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At least 109 records · Page 6

A Blind Test of Hapke's Photometric Model

Hapke's bidirectional reflectance equation is a versatile analytical tool for predicting (i.e. forward modeling) the photometric behavior of a particulate surface from the observed optical and structural properties of its constituents. Remote sensing applications of Hapke s model, however, generally seek to predict the optical and structural properties of particulate soil constituents from the observed photometric behavior of a planetary surface (i.e. inverse-modeling). Our confidence in the latter approach can be established only if we ruthlessly test and optimize it. Here, we summarize preliminary results from a blind-test of the Hapke model using laboratory measurements obtained with the Bloomsburg University Goniometer (B.U.G.). The first author selected eleven well-characterized powder samples and measured the spectrophotometric behavior of each. A subset of twenty undisclosed examples of the photometric measurement sets were sent to the second author who fit the data using the Hapke model and attempted to interpret their optical and mechanical properties from photometry alone.

Helfenstein, P.↗

An Assessment of GEO Orbital Debris Photometric Properties Derived from Laboratory-Based Measurements

Optical observations of orbital debris offer insights that differ from radar measurements (specifically the size parameter and wavelength regime). For example, time-dependent photometric data yield lightcurves in multiple bandpasses that aid in material identification and possible periodic orientations. This data can also be used to help identify shapes and optical properties at multiple phase angles. Capitalizing on optical data products and applying them to generate a more complete understanding of orbital space objects, is a key objective of NASA s Optical Measurement Program, and a primary driver for creation of the Optical Measurements Center (OMC). The OMC attempts to emulate space-based illumination conditions using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. The OMC uses a 300 Watt Xenon arc lamp as a solar simulator, a CCD camera with Johnson/Bessel colored filters, and a robotic arm to orientate/rotate objects to simulate an object's orbit/rotational period. A high-resolution, high bandwidth (350nm-2500nm) Analytical Spectral Devices (ASD) spectrometer is also employed to baseline various material types. Since observation of GEO targets are generally restricted to the optical regime (due to radar range limitations), analysis of their properties is tailored to those revealed by optical data products. In this connection, much attention has been directed towards understanding the lightcurves of orbital debris with high area-to-mass (A/m) ratios (greater than 0.9 square meters per kilogram). A small population of GEO debris was recently identified, which exhibits the properties of high A/m objects, such as variable eccentricities and inclinations a dynamical characteristic generally resulting from varying solar radiation pressure on high A/m objects. Materials such as multi-layered insulation (MLI) and solar panels are two examples of materials with high area-to mass ratios. Lightcurves for such objects can vary greatly (even for the same object under different illumination conditions). For example, specular reflections from multiple facets of the target surface (e.g. Mylar or Aluminized Kapton) can lead to erratic, orientation-dependent light curves. This paper will investigate published color photometric data for a series of orbital debris targets and compare it to the empirical photometric measurements generated in the OMC. The specific materials investigated (known to exist in GEO) are: an intact piece of MLI, separated layers of MLI, and multiple solar cells materials. Using the data acquired over specific rotational angles through different filters (B, V, R, I), a color index is acquired (B-R, R-I). As a secondary check, the spectrometer is used to define color indexes for the same material. Using these values and their associated lightcurves, this laboratory data is compared to observational data obtained on the 1m telescope of the Astronomical Institute of the University of Bern (AUIB) and the 0.9 m Small and Moderate Aperture Research Telescope System (SMARTS) telescope at Cerro Tololo Inter-American Observatory (CTIO). We will present laboratory generated lightcurves with color indexes of the high A/m materials alongside telescopic data of targets with high A/m values. We will discuss the relationship of laboratory to telescope data in the context of classification of GEO debris objects.

Rodriquez-Cowardin, H.↗

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss the science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Twicken, Joseph D.↗

Can Selforganizing Maps Accurately Predict Photometric Redshifts?

