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At least 253 records · Page 14

TESS Data Release Notes: Sector 24, DR35

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel fi les, light curve fi les, collateral pixel fi les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml fi les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD). The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2019).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

TESS↗

TESS Data Release Notes: Sector 47, DR67

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel files, light curve files, collateral pixel files, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml files.

TESS↗

TESS Data Release Notes:Sector 48, DR70

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel files, light curve files, collateral pixel files, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml files.

TESS↗

TESS Data Release Notes: Sector 49, DR71

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel files, light curve files, collateral pixel files, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml files

TESS↗

TESS Data Release Notes: Sector 57, DR82

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel files, light curve files, collateral pixel files, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml files.

TESS↗

Self-Supervised Anomaly Detection via Neural Autoregressive Flows with Active Learning

Many self-supervised methods have been proposed with the target of image anomaly detection. These methods often rely on the paradigm of data augmentation with predefined transformations such as flipping, cropping, and rotations. However, it is not straightforward to apply these techniques for non-image data, such as time series or tabular data, while the performance of the existing deep approaches has been under our expectation on tasks beyond images. In this work, we propose a novel active learning (AL) scheme that relied on neural autoregressive flows (NAF) for self-supervised anomaly detection, specifically on small-scale data. Unlike other generative models such as GANs or VAEs, flow-based models allow to explicitly learn the probability density and thus can assign accurate likelihoods to normal data which makes it usable to detect anomalies. The proposed NAF-AL method is achieved by efficiently generating random samples from latent space and transforming them into feature space along with likelihoods via invertible mapping. The samples with lower likelihoods are selected and further checked by outlier detection using Mahalanobis distance. The augmented samples incorporating with normal samples are used for training a better detector so as to approach decision boundaries. Compared with random transformations, NAF-AL can be interpreted as a likelihood-oriented data augmentation that is more efficient and robust. Extensive experiments show that our approach outperforms existing baselines on multiple time series and tabular datasets, and a real-world application in advanced manufacturing, with significant improvement on anomaly detection accuracy and robustness over the state-of-the-art.

Zhang, Jiaxin↗

Content-aware foveated camera for multi-target tracking

Modern image sensors deliver substantial space-time bandwidth, yet indiscriminate acquisition often overwhelms memory, computation, and downstream perception. We present a content-aware, multi-foveated camera that dynamically reallocates sensing and magnification to multiple regions of interest (ROIs). A phase-only spatial light modulator (SLM) serves as a solid-state, inertia-free beam-steering and lens element, enabling per-frame field-of-view (FOV) reconfiguration and content-aware target tracking. By interleaving frames across foveae, our system preserves a wide-FOV situational context while refreshing each ROI at high rates, thereby reducing data volume without degrading task performance. We constructed a prototype employing a single-SLM, single-sensor architecture and demonstrated its application in real-time multi-object tracking with dynamic ROI maintenance across multiple viewpoints. The approach offers a general pathway to integrate detection, tracking, and segmentation algorithms in the acquisition loop, shifting workload from post hoc processing to intelligent capture.

Zang, Zihan [Univ. of California, Los Angeles, CA ↗

Visual Target Tracking on the Mars Exploration Rovers

Visual Target Tracking (VTT) has been implemented in the new Mars Exploration Rover (MER) Flight Software (FSW) R9.2 release, which is now running on both Spirit and Opportunity rovers. Applying the normalized cross-correlation (NCC) algorithm with template image magnification and roll compensation on MER Navcam images, VTT tracks the target and enables the rover to approach the target within a few cm over a 10 m traverse. Each VTT update takes 1/2 to 1 minute on the rovers, 2-3 times faster than one Visual Odometry (Visodom) update. VTT is a key element to achieve a target approach and instrument placement over a 10-m run in a single sol in contrast to the original baseline of 3 sols. VTT has been integrated into the MER FSW so that it can operate with any combination of blind driving, Autonomous Navigation (Autonav) with hazard avoidance, and Visodom. VTT can either guide the rover towards the target or simply image the target as the rover drives by. Three recent VTT operational checkouts on Opportunity were all successful, tracking the selected target reliably within a few pixels.

target approach↗

Doppler radar imaging of spherical planetary surfaces

This paper describes a technique for using echo power-spectra for making radar images of spherical planetary targets. In developing the Doppler-radar imaging system, the target's reflectivity distribution is expanded in a truncated spherical harmonic series; the distribution of echo power in rotational phase and the Doppler frequency are obtained in form of a system of linear equations which express the echo spectra as functions of the series coefficients. To estimate the coefficients from an observed phase-Doppler distribution, the inversion is cast as a least-squares problem, and is solved using singular value decompositions, yielding a linear imaging system which can be fully characterized by its impulse response as a function of latitude. Simulations were designed and used to explore the capabilities of Doppler radar imaging, and the sensitivity of imaging to such factors as subradar altitude coverage and signal-to-noise ratio was investigated.

