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James Bosch

Publications and source records attributed to James Bosch.

36 records · Page 2Linked to original sources

Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). V. Quasar Luminosity Function and Contribution to Cosmic Reionization at z = 6

We present new measurements of the quasar luminosity function (LF) at $z \sim 6$, over an unprecedentedly wide range of the rest-frame ultraviolet luminosity $M_{1450}$ from $-30$ to $-22$ mag. This is the fifth in a series of publications from the Subaru High-$z$ Exploration of Low-Luminosity Quasars (SHELLQs) project, which exploits the deep multi-band imaging data produced by the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey. The LF was calculated with a complete sample of 110 quasars at $5.7 \le z \le 6.5$, which includes 48 SHELLQs quasars discovered over 650 deg$^2$, and 63 brighter quasars discovered by the Sloan Digital Sky Survey and the Canada-France-Hawaii Quasar Survey (including one overlapping object). This is the largest sample of $z \sim 6$ quasars with a well-defined selection function constructed to date, and has allowed us to detect significant flattening of the LF at its faint end. A double power-law function fit to the sample yields a faint-end slope $α= -1.23^{+0.44}_{-0.34}$, a bright-end slope $β= -2.73^{+0.23}_{-0.31}$, a break magnitude $M_{1450}^* = -24.90^{+0.75}_{-0.90}$, and a characteristic space density $Φ^* = 10.9^{+10.0}_{-6.8}$ Gpc$^{-3}$ mag$^{-1}$. Integrating this best-fit model over the range $-18 < M_{1450} < -30$ mag, quasars emit ionizing photons at the rate of $\dot{n}_{\rm ion} = 10^{48.8 \pm 0.1}$ s$^{-1}$ Mpc$^{-3}$ at $z = 6.0$. This is less than 10 % of the critical rate necessary to keep the intergalactic medium ionized, which indicates that quasars are not a major contributor to cosmic reionization.

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Weak lensing shear calibration with simulations of the HSC survey

We present results from a set of simulations designed to constrain the weak lensing shear calibration for the Hyper Suprime-Cam (HSC) survey. These simulations include HSC observing conditions and galaxy images from the Hubble Space Telescope (HST), with fully realistic galaxy morphologies and the impact of nearby galaxies included. We find that the inclusion of nearby galaxies in the images is critical to reproducing the observed distributions of galaxy sizes and magnitudes, due to the non-negligible fraction of unrecognized blends in ground-based data, even with the excellent typical seeing of the HSC survey (0.58" in the $i$-band). Using these simulations, we detect and remove the impact of selection biases due to the correlation of weights and the quantities used to define the sample (S/N and apparent size) with the lensing shear. We quantify and remove galaxy property-dependent multiplicative and additive shear biases that are intrinsic to our shear estimation method, including a $\sim 10$ per cent-level multiplicative bias due to the impact of nearby galaxies and unrecognized blends. Finally, we check the sensitivity of our shear calibration estimates to other cuts made on the simulated samples, and find that the changes in shear calibration are well within the requirements for HSC weak lensing analysis. Overall, the simulations suggest that the weak lensing multiplicative biases in the first-year HSC shear catalog are controlled at the 1 per cent level.

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SCARLET: Source separation in multi-band images by Constrained Matrix Factorization

We present the source separation framework SCARLET for multi-band images, which is based on a generalization of the Non-negative Matrix Factorization to alternative and several simultaneous constraints. Our approach describes the observed scene as a mixture of components with compact spatial support and uniform spectra over their support. We present the algorithm to perform the matrix factorization and introduce constraints that are useful for optical images of stars and distinct stellar populations in galaxies, in particular symmetry and monotonicity with respect to the source peak position. We also derive the treatment of correlated noise and convolutions with band-dependent point spread functions, rendering our approach applicable to coadded images observed under variable seeing conditions. SCARLET thus yields a PSF-matched photometry measurement with an optimally chosen weight function given by the mean morphology in all available bands. We demonstrate the performance of SCARLET for deblending crowded extragalactic scenes and on an AGN jet -- host galaxy separation problem in deep 5-band imaging from the Hyper Suprime-Cam Stategic Survey Program. Using simulations with prominent crowding we show that SCARLET yields superior results to the HSC-SDSS deblender for the recovery of total fluxes, colors, and morphologies. Due to its non-parametric nature, a conceptual limitation of SCARLET is its sensitivity to undetected sources or multiple stellar population within detected sources, but an iterative strategy that adds components at the location of significant residuals appears promising. The code is implemented in Python with C++ extensions and is available at https://github.com/fred3m/scarlet

