Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “pixel”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

SCA Test Report: H4RG-20833 WFIRST

This report summarizes the measured performance for the Sensor Chip Assembly (SCA), which is identified in Table 1. The SCA architecture is a substrate-removed HgCdTe detector with an area of 4096x4096 pixels (with a reference pixel area of four pixels deep around all four sides, available to substitute corresponding image pixels) and a pixel pitch of 10 μm. This SCA has been tested at the Goddard Space Flight Center (GSFC/NASA) Detector Characterization Laboratory (DCL). Teledyne (the vendor) classifies its detectors into different grades based on testing performed at its facility. The classification of this SCA and the tested dates are included in Table 1 below.The tests performed on this array are derived from the document WFIRST-PROC-09220_WFIRST-SCA-ATP_-.docx. A summary of the test parameters, requirements, and test results is presented in Table 2. The details of each test are subsequently described in the report. In the Summary (Table 2), SCA results are reported at an operating temperature of 95K, and 1.0 V bias voltage. In the detailed section of each test, the results for 90 K (1.0V bias voltage) and 95 K (0.5V bias voltage) are also reported. For all cases, the frame time used is 2.764 seconds. Reference pixel correction was applied to every raw frame.

Laddawan Miko↗
NASA NTRS2020

SCA Test Report: H4RG-20849 WFIRST

This report summarizes the measured performance for the Sensor Chip Assembly (SCA), which is identified in Table 1. The SCA architecture is a substrate-removed HgCdTe detector with an area of 4096x4096 pixels (with a reference pixel area of four pixels deep around all four sides, available to substitute corresponding image pixels) and a pixel pitch of 10 μm. This SCA has been tested at the Goddard Space Flight Center (GSFC/NASA) Detector Characterization Laboratory (DCL). Teledyne (the vendor) classifies its detectors into different grades based on testing performed at its facility. The classification of this SCA and the tested dates are included in Table 1 below. The tests performed on this array are derived from the document WFIRST-PROC-09220_WFIRST-SCA-ATP_-.docx. A summary of the test parameters, requirements, and test results is presented in Table 2. The details of each test are subsequently described in the report. In the Summary (Table 2), SCA results are reported at an operating temperature of 95K, and 1.0 V bias voltage. In the detailed section of each test, the results for 95 K and 0.5V bias voltage is also reported. For all cases, the frame time used is 2.764 seconds. Reference pixel correction was applied to every raw frame.

Laddawan Miko↗
NASA NTRSDate not supplied

Fine Optimization of TES Design for the X-IFU Instrument on ATHENA

The X-ray Integral Field Unit (X-IFU) instrument on the Advanced Telescope for High ENergy Astrophysics (ATHENA) is baselined to have 3168 transition-edge sensor (TES) microcalorimeter pixels. These pixels will be DC biased and readout using time division multiplexing. We recently reported a demonstration of the required pixel and readout performance in 252 pixels from a 1 kilo-pixel array (e.g. 2.16 eV resolution for 6.9 keV X-rays). Having achieved the required performance, the 50um square TES design in this demonstration array is considered the baseline pixel design for X-IFU. However, by making small adjustments to the TES design, we may be able to make small but consequential improvements to the instrument performance, while staying within the many constraints of the X-IFU requirements. In this presentation, we will show results from newly fabricated devices with subtle changes from the baseline TES design to further optimize the performance for X-IFU. We will discuss optimizing the TES sheet resistance, normal metal features, X-ray absorber attachment points, TES aspect ratio, and heat capacity. These minor design changes can have significant effects on thermo-electric time constants, thermal fluctuation noise, resistive transition shape and uniformity, and non-linearity of X-ray event pulses. In addition, full characterization of these new TES designs allows greater understanding of the relevant physics within the TES and gives routes for further optimization.

