arXiv subjects

Ilija Medan

Publications and source records attributed to Ilija Medan.

At least 19 recordsLinked to original sources

arXiv2026

BOSS-CLAM: Utilizing a Constrained Linear Absorption Model to Infer Stellar Parameters from BOSS Spectra

Large spectroscopic surveys require robust pipelines capable of inferring stellar parameters over a wide range of the Hertzsprung-Russell (HR) diagram from data of varying quality. SDSS-V is one such survey, where the data from the lower-resolution, optical BOSS spectrograph will provide a large dataset covering a wide range of Galactic stellar populations. To better analyze these data, we present BOSS-CLAM, a generative, forward modeling pipeline for inferring effective temperature ($T_\mathrm{eff}$), surface gravity ($\log g$), metallicity ($[\mathrm{Fe/H}]$), and $α-$abundance ($[α/\mathrm{M}]$) from continuum-normalized BOSS spectra. BOSS-CLAM maps stellar labels to Non-negative Matrix Factorization (NMF) basis vector weights via a polynomial mapping jointly optimized with the spectral decomposition, which provides a more flexible framework for working with the lower-resolution BOSS data. Additionally, training labels are drawn from four complementary sources (ASPCAP, BOSS-MINESweeper, wide binaries, and a hot star validation sample), which enables coverage from cool M dwarfs through hot OB stars, and across a wide range of metallicity. We infer parameters for 1,708,214 BOSS spectra, with a recommended clean catalog of 915,514 sources. Validation against open and globular clusters demonstrates homogeneous, accurate abundances across a wide range of metallicity. Wide binary tests yield abundance uncertainties of $σ_{[\mathrm{Fe/H}]} \approx 0.15$ dex and $σ_{[α/\mathrm{M}]} \approx 0.06$ dex at SNR = 10. Finally, we demonstrate that the BOSS-CLAM catalog recovers known chemical structure of the Milky Way disk and is well-suited for Galactic archaeology, chemical tagging, and stellar population modeling. The pipeline, trained model, and catalog are publicly released as part of SDSS-V DR20.

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arXiv2026

The Open Cluster Chemical Abundances and Mapping Survey XI. First Gradients from SDSS/MWM BOSS Determined Clusters

The Milky Way Mapper program in the fifth generation of the Sloan Digital Sky Survey (SDSS-V/MWM) has observed millions of stars, thousands of them in open clusters. The Open Cluster Chemical Abundances and Mapping (OCCAM) survey continues to create comprehensive datasets of open clusters and their members in order to constrain Galactic parameters. This eleventh contribution from the OCCAM survey is the first to use stellar parameters from stars observed with the optical Baryon Oscillation Spectroscopic Survey (BOSS) spectrograph to determine cluster membership. We use data from SDSS-V/MWM's 20th Data Release (DR20) and curate a sample of 1883 stars in 111 open clusters, including 95 not in previous OCCAM samples based on infrared data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectrograph. The sample includes 16 clusters with stars observed using both the BOSS and APOGEE spectrographs, and we find consistent agreement in measurements of both [Fe/H] and [$α/M$]. The BOSS sample includes the majority of the clusters at young ages (Age $< 150$ Myr) that complement the APOGEE sample of primarily older clusters. We use the combined BOSS+APOGEE OCCAM sample to constrain the radial metallicity gradient with respect to $R_{guide}$ ($-0.079 \pm 0.005 \text{ dex kpc}^{-1}$) and $R_{gc}$ ($-0.082 \pm 0.006 \text{ dex kpc}^{-1}$), which agree well with results from previous OCCAM papers using only APOGEE data. Finally, the inclusion of the primarily young BOSS clusters has not changed that the OCCAM open cluster sample indicates no significant evolution of this gradient in different mono-age populations.

