arXiv subjects

Lee S. Kelvin

Publications and source records attributed to Lee S. Kelvin.

At least 19 recordsLinked to original sources

arXiv2026

Modeling of the diffuse background produced by the Vera C. Rubin Observatory M2 baffle scattered light

The Vera C. Rubin Observatory, with its unprecedented field of view and fast focal ratio, will survey the entire sky every 3.5 nights. This unique capacity requires dealing with off axis light that can produce stray light artefacts on the images. The secondary mirror (M2) baffle restricts the light that reaches the LSSTCam detector and it contributes to shaping the inner edge of the telescope optical pupil. This work studies the contribution to the background from the light scattered by the M2 baffle itself. The evanescence of this feature, together with the challenge of isolating it from the sky background, led to the necessity of performing in dome tests using a Collimated Beam Projector (CBP), normally used for calibration purposes. To complete the analysis, in addition to the in dome tests, an on sky observational campaign was conducted. This campaign employed both stellar targets and the Moon as illumination sources in order to determine the actual energy associated with the feature. The test data have been retro fitted thanks to the combination of ray tracing simulation, CBP and on sky data to infer the intensity and spatial distribution of the background scattered light within the different LSSTCam filters. We quantified the on sky impact of scattered light from the M2 baffle, both for light coming from bright and red stars and from the Moon. We also developed an approximate relation to transform the in dome measurements into predictions of on sky behavior. This transformation was achieved by comparing the illumination footprint produced by an off axis star with that generated by the CBP and by mapping the stellar Spectral Energy Distribution (SED) onto the CBP's set of discrete wavelengths. Finally, we extrapolated the scattered light behavior of the Moon to stellar sources, in order to build a compplete description of the M2 baffle contribution over the full range of magnitudes.

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arXiv2026

In Situ Measurements of the Reflectances of the LSSTCam Optics and Assessing the Impact of Optical Ghosts

Optical ghosts are image artifacts caused by successive reflections of light between optical surfaces such as lenses, filters, and detectors. These artifacts are unavoidable due to the nonzero reflectances of optical elements and are a major source of contamination for low-surface-brightness science. We use optical ray tracing simulations tuned to observations from LSST Commissioning to quantify the impact of optical ghosts on the LSST data. In particular, we find that ~0.57% of the LSSTCam focal plane is impacted by optical ghosts when averaged across all bands. We also use data from the Collimated Beam Projector to measure the reflectances of various optical elements, generally confirming estimates of ~2% from the systems engineering throughput predictions.

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arXiv2026

Investigation and Mitigation of a Prominent Off-Axis Stray Light Path in Rubin Observatory Commissioning

The "scratched tape" stray light feature is the most prominent and prevalent stray light artifact identified during the commissioning of the Vera C. Rubin Observatory. The scratched tape feature originates when light from large off-axis angles (~20 deg) passes between the mid-level and center-section light baffles, reflects off the primary mirror, and illuminates the LSST Camera focal plane. This scenario represented an unobstructed stray light path to the sky during Rubin commissioning due to delays in the integration of the dome slit light-wind screen. This document describes the identification, modeling, characterization, and mitigation of the scratched tape stray light artifact.

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arXiv2025

The Merian Survey: A Statistical Census of Bright Satellites of Milky Way Analogs

We present a statistical census of bright, star-forming satellite galaxies around Milky Way (MW) analogs using the first data release of the Merian Survey. Our sample consists of 393 MW analogs with stellar masses $10^{10.5} < M_{\star, \rm host} < 10^{10.9} M_\odot$ at redshifts $0.07 < z < 0.09$, all central galaxies of their own dark matter halos. Using photometric selection -- including magnitude, color, angular size, photometric redshift, and size-mass cuts -- we identify 793 satellite candidates around these 393 hosts. Our selection leverages two medium-band filters targeting H$α$ and [O \textsc{iii}] emission, enabling a nearly complete sample of star-forming, Magellanic Clouds-like satellites with $M_{\star, \rm sat} \gtrsim 10^{8} M_\odot$. We find that $\sim80\%$ of hosts have 0-3 massive satellites, and $13\pm4\%$ have two satellites (similar to the MW). Satellite abundance correlates with total stellar mass, and we provide significantly improved statistics for the most massive satellites at $\log_{10}[M_{\star, \rm sat}/M_{\odot}] \gtrsim 10$. The completeness-corrected radial distribution is less centrally concentrated than an NFW profile. In contrast, the Milky Way satellites are more centrally concentrated than the 50\% richest Merian systems, but are broadly consistent with the 50\% most centrally concentrated Merian systems. Our results highlight the power of medium-band photometry for satellite identification and provide a key benchmark for studying satellite quenching, environmental effects, and hierarchical galaxy formation.