Nick Wakeham↗
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.↗
NASA NTRS2022

A New Machine Learning Based Analysis for Improving Satellite Retrieved Atmospheric Composition Data: OMI SO2 as an Example

Despite recent progress, satellite retrievals of anthropogenic SO2 still suffer from relatively low signal-tonoise ratios. In this study, we demonstrate a new machine learning data analysis method to improve the quality of satellite SO2 products. In the absence of large ground-truth datasets for SO2, we start from SO2 slant column densities (SCDs) retrieved from the Ozone Monitoring Instrument (OMI) using a data-driven, physically based algorithm and calculate the ratio between the SCD and the root mean square (rms) of the fitting residuals for each pixel. To build the training data, we select presumably clean pixels with small SCD / rms ratios (SRRs) and set their target SCDs to zero. For polluted pixels with relatively large SRRs, we set the target to the original retrieved SCDs. We then train neural networks (NNs) to reproduce the target SCDs using predictors including SRRs for individual pixels, solar zenith, viewing zenith and phase angles, scene reflectivity, and O3 column amounts, as well as the monthly mean SRRs. For data analysis, we employ two NNs: (1) one trained daily to produce analyzed SO2 SCDs for polluted pixels each day and (2) the other trained once every month to produce analyzed SCDs for less polluted pixels for the entire month. Test results for 2005 show that our method can significantly reduce noise and artifacts over background regions. Over polluted areas, the monthly mean NN-analyzed and original SCDs generally agree to within ±15 %, indicating that our method can retain SO2 signals in the original retrievals except for large volcanic eruptions. This is further confirmed by running both the NN-analyzed and original SCDs through a topdown emission algorithm to estimate the annual SO2 emissions for ∼ 500 anthropogenic sources, with the two datasets yielding similar results. We also explore two alternative approaches to the NN-based analysis method. In one, we employ a simple linear interpolation model to analyze the original SCD retrievals. In the other, we develop a PCA–NN algorithm that uses OMI measured radiances, transformed and dimension-reduced with a principal component analysis (PCA) technique, as inputs to NNs for SO2 SCD retrievals. While the linear model and the PCA–NN algorithm can reduce retrieval noise, they both underestimate SO2 over polluted areas. Overall, the results presented here demonstrate that our new data analysis method can significantly improve the quality of existing OMI SO2 retrievals. The method can potentially be adapted for other sensors and/or species and enhance the value of satellite data in air quality research and applications.

Can Li↗
NASA NTRSDate not supplied

Geometric Assessment of PlanetScope Imagery

Commercial companies such as Maxar, Planet Labs, and BlackSky have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. The high spatial resolution allows scientists to push studies to a fine scale such as monitoring agricultural growth experiments or detecting vehicles for traffic management. Scientists using these data need to know geolocation accuracy, band-to-band registration (BBR), and pixel footprint size to best determine appropriate applications as well as what extra steps they will need to take to use the data. Here, we find those key geometric properties for images from Planet Labs’ SuperDove constellation. Geolocation accuracy is assessed relative to WorldView images at globally distributed cities, band-to-band registration (BBR) is examined for every image we acquired (200+ images), and pixel footprint sizes are calculated from edge responses of the images over Cal/Val sites in China, India, or USA both near launch time and 1+ years after launch. We find that SuperDove geolocation is highly self-consistent with average global offsets among SuperDove images of 3.80 m (1.27 pixels). Despite this self-consistency, relative geolocation accuracy (with WorldView images as reference) varies by location from 3.20 m – 28.09 m mean offset. SuperDove BBR is sub-pixel and varies by band, with a mean radial offset relative to red band varying from 0.39 - 1.13 m. SuperDove image footprint size improves after 1+ years in orbit, with an average footprint size of 3.41 pixels (10.24 m) soon after launch and 3.23 pixels (9.7 m) 1+ years after launch. The BBR and self-consistency offsets are relatively small, given the large footprint sizes. A similarly extensive investigation is in progress for Planet Labs’ Dove-R series.

Alana G. Semple↗
DOE OSTI2018

System and method for detecting high-energy photons

A system for detecting high-energy photons includes a pixelated image detector exposed to visible light and high-energy photons, and the pixelated image detector generates one or more images from the exposure to the visible light and high-energy photons. The system further includes one or more processors operably connected to the pixelated image detector and configured to perform operations on the one or more images to discriminate between visible light and high-energy photons. A method for detecting high-energy photons includes exposing a pixelated image detector to visible light and high-energy photons and discriminating between the visible light that interacts with the pixelated image detector and the high-energy photons that interact with the pixelated image detector.

