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At least 127 records · Page 7

A Bayesian Analysis of SDSS J0914+0853, a Low-mass Dual AGN Candidate

We present the first results from Bayesian AnalYsis of Multiple AGN in X-rays (BAYMAX), a tool that uses a Bayesian framework to quantitatively evaluate whether a given Chandra observation is more likely a single or dual point source. Although the most robust method of determining the presence of dual active galactic nuclei (AGNs) is to use X-ray observations, only sources that are widely separated relative to the instrumentʼs point-spread function are easy to identify. It becomes increasingly difficult to distinguish dual AGNs from single AGNs when the separation is on the order of Chandraʼs angular resolution (<1″). Using likelihood models for single and dual point sources, BAYMAX quantitatively evaluates the likelihood of an AGN for a given source. Specifically, we present results from BAYMAX analyzing the lowest-mass dual AGN candidate to date, SDSS J0914+0853, where archival Chandra data shows a possible secondary AGN ∼ 0"3 from the primary. Analyzing a new 50 ks Chandra observation, results from BAYMAX shows that SDSS J0914+0853 is most likely a single AGN with a Bayes factor of 13.5 in favor of a single point source model. Further, posterior distributions from the dual point source model are consistent with emission from a single AGN. We find a very low probability of SDSS J0914+0853 being a dual AGN system with a flux ratio f>0.3 and separation r>0"3. Overall, BAYMAX will be an important tool for correctly classifying candidate dual AGNs in the literature, as well as studying the dual AGN population where past spatial resolution limits have prevented systematic analyses.

Active galaxies↗

Optical Performance Modeling of FUSE Telescope Mirror

We describe the Metrology Data Processor (METDAT), the Optical Surface Analysis Code (OSAC), and their application to the image evaluation of the Far Ultraviolet Spectroscopic Explorer (FUSE) mirrors. The FUSE instrument - designed and developed by the Johns Hopkins University and launched in June 1999 is an astrophysics satellite which provides high resolution spectra (lambda/Delta(lambda) = 20,000 - 25,000) in the wavelength region from 90.5 to 118.7 nm The FUSE instrument is comprised of four co-aligned, normal incidence, off-axis parabolic mirrors, four Rowland circle spectrograph channels with holographic gratings, and delay line microchannel plate detectors. The OSAC code provides a comprehensive analysis of optical system performance, including the effects of optical surface misalignments, low spatial frequency deformations described by discrete polynomial terms, mid- and high-spatial frequency deformations (surface roughness), and diffraction due to the finite size of the aperture. Both normal incidence (traditionally infrared, visible, and near ultraviolet mirror systems) and grazing incidence (x-ray mirror systems) systems can be analyzed. The code also properly accounts for reflectance losses on the mirror surfaces. Low frequency surface errors are described in OSAC by using Zernike polynomials for normal incidence mirrors and Legendre-Fourier polynomials for grazing incidence mirrors. The scatter analysis of the mirror is based on scalar scatter theory. The program accepts simple autocovariance (ACV) function models or power spectral density (PSD) models derived from mirror surface metrology data as input to the scatter calculation. The end product of the program is a user-defined pixel array containing the system Point Spread Function (PSF). The METDAT routine is used in conjunction with the OSAC program. This code reads in laboratory metrology data in a normalized format. The code then fits the data using Zernike polynomials for normal incidence systems or Legendre-Fourier polynomials for grazing incidence systems. It removes low order terms from the metrology data, calculates statistical ACV or PSD functions, and fits these data to OSAC models for the scatter analysis. In this paper we briefly describe the laboratory image testing of FUSE spare mirror performed in the near and vacuum ultraviolet at John Hopkins University and OSAC modeling of the test setup performed at NASA/GSFC. The test setup is a double-pass configuration consisting of a Hg discharge source, the FUSE off-axis parabolic mirror under test, an autocollimating flat mirror, and a tomographic imaging detector. Two additional, small fold flats are used in the optical train to accommodate the light source and the detector. The modeling is based on Zernike fitting and PSD analysis of surface metrology data measured by both the mirror vendor (Tinsley) and JHU. The results of our models agree well with the laboratory imaging data, thus validating our theoretical model. Finally, we predict the imaging performance of FUSE mirrors in their flight configuration at far-ultraviolet wavelengths.