Hudson, R. Scott↗

TDCOSMO - XVII. New time delays in 22 lensed quasars from optical monitoring with the ESO-VST 2.6m and MPG 2.2m telescopes

We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-σ depth of the combined exposures typically reaches the 27th magnitude, while that of single visits is 24.5 mag – similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed in Hubble Space Telescope imaging. This was made possible thanks to a new photometric pipeline, lightcurver, and the forward modelling method STARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal.Key words: methods: data analysis / surveys / distance scale

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Few-view computed tomography reconstruction using deep neural network inference

A system for generating 2D slices of a 3D image of a target volume is provided. The system receives a target sinogram collected during a computed tomography scan of the target volume. The system inputs the target sinogram to a convolutional neural network (CNN) to generate predicted 2D slices of the 3D image. The CNN is trained using training 2D slices of training 3D images. The system initializes 2D slices to the predicted 2D slices. The system reconstructs 2D slices of the 3D image from the target sinogram and the initialized 2D slices.

Kim, Hyojin↗

Forest and grassland ecosystem studies using the advanced solid-state array spectroradiometer

The advanced solid-state array spectroradiometer (ASAS) is an airborne, off-nadir pointing imaging spectroradiometer used to acquire bidirectional radiance data for terrestrial targets. As its platform aircraft flies over a target the sensor can image the target through a sequence of at least seven fore-to-aft view directions ranging up to 45 deg on either side of nadir. ASAS acquires data for 29 spectral bands in the visible and near-infrared portions of the spectrum with a resolution of 15 nm. ASAS data were recently acquired for a prairie ecosystem and a northern forest ecosystem. The data demonstrate the combined effects of reflectance anisotropy and increased atmospheric path length on off-nadir observations. One result of these effects is a variation in vegetation indices as a function of view direction. Normalized-difference-vegetation-indices for prairie grass, coniferous, and deciduous canopies varied up to 14 percent, 23 percent, and 6 percent, respectively, relative to nadir as a function of view zenith angle along the solar principal plane.

Irons, James R.↗

Applying the Dark Target Aerosol Algorithm with Advanced Himawari Imager Observations During the KORUS-AQ Field Campaign

For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With the launch of the Advanced Himawari Imager (AHI) and the Advanced Baseline Imagers (ABIs) into geosynchronous orbits, we have the new ability to expand temporal coverage of the traditional aerosol optical depth (AOD) to resolve the diurnal signature of aerosol loading during daylight hours. The Korean–United States Air Quality (KORUS-AQ) campaign taking place in and around the Korean peninsula during May–June 2016 initiated a special processing of full-disk AHI observations that allowed us to make a preliminary adoption of Dark Target aerosol algorithms to the wavelengths and resolutions of AHI. Here,we describe the adaptation and show retrieval results from AHI for this 2-month period. The AHI-retrieved AOD is collocated in time and space with existing AErosol RObotic NETwork stations across Asia and with collocated Terra and Aqua MODIS retrievals. The new AHI AOD product matches AERONET, and the standard MODIS product does as well, and the agreement between AHI and MODIS retrieved AOD is excellent, as can be expected by maintaining consistency in algorithm architecture and most algorithm assumptions. Furthermore, we show that the new product approximates the AERONET-observed diurnal signature. Examining the diurnal patterns of the new AHI AOD product we find specific areas over land where the diurnal signal is spatially cohesive. For example, in Bangladesh the AOD in-creases by 0.50 from morning to evening, and in northeast China the AOD decreases by 0.25. However, over open ocean the observed diurnal cycle is driven by two artifacts, one associated with solar zenith angles greater than 70t hat may be caused by a radiative transfer model that does not properly represent the spherical Earth and the other artifact associated with the fringes of the 40 degree glint angle mask. This opportunity during KORUS-AQ provides encouragement to move towards an operational Dark Target algorithm for AHI. Future work will need to re-examine masking including snow mask, reevaluate assumed aerosol models for geosynchronous geometry, address the artifacts over the ocean, and investigate size parameter retrieval from the over-ocean algorithm.

Gupta, Pawan↗

Air-To-Air Background Oriented Schlieren Technique

An air-to-air background-oriented Schlieren system and method for measuring and rendering visible density changes in air that cause a refractive index change by an airborne vehicle. A sensor aircraft equipped with a high-speed visible spectrum camera travels at low airspeed on a predetermined route and on a level altitude over a background having consistent contrast and sunlight reflectivity. The target aircraft, traveling on the same predetermined route but at an altitude between the sensor aircraft and the ground (background) passes beneath the sensor aircraft. The camera on the sensor aircraft captures a series of images including a reference image immediately before the target aircraft enters the image frame followed by several data images as the target aircraft passes through the image frame. The data images are processed to calculate density gradients around the target aircraft. These density gradients include shockwaves, vortices, engine exhaust, and wakes. Air density gradients cause a refractive index change in the fluid and a slight distortion in the background pattern of the data image. Image processing that compares the data image to the reference image yields the difference caused by the density gradient.