Gibbs, Kenneth M.↗
DOE OSTI2026

Evaluation of an event-driven 3FI ASIC for spectroscopic X-ray detection with synchrotron radiation

The novel design and evaluation on the NSLS-II beamline of the 3FI application-specific integrated circuit (ASIC) bump-bonded to a simple, planar, 2D segmented silicon sensor are presented. The ASIC was developed for full-field fluorescence spectral X-ray imaging (3FI). It is a small-scale prototype that features a square array of 32 × 32 pixels, and the size of the pixels is 100 µm × 100 µm. The ASIC was implemented in a 65 nm CMOS integrated circuit fabrication process. Each pixel incorporates a charge-sensitive amplifier, a shaping filter, a discriminator, a peak detector and a sample-and-hold circuit, allowing detection of events and storage of signal amplitudes. The system operates in a frameless event-driven readout mode, outputting analog values for threshold-triggered events, allowing high-speed multi-element X-ray fluorescence data acquisition. The 3FI ASIC achieves per-channel spectrometric performance at a power consumption of only 200 µW per pixel, with nearly all dissipation confined to the analog front-end. An energy resolution is measured at the level of 308 eV full width at half-maximum (FWHM) at 8.04 keV (Cu Kα), and 138 eV FWHM at 3.69 keV (Ca Kα). This per-pixel capability makes the prototype suitable for in situ trace element microanalysis in biological and environmental studies. Moreover, the frameless architecture of the detector is designed to address limitations of conventional X-ray fluorescence microscopy, which typically requires mechanical scanning, by enabling continuous high-throughput data acquisition in future full-field implementations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?

Purpose: To determine if texture analysis can differentiate placenta accreta spectrum (PAS) from normal placenta on MRI. Methods: We performed retrospective image analysis of 80 patients, comprised of 46 patients with PAS and 34 patients without PAS. Histopathology was used as the reference standard. Sagittal single shot fast spin echo T2-weighted MRI sequences acquired from a single institution were analyzed. Placental heterogeneity was quantified using in-house software on a Matlab platform, including the standard deviation of pixel intensity, coefficient of variation, gray-level co-occurrence matrices (GLCM), histogram-oriented gradients (HOG), and fractal analysis with box sizes from 2 to 512. Two-tailed unpaired Student’s t test was used with statistical significance of p < 0.05. Results: PAS was associated with higher values for standard deviation of pixel intensity and fractal analysis at every box size. Fractal analysis at box sizes 256 (p = 0.011) and 32 (p = 0.021), and standard deviation of pixel intensity (p = 0.023) were the most statistically significant. Fractal values at box size 256 for PAS was 0.13 versus 0.090 for patients without PAS, while standard deviation of pixel intensity was 3.7 for PAS versus 2.5 for patients without PAS. No statistically significant association between PAS and GLCM, coefficient of variation, and HOG was found. Conclusion: Statistically significant differences were found between normal and abnormal groups using standard deviation of pixel intensity and fractal analysis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Signatures of Thermal and Electrical Crosstalk in a Microwave Multiplexed Hard X-ray Transition Edge Sensor Array

We investigate the crosstalk between Transition-Edge Sensor (TES) pixels in a 24-pixel hard X-ray spectrometer array fabricated at the Advanced Photon Source, Argonne National Laboratory. Analysis shows thermal cross talk, possibly associated with insufficient thermalization, and rare but larger in magnitude electrical crosstalk between specific perpetrator-victim pixel combinations, potentially due to defects in the bias wiring or microwave multiplexing circuit. We use a method based on group-triggering and averaging to isolate the crosstalk response despite only having access to X-ray photon illumination uniform across the entire array. This allows us to identify thermal and electrical crosstalk between pixel pairs in repeated measurements to the level of 1 part in 1000 or better. In the array under study, the magnitude of observed crosstalk is small but comparable to the resolving power of this pixel design (E/Delta E similar to\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$E/\Delta {}E \sim$$\end{document} 1000 at 20 keV) and so potentially responsible for a degradation in energy resolution of the array at high incident photon rates. Having proven the methods to identify and quantify crosstalk in our setup, we can now consider mitigations.