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The first-year shear catalog of the Subaru Hyper Suprime-Cam SSP Survey

We present and characterize the catalog of galaxy shape measurements that will be used for cosmological weak lensing measurements in the Wide layer of the first year of the Hyper Suprime-Cam (HSC) survey. The catalog covers an area of 136.9 deg$^2$ split into six fields, with a mean $i$-band seeing of $0.58$ arcsec and $5σ$ point-source depth of $i\sim 26$. Given conservative galaxy selection criteria for first year science, the depth and excellent image quality results in unweighted and weighted source number densities of 24.6 and 21.8 arcmin$^{-2}$, respectively. We define the requirements for cosmological weak lensing science with this catalog, then focus on characterizing potential systematics in the catalog using a series of internal null tests for problems with point-spread function (PSF) modeling, shear estimation, and other aspects of the image processing. We find that the PSF models narrowly meet requirements for weak lensing science with this catalog, with fractional PSF model size residuals of approximately $0.003$ (requirement: 0.004) and the PSF model shape correlation function $ρ_1<3\times 10^{-7}$ (requirement: $4\times 10^{-7}$) at 0.5$^\circ$ scales. A variety of galaxy shape-related null tests are statistically consistent with zero, but star-galaxy shape correlations reveal additive systematics on $>1^\circ$ scales that are sufficiently large as to require mitigation in cosmic shear measurements. Finally, we discuss the dominant systematics and the planned algorithmic changes to reduce them in future data reductions.

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First Data Release of the Hyper Suprime-Cam Subaru Strategic Program

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) is a three-layered imaging survey aimed at addressing some of the most outstanding questions in astronomy today, including the nature of dark matter and dark energy. The survey has been awarded 300 nights of observing time at the Subaru Telescope and it started in March 2014. This paper presents the first public data release of HSC-SSP. This release includes data taken in the first 1.7 years of observations (61.5 nights) and each of the Wide, Deep, and UltraDeep layers covers about 108, 26, and 4 square degrees down to depths of i~26.4, ~26.5, and ~27.0 mag, respectively (5sigma for point sources). All the layers are observed in five broad bands (grizy), and the Deep and UltraDeep layers are observed in narrow bands as well. We achieve an impressive image quality of 0.6 arcsec in the i-band in the Wide layer. We show that we achieve 1-2 per cent PSF photometry (rms) both internally and externally (against Pan-STARRS1), and ~10 mas and 40 mas internal and external astrometric accuracy, respectively. Both the calibrated images and catalogs are made available to the community through dedicated user interfaces and database servers. In addition to the pipeline products, we also provide value-added products such as photometric redshifts and a collection of public spectroscopic redshifts. Detailed descriptions of all the data can be found online. The data release website is https://hsc-release.mtk.nao.ac.jp/.

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Two- and three-dimensional wide-field weak lensing mass maps from the Hyper Suprime-Cam Subaru Strategic Program S16A data

We present wide-field (167 deg$^2$) weak lensing mass maps from the Hyper Supreme-Cam Subaru Strategic Program (HSC-SSP). We compare these weak lensing based dark matter maps with maps of the distribution of the stellar mass associated with luminous red galaxies. We find a strong correlation between these two maps with a correlation coefficient of $ρ=0.54\pm0.03$ (for a smoothing size of $8'$). This correlation is detected even with a smaller smoothing scale of $2'$ ($ρ=0.34\pm 0.01$). This detection is made uniquely possible because of the high source density of the HSC-SSP weak lensing survey ($\bar{n}\sim 25$ arcmin$^{-2}$). We also present a variety of tests to demonstrate that our maps are not significantly affected by systematic effects. By using the photometric redshift information associated with source galaxies, we reconstruct a three-dimensional mass map. This three-dimensional mass map is also found to correlate with the three-dimensional galaxy mass map. Cross-correlation tests presented in this paper demonstrate that the HSC-SSP weak lensing mass maps are ready for further science analyses.

