations. However, for some applications which require the location of the sunspot groups the same correction factors should not be used. We estimate the irradiance deficit due to sunspot through the Photometric Sunspot Index and compare the output from similar data sets to quantify the effect of missing groups. We find differences as high as 150 ppm during the maximum of solar cycle. The effect increases for sunspot groups near the center of the disk accounting for about 80% of the observed differences.

Luis Leuzzi↗

NASA NTRS1980

Low-pass interference filters for submillimeter astronomy

Low-pass (long-wave transmitting) interference filters, suitable for broadband photometric observations, previously have been constructed from series of capacitive grids stretched on thin Mylar. These filters have the desired optical properties of high transmission, sharp cut-ons, and good blocking at short wavelengths. Their designs, however, do not scale from one wavelength to another and their performance can deteriorate at low temperatures due to differential contraction of the dielectric backing and the supporting structure. The deviation of these early filters from the predicted scaling was due primarily to the difference in refractive index between the backing material and the medium between the grids. In the present paper, filters are described in which dielectric spacers are used, instead of air, as the medium between the grids. This technique has improved the scaling and has reduced the distortion from differential contraction.

Whitcomb, S. E.↗

NASA NTRS2010

Orbital Debris Detection and Tracking Strategies for the NASA/AFRL Meter Class Autonomous Telescope (MCAT)

MCAT (Meter-Class Autonomous Telescope) is a 1.3m f/4 Ritchey-Chr tien on a double horseshoe equatorial mount that will be deployed in early 2011 to the western pacific island of Legan in the Kwajalein Atoll to perform orbital debris observations. MCAT will be capable of tracking earth orbital objects at all inclinations and at altitudes from 200 km to geosynchronous. MCAT s primary objective is the detection of new orbital debris in both low-inclination low-earth orbits (LEO) and at geosynchronous earth orbit (GEO). MCAT was thus designed with a fast focal ratio and a large unvignetted image circle able to accommodate a detector sized to yield a large field of view. The selected primary detector is a close-cycle cooled 4Kx4K 15um pixel CCD camera that yields a 0.9 degree diagonal field. For orbital debris detection in widely spaced angular rate regimes, the camera must offer low read-noise performance over a wide range of framing rates. MCAT s 4-port camera operates from 100 kHz to 1.5 MHz per port at 2 e- and 10 e- read noise respectively. This enables low-noise multi-second exposures for GEO observations as well as rapid (several frames per second) exposures for LEO. GEO observations will be performed using a counter-sidereal time delay integration (TDI) technique which NASA has used successfully in the past. For MCAT the GEO survey, detection, and follow-up prediction algorithms will be automated. These algorithms will be detailed herein. For LEO observations two methods will be employed. The first, Orbit Survey Mode (OSM), will scan specific orbital inclination and altitude regimes, detect new orbital debris objects against trailed background stars, and adjust the telescope track to follow the detected object. The second, Stare and Chase Mode (SCM), will perform a stare, then detect and track objects that enter the field of view which satisfy specific rate and brightness criteria. As with GEO, the LEO operational modes will be fully automated and will be described herein. The automation of photometric and astrometric processing (thus streamlining data collection for environmental modeling) will also be discussed.

Mulrooney, M.↗

NASA NTRS2002

The Discovery of Extrasolar Planets by Backyard Astronomers

The discovery since 1995 of more than 80 planets around nearby solar-like stars and the photometric measurement of a transit of the jovian mass planet orbiting the solar-like star HD 209458 (producing a more than 1% drop in brightness that lasts 3 hours) has heralded a new era in astronomy. It has now been demonstrated that small telescopes equipped with sensitive and stable electronic detectors can produce fundamental scientific discoveries regarding the frequency and nature of planets outside the solar system. The modest equipment requirements for the discovery of extrasolar planetary transits of jovian mass planets in short period orbits around solar-like stars are fulfilled by commercial small aperture telescopes and CCD (charge coupled device) imagers common among amateur astronomers. With equipment already in hand and armed with target lists, observing techniques and software procedures developed by scientists at NASA's Ames Research Center and the University of California at Santa Cruz, non-professional astronomers can contribute significantly to the discovery and study of planets around others stars. In this way, we may resume (after a two century interruption!) the tradition of planet discoveries by amateur astronomers begun with William Herschel's 1787 discovery of the 'solar' planet Uranus.