Triamkitsawat, Panthita↗
DOE OSTI2024

Advanced Energy Scale Correction Techniques for the X-ray Transition Edge Sensors of the Athena mission

The X-ray Integral Field Unit (X-IFU) onboard the future European X-ray telescope Athena will be the first space instrument carrying an array of more than a thousand transition edge sensors. One of the key challenges of the X-IFU is the measurement of narrow X-ray atomic lines to determine velocity shifts at an unprecedented level of accuracy. For this reason, the energy scale of the instrument needs to be known with extreme accuracy, of 0.4 eV (1σ) up to 7 keV. The energy scale will be measured on the ground through a dedicated calibration campaign using fiducial X-ray sources. Though calibrated, the energy scale is extremely sensitive to the environmental conditions around the TES array, and drifts in the readout chain electronics. Uncorrected, the energy scale can naturally drift up to hundreds of eVs. Changes of the TES gain will be monitored via onboard X-ray calibration sources, and the energy scale will be corrected either per pixel, or within a small groups of pixels. Although simulations show that a 0.4 eV level can be achieved, the very high accuracy required by the X-IFU calls for experimental validation. A dedicated measurement campaign has been performed by NASA Goddard Space Flight Center to characterize the energy scale of a prototype kilo-pixel array of X-IFU-representative TESs. The analysis of the data demonstrated the ability to correct for various drifts using two fiducial lines to track the temporal gain variation. In this paper, we propose to extend this study on the same data set by investigating multi-parameter correction techniques based on both the pulse-height of the fiducial line and the prepulse baseline level, using the knowledge of the TES energy scale at reference temperature/magnetic field set points acquired on the ground. Investigations on the co-adding of pixels to perform a joint correction over pools of pixels is also explored.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Numerical estimation of photon reabsorption process and optical crosstalk in arrays of HgCdTe photodiodes

The effect of photon reabsorption (recycling) on photoelectric parameters of non-equilibrium P{sup +}nN{sup +} photodiodes, for example the pixels of the detector array, was analyzed. We solved the system of transport equations additionally extended by two balances equations for photons. It was shown that the density of photons in photodiodes is strongly dependent on the concentration of charge carriers. This phenomenon results in a drastic reduction in the rate of radiative recombination and generation in analyzed photodiodes. Additionally, the phenomenon of optical crosstalk between the nearest pixels in the matrix was examined. The increase in the dark current caused by this phenomenon was estimated. It depends on the size of the pixel, the distance between pixels, and the value of bias voltage. The increase in the current is around 0.5% for a pixel with surface 10 × 10 µm{sup 2}, and around 1% for one with 5 × 5 µm{sup 2}, both reverse biased with 0.2 V.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Subfield crop yields and temporal stability in thousands of US Midwest fields

Understanding subfield crop yields and temporal stability is critical to better manage crops. Several algorithms have proposed to study within-field temporal variability but they were mostly limited to few fields. In this study, a large dataset composed of 5520 yield maps from 768 fields provided by farmers was used to investigate the influence of subfield yield distribution skewness on temporal variability. The data are used to test two intuitive algorithms for mapping stability: one based on standard deviation and the second based on pixel ranking and percentiles. The analysis of yield monitor data indicates that yield distribution is asymmetric, and it tends to be negatively skewed (p < 0.05) for all of the four crops analyzed, meaning that low yielding areas are lower in frequency but cover a larger range of low values. The mean yield difference between the pixels classified as high-and-stable and the pixels classified as low-and-stable was 1.04 Mg ha –1 for maize, 0.39 Mg ha –1 for cotton, 0.34 Mg ha –1 for soybean, and 0.59 Mg ha —1 for wheat. The yield of the unstable zones was similar to the pixels classified as low-and-stable by the standard deviation algorithm, whereas the two-way outlier algorithm did not exhibit this bias. Furthermore, the increase in the number years of yield maps available induced a modest but significant increase in the certainty of stability classifications, and the proportion of unstable pixels increased with the precipitation heterogeneity between the years comprising the yield maps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Automated co-adding and energy calibration of large array microcalorimeter data with zero sample knowledge