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arXiv2025

Enabling Early Transient Discovery in LSST via Difference Imaging with DECam

We present SLIDE, a pipeline that enables transient discovery in data from the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), using archival images from the Dark Energy Camera (DECam) as templates for difference imaging. We apply this pipeline to the recently released Data Preview 1 (DP1; the first public release of Rubin commissioning data) and search for transients in the resulting difference images. The image subtraction, photometry extraction, and transient detection are all performed on the Rubin Science Platform. We demonstrate that SLIDE effectively extracts clean photometry by circumventing poor or missing LSST templates. We identified 29 previously unreported transients, 12 of which would not have been detected based on the DP1 DiaObject catalog. SLIDE will be especially useful for transient analysis in the early years of LSST, when template coverage will be largely incomplete or when templates may be contaminated by transients present at the time of acquisition. We present multiband light curves for a sample of known transients, along with new transient candidates identified through our search. Finally, we discuss the prospects of applying this pipeline during the main LSST survey. Our pipeline is broadly applicable and will support studies of all transients with slowly evolving phases.

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arXiv2025

Identification and photometric classification of extragalactic transients in the Vera C. Rubin Observatory's Data Preview 1

The Vera C. Rubin Observatory will soon survey the southern sky, delivering a depth and sky coverage that is unprecedented in time domain astronomy. As part of commissioning, Data Preview 1 (DP1) has been released. It comprises a LSSTComCam observing campaign between November and December 2024 with multi-band imaging of seven fields, covering roughly 0.4 square degrees each, providing a first glimpse into the data products that will become available once the Legacy Survey of Space and Time begins. In this work, we search three fields for extragalactic transients. We identify eight new likely supernovae, and three known ones from a sample of 369,644 difference image analysis objects. Photometric classification using Superphot+ assigns sub-classes with >95% confidence to only one SN Ia and one SN II in this sample. Our findings are in agreement with supernova detection rate predictions of $15\pm4$ supernovae from simulations using simsurvey. The supernova detection rate in the data is possibly affected by the lack of suitable templates. Nevertheless, this work demonstrates the quality of the data products delivered in DP1 and indicates that the Rubin Observatory's Legacy Survey of Space and Time (LSST) is well placed to fulfill its discovery potential in time domain astronomy.

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arXiv2024

Bright Star Subtraction Pipeline for LSST: Phase one report

We present the phase one report of the Bright Star Subtraction (BSS) pipeline for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). This pipeline is designed to create an extended PSF model by utilizing observed stars, followed by subtracting this model from the bright stars present in LSST data. Running the pipeline on Hyper Suprime-Cam (HSC) data shows a correlation between the shape of the extended PSF model and the position of the detector within the camera's focal plane. Specifically, detectors positioned closer to the focal plane's edge exhibit reduced circular symmetry in the extended PSF model. To mitigate this effect, we present an algorithm that enables users to account for the location dependency of the model. Our analysis also indicates that the choice of normalization annulus is crucial for modeling the extended PSF. Smaller annuli can exclude stars due to overlap with saturated regions, while larger annuli may compromise data quality because of lower signal-to-noise ratios. This makes finding the optimal annulus size a challenging but essential task for the BSS pipeline. Applying the BSS pipeline to HSC exposures allows for the subtraction of, on average, 100 to 700 stars brighter than 12th magnitude measured in g-band across a full exposure, with a full HSC exposure comprising ~100 detectors.

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arXiv2024

Bright Star Subtraction Pipeline for LSST: Progress Review

We present the Bright Star Subtraction (BSS) pipeline for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). This pipeline generates an extended PSF model using observed stars and subtracts the model from the bright stars in LSST data. When testing the pipeline on Hyper Suprime-Cam (HSC) data, we find that the shape of the extended PSF model depends on the location of the detector on the camera's focal plane. The closer a detector is to the edge of the focal plane, the less the extended PSF model is circularly symmetric. We introduce an algorithm that allows the user to consider the location dependency of the model.