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arXiv2026

A Test of FeH Line Parameters using DR19 APOGEE spectra of Benchmark M Dwarfs

Recent studies have suggested a mismatch of up to 0.20 dex between iron abundances derived from Fe I and FeH lines in the H-band spectra of M dwarfs, and in this work we investigate the nature of this possible offset. We analyze near-infrared H-band APOGEE spectra of stars in 18 binaries composed of a G-dwarf primary and an M-dwarf secondary, together with four M-dwarf stars having measured angular diameters from the literature, and six M-dwarf members of the Hyades and Coma Berenices open clusters. These three families of benchmarks were used to evaluate the FeH line list and check for possible systematic uncertainties in the FeH $gf$-values. Our tests used 1-D LTE plane-parallel model atmospheres, a radiative transfer code, and the baseline APOGEE spectral line list to derive metallicities for the binary G-dwarf primaries using Fe I lines, while stellar parameters and metallicities for the M dwarfs used both FeH and Fe I lines. The mean metallicity obtained for the Hyades M-dwarfs was $\langle$[Fe/H]$\rangle$=+0.08$\pm$0.04, and for Coma Berenices $\langle$[Fe/H]$\rangle$=+0.02$\pm$0.08. The metallicities of the G- and M-dwarfs in binary systems showed excellent agreement (0.06 dex), and the mean metallicities for the open clusters were also consistent with literature values from high-resolution optical analyses. We investigated the consistency between the spectroscopic and interferometric $T_{\rm eff}$ scales, finding agreement within the uncertainties. Forcing full agreement between the spectroscopic and interferometric $T_{\rm eff}$ scales resulted in a poorer match for the metallicities in the binaries and the open clusters. We conclude that the best overall concordance is obtained when no adjustments are made to the FeH $gf$-values, which are based on the Hargreaves et al. (2010) line list.

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arXiv2026

A Probabilistic Framework for Population Studies of the Solar Neighborhood: Application to SDSS-V and Gaia

Studies of the Solar Neighborhood require spectroscopic follow-up of stars identified in astrometric surveys to fully characterize their physical properties. The SDSS-V Solar Neighborhood Census (SNC) is a dedicated program to observe stars within 100~pc. However, due to competing observing programs and fiber assignment constraints, the resulting sample carries severe and complex selection effects. A framework is presented for characterizing the selection function of the SDSS-V SNC relative to the Gaia Catalog of Nearby Stars (GCNS), along with a forward modeling method to infer the properties of stellar subpopulations across the GCNS-defined 100 pc sample. The selection function is based on a method that models the selection probability as a function of sky position, Gaia G magnitude, and BP-RP. The resulting detection probabilities faithfully reproduce the known survey planning logic. This work further introduces the concept of a "subpopulation probability" -- a grid of posterior estimates across the Hertzsprung-Russell (HR) diagram representing the likelihood that a GCNS member belongs to a given SDSS-V defined subpopulation. The framework is validated with a mock dataset and its scientific utility is demonstrated through two applications using data from the Data Release 19: mapping H$α$ emission across the HR diagram and measuring the variation of stellar density with mass and metallicity. These results illustrate how statistically robust population studies can be conducted with an incomplete spectroscopic survey when the selection function is well characterized. The code is made publicly available with this work, which will serve as an important tool for future studies.

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arXiv2026

Probabilistic neural network approach to determining parameters of eclipsing binaries

Eclipsing binaries provide one of the most direct mechanisms for measuring stellar properties such as mass and radius, but historically, determining these properties has been non-trivial and computationally prohibitive. As such, only a small fraction of all eclipsing binaries for which data have been available have been fully characterized. To improve computational efficiency, we construct an uncertainty-aware neural network which can ingest phase-folded light curves in any of 50 commonly used passbands, combined with phase-folded radial velocity measurements for both primary and secondary, as well as fluxes across the spectral energy distribution to predict stellar and orbital parameters of eclipsing binaries. The model was trained to be agnostic to the presence of third light, spots (both cool and hot), and incomplete data. As the model is operating in a probabilistic framework, it is also capable of outputting uncertainties in all of the parameters. The model was trained on synthetic data, and applied to a set of $\sim$200 previously solved real eclipsing binaries to demonstrate its performance. The model is capable of determining masses and radii of eclipsing binaries with precision of $\lesssim$20\% and $T_{\rm eff}$ with precision of $\sim$500 K in only a fraction of the time it takes the more traditional solvers. Although the resulting uncertainties are larger than what is possible to produce using more boutique analysis of individual stars, in the era of large photometric surveys, this approach allows to identify the most interesting systems, and it provides a starting point of the distributions in all of the parameters that these solvers could improve upon.