We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using delta(z) = z(sub phot) - z(sub spec)) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods

Way, Michael J.↗

Improving Photometric Calibration of Meteor Video Camera Systems

Current optical observations of meteors are commonly limited by systematic uncertainties in photometric calibration at the level of approximately 0.5 mag or higher. Future improvements to meteor ablation models, luminous efficiency models, or emission spectra will hinge on new camera systems and techniques that significantly reduce calibration uncertainties and can reliably perform absolute photometric measurements of meteors. In this talk we discuss the algorithms and tests that NASA's Meteoroid Environment Office (MEO) has developed to better calibrate photometric measurements for the existing All-Sky and Wide-Field video camera networks as well as for a newly deployed four-camera system for measuring meteor colors in Johnson-Cousins BV RI filters. In particular we will emphasize how the MEO has been able to address two long-standing concerns with the traditional procedure, discussed in more detail below.

Ehlert, Steven↗

Photometric Analysis in the Kepler Science Operations Center Pipeline

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) Science Processing Pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

photocenter↗

Online Photometric Calibration of Automatic Gain Thermal Infrared Cameras

Thermal infrared cameras are increasingly being used in various applications such as robot vision, industrial inspection and medical imaging, thanks to their improved resolution and portability. However, the performance of traditional computer vision techniques developed for electro-optical imagery does not directly translate to the thermal domain due to two major reasons: these algorithms require photometric assumptions to hold, and methods for photometric calibration of RGB cameras cannot be applied to thermal-infrared cameras due to difference in data acquisition and sensor phenomenology. In this paper, we take a step in this direction, and introduce a novel algorithm for online photometric calibration of thermalinfrared cameras. Our proposed method does not require any specific driver/hardware support and hence can be applied to any commercial off-the-shelf thermal IR camera. We present this in the context of visual odometry and SLAM algorithms, and demonstrate the efficacy of our proposed system through extensive experiments for both standard benchmark datasets, and real-world field tests with a thermal-infrared camera in natural outdoor environments.

Daftry, Shreyansh↗

Dwarf galaxy halo masses from spectroscopic and photometric lensing in DESI and DES

We present the most precise and lowest-mass weak lensing measurements of dwarf galaxies to date, enabled by spectroscopic lenses from the Dark Energy Spectroscopic Instrument (DESI) and photometric lenses from the Dark Energy Survey (DES) calibrated with DESI redshifts. Using DESI spectroscopy from the first data release, we construct clean samples of galaxies with median stellar masses $\log_{10}(M_*/M_{\odot})=8.3-10.1$ and measure their weak lensing signals with sources from DES, KiDS, and SDSS, achieving detections with $S/N$ up to 14 for dwarf galaxies ($\log_{10}(M_*/M_{\odot})<$9.25) -- opening up a new regime for lensing measurements of low-mass systems. Leveraging DES photometry calibrated with DESI, we extend to a photometric dwarf sample of over 700,000 galaxies, enabling robust lensing detections of dwarf galaxies with combined $S/N=38$ and a significant measurement down to $\log_{10}(M_*/M_{\odot})=8.0$. We show that the one-halo regime (scales $\lesssim 0.15h^{-1}\rm Mpc$) is insensitive to various systematic and sample selection effects, providing robust halo mass estimates, while the signal in the two-halo regime depends on galaxy color and environment. These results demonstrate that DESI already enables precise dwarf lensing measurements, and that calibrated photometric samples extend this capability. Together, they pave the way for novel constraints on dwarf galaxy formation and dark matter physics with upcoming surveys like the Vera C. Rubin Observatory's LSST.