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arXiv2024

The Merian Survey: Design, Construction, and Characterization of a Filter Set Optimized to Find Dwarf Galaxies and Measure their Dark Matter Halo Properties with Weak Lensing

The Merian survey is mapping $\sim$ 850 degrees$^2$ of the Hyper Suprime-Cam Strategic Survey Program (HSC-SSP) wide layer with two medium-band filters on the 4-meter Victor M. Blanco telescope at the Cerro Tololo Inter-American Observatory, with the goal of carrying the first high signal-to-noise (S/N) measurements of weak gravitational lensing around dwarf galaxies. This paper presents the design of the Merian filter set: N708 ($λ_c = 7080 \unicode{x212B}$, $Δλ= 275\unicode{x212B}$) and N540 ($λ_c = 5400\unicode{x212B}$, $Δλ= 210\unicode{x212B}$). The central wavelengths and filter widths of N708 and N540 were designed to detect the $\rm Hα$ and $\rm [OIII]$ emission lines of galaxies in the mass range $8<\rm \log M_*/M_\odot<9$ by comparing Merian fluxes with HSC broad-band fluxes. Our filter design takes into account the weak lensing S/N and photometric redshift performance. Our simulations predict that Merian will yield a sample of $\sim$ 85,000 star-forming dwarf galaxies with a photometric redshift accuracy of $σ_{Δz/(1+z)}\sim 0.01$ and an outlier fraction of $η=2.8\%$ over the redshift range $0.058<z<0.10$. With 60 full nights on the Blanco/Dark Energy Camera (DECam), the Merian survey is predicted to measure the average weak lensing profile around dwarf galaxies with lensing $\rm S/N \sim 32$ within $r<0.5$ Mpc and lensing $\rm S/N \sim 90$ within $r<1.0$ Mpc. This unprecedented sample of star-forming dwarf galaxies will allow for studies of the interplay between dark matter and stellar feedback and their roles in the evolution of dwarf galaxies.

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arXiv2023

Sky Subtraction in an Era of Low Surface Brightness Astronomy

The Vera C. Rubin Observatory Wide-Fast Deep (WFD) sky survey will reach unprecedented surface brightness depths over tens of thousands of square degrees. Surface brightness photometry has traditionally been a challenge. Current algorithms which combine object detection with sky estimation systematically over-subtract the sky, biasing surface brightness measurements at the faint end and destroying or severely compromising low surface brightness light. While it has recently been shown that properly accounting for undetected faint galaxies and the wings of brighter objects can in principle recover a more accurate sky estimate, this has not yet been demonstrated in practice. Obtaining a consistent spatially smooth underlying sky estimate is particularly challenging in the presence of representative distributions of bright and faint objects. In this paper we use simulations of crowded and uncrowded fields designed to mimic Hyper Suprime-Cam data to perform a series of tests on the accuracy of the recovered sky. Dependence on field density, galaxy type and limiting flux for detection are all considered. Several photometry packages are utilised: Source Extractor, Gnuastro, and the LSST Science Pipelines. Each is configured in various modes, and their performance at extreme low surface brightness analysed. We find that the combination of the Source Extractor software package with novel source model masking techniques consistently produce extremely faint output sky estimates, by up to an order of magnitude, as well as returning high fidelity output science catalogues.

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arXiv2022

Galaxy And Mass Assembly: Galaxy Morphology in the Green Valley, Prominent rings and looser Spiral Arms

Galaxies broadly fall into two categories: star-forming (blue) galaxies and quiescent (red) galaxies. In between, one finds the less populated ``green valley". Some of these galaxies are suspected to be in the process of ceasing their star-formation through a gradual exhaustion of gas supply or already dead and are experiencing a rejuvenation of star-formation through fuel injection. We use the Galaxy And Mass Assembly database and the Galaxy Zoo citizen science morphological estimates to compare the morphology of galaxies in the green valley against those in the red sequence and blue cloud. Our goal is to examine the structural differences within galaxies that fall in the green valley, and what brings them there. Previous results found disc features such as rings and lenses are more prominently represented in the green valley population. We revisit this with a similar sized data set of galaxies with morphology labels provided by the Galaxy Zoo for the GAMA fields based on new KiDS images. Our aim is to compare qualitatively the results from expert classification to that of citizen science. We observe that ring structures are indeed found more commonly in green valley galaxies compared to their red and blue counterparts. We suggest that ring structures are a consequence of disc galaxies in the green valley actively exhibiting characteristics of fading discs and evolving disc morphology of galaxies. We note that the progression from blue to red correlates with loosening spiral arm structure.