Castellano, Tim↗

NASA NTRS1980

Vector space methods of photometric analysis. II - Refinement of the MK grid for B stars. III - The two components of ultraviolet reddening

This paper discusses systematic errors which arise from exclusive use of the MK system to determine reddening. It is found that implementation of uvby, beta photometry to refine the qualitative MK grid substantially reduces stellar mismatch error. A working definition of 'identical' ubvy, beta types is investigated and the relationship of uvby to B-V color excesses is determined. A comparison is also made of the hydrogen based uvby, beta types with the MK system based on He and metal lines. A small core correlated effective temperature luminosity error in the MK system for the early B stars is observed along with a breakdown of the MK luminosity criteria for the late B stars. The second part investigates the wavelength dependence of interstellar extinction in the ultraviolet wavelength range observed with the TD-1 satellite. In this study the sets of identical stars employed to find reddening are determined more precisely than in previous studies and consist only of normal, nonsupergiant stars. A multivariate analysis of variance techniques in an unbiased coordinate system is used for determining the wavelength dependence of reddening.

Massa, D.↗

NASA NTRS2004

Stellar, Remnant, Planetary, and Dark-Object Masses from Astrometric Microlensing

The primary goal of our project is to make a complete census of the stellar population of the Galaxy. We are broadening the term stellar here to include both ordinary stars and dark stars. Ordinary stars, burning their nuclear fuel and shining, can perhaps best be studied with traditional astronomical techniques, but dark stars, by which we include old brown dwarfs, black holes, old white dwarfs, neutron stars, and perhaps exotic objects such as mirror matter stars or primordial black holes, can only be studied by their gravitational effects. Traditionally, these objects have been probed in binaries, and thus selected in a way that may or may not be representative of their respective field populations. The only way to examine the field population of these stars is through microlensing, the deflection of light from a visible star in the background by an object (dark or not) in the foreground. When lensed, there are two images of the background star. Although these images cannot be resolved when the lens has a stellar mass, the lensing effect can be detected in two ways: photometrically, i.e. by measuring the magnification of the source by the lens, and astrometrically, i.e. by measuring the shift in the centroid of the two images. Photometric microlensing experiments have detected hundreds of microlensing events over the past decade. Despite its successes, photometric microlensing has so far been somewhat frustrating because these events are difficult to interpret. Almost nothing is known about the masses of individual lenses and very little is known about the statistical properties of the lenses treated as a whole, such as their average mass. Although probably over 100 of the lenses are in fact dark objects, we can't determine which they are, let alone investigate finer details such as what their masses are, and where they are in the Galaxy. With SIM, we will break the microlensing degeneracy, and allow detailed interpretation of individual microlensing events. We will thus develop a detailed census of the dark and luminous stellar population of the Galaxy.

Gould, Andrew P.↗

DOE OSTI2022

Photometry on Structured Backgrounds: Local Pixel-wise Infilling by Regression

Photometric pipelines struggle to estimate both the flux and flux uncertainty for stars in the presence of structured backgrounds such as filaments or clouds. However, it is exactly stars in these complex regions that are critical to understanding star formation and the structure of the interstellar medium. We develop a method, similar to Gaussian process regression, which we term local pixel-wise infilling (LPI). Using a local covariance estimate, we predict the background behind each star and the uncertainty of that prediction in order to improve estimates of flux and flux uncertainty. We show the validity of our model on synthetic data and real dust fields. We further demonstrate that the method is stable even in the crowded field limit. While we focus on optical-IR photometry, this method is not restricted to those wavelengths. We apply this technique to the 34 billion detections in the second data release of the Dark Energy Camera Plane Survey. In addition to removing many >3σ outliers and improving uncertainty estimates by a factor of ~2–3 on nebulous fields, we also show that our method is well behaved on uncrowded fields. The entirely post-processing nature of our implementation of LPI photometry allows it to easily improve the flux and flux uncertainty estimates of past as well as future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1992