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Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs). II. Discovery of 32 Quasars and Luminous Galaxies at 5.7 < z < 6.8

We present spectroscopic identification of 32 new quasars and luminous galaxies discovered at 5.7 < z < 6.8. This is the second in a series of papers presenting the results of the Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs) project, which exploits the deep multi-band imaging data produced by the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey. The photometric candidates were selected by a Bayesian probabilistic algorithm, and then observed with spectrographs on the Gran Telescopio Canarias and the Subaru Telescope. Combined with the sample presented in the previous paper, we have now identified 64 HSC sources over about 430 deg2, which include 33 high-z quasars, 14 high-z luminous galaxies, 2 [O III] emitters at z ~ 0.8, and 15 Galactic brown dwarfs. The new quasars have considerably lower luminosity (M1450 ~ -25 to -22 mag) than most of the previously known high-z quasars. Several of these quasars have luminous (> 10^(43) erg/s) and narrow (< 500 km/s) Ly alpha lines, and also a possible mini broad absorption line system of N V 1240 in the composite spectrum, which clearly separate them from typical quasars. On the other hand, the high-z galaxies have extremely high luminosity (M1450 ~ -24 to -22 mag) compared to other galaxies found at similar redshift. With the discovery of these new classes of objects, we are opening up new parameter spaces in the high-z Universe. Further survey observations and follow-up studies of the identified objects, including the construction of the quasar luminosity function at z ~ 6, are ongoing.

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The bright-star masks for the HSC-SSP survey

We present the procedure to build and validate the bright-star masks for the Hyper-Suprime-Cam Strategic Subaru Proposal (HSC-SSP) survey. To identify and mask the saturated stars in the full HSC-SSP footprint, we rely on the Gaia and Tycho-2 star catalogues. We first assemble a pure star catalogue down to $G_{\rm Gaia} < 18$ after removing $\sim1.5\%$ of sources that appear extended in the Sloan Digital Sky Survey (SDSS). We perform visual inspection on the early data from the S16A internal release of HSC-SSP, finding that our star catalogue is $99.2\%$ pure down to $G_{\rm Gaia} < 18$. Second, we build the mask regions in an automated way using stacked detected source measurements around bright stars binned per $G_{\rm Gaia}$ magnitude. Finally, we validate those masks from visual inspection and comparison with the literature of galaxy number counts and angular two-point correlation functions. This version (Arcturus) supersedes the previous version (Sirius) used in the S16A internal and DR1 public releases. We publicly release the full masks and tools to flag objects in the entire footprint of the planned HSC-SSP observations at this address: ftp://obsftp.unige.ch/pub/coupon/brightStarMasks/HSC-SSP/.

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The Hyper Suprime-Cam Software Pipeline

In this paper, we describe the optical imaging data processing pipeline developed for the Subaru Telescope's Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope's Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high level processing steps that generate coadded images and science-ready catalogs as well as low-level detrending and image characterizations.