Saha, Timo T.↗

Autocorrelation and regularization in digital images. I - Basic theory

Spatial structure occurs in remotely sensed images when the imaged scenes contain discrete objects that are identifiable in that their spectral properties are more homogeneous within than between them and other scene elements. The spatial structure introduced is manifest in statistical measures such as the autocovariance function and variogram associated with the scene, and it is possible to formulate these measures explicitly for scenes composed of simple objects of regular shapes. Digital images result from sensing scenes by an instrument with an associated point spread function (PSF). Since there is averaging over the PSF, the effect, termed regularization, induced in the image data by the instrument will influence the observable autocovariance and variogram functions of the image data. It is shown how the autocovariance or variogram of an image is a composition of the underlying scene covariance convolved with an overlap function, which is itself a convolution of the PSF. The functional form of this relationship provides an analytic basis for scene inference and eventual inversion of scene model parameters from image data.

Jupp, David L. B.↗

Target Selection and Imaging Requirements for JWST Fine Phasing

To achieve and maintain the fine alignment of its segmented primary mirror the James Webb Space Telescope (JWST) plans to use focus-diverse wavefront sensing (WFS) techniques with science camera imagery. The optical requirements for JWST are such that the error contribution from the WFS itself must be limited 10nm rms over all the controllable degrees of freedom of the telescope. In this paper, we will explore the requirements on the target selection and imaging requirements necessary to achieve the desired level of WFS accuracy. Using Monte Carlo simulations we explore the WFS error as a function of wavefront aberrations level, defocus-diversity level, optical bandwidth and imaging signal-to-noise ratio to establish the key imaging requirements. By taking into account practical integration time limits along with the distribution of the defocused point-spread functions, we establish the bright and faint star magnitude limits suitable for WFS target selection.

wavefront sensing↗

Hubble Space Telescope Images of Nearby Luminous Quasars: Results for Eight Quasars and Tests of the Detection Sensitivity - 2

Observations with the Wide-Field Camera of the Hubble Space Telescope (HST) are presented for eight intrinsically luminous quasars with redshifts between 0.16 and 0.29. These observations, when combined with a similar HST study of the quasar PKS 2349-014, show that luminous nearby quasars exist in a variety of environments. Seven companion galaxies brighter than M(V) = 16.5 (H(sub 0) = 100 km s(sup -1) Mpc(sup -1), Omega(sub 0) = 1.0) lie within a projected distance of 25 kpc of the quasars; three of the companions are located closer than 3'' (6 kpc projected distance) from the quasars, well within the volume that would be enclosed by a typical L* host galaxy. The observed association of quasars and companion galaxies is statistically significant and may he an important element in the luminous-quasar phenomenon. Apparent host galaxies are detected for three of the quasars: PG 1116+215, 3C 273, and PG 1444+407; the hosts have an average absolute magnitude of about 0.6 mag brighter than L*. The agreement between the previously published major-axis directions in ground-based images and in the present HST images of 3C 273 and PG 1444+407 constitutes important evidence supporting the reality of these candidate host galaxies. Upper limits are placed on the visual-band brightnesses of representative galactic hosts for all the quasars. These limits are established by placing galaxy images obtained with HST underneath the quasars and measuring at what faintness level the known galaxies are detected. On average, the HST spirals would have been detected if they were as faint as 1 mag below L*, and the early-type galaxies could have been detected down to a brightness level of about L*, where L* is the Schechter characteristic luminosity of field galaxies. Smooth, featureless galaxy models (exponential disks or de Vaucouleurs profiles) are fitted to the residual light after a best-fitting point source is subtracted from the quasar images. The results show that smooth spiral galaxies brighter than, on average, about L*, would have been detected. These upper limits, or possible detections, are consistent with, for example, the eight luminous quasars studied in this paper, occurring in host galaxies that have a Shechter luminosity function with a lower cutoff in the range 0.01-0.1 L*. Tests are performed to determine if our failure to detect, in some cases, luminous host galaxies could be an artifact caused by our analysis procedures. These tests include comparing the measured point-spread function (PSF) for our HST observations with the PSFs used in previous ground-based studies of host galaxies, measuring the fluctuations in the sky signals that were subtracted from the quasar images, evaluating empirically the effects of using different stellar PSFs in the analysis, carrying out the subtraction of the stellar (nuclear) source in different ways, creating and analyzing artificial active galactic nuclei (AGNs) with known surface brightnesses, and fitting the observed quasar light to an analytic model that includes a host galaxy.