Treiber, Helena [Princeton U., Astrophys. Sci. Dep↗

The DECam MAGIC Survey: Investigating the Jet Stellar Stream with Photometric Metallicities

Stellar streams are dynamically fragile structures formed by the tidal disruption of dwarf galaxies and stellar clusters. These objects are valuable tracers of the gravitational potential and accretion history of the Milky Way, and are key probes for the presence and interactions of starless dark matter subhalos. The Jet stream is a $\sim 30^\circ$-long stellar stream that is situated at 30.4 kpc and originates from a disrupted globular cluster. It consists of metal-poor stars that follow a retrograde orbit, reducing the impulse imparted from the Milky Way bar and making it especially sensitive to gravitational perturbations from dark matter subhalos. This paper investigates the known extent of the Jet stream by leveraging photometric metallicities derived from a narrowband filter centered on the Ca II H&K lines at $\sim$3950A on the Dark Energy Camera (DECam), as part of the Mapping the Ancient Galaxy in CaHK (MAGIC) survey. The wide field-of-view of DECam enables the efficient derivation of photometric metallicities for stars across the full extent of the stream, allowing for a metallicity-based selection to identify likely members. We demonstrate the efficacy of photometric metallicities in isolating stream members when used with Gaia DR3 proper motions, identifying a sample of 213 candidate Jet stream member stars. This then allows for the study of stream morphology, through which we identify a clear fanning of the stream toward the end farther from the Milky Way bar. We provide a list of candidate members, enabling spectroscopic follow-up of the Jet stream to facilitate further studies of its dynamics.

Do, Ha Q. [Chicago U., Astron. Astrophys. Ctr.] (O↗

Infrared-enhanced Photometric Redshifts for the Dark Energy Survey Y6 Gold catalogue

The Dark Energy Survey (DES) provides optical data across 5000 square degrees of the southern sky, enabling a broad range of extragalactic and cosmological studies. Combining DES data with infrared surveys offers the opportunity to improve its photometric redshift (photo-z) estimates. We aim to investigate improvements in photometric redshift estimation achieved by combining DES optical data with infrared measurements from the VISTA Hemisphere Survey (VHS) and the Wide-field Infrared Survey Explorer (WISE), and release an updated version of the catalogue. We performed a positional sky cross-match between the DES Y6 Gold catalogue matched to a spectroscopic dataset, the 2013 AllWISE Data Release, and VHS Data Release 5, in order to test these improvements using the Directional Neighbourhood Fitting (DNF) algorithm (Y6 Gold catalogue reference estimator). We additionally matched it to the unWISE catalogue to verify the performance against this deeper dataset. Adding infrared data reduces all the metrics (scatter, bias and outlier fraction) in photo-z estimates, particularly at higher redshifts in comparison with only using optical data from DES. The obtained results are globally better for the DES+WISE sample, with improvements that are statistically significant. On the other hand, the addition of the VHS bands to available depth is only marginal. The combined use of DES and WISE W1 and W2 data improves the photometric redshift metrics analysed here. The addition of VHS data at the DES and VHS depths explored here does not provide any further improvement at z less than 1.5, indicating that, under these constraints, WISE data may already capture the key infrared features and depth needed for accurate photo-z estimation. In addition, low signal-to-noise (less than 10) infrared data does not contribute to any improvement beyond the DES optical dataset.

Puebla, M. M. [Madrid U.; Madrid, CIEMAT]↗

Photometric metallicity for 694 233 Galactic giant stars from Gaia DR3 synthetic Strömgren photometry: Metallicity distribution functions of halo substructures

We used two previous calibrations and the standardised synthetic photometry in the v, b, and y Strömgren passbands from Gaia DR3 BP/RP spectra to obtain photometric metallicities for a selected sample of 694 233 old Galactic giant stars having |b|> 20.0° and parallax uncertainties lower than 10%. The zero point of both sets of photometric metallicities has been shifted to ensure an optimal match with the spectroscopic [Fe/H] values for 44 785 stars in common with APOGEE DR17, focusing on the metallicity range where they provide the highest accuracy. The metallicities derived in this way from one calibration display a typical accuracy of ≲0.1 dex and 1σ precision ≲0.2 dex in the range -2.2 ≲ [Fe/H] ≲ - 0.4, while they show a systematic trend with [Fe/H] at higher metallicity, beyond the applicability range of the relation. Those derived from the other calibration display, in general, reduced precision, and lower accuracy in the metal-poor regime, but have a median accuracy < 0.05 dex for [Fe/H] ≥ - 0.8. These results are confirmed and, consequently, the metallicities are validated, by comparison with large sets of spectroscopic metallicities from various surveys. The newly obtained metallicities are used to derive metallicity distributions for several previously identified substructures in the Galactic halo with an unprecedented number of stars. The catalogue including the two sets of metallicities and the associated uncertainties is made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