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Characterization and Photometric Performance of the Hyper Suprime-Cam Software Pipeline

The Subaru Strategic Program (SSP) is an ambitious multi-band survey using the Hyper Suprime-Cam (HSC) on the Subaru telescope. The Wide layer of the SSP is both wide and deep, reaching a detection limit of i~26.0 mag. At these depths, it is challenging to achieve accurate, unbiased, and consistent photometry across all five bands. The HSC data are reduced using a pipeline that builds on the prototype pipeline for the Large Synoptic Survey Telescope. We have developed a Python-based, flexible framework to inject synthetic galaxies into real HSC images called SynPipe. Here we explain the design and implementation of SynPipe and generate a sample of synthetic galaxies to examine the photometric performance of the HSC pipeline. For stars, we achieve 1% photometric precision at i~19.0 mag and 6% precision at i~25.0 in the i-band. For synthetic galaxies with single-Sersic profiles, forced CModel photometry achieves 13% photometric precision at i~20.0 mag and 18% precision at i~25.0 in the i-band. We show that both forced PSF and CModel photometry yield unbiased color estimates that are robust to seeing conditions. We identify several caveats that apply to the version of HSC pipeline used for the first public HSC data release (DR1) that need to be taking into consideration. First, the degree to which an object is blended with other objects impacts the overall photometric performance. This is especially true for point sources. Highly blended objects tend to have larger photometric uncertainties, systematically underestimated fluxes and slightly biased colors. Second, >20% of stars at 22.5< i < 25.0 mag can be misclassified as extended objects. Third, the current CModel algorithm tends to strongly underestimate the half-light radius and ellipticity of galaxy with i>21.5 mag.

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Clustering of quasars in a wide luminosity range at redshift 4 with Subaru Hyper Suprime-Cam wide field imaging

We examine the clustering of quasars over a wide luminosity range, by utilizing 901 quasars at $\overline{z}_{\rm phot}\sim3.8$ with $-24.73<M_{\rm 1450}<-22.23$ photometrically selected from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) S16A Wide2 date release and 342 more luminous quasars at $3.4<z_{\rm spec}<4.6$ having $-28.0<M_{\rm 1450}<-23.95$ from the Sloan Digital Sky Survey (SDSS) that fall in the HSC survey fields. We measure the bias factors of two quasar samples by evaluating the cross-correlation functions (CCFs) between the quasar samples and 25790 bright $z\sim4$ Lyman Break Galaxies (LBGs) in $M_{\rm 1450}<-21.25$ photometrically selected from the HSC dataset. Over an angular scale of \timeform{10.0"} to \timeform{1000.0"}, the bias factors are $5.93^{+1.34}_{-1.43}$ and $2.73^{+2.44}_{-2.55}$ for the low and high luminosity quasars, respectively, indicating no luminosity dependence of quasar clustering at $z\sim4$. It is noted that the bias factor of the luminous quasars estimated by the CCF is smaller than that estimated by the auto-correlation function (ACF) over a similar redshift range, especially on scales below \timeform{40.0"}. Moreover, the bias factor of the less-luminous quasars implies the minimal mass of their host dark matter halos (DMHs) is $0.3$-$2\times10^{12}h^{-1}M_{\odot}$, corresponding to a quasar duty cycle of $0.001$-$0.06$.

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The Quasar Luminosity Function at Redshift 4 with Hyper Suprime-Cam Wide Survey

We present the luminosity function of z=4 quasars based on the Hyper Suprime-Cam Subaru Strategic Program Wide layer imaging data in the g, r, i, z, and y bands covering 339.8 deg^2. From stellar objects, 1666 z~4 quasar candidates are selected by the g-dropout selection down to i=24.0 mag. Their photometric redshifts cover the redshift range between 3.6 and 4.3 with an average of 3.9. In combination with the quasar sample from the Sloan Digital Sky Survey in the same redshift range, the quasar luminosity function covering the wide luminosity range of M1450=-22 to -29 mag is constructed. It is well described by a double power-law model with a knee at M1450=-25.36+-0.13 mag and a flat faint-end slope with a power-law index of -1.30+-0.05. The knee and faint-end slope show no clear evidence of redshift evolution from those at z~2. The flat slope implies that the UV luminosity density of the quasar population is dominated by the quasars around the knee, and does not support the steeper faint-end slope at higher redshifts reported at z>5. If we convert the M1450 luminosity function to the hard X-ray 2-10keV luminosity function using the relation between UV and X-ray luminosity of quasars and its scatter, the number density of UV-selected quasars matches well with that of the X-ray-selected AGNs above the knee of the luminosity function. Below the knee, the UV-selected quasars show a deficiency compared to the hard X-ray luminosity function. The deficiency can be explained by the lack of obscured AGNs among the UV-selected quasars.