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arXiv2022

Galaxy And Mass Assembly (GAMA): Bulge-disk decomposition of KiDS data in the nearby universe

We derive single Sérsic fits and bulge-disk decompositions for 13096 galaxies at redshifts z < 0.08 in the GAMA II equatorial survey regions in the Kilo-Degree Survey (KiDS) g, r and i bands. The surface brightness fitting is performed using the Bayesian two-dimensional profile fitting code ProFit. We fit three models to each galaxy in each band independently with a fully automated Markov-chain Monte Carlo analysis: a single Sérsic model, a Sérsic plus exponential and a point source plus exponential. After fitting the galaxies, we perform model selection and flag galaxies for which none of our models are appropriate (mainly mergers/Irregular galaxies). The fit quality is assessed by visual inspections, comparison to previous works, comparison of independent fits of galaxies in the overlap regions between KiDS tiles and bespoke simulations. The latter two are also used for a detailed investigation of systematic error sources. We find that our fit results are robust across various galaxy types and image qualities with minimal biases. Errors given by the MCMC underestimate the true errors typically by factors 2-3. Automated model selection criteria are accurate to > 90 % as calibrated by visual inspection of a subsample of galaxies. We also present g-r component colours and the corresponding colour-magnitude diagram, consistent with previous works despite our increased fit flexibility. Such reliable structural parameters for the components of a diverse sample of galaxies across multiple bands will be integral to various studies of galaxy properties and evolution. All results are integrated into the GAMA database.

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arXiv2022

Faro: A framework for measuring the scientific performance of petascale Rubin Observatory data products

The Vera C. Rubin Observatory will advance many areas of astronomy over the next decade with its unique wide-fast-deep multi-color imaging survey, the Legacy Survey of Space and Time (LSST). The LSST will produce approximately 20TB of raw data per night, which will be automatically processed by the LSST Science Pipelines to generate science-ready data products -- processed images, catalogs and alerts. To ensure that these data products enable transformative science with LSST, stringent requirements have been placed on their quality and scientific fidelity, for example on image quality and depth, astrometric and photometric performance, and object recovery completeness. In this paper we introduce faro, a framework for automatically and efficiently computing scientific performance metrics on the LSST data products for units of data of varying granularity, ranging from single-detector to full-survey summary statistics. By measuring and monitoring metrics, we are able to evaluate trends in algorithmic performance and conduct regression testing during development, compare the performance of one algorithm against another, and verify that the LSST data products will meet performance requirements by comparing to specifications. We present initial results using faro to characterize the performance of the data products produced on simulated and precursor data sets, and discuss plans to use faro to verify the performance of the LSST commissioning data products.

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arXiv2022

Galapagos-2/Galfitm/GAMA -- multi-wavelength measurement of galaxy structure: separating the properties of spheroid and disk components in modern surveys

We present the capabilities of Galapagos--2 and Galfitm in the context of fitting 2-component profiles to galaxies, on the way to providing complete multi-band, multi-component fitting of large samples of galaxies in future surveys. We release both the code and the fit results to 234,239 objects from the DR3 of the Gama survey, a sample significantly deeper than previous works. We use stringent tests on both simulated and real data, as well as comparison to public catalogues to evaluate the advantages of using multi-band over single-band data. We show that multi-band fitting using Galfitm provides significant advantages when trying to decompose galaxies into their individual constituents, as more data are being used, by effectively being able to use the colour information buried in the individual exposures to its advantage. Using simulated data, we find that multi-band fitting significantly reduces the deviations from real parameter values, allows component sizes and Sérsic indices to be recovered more accurately, and, by design, constrains the band-to-band variations of these parameters to more physical values. On both simulated and real data, we confirm that the SEDs of the 2 main components can be recovered to fainter magnitudes compared to using single-band fitting, which tends to recover disks and bulges to - on average - have identical SEDs when the galaxies become too faint, instead of the different SEDs they truly have. By comparing our results to those provided by other fitting codes, we confirm that they agree in general, but measurement errors can be significantly reduced by using the multi-band tools developed by the MegaMorph project. We conclude that the multi-band fitting employed by Galapagos-2 and Galfitm significantly improves the accuracy of structural galaxy parameters and enables much larger samples to be be used in a scientific analysis.