Dark Energy Survey Deep Field photometric redshift performance and training incompleteness assessment

Context. The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches are machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims. The goal of this work is to calculate the photo-zs for the Y3 DES Deep Fields catalogue using the DNF machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained with respect to the EAzY template fitting approach on Y3 DES Deep Fields catalogue. Methods. We have emulated -- at brighter magnitude -- the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We have used a principal component analysis to graphically assess incompleteness and to relate it with the performance parameters provided by DNF. Finally, we have applied the results about the incompleteness to the photo-z computation on Y3 DES Deep Fields with DNF and estimated its performance. Results. The photo-zs for the galaxies on DES Deep Fields have been computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. They are available at https://des.ncsa.illinois.edu/releases/y3a2/Y3deepfields. Some techniques have been developed to evaluate the performance in the absence of "true" redshift and to assess completeness. We have studied... (Partial abstract)

79 ASTRONOMY AND ASTROPHYSICS↗

Early photometric and spectroscopic observations of the extraordinarily bright INTEGRAL-detected GRB 221009A

Context. GRB 221009A, initially detected as an X-ray transient by Swift, was later revealed to have triggered the Fermi satellite about an hour earlier, marking it as a post-peak observation of the event’s emission. This GRB distinguished itself as the brightest ever recorded, presenting an unparalleled opportunity to probe the complexities of GRB physics. The unprecedented brightness, however, challenged observation efforts, as it led to the saturation of several high-energy instruments.Aims. Our study seeks to investigate the nature of the INTEGRAL-detected GRB 221009A and elucidate the environmental conditions conducive to these exceptionally powerful bursts. Moreover, we aim to understand the fundamental physics illuminated by the detection of teraelectronvolt (TeV) photons emitted by GRB 221009A.Methods. We conducted detailed analyses of early photometric and spectroscopic observations that span from the Fermi trigger through to the initial days following the prompt emission phase in order to characterize GRB 221009A’s afterglow, and we complemented these analyses with a comparative study.Results. Our findings from analyzing INTEGRAL data confirm GRB 221009A as the most energetic event observed to date. Early optical observations during the prompt phase negate the presence of bright optical emissions with internal or external shock origins. Spectroscopic analyses enabled us to measure GRB 221009A’s distance and line-of-sight properties. The afterglow’s temporal and spectral analysis suggests prolonged activity of the central engine and a transition in the circumburst medium’s density. Finally, we discuss the implications for fundamental physics of detecting photons as energetic as 18 TeV from GRB 221009A.Conclusions. Early optical observations have proven invaluable for distinguishing between the potential origins of optical emissions in GRB 221009A, underscoring their utility in GRB physics studies. However, the rarity of such data underscores the need for dedicated telescopes capable of synchronous multiwavelength observations. Additionally, our analysis suggests that the host galaxies of TeV GRBs share commonalities with those of long and short GRBs. Expanding the sample of TeV GRBs could further solidify these findings.Key words: techniques: photometric / techniques: spectroscopic / gamma-ray burst: general / gamma-ray burst: individual: GRB 221009A

79 ASTRONOMY AND ASTROPHYSICS↗

The PAU Survey: Photometric redshifts using transfer learning from simulations

In this paper, we introduce the DEEPZ deep learning photometric redshift (photo-z) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. DEEPZ reduces the σ68 scatter statistic by 50 percent at iAB = 22.5 compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-z scatter by 10 percent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