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Subaru high-z exploration of low-luminosity quasars (SHELLQs). I. Discovery of 15 quasars and bright galaxies at 5.7 < z < 6.9

We report the discovery of 15 quasars and bright galaxies at 5.7 < z < 6.9. This is the initial result from the Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs) project, which exploits the exquisite multiband imaging data produced by the Subaru Hyper Suprime-Cam (HSC) Strategic Program survey. The candidate selection is performed by combining several photometric approaches including a Bayesian probabilistic algorithm to reject stars and dwarfs. The spectroscopic identification was carried out with the Gran Telescopio Canarias and the Subaru Telescope for the first 80 deg2 of the survey footprint. The success rate of our photometric selection is quite high, approaching 100 % at the brighter magnitudes (zAB < 23.5 mag). Our selection also recovered all the known high-z quasars on the HSC images. Among the 15 discovered objects, six are likely quasars, while the other six with interstellar absorption lines and in some cases narrow emission lines are likely bright Lyman-break galaxies. The remaining three objects have weak continua and very strong and narrow Ly alpha lines, which may be excited by ultraviolet light from both young stars and quasars. These results indicate that we are starting to see the steep rise of the luminosity function of z > 6 galaxies, compared with that of quasars, at magnitudes fainter than M1450 ~ -22 mag or zAB ~24 mag. Follow-up studies of the discovered objects as well as further survey observations are ongoing.

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The LSST Data Management System

The Large Synoptic Survey Telescope (LSST) is a large-aperture, wide-field, ground-based survey system that will image the sky in six optical bands from 320 to 1050 nm, uniformly covering approximately $18,000$deg$^2$ of the sky over 800 times. The LSST is currently under construction on Cerro Pachón in Chile, and expected to enter operations in 2022. Once operational, the LSST will explore a wide range of astrophysical questions, from discovering "killer" asteroids to examining the nature of Dark Energy. The LSST will generate on average 15 TB of data per night, and will require a comprehensive Data Management system to reduce the raw data to scientifically useful catalogs and images with minimum human intervention. These reductions will result in a real-time alert stream, and eleven data releases over the 10-year duration of LSST operations. To enable this processing, the LSST project is developing a new, general-purpose, high-performance, scalable, well documented, open source data processing software stack for O/IR surveys. Prototypes of this stack are already capable of processing data from existing cameras (e.g., SDSS, DECam, MegaCam), and form the basis of the Hyper-Suprime Cam (HSC) Survey data reduction pipeline.

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Hyper-luminous Dust Obscured Galaxies discovered by the Hyper Suprime-Cam on Subaru and WISE

We present the photometric properties of a sample of infrared (IR) bright dust obscured galaxies (DOGs). Combining wide and deep optical images obtained with the Hyper Suprime-Cam (HSC) on the Subaru Telescope and all-sky mid-IR (MIR) images taken with Wide-Field Infrared Survey Explorer (WISE), we discovered 48 DOGs with $i - K_\mathrm{s} > 1.2$ and $i - [22] > 7.0$, where $i$, $K_\mathrm{s}$, and [22] represent AB magnitude in the $i$-band, $K_\mathrm{s}$-band, and 22 $μ$m, respectively, in the GAMA 14hr field ($\sim$ 9 deg$^2$). Among these objects, 31 ($\sim$ 65 %) show power-law spectral energy distributions (SEDs) in the near-IR (NIR) and MIR regime, while the remainder show a NIR bump in their SEDs. Assuming that the redshift distribution for our DOGs sample is Gaussian, with mean and sigma $z$ = 1.99 $\pm$ 0.45, we calculated their total IR luminosity using an empirical relation between 22 $μ$m luminosity and total IR luminosity. The average value of the total IR luminosity is (3.5 $\pm$ 1.1) $\times$ $10^{13}$ L$_{\odot}$, which classifies them as hyper-luminous infrared galaxies (HyLIRGs). We also derived the total IR luminosity function (LF) and IR luminosity density (LD) for a flux-limited subsample of 18 DOGs with 22 $μ$m flux greater than 3.0 mJy and with $i$-band magnitude brighter than 24 AB magnitude. The derived space density for this subsample is log $ϕ$ = -6.59 $\pm$ 0.11 [Mpc$^{-3}$]. The IR LF for DOGs including data obtained from the literature is well fitted by a double-power law. The derived lower limit for the IR LD for our sample is $ρ_{\mathrm{IR}}$ $\sim$ 3.8 $\times$ 10$^7$ [L$_{\odot}$ Mpc$^{-3}$] and its contributions to the total IR LD, IR LD of all ultra-luminous infrared galaxies (ULIRGs), and that of all DOGs are $>$ 3 %, $>$ 9 %, and $>$ 15 %, respectively.