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arXiv2026

21,864 Unresolved, Low-mass Binaries Identified via their Overluminosity in \textit{Gaia} DR3 and a Catalog of 347,440 Systems within 100 pc of the Sun

The fundamental parameters of a low-mass star can potentially be determined from its photometry and astrometry. This is complicated by the fact that 10-20 percent of low-mass stars are predicted to be equal-mass binaries. These unresolved systems appear more luminous compared to single stars with the same fundamental parameters. We present a method to differentiate binary stars from single-star main sequence K and M dwarfs using their \textit{Gaia} DR3 XP spectra. We assemble a training set of stars which have pristine astrometry and photometry, are located within 100pc of the Sun, and exclude stars with \textit{Gaia} DR3 flags suggesting they may be unequal mass systems, thereby leaving stars that are predominantly either single- or equal-mass binaries. We then iteratively train Random Forest Regression (RFR) models to predict absolute magnitude and color given the RP spectral coefficients of a star. After each model, we remove the stars that have absolute magnitudes significantly brighter than their predicted values. This method converges on a model trained only on single stars. We then use this model to identify the ``overluminous'' K and M stars in \textit{Gaia} DR3 within 100 parsecs, with some quality cuts. We find that $\sim13\%$ of the sample is significantly overluminous and assume these to be unresolved binaries. We aggregate several multiplicity surveys across different projected separations and incorporate our overluminous binaries to create a general \textit{Catalog of Systems} within 100 pc. We use this \textit{Catalog} to provide lower limits on the multiplicity fraction for stars between $0.1$ and $0.7~M_{\odot}$.

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arXiv2026

Variations in the Milky Way's Stellar Mass Function at [Fe/H] < -1

We present the first determination of the Galactic stellar mass function (MF) for low-mass stars (0.2-0.5 M_sun) at metallicities [Fe/H] < -1. A sample of ~53,000 stars was selected as metal-poor on the basis of both their halo-like orbits and their spectroscopic [Fe/H] from Gaia DR3 BP/RP (XP) spectra. These metallicity estimates for low-mass stars were enabled by calibrating Gaia XP spectra with stellar parameters from SDSS-V. For -1.5 < [Fe/H] < -1, we find that the MF below 0.5 M_sun exhibits a "bottom-heavy" power-law slope of alpha ~ -1.6. We tentatively find that at even lower metallicities, the MF becomes very bottom-light, with a near-flat power-law slope of alpha ~ 0 that implies a severe deficit of low-mass stars. This metallicity-dependent variation is insensitive to the adopted stellar evolution model. These results show that the Galactic low-mass MF is not universal, with variations in the metal-poor regime. A further calibration of XP metallicities in the regime of M < 0.5 M_sun and [Fe/H] < -1.5 will be essential to verify these tentative low-metallicity trends.