A Statistical Analysis of the Accuracy of the Digitized Magnitudes of Photometric Plates on the Timescale of Decades with an Application to the Century-Long Light Curve of KIC 8462852

We present a statistical analysis of the accuracy of the digitized magnitudes of photometric plates on the timescale of decades. In our examination of archival Johnson B photometry from the Harvard DASCH archive, we find a median rt mean square scatter of light curves of the order of 0.15 magnitude over the range B approximately equal to 9-17 for all calibrations. Slight underlying systematics (trends or flux discontinuities) are on a level of less than or equal to 0.2 magnitudes per century (1889–1990) for the majority of constant stars. These historic data can be unambiguously used for processes that happen on scales of magnitudes, and need to be carefully examined in cases approaching the noise floor. The characterization of these limits in photometric stability may guide future studies in their use of plate archives. We explain these limitations for the example case of KIC 8462852, which has been claimed to dim by 0.16 magnitudes per century, and show that this trend cannot be considered as significant.

digitized magnitudes of photometric plates↗

A Photometric Machine-Learning Method to Infer Stellar Metallicity

Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' < or = 18 mag), with 4500 K < or = Teff < or = 7000 K, corresponding to those with the most reliable SSPP estimates, I find that the model predicts [Fe/H] values with a root-mean-squared-error (RMSE) of approx.0.27 dex. The RMSE from this machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

machine learning↗

Is the Pale Blue Dot Unique? Optimized Photometric Bands for Identifying Earth-Like Exoplanets

The next generation of ground- and space-based telescopes will image habitable planets around nearby stars. A growing literature describes how to characterize such planets with spectroscopy, but less consideration has been given to the usefulness of planet colors. Here, we investigate whether potentially Earth-like exoplanets could be identified using UV-visible-to-NIR wavelength broadband photometry (350–1000 nm). Specifically, we calculate optimal photometric bins for identifying an exo-Earth and distinguishing it from uninhabitable planets including both Solar System objects and model exoplanets. The color of some hypothetical exoplanets—particularly icy terrestrial worlds with thick atmospheres—is similar to Earth's because of Rayleigh scattering in the blue region of the spectrum. Nevertheless, subtle features in Earth's reflectance spectrum appear to be unique. In particular, Earth's reflectance spectrum has a “U-shape” unlike all our hypothetical, uninhabitable planets. This shape is partly biogenic because O2-rich, oxidizing air is transparent to sunlight, allowing prominent Rayleigh scattering, while ozone absorbs visible light, creating the bottom of the “U.” Whether such uniqueness has practical utility depends on observational noise. If observations are photon limited or dominated by astrophysical sources (zodiacal light or imperfect starlight suppression), then the use of broadband visible wavelength photometry to identify Earth twins has little practical advantage over obtaining detailed spectra. However, if observations are dominated by dark current, then optimized photometry could greatly assist preliminary characterization. We also calculate the optimal photometric bins for identifying extrasolar Archean Earths, and find that the Archean Earth is more difficult to unambiguously identify than a modern Earth twin.

Astrobiology↗

Photometric detection of internal gravity waves in upper main-sequence stars

Massive stars are predicted to excite internal gravity waves (IGWs) by turbulent core convection and from turbulent pressure fluctuations in their near-surface layers. These IGWs are extremely efficient at transporting angular momentum and chemical species within stellar interiors, but they remain largely unconstrained observationally. In this work, we aim to characterise the photometric detection of IGWs across a large number of O and early-B stars in the Hertzsprung–Russell diagram, and explain the ubiquitous detection of stochastic variability in the photospheres of massive stars. Furthermore, we combined high-precision time-series photometry from the NASA Transiting Exoplanet Survey Satellite with high-resolution ground-based spectroscopy of 70 stars with spectral types O and B to probe the relationship between the photometric signatures of IGWs and parameters such as spectroscopic mass, luminosity, and macroturbulence.

79 ASTRONOMY AND ASTROPHYSICS↗