Bahcall, John N.↗

A new approach to remove interorder background in high dispersion IUE images

A two dimensional Chebyshev interpolating scheme, followed by modeling of point spread functions as Voigt profiles, is proposed for final archiving IUESIPS to remove the interorder overlap from the smoothed background fluxes of high dispersion International Ultraviolet Explorer (IUE) images. Tests of the first and last stages of the algorithm suggest that it can give a considerably better zero point than the old IUESIPS algorithm which samples local interorder background.

Smith, Myron A.↗

Scale effects: HCMM data simulation. Usage of filtering techniques for scaling-up simulations

Image reduction used to simulate increase in altitude of an acquisition platform is equivalent to data smoothing, and can be achieved either by neighborhood averaging or by filtering techniques. The averaging approach is limited for accurate simulation. A filtering method is described which was based on the hypothesis that all changes due to altitude increase can be represented by a point spread function. Determination of the scale function and factor are discussed as well as implementation of the filtering. Filtering can be either in the spatial or frequency domain. In the spatial domain, filtering consists of the convolution of the image with the weights mask, and then of the declination of the points according to the appropriates scale factor. A simulation of an aircraft day image in the infrared channel is examined.

Digennaro, V.↗

LANDSAT-D investigations in snow hydrology

The atmospheric radiative transfer calculation program (ATARD) and its supporting programs (setting up atmospheric profile, making Mie tables and an exponential-sum-fitting table) were completed. More sophisticated treatment of aerosol scattering (including angular phase function or asymmetric factor) and multichannel analysis of results from ATRAD are being developed. Some progress was made on a Monte Carlo program for examining two dimensional effects, specifically a surface boundary condition that varies across a scene. The MONTE program combines ATRAD and the Monte Carlo method together to produce an atmospheric point spread function. Currently the procedure passes monochromatic tests and the results are reasonable.

Dozier, J.↗

Limb brightening on Uranus - The visible spectrum

Results are presented for pinhole and slit narrowband photoelectric area-scanning photometry of the Uranus disk at eight central wavelengths ranging from 5600 to 7500 A. The observations were undertaken to detect limb brightening on the planet and to study the nature of its disk profile as a function of geometrical albedo. A coarse analysis of the results shows that the disk must exhibit limb brightening in the two CH4 bands at 6190 and 7300 A relative to all other wavebands investigated. Except for the two CH4 bands, the shapes and widths of the images are found to be essentially identical; point-spread-function data for all wavebands indicate no significant variation in the representative Gaussian l/e width with wavelength. A fine analysis of the data reveals absolute limb brightening in the 7300-A CH4 band and absolute limb darkening in the adjacent wavebands. These results are shown to be consistent with the hypothesis that clouds are absent from the visible atmosphere of Uranus.

Price, M. J.↗

Optimum constrained image restoration filters

The research described centered on development of an optimum image restoration filter (IRF) minimizing the radius of gyration of the corrected or composite system point-spread function (P-SF) subject to contraints, and reducing 2-dimensional spatial smearing or blurring of an image. The constraints are imposed on the radius of gyration of the IRF P-SF, the total restored image noise power, and the shape of the composite system frequency spectrum. The image degradation corresponds to mapping many points from the original image into a single resolution element. The P-SF is obtained as solution to a set of simultaneous differential equations obeying nonlinear integral constraints. Truncation errors due to edge effects are controlled by constraining the radius of gyration of the IRF P-SF. An iterative technique suppresses sidelobes of the composite system P-SF.