State-of-the-art microcalorimeter spectrometers now contain large detector arrays with hundreds of individual pixels. Each individual pixel outputs a unique and non-linear response with respect to deposited energy. This work describes a pattern-recognition algorithm to combine these responses into a single energy-calibrated histogram, referred to as co-adding pixels. Photo-peaks from different pixels are matched together based upon how well the match aligns the centroids and heights of neighboring peaks. This usually results in around 100 co-adding calibration points from 30 to 300 keV for a several day acquisition of plutonium items with masses between 0.5 and 10 grams. An additional algorithm energy-calibrates this co-added spectrum using the fluoresced K x-ray emissions from a tantalum absorber and inherent x-ray escape peaks from the tin absorbers. Both algorithms operate without knowledge of the source and are fully automated. This work presents results from the acquisitions of high and low burnup plutonium, 10% enriched uranium, a 153 Gd calibration source, and a 57 Co+ 166m Ho calibration source. In all measurements, resolution defined as the full-width at half-maximum (FWHM) of photo-peaks is preserved between the individual pixel and co-added spectra at around 65 eV for incident photon energies between 60 and 208 keV. The energy calibration algorithm is approximate and yields a calibration curve off by an average of around 200 eV for incident photon energies between 60 and 208 keV.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Analysis of the EMCCD point-source response using x-rays

Electron Multiplying Charge Coupled Devices, EMCCD are used as x-ray detectors. The NSLS-II Soft Inelastic x-ray Scattering (SIX) beam line has two EMCCDs for x-ray detection in the spectrometer arm. The spectrometer with high resolving power disperses x-rays vertically. The x-ray vertical position on the sensor plane is related to its energy. This allows for very accurate x-ray energy measurements through x-ray coordinates. X-rays interact with silicon and create a number of electron-hole pairs proportional to the x-ray energy. Electrons drift and diffuse toward pixel gates and are collected there. The diffused electrons form a charge cloud distributed over several neighboring pixels. This charge sharing enables coordinate measurements with accuracy better than the pixel pitch. The charge distribution shape has to be taken into account to achieve ultimate accuracy in coordinate measurements. In this paper, we present a method of the charge distribution shape analysis and demonstrate its applications. The drift and diffusion of electrons ftom the point of generation to pixel gates results in the bell-shaped electron cloud usually approximated by Gaussian shape. The number of electrons collected under a pixel is proportional to the shape function integral. These electron packets get transferred to the sense node of the output amplifier. The transfer process could introduce distortions to the original charge distribution. For example, during transfers, electrons in the packet could be exposed to traps if they are present in the sensor. The trapping and later the release processes distort the apparent shape of the charge distribution. Therefore, deviations of the charge distribution shape ftom the originally symmetrical form can indicate the presence of trap centers in the sensor and can be used for sensor diagnostics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Compressive Classification for TEM-EELS