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GalSim: The modular galaxy image simulation toolkit

GALSIM is a collaborative, open-source project aimed at providing an image simulation tool of enduring benefit to the astronomical community. It provides a software library for generating images of astronomical objects such as stars and galaxies in a variety of ways, efficiently handling image transformations and operations such as convolution and rendering at high precision. We describe the GALSIM software and its capabilities, including necessary theoretical background. We demonstrate that the performance of GALSIM meets the stringent requirements of high precision image analysis applications such as weak gravitational lensing, for current datasets and for the Stage IV dark energy surveys of the Large Synoptic Survey Telescope, ESA's Euclid mission, and NASA's WFIRST-AFTA mission. The GALSIM project repository is public and includes the full code history, all open and closed issues, installation instructions, documentation, and wiki pages (including a Frequently Asked Questions section). The GALSIM repository can be found at https://github.com/GalSim-developers/GalSim .

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Modeling Techniques for Measuring Galaxy Properties in Multi-Epoch Surveys

Data analysis methods have always been of critical importance for quantitative sciences. In astronomy, the increasing scale of current and future surveys is driving a trend towards a separation of the processes of low-level data reduction and higher-level scientific analysis. Algorithms and software responsible for the former are becoming increasingly complex, and at the same time more general - measurements will be used for a wide variety of scientific studies, and many of these cannot be anticipated in advance. On the other hand, increased sample sizes and the corresponding decrease in stochastic uncertainty puts greater importance on controlling systematic errors, which must happen for the most part at the lowest levels of data analysis. Astronomical measurement algorithms must improve in their handling of uncertainties as well, and hence must be designed with detailed knowledge of the requirements of different science goals. In this thesis, we advocate a Bayesian approach to survey data reduction as a whole, and focus specifically on the problem of modeling individual galaxies and stars. We present a Monte Carlo algorithm that can efficiently sample from the posterior probability for a flexible class of galaxy models, and propose a method for constructing and convolving these models using Gauss-Hermite ("shapelet") functions. These methods are designed to be efficient in a multi-epoch modeling ("multifit") sense, in which we compare a generative model to each exposure rather than combining the data from multiple exposures in advance. We also discuss how these methods are important for specific higher-level analyses - particularly weak gravitational lensing - as well as their interaction with the many other aspects of a survey reduction pipeline.

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Galaxy Modeling with Compound Elliptical Shapelets

Gauss-Hermite and Gauss-Laguerre ("shapelet") decompositions of images have become important tools in galaxy modeling, particularly for the purpose of extracting ellipticity and morphological information from astronomical data. However, the standard shapelet basis functions cannot compactly represent galaxies with high ellipticity or large Sersic index, and the resulting underfitting bias has been shown to present a serious challenge for weak-lensing methods based on shapelets. We present here a new convolution relation and a compound "multi-scale" shapelet basis to address these problems, and provide a proof-of-concept demonstration using a small sample of nearby galaxies.

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