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arXiv2025

Stellar Parameters of BOSS M dwarfs in SDSS-V DR19

We utilized the Stellar LAbel Machine (SLAM), a data-driven model based on Support Vector Regression, to derive stellar parameters ([Fe/H], $T_{\rm eff}$, and $\log{g}$) for SDSS-V M dwarfs using low-resolution optical spectra (R$\sim$2000) obtained with the BOSS spectrographs. These parameters are calibrated using LAMOST F, G or K dwarf companions ([Fe/H]), and APOGEE Net ($T_{\rm eff}$ and $\log{g}$), respectively. Comparisons of SLAM predicted [Fe/H] values between two components of M+M dwarfs wide binaries show no bias but with a scatter of 0.11 dex. Further comparisons with two other works, which also calibrated the [Fe/H] of M dwarfs by using the F/G/K companions, reveal biases of -0.06$\pm$0.16 dex and 0.02$\pm$0.14 dex, respectively. The SLAM-derived effective temperatures agree well with the temperature which is calibrated by using interferometric angular diameters (bias: -27$\pm$92 K) and those of the LAMOST (bias: -34$\pm$65 K), but are systematically lower than those from an empirical relationship between the color index and $T_{\rm eff}$ by 146$\pm$45 K. The SLAM surface gravity aligns well with those of LAMOST (bias: -0.01$\pm$0.07 dex) and those derived from the stellar mass and radius (bias: -0.04$\pm$0.09 dex). Finally, we investigated a bias in [Fe/H] between SLAM and APOGEE ASPCAP. It depends on ASPCAP's [Fe/H] and $T_{\rm eff}$, we provide an equation to correct the ASPCAP metallicities.

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arXiv2025

robostrategy: Field and Target Assignment Optimization in the Sloan Digital Sky Survey V

We present an algorithmic method for efficiently planning a long-term, large-scale multi-object spectroscopy program. The Sloan Digital Sky Survey V (SDSS-V) Focal Plane System performs multi-object spectroscopy using 500 robotic positioners to place fibers feeding optical and infrared spectrographs across a wide field. SDSS-V uses this system to observe targets throughout the year at two observatories in support of the science goals of its Milky Way Mapper and Black Hole Mapper programs. These science goals require observations of objects over time with preferred temporal spacinges (referred to as "cadences"), which can differ from object to object even in the same area of sky. robostrategy is the software we use to construct our planned observations so that they can best achieve the desired goals given the time available as a function of sky brightness and local sidereal time, and to assign fibers to targets during specific observations. We use linear programming techniques to seek optimal allocations of time under the constraints given. We present the methods and example results obtained with this software.

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arXiv2025

The Importance of Standardizing Spectra in the Era of Large Spectroscopic Surveys: A Case Study of M Dwarfs in SDSS-V

SDSS-V will obtain 100,000s of medium-resolution, optical spectra of M dwarfs with the BOSS instrument. M dwarfs have complex atmospheres, and their spectra contain many wide and dense, overlapping molecular features, so determining accurate stellar parameters by fitting models has been difficult. To circumvent this, other surveys have employed machine learning methods to transfer measurements of stellar parameters from high-resolution spectra to their medium-resolution counterparts. These methods provide large catalogs of stellar parameters but, if not addressed properly, are plagued by biases which are, in part, due to the normalization of the spectra. Typical spectral normalization removes the continuum but preserves the relative depths of the absorption features, but optical M dwarf spectra are almost entirely made up of molecular absorption, which makes this difficult. Here, we develop a standardization method that instead defines a pseudo-continuum. We use the spectrum's alpha shape to find the points which lie between the absorption features and apply local polynomial regression to find this pseudo-continuum. To tune the hyperparameters of this method, we create BOSS-like spectra from BT-NextGen models to replicate instrumental, signal-to-noise, and reddening effects. We find that in both this generated set and a validation set of the SDSS-V data, our method performs better than alternative standardizations by producing spectra that are both more uniform for M dwarfs with similar stellar parameters and more easily distinguished compared to M dwarfs of differing parameters. These results from our method will be crucial for better determining stellar parameters of M dwarfs using generative models.