Acquiring atomic-resolution images of beam sensitive materials or under dynamic conditions (e.g. operando STEM) is very difficult and requires precise dose fractioning to minimize the dose delivered to the sample and acquire the data more rapidly than dynamics present. Typical methods of low-dose STEM imaging include adjusting the beam current, dwell-time, and probe Scanning transmission electron microscopy (STEM) is used routinely to obtain atomic-resolution images of a small selection of radiation tolerant materials under stable conditions.size. All three of these determine the dose over a spatial area in STEM. Recently, compressive sensing [1] has been applied to electron microscopy. The computational imaging method of inpainting [2] has been proposed as a method to reduce dose and increase acquisition speed for STEM. Inpainting is a technique to recover missing pixels in an image. By skipping pixels (randomly) during acquisition, a fourth dose-control mechanism is realized [3]. A few implementations of randomly-subsampled STEM exist (e.g., [4]). To make the concepts of compressive sensing accessible to the microscopy community we begin with an example using atomic resolution images of a GaAs crystal (see Figure 1). Because the crystal is periodic it has a sparse representation in reciprocal space. In fact, a sparse representation is a key component of compressive sensing. If an image is sub-sampled randomly we find that the Fourier transform remains sparse, but becomes increasing noisy as less and less data is acquired. Yet, by finding the peaks in the reciprocal image and removing the noise it is possible to recover atomic resolution images with only 1% of the pixels. Figure 1 shows the reconstruction process for GaAs sub-sampled at 50%, 10%, 5%, and 1%. Periodic images form a special class for which the optimal sampling approach (according to CS theory) is a random selection of pixels. For non-periodic images, such as those arising in in-situ STEM, methods such as dictionary learning are necessary [2,5]. The data can be compressed in time for TEM [5] or pixels can be skipped randomly for STEM. There are several issues that arise in developing a random scan for STEM [4] and a coded aperture for TEM. The remainder of the talk will address these issues. References: [1] E Candes and M Wakin. Signal Processing Magazine, IEEE. 2(25) (2008), pp. 21. [2] A Stevens, Pu Y, Sun Y, et al. Artificial Intelligence & Statistics (AISTATS), 2017. [3] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [4] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016). [5] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [6] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Hao, Weituo↗
DOE OSTI2014

Fluctuation spectroscopy: a new probe of old stellar populations

We introduce a new method to determine the relative contributions of different types of stars to the integrated light of nearby early-type galaxies. As is well known, the surface brightness of these galaxies shows pixel-to-pixel fluctuations due to Poisson variations in the number of giant stars. Differential spectroscopy of pixels as a function of fluctuation strength ({sup f}luctuation spectroscopy{sup )} effectively measures the spectral variation of stars as a function of their luminosity, information that is otherwise difficult to obtain for individual stars outside of the Local Group. We apply this technique to the elliptical galaxy NGC 4472, using Hubble Space Telescope/Advanced Camera for Surveys imaging in six narrow-band ramp filters tuned to spectral features in the range 0.8 μm-1.0 μm. Pixels with ±5% broad-band variations show differential color variations of 0.1%-1.0% in the narrow-band filters. These variations are primarily due to the systematic increase in TiO absorption strength with increasing luminosity on the upper giant branch. The data are very well reproduced by the same Conroy and van Dokkum stellar population synthesis model that is the best fit to the integrated light, with residuals in the range 0.03%-0.09%. Models with ages or metallicities that are significantly different from the integrated-light values do not yield good fits. We can also rule out several modifications to the underlying model, including the presence of a significant (>3% of the light) population of late M giants. The current observations constitute a powerful test of the expected luminosities and temperatures of metal-rich giants in massive early-type galaxies. Studies of pixels with much larger (negative) fluctuations will provide unique information on main sequence stars and the stellar initial mass function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

On the regularity of the covariance matrix of a discretized scalar field on the sphere

We present a comprehensive study of the regularity of the covariance matrix of a discretized field on the sphere. In a particular situation, the rank of the matrix depends on the number of pixels, the number of spherical harmonics, the symmetries of the pixelization scheme and the presence of a mask. Taking into account the above mentioned components, we provide analytical expressions that constrain the rank of the matrix. They are obtained by expanding the determinant of the covariance matrix as a sum of determinants of matrices made up of spherical harmonics. We investigate these constraints for five different pixelizations that have been used in the context of Cosmic Microwave Background (CMB) data analysis: Cube, Icosahedron, Igloo, GLESP and HEALPix, finding that, at least in the considered cases, the HEALPix pixelization tends to provide a covariance matrix with a rank closer to the maximum expected theoretical value than the other pixelizations. The effect of the propagation of numerical errors in the regularity of the covariance matrix is also studied for different computational precisions, as well as the effect of adding a certain level of noise in order to regularize the matrix. In addition, we investigate the application of the previous results to a particular example that requires the inversion of the covariance matrix: the estimation of the CMB temperature power spectrum through the Quadratic Maximum Likelihood algorithm. Finally, some general considerations in order to achieve a regular covariance matrix are also presented.

79 ASTRONOMY AND ASTROPHYSICS↗