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arXiv2022

Galaxy And Mass Assembly (GAMA): Self-Organizing Map Application on Nearby Galaxies

Galaxy populations show bimodality in a variety of properties: stellar mass, colour, specific star-formation rate, size, and Sérsic index. These parameters are our feature space. We use an existing sample of 7556 galaxies from the Galaxy and Mass Assembly (GAMA) survey, represented using five features and the K-means clustering technique, showed that the bimodalities are the manifestation of a more complex population structure, represented by between 2 and 6 clusters. Here we use Self Organizing Maps (SOM), an unsupervised learning technique which can be used to visualize similarity in a higher dimensional space using a 2D representation, to map these five-dimensional clusters in the feature space onto two-dimensional projections. To further analyze these clusters, using the SOM information, we agree with previous results that the sub-populations found in the feature space can be reasonably mapped onto three or five clusters. We explore where the "green valley" galaxies are mapped onto the SOM, indicating multiple interstitial populations within the green valley population. Finally, we use the projection of the SOM to verify whether morphological information provided by GalaxyZoo users, for example, if features are visible, can be mapped onto the SOM-generated map. Voting on whether galaxies are smooth, likely ellipticals, or "featured" can reasonably be separated but smaller morphological features (bar, spiral arms) can not. SOMs promise to be a useful tool to map and identify instructive sub-populations in multidimensional galaxy survey feature space, provided they are large enough.

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arXiv2022

Galaxy And Mass Assembly (GAMA): Data Release 4 and the z < 0.1 total and z < 0.08 morphological galaxy stellar mass functions

In Galaxy And Mass Assembly Data Release 4 (GAMA DR4), we make available our full spectroscopic redshift sample. This includes 248682 galaxy spectra, and, in combination with earlier surveys, results in 330542 redshifts across five sky regions covering ~250deg^2. The redshift density, is the highest available over such a sustained area, has exceptionally high completeness (95 per cent to r_KIDS=19.65mag), and is well suited for the study of galaxy mergers, galaxy groups, and the low redshift (z<0.25) galaxy population. DR4 includes 32 value-added tables or Data Management Units (DMUs) that provide a number of measured and derived data products including GALEX, ESO KiDS, ESO VIKING, WISE and Herschel Space Observatory imaging. Within this release, we provide visual morphologies for 15330 galaxies to z<0.08, photometric redshift estimates for all 18million objects to r_KIDS~25mag, and stellar velocity dispersions for 111830 galaxies. We conclude by deriving the total galaxy stellar mass function (GSMF) and its sub-division by morphological class (elliptical, compact-bulge and disc, diffuse-bulge and disc, and disc only). This extends our previous measurement of the total GSMF down to 10^6.75 M_sol h^-2_70 and we find a total stellar mass density of rho_*=(2.97+/-0.04)x10^8 M_sol h_70 Mpc^-3 or Omega_*=(2.17+/-0.03)x10^-3 h^-1_70. We conclude that at z<0.1, the Universe has converted 4.9+/-0.1 per cent of the baryonic mass implied by Big Bang Nucleosynthesis into stars that are gravitationally bound within the galaxy population.

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arXiv2022

Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies

We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r=23.6 vs. r=22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314,000 galaxies. 140,000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314,000 galaxies. When measured against confident volunteer classifications, the networks are approximately 99% accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve.

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arXiv2021

The Growth of Intracluster Light in XCS-HSC Galaxy Clusters from $0.1 < z < 0.5$

We estimate the Intracluster Light (ICL) component within a sample of 18 clusters detected in XMM Cluster Survey (XCS) data using deep ($\sim$ 26.8 mag) Hyper Suprime Cam Subaru Strategic Program DR1 (HSC-SSP DR1) $i$-band data. We apply a rest-frame $μ_{B} = 25 \ \mathrm{mag/arcsec^{2}}$ isophotal threshold to our clusters, below which we define light as the ICL within an aperture of $R_{X,500}$ (X-ray estimate of $R_{500}$) centered on the Brightest Cluster Galaxy (BCG). After applying careful masking and corrections for flux losses from background subtraction, we recover $\sim$20% of the ICL flux, approximately four times our estimate of the typical background at the same isophotal level ($\sim$ 5%). We find that the ICL makes up about $\sim$ 24% of the total cluster stellar mass on average ($\sim$ 41% including the flux contained in the BCG within 50 kpc); this value is well-matched with other observational studies and semi-analytic/numerical simulations, but is significantly smaller than results from recent hydrodynamical simulations (even when measured in an observationally consistent way). We find no evidence for any links between the amount of ICL flux with cluster mass, but find a growth rate of $2-4$ for the ICL between $0.1 < z < 0.5$. We conclude that the ICL is the dominant evolutionary component of stellar mass in clusters from $z \sim 1$. Our work highlights the need for a consistent approach when measuring ICL alongside the need for deeper imaging, in order to unambiguously measure the ICL across as broad a redshift range as possible (e.g. 10-year stacked imaging from the Vera C. Rubin Observatory).

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