HST image restoration: A comparison of pre- and post-servicing mission results

A variety of image restoration techniques (e.g., Wiener filter, Lucy-Richardson, MEM) have been applied quite successfully to the aberrated HST images. The HST servicing mission (scheduled for late 1993 or early 1994) will install a corrective optics system (COSTAR) for the Faint Object Camera and spectrographs and replace the Wide Field/Planetary Camera with a second generation instrument (WF/PC-II) having its own corrective elements. The image quality is expected to be improved substantially with these new instruments. What then is the role of image restoration for the HST in the long term? Through a series of numerical experiments using model point-spread functions for both aberrated and unaberrated optics, we find that substantial improvements in image resolution can be obtained for post-servicing mission data using the same or similar algorithms as being employed now to correct aberrated images. Included in our investigations are studies of the photometric integrity of the restoration algorithms and explicit models for HST pointing errors (spacecraft jitter).

Hanisch, R. J.↗

DOE OSTI2026

Dimensional Reduction for Sampled Priors and Application to Photometric Redshift Distributions

A typical Bayesian inference on the values of some parameters of interest q from some data D involves running a Markov Chain (MC) to sample from the posterior $p$($q$,$n$|$D$) $\propto$ $\mathcal{L}$($D$|$q$,$n$)$p$(q)$p$($n$), where n are some nuisance parameters with a separable prior. In some cases, the nuisance parameters are high-dimensional, and their prior p(n) is itself defined only by a set of samples that have been drawn from some other MC. The MC for the posterior will typically require evaluation of p(n) at arbitrary values of n, i.e., one needs to provide a density estimator over the full n space from the provided samples. But the high dimensionality of n hinders both the density estimation and the efficiency of the MC for the posterior. We describe a solution to this problem: a linear compression of the n space into a much lower-dimensional space u, which projects away directions in n space that cannot appreciably alter $\mathcal{L}$. The algorithm for doing so is a slight modification to principal components analysis, and is less restrictive on p(n) than other proposed solutions to this issue. We demonstrate this “mode projection” technique using the analysis of 2-point correlation functions of weak lensing fields and galaxy density in the Dark Energy Survey, where n is a binned representation of the redshift distribution n(z) of the galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1992

Evidence for a massive stellar black hole in x ray Nova Muscae

We present evidence that the X-ray Nova Muscae system contains a massive, greater than 10 M solarmass, black hole. A recently measured photometric binary mass function gives the black hole mass for this system as a function of orbital inclination angle. From the spectral redshift and width of the positron annihilation gamma-ray line observed by GRANAT/SIGMA, we find the accretion disk inclination angle to be 22 deg plus or minus 18 deg. Assuming the accretion disk lies in the orbital plane of the system, the black hole mass is found to have a lower limit of 14 M solar mass although statistics are poor. This is supported by spectral modeling of combined optical/UV/x-ray/gamma-ray data and by a new Nova Muscae distance limit we derive of greater than 3 kpc. The large mass for this black hole and the high binary mass ratio it implies (greater than 20) raise a serious challenge to theoretical models of the formation and evolution of massive binaries. The gamma-ray line technique introduced here can give tight constraints on orbital parameters when high-sensitivity line measurements are made by such missions as GRO.

Chen, Wan↗

DOE OSTI2020

Angular Correlation Function Estimators Accounting for Contamination from Probabilistic Distance Measurements

With the advent of surveys containing millions to billions of galaxies, it is imperative to develop analysis techniques that utilize the available statistical power. In galaxy clustering, even small sample contamination arising from distance uncertainties can lead to large artifacts, which the standard estimator for two-point correlation functions does not account for. We first introduce a formalism, termed decontamination, that corrects for sample contamination by utilizing the observed cross-correlations in the contaminated samples; this corrects any correlation function estimator for contamination. Using this formalism, we present a new estimator that uses the standard estimator to measure correlation functions in the contaminated samples but then corrects for contamination. We also introduce a weighted estimator that assigns each galaxy a weight in each redshift bin based on its probability of being in that bin. We demonstrate that these estimators effectively recover the true correlation functions and their covariance matrices. Our estimators can correct for sample contamination caused by misclassification between object types as well as photometric redshifts; they should be particularly helpful for studies of galaxy evolution and baryonic acoustic oscillations, where forward modeling the clustering signal using the contaminated redshift distribution is undesirable.

79 ASTRONOMY AND ASTROPHYSICS↗