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arXiv2025

Procedures for Constraining Robotic Fiber Positioning for Highly Multiplexed Spectroscopic Surveys: The Case of FPS for SDSS-V

One crucial aspect of planning any large scale astronomical survey is constructing an observing strategy that maximizes reduced data quality. This is especially important for surveys that are rather heterogeneous and broad-ranging in their science goals. The Sloan Digital Sky Survey V (SDSS-V), which now utilizes the Focal Plane System (FPS) to robotically place fibers that feed the spectrographs, certainly meets these criteria. The addition of the FPS facilities an increase in survey efficiency, number of targets and target diversity, but also means the positions of fibers must be constrained to allow for simultaneous observations of sometimes competing programs. The constraints on the positions of the fibers are clearly driven by properties of the science targets e.g., the type of target, brightness of the target, position of the target relative to others in the field, etc. The parameters used to describe these constraints will also depend on the intended science goal of the observation, which will vary with the types of objects requested for the particular observation and the planned sky conditions for the observation. In this work, we detail the SDSS-V data collection scenarios, which consist of sets of parameters that serve as the framework for constraining fiber placements. The numerical values of these parameters were set based on either past experiences or from a series of new tests, which we describe in detail here. These parameters allow a survey like SDSS-V to be algorithmically planned to maximize the science output, while guaranteeing data quality throughout its operation.

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arXiv2025

Mapping the Distant and Metal-Poor Milky Way with SDSS-V

The fifth-generation Sloan Digital Sky Survey (SDSS-V) is conducting the first all-sky low-resolution spectroscopic survey of the Milky Way's stellar halo. We describe the stellar parameter pipeline for the SDSS-V halo survey, which simultaneously models spectra, broadband photometry, and parallaxes to derive stellar parameters, metallicities, alpha abundances, and distances. The resulting BOSS-MINESweeper catalog is validated across a wide range of stellar parameters and metallicities using star clusters and a comparison to high-resolution spectroscopic surveys. We demonstrate several scientific capabilities of this dataset: identifying the most chemically peculiar stars in our Galaxy, discovering and mapping distant halo substructures, and measuring the all--sky dynamics of the Milky Way on the largest scales. The BOSS-MINESweeper catalog for SDSS DR19 is publicly available and will be updated for future data releases.

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arXiv2025

Resolving the Unresolved: Using NESSI to Search for Unresolved Companions in Low-mass Disk Wide Binaries

Stellar systems consisting of three or more stars are not an uncommon occurrence in the Galaxy. Nearly 50% of solar-type wide binaries with separations >1000 au are actually higher-order multiples with one component being a close binary. Additionally, the higher-order multiplicity fraction appears to be correlated with the physical separation of the widest component. These facts have motivated some of our current theories behind how the widest stellar systems formed, which can have separations on the order of or larger than protostellar cores. However, it is unclear if the correlation between wide binary separation and higher-order multiplicity extends to low-mass binaries. We present initial results of an ongoing speckle imaging survey of nearby low-mass wide binaries. We find an overall higher-order multiplicity fraction for our sample of $42.0\% \pm 10.9\%$. If we include systems where Gaia indicates that a companion is likely present, this fraction increases to $62.0\% \pm 14.2\%$. This is consistent with previous results from both higher-mass stars and a previous result for low-mass wide binaries. However, we do not detect the expected increase in higher-order multiplicity fraction with separation, as was seen with previous studies. We briefly explore why higher-order multiplicity statistics could be different in low-mass stars, and what the significance might be for models of wide binary formation.

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arXiv2024

Detecting New Visual Binaries in Gaia DR3 with Gaia and Two Micron All Sky Survey (2MASS) Photometry II. Speckle Observations of 16 Low-Separation Systems

Here we present speckle observations of 16 low-separation ($s<30$ AU) high probability candidate binaries from the catalog by Medan et al., where secondaries typically lack astrometric solutions in Gaia. From these speckle observations, we find a second component is always detected within the field of view. To determine if the detection is consistent with a physical companion or a chance alignment with a background source, we utilize a statistic from Tokovinin & Kiyaeva that compares the apparent motion of the systems to the expected orbital motion ($μ^\prime$). Using simulated binary orbits, we construct likelihood distributions of $μ^\prime$ assuming various total errors on the measurements. With the hypothesis that the system is a true binary, we show that large measurement errors can result in $μ^\prime$ values higher than expected for bound systems. Using simulated chance alignments, we also create similar likelihoods to test this alternative hypothesis. By combining likelihoods of both true binaries and chance alignments, we find that 15 of the 16 candidates are physical systems regardless of the level of measurement error. Our findings also accommodate all 16 as physical systems if the average, relative measurement error on the binary separations and position angles is $\sim4.3\%$, which is consistent with our knowledge of the Gaia and Gemini speckle pipelines. Importantly, beyond assessing the likelihood of a true binary vs. chance alignment, this quantitative assessment of the true average measurement error will allow more robust error estimates of mass determinations from short separation binaries with Gaia and/or Gemini speckle data.