Heineck, James Thomas↗

A new adaptive classifier using iterative filtering

To cope with signature variability, an algorithm has been defined which will adaptively classify remotely sensed data in the visible and near infrared band. The signal is divided into a space-dependent component and a target-dependent component. The target-dependent component is assumed fixed across the image for each target type. The space-dependent component is estimated iteratively by a weighted, least-squares algorithm. Included are the derivations of the sensor model and the two-dimensional, estimation algorithm.

Actkinson, A. L.↗

macroMS: Image-Guided Analysis of Random Objects by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Mass spectrometry imaging is well-suited to characterizing sample surfaces for their chemical content in a spatially resolved manner. However, when the surface contains small objects with significant empty spaces between them, more efficient approaches to sample acquisition are possible. Image-guided mass spectrometry (MS) enables high-throughput analysis of a diverse range of sample types, such as microbial colonies, liquid microdroplets, and others, by recognizing and analyzing selected location targets in an image. Here, we describe an imaging protocol and macroMS, an online software suite that can be used to enhance MS measurements of macroscopic samples that are imaged by a camera or a flatbed scanner. Furthermore, the web-based tool enables users to find and filter targets from the optical images, correct optical distortion issues for improved spatial location of selected targets, input the custom geometry files into an MS device to acquire spectra at the selected locations, and finally, perform limited data analysis and use visualization tools to aid locating samples containing compounds of interest. Using the macroMS suite, an enzyme mutant library of Saccharomyces cerevisiae and nL droplet arrays of Escherichia coli and Pseudomonas fluorescens have been assayed at a rate of ~2 s/sample.

47 OTHER INSTRUMENTATION↗

Multi-Star Wavefront Control at the Occulting Mask Coronagraph Testbed: Monochromatic Laboratory Demonstration for the Roman Coronagraph Instrument

The Astro2020 decadal survey recommended a direct imaging flagship mission with a goal for mission yield of 25 or more potentially habitable exoplanets. A majority of Sun-like stars have a stellar companion that can introduce additional noise into the field of view of any high-contrast imaging instrument and enabling exoplanet discovery around binary stars represents a path to increased coronagraphic instrument efficiency. This includes both of the Alpha Centauri A and B stars which would represent the top science target for direct imaging if companion leakage can be suppressed. Multi-Star Wavefront Control (MSWC) is a technique that removes stellar leakage from both stellar components, enabling direct imaging of exoplanets in many binary star systems. We present the latest testbed results obtained with MSWC as part of the technology development effort focusing on demonstrations conducted on the Occulting Mask Coronagraph (OMC) testbed at JPL. OMC has a layout similar to the Roman Space Telescope coronagraph instrument (CGI) and is outfitted with a MSWC mask with the same design as the contributed mask for the Roman CGI. Our testbed results represent the first demonstrations of this technique using the recently installed full binary source for a geometry matching potential Alpha Centauri observations. Technical Review Abstract: The Astro2020 decadal survey recommended a direct imaging flagship mission with a goal for mission yield of 25 or more potentially habitable exoplanets. A majority of Sun-like stars have a stellar companion that can introduce additional noise into the field of view of any high-contrast imaging instrument and enabling exoplanet discovery around binary stars represents a path to increased coronagraphic instrument efficiency by increasing the available science target pool of bright nearby stars. This includes both of the Alpha Centauri A and B stars which would represent the top science target for direct imaging if companion leakage can be suppressed. Multi-Star Wavefront Control (MSWC) is a technique that removes stellar leakage from both stellar components, enabling direct imaging of exoplanets in many binary star systems . We present the latest testbed results obtained with MSWC as part of the technology development effort focusing on demonstrations conducted on the Occulting Mask Coronagraph (OMC) testbed at JPL during the completed first vacuum window and recent results from the ongoing second vacuum window. The MSWC mask consists of a shaped pupil mask similar to the one used for the Wide-Field of View mode but also includes a set of superimposed, regularly-spaced dots that serve as a diffraction grating. OMC has a layout similar to the Roman Space Telescope coronagraph instrument (CGI) and is configured with a binary imaging mode with a MSWC mask using same design as the contributed mask for the Roman CGI. Our testbed results represent the first demonstrations of this technique using the recently installed full binary source. We present results obtained in Super-Nyquist regime demonstrating suppression in the Super-Nyquist regime for the 3rd diffraction order reaching 8.7e-9 contrast with the Roman pupil. In addition, we present results obtained with the binary-star regime demonstrating 9.6e-8 contrast for a geometry matching potential Alpha Centauri observations in a monochromatic wavelength similar to Band 1. Planned demonstrations in the 2nd vacuum window will focus on Band 3d and Band 4 using the full MSWC mode for an Alpha Centauri geometry.

High-contrast imaging↗