Riemer, T. E.↗

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=about 15 orbits/day].

NEAR IR IMAGERY↗

MISR Level 1B1 Radiance Data (MI1B1_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, about 15 orbits/day, Daily - < Weekly].

EOSDIS↗

MISR Level 1B1 Radiance Data (MI1B1_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

AM-1↗

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Temporal_Resolution=about 15 orbits/day].

AM-1↗

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.↗

Dual Double-Wedge Pseudo-Depolarizer with Anamorphic PSF

A polarized scene, which may occur at oblique illumination angles, creates a radiometric signal that varies as a function of viewing angle. One common optical component that is used to minimize such an effect is a polarization scrambler or depolarizer. As part of the CLARREO mission, the SOLARIS instrument project at Goddard Space Flight Center has developed a new class of polarization scramblers using a dual double-wedge pseudo-depolarizer that produces an anamorphic point spread function (PSF). The SOLARIS instrument uses two Wollaston type scramblers in series, each with a distinct wedge angle, to image a pseudo-depolarized scene that is free of eigenstates. Since each wedge is distinct, the scrambler is able to produce an anamorphic PSF that maintains high spatial resolution in one dimension by sacrificing the spatial resolution in the other dimension. This scrambler geometry is ideal for 1-D imagers, such as pushbroom slit spectrometers, which require high spectral resolution, high spatial resolution, and low sensitivity to polarized light. Moreover, the geometry is applicable to a wide range of scientific instruments that require both high SNR (signal-to-noise ratio) and low sensitivity to polarized scenes

Hill, Peter↗

Experimental Evaluation of Optically Polished Aluminum Panels on the Deep Space Network's 34 Meter Antenna

The potential development of large aperture ground?based "photon bucket" optical receivers for deep space communications has received considerable attention recently. One approach currently under investigation is to polish the aluminum reflector panels of 34?meter microwave antennas to high reflectance, and accept the relatively large spotsize generated by state of?the?art polished aluminum panels. Theoretical analyses of receiving antenna pointing, temporal synchronization and data detection have been addressed in previous papers. Here we describe the experimental effort currently underway at the Deep Space Network (DSN) Goldstone Communications Complex in California, to test and verify these concepts in a realistic operational environment. Two polished aluminum panels (a standard DSN panel polished to high reflectance, and a custom designed aluminum panel with much better surface quality) have been mounted on the 34 meter research antenna at Deep?Space Station 13 (DSS?13), and a remotely controlled CCD camera with a large CCD sensor in a weather?proof container has been installed next to the subreflector, pointed directly at the custom polished panel. The point?spread function (PSF) generated by the Vertex polished panel has been determined to be smaller than the sensor of the CCD camera, hence a detailed picture of the PSF can be obtained every few seconds, and the sensor array data processed to determine the center of the intensity distribution. In addition to estimating the center coordinates, expected communications performance can also been evaluated with the recorded data. The results of preliminary pointing experiments with the Vertex polished panel receiver using the planet Jupiter to simulate the PSF generated by a deep?space optical transmitter are presented and discussed in this paper.

optical receiver↗

SPECFOCUS: An IRAF task for focusing spectrographs

An IRAF task for measuring the point-spread function (PSF) along the dispersion and wavelength shifts across the dispersion in two dimensional arc spectra is described. In typical use, a set of spectra are obtained with various spectrograph focusing and alignment adjustments and the PSF information and shift information is derived and presented in tabular and graphical forms. Within each image the spectra may be divided into a number of samples along the dispersion and across the dispersion to investigate variations at different points in the detector at fixed focus settings. With many spectra and many samples interpreting the measurements is challenging. The task provides an interactive graphical interface to display the measurements in a number of interesting ways. The underlying algorithm for measuring the PSF and shifts in the auto/cross-correlation of spectral are samples.

Valdes, F.↗