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arXiv2023

Detecting New Visual Binaries in Gaia DR3 with Gaia and 2MASS Photometry I. New Candidate Binaries Within 200 pc of the Sun

We present a method to identify likely visual binaries in Gaia eDR3 that does not rely on parallax or proper motion. This method utilizes the various PSF sizes of 2MASS/Gaia, where at $<2.5$" two stars may be unresolved in 2MASS but resolved by Gaia. Due to this, if close neighbors listed in Gaia are a resolved pair, the associated 2MASS source will have a predictable excess in the J-band that depends on the $ΔG$ of the pair. We demonstrate that the expected relationship between 2MASS excess and $ΔG$ differs for chance alignments, as compared to true binary systems, when parameters like magnitude and location on the sky are also considered. Using these multidimensional distributions, we compute the likelihood of a close pair of stars to be a chance alignment, resulting in a total(clean) catalog of 68,725(50,230) likely binaries within 200 pc with a completeness rate of $\sim75\%$($\sim64\%$) and contamination rate of $\sim14\%$($\sim0.4\%$). Within this, we find 590 previously unidentified binaries from Gaia eDR3 with projected physical separations $<30$ AU, where 138 systems were previously identified, and for $s<10$ AU we find that 4 out of 15 new likely binaries have not yet been observed with high-resolution imaging. We also demonstrate the potential of our catalog to determine physical separation distributions and binary fraction estimates, from this increase in low separation binaries. Overall, this catalog provides a good complement for the study of local binary populations by probing smaller physical separations and mass ratios, and provides prime targets for speckle monitoring.

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arXiv2023

The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V

The eighteenth data release of the Sloan Digital Sky Surveys (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs, or "Mappers": Milky Way Mapper (MWM), Black Hole Mapper (BHM), and Local Volume Mapper (LVM). This data release contains extensive targeting information for the two multi-object spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration- and scientifically-focused components. DR18 also includes ~25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.

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arXiv2023

Chemodynamical Ages of Small-Scale Kinematic Structures of the Galactic Disc in the Solar Neighborhood from ~250,000 K and M Dwarfs

We combine photometric metallicities with astrometry from Gaia DR3 to examine the chemodynamic structure of ~250,000 K dwarfs in the Solar Neighborhood (SN). In kinematics, we observe ridges/clumps of "kinematic groups", like studies of more massive main-sequence stars. Here we note clear differences in both metallicity and vertical velocity as compared to the surrounding regions in velocity space and hypothesize this is due to differences in mean age. To test this, we develop a method to estimate the age distribution of sub-populations of stars. In this method, we use GALAH data to define probability distributions of W vs. [M/H] in age bins of 2 Gyr and determine optimal age distributions as the best fit weighted sum of these distributions. This process is then validated using the GALAH subset. We estimate the probable age distribution for regions in the kinematic plane, where we find significant sub-structure that is correlated with the kinematic groups. Most notably, we find an age gradient across the Hercules streams that is correlated with birth radius. Finally, we examine the bending and breathing modes as a function of age. From this, we observe potential hints of an increase in the bending amplitude with age, which will require further analysis in order to confirm it. This is one of the first studies to examine these chemodynamics in the SN using primarily low-mass stars and we hope these findings can better constrain dynamical models of the Milky Way due to the increase in resolution the sample size provides.

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arXiv2022

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.

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