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In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency of galaxies to naturally align towards overdensities, an effect called intrinsic alignments (IA), can be a major source of systematics in the weak lensing analysis. As the details of galaxy formation and evolution relevant to IA cannot be simulated in practice on such volumes, we propose as an alternative a Deep Generative Model. This model is trained on the IllustrisTNG-100 simulation and is capable of sampling the orientations of a population of galaxies so as to recover the correct alignments. In our approach, we model the cosmic web as a set of graphs, where the graphs are constructed for each halo, and galaxy orientations as a signal on those graphs. The generative model is implemented on a Generative Adversarial Network architecture and uses specifically designed Graph-Convolutional Networks sensitive to the relative 3D positions of the vertices. Given (sub)halo masses and tidal fields, the model is able to learn and predict scalar features such as galaxy and dark matter subhalo shapes; and more importantly, vector features such as the 3D orientation of the major axis of the ellipsoid and the complex 2D ellipticities. For correlations of 3D orientations the model is in good quantitative agreement with the measured values from the simulation, except for at very small and transition scales. For correlations of 2D ellipticities, the model is in good quantitative agreement with the measured values from the simulation on all scales. Additionally, the model is able to capture the dependence of IA on mass, morphological type and central/satellite type., Comment: 15 pages, 7 figures (+2 figures in Appendix), matches published version at MNRAS

Galaxies exhibit coherent alignments with local structure in the Universe. This effect, called Intrinsic Alignments (IA), is an important contributor to the systematic uncertainties for wide-field weak lensing surveys. On cosmological distance scales, intrinsic shape alignments have been observed in red galaxies, which are usually bulge-dominated; while blue galaxies, which are mostly disc-dominated, exhibit shape alignments consistent with a null detection. However, disc-dominated galaxies typically consist of two prominent structures: disc and bulge. Since the bulge component has similar properties as elliptical galaxies and is thought to have formed in a similar fashion, naturally one could ask whether the bulge components exhibit similar alignments as ellipticals? In this paper, we investigate how different components of galaxies exhibit IA in the TNG100-1 cosmological hydrodynamical simulation, as well as the dependence of IA on the fraction of stars in rotation-dominated structures at $z=0$. The measurements were controlled for mass differences between the samples. We find that the bulges exhibit significantly higher IA signals, with a nonlinear alignment model amplitude of $A_I = 2.98^{+0.36}_{-0.37}$ compared to the amplitude for the galaxies as a whole (both components), $A_I = 1.13^{+0.37}_{-0.35}$. The results for bulges are statistically consistent with those for elliptical galaxies, which have $A_I = 3.47^{+0.57}_{-0.57}$. These results highlight the importance of studying galaxy dynamics in order to understand galaxy alignments and their cosmological implications., Comment: 14 pages, 7 figures. Matches the version published at MNRAS

Weak gravitational lensing is one of the most powerful tools for cosmology, while subject to challenges in quantifying subtle systematic biases. The Point Spread Function (PSF) can cause biases in weak lensing shear inference when the PSF model does not match the true PSF that is convolved with the galaxy light profile. Although the effect of PSF size and shape errors - i.e., errors in second moments - is well studied, weak lensing systematics associated with errors in higher moments of the PSF model require further investigation. The goal of our study is to estimate their potential impact for LSST weak lensing analysis. We go beyond second moments of the PSF by using image simulations to relate multiplicative bias in shear to errors in the higher moments of the PSF model. We find that the current level of errors in higher moments of the PSF model in data from the Hyper Suprime-Cam (HSC) survey can induce a $\sim 0.05 $ per cent shear bias, making this effect unimportant for ongoing surveys but relevant at the precision of upcoming surveys such as LSST., Comment: 19 pages, 10 figures, 3 tables; Accepted by MNRAS

Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples, and illustrate the approach on CosmoDC2 simulations. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1+z), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes., Comment: Updated to match the version accepted by the MNRAS, 23 pages, 9 figures, 2 tables

In the era of precision cosmology and ever-improving cosmological simulations, a better understanding of different galaxy components such as bulges and discs will give us new insight into galactic formation and evolution. Based on the fact that the stellar populations of the constituent components of galaxies differ by their dynamical properties, we develop two simple models for galaxy decomposition using the IllustrisTNG cosmological hydrodynamical simulation. The first model uses a single dynamical parameter and can distinguish 4 components: thin disc, thick disc, counter-rotating disc and bulge. The second model uses one more dynamical parameter, was defined in a probabilistic manner, and distinguishes two components: bulge and disc. The number fraction of disc-dominated galaxies at a given stellar mass obtained by our models agrees well with observations for masses exceeding $ \log_{10}(M_*/M_\odot)=10$. S\'ersic indices and half-mass radii for the bulge components agree well with those for real galaxies. The mode of the distribution of S\'ersic indices for the disc components is at the expected value of $n=1$. However, disc half-mass radii are smaller than those for real galaxies, in accordance with previous findings that the IllustrisTNG simulation produces undersized discs., Comment: 15 pages, 12 figures

We use galaxies from the IllustrisTNG, MassiveBlack-II and Illustris hydrodynamic simulations to investigate the behaviour of large scale galaxy intrinsic alignments. Our analysis spans four redshift slices over the approximate range of contemporary lensing surveys $z=0-1$. We construct comparable weighted samples from the three simulations, which we then analyse using an alignment model that includes both linear and quadratic alignment contributions. Our data vector includes galaxy-galaxy, galaxy-shape and shape-shape projected correlations, with the joint covariance matrix estimated analytically. In all of the simulations, we report non-zero IAs at the level of several $\sigma$. For a fixed lower mass threshold, we find a relatively strong redshift dependence in all three simulations, with the linear IA amplitude increasing by a factor of $\sim 2$ between redshifts $z=0$ and $z=1$. We report no significant evidence for non-zero values of the tidal torquing amplitude, $A_2$, in TNG, above statistical uncertainties, although MassiveBlack-II favours a moderately negative $A_2\sim-2$. Examining the properties of the TATT model as a function of colour, luminosity and galaxy type (satellite or central), our findings are consistent with the most recent measurements on real data. We also outline a novel method for constraining the TATT model parameters directly from the pixelised tidal field, alongside a proof of concept exercise using TNG. This technique is shown to be promising, although the comparison with previous results obtained via other methods is non-trivial., Comment: 28 pages, 18 Figures; submitted to MNRAS

We describe the bug in the ellipticity values and related quantities that are present in the cosmoDC2 catalogs and SkySim5000_v1.1.1 and discuss how the error should be corrected. We show distributions of the uncorrected and corrected values. The bug resulted in the distribution of ellipticities being skewed to lower values, i.e., galaxies are rounder than they should have been. This bug affects the intrinsic (pre-lensing) galaxy ellipticities; the lensing shape distortions were unaffected in the catalog, and are added to the too-round intrinsic shapes. These ellipticities were used as the inputs for the DC2 image simulations, therefore the DC2 image simulations and resulting object catalogs are affected., Technical note

We investigate the performance of the Metacalibration shear calibration framework using simulated imaging data for the Nancy Grace Roman Space Telescope (Roman) reference High-Latitude Imaging Survey (HLIS). The weak lensing program of the Roman mission requires the mean weak lensing shear estimate to be calibrated within about 0.03%. To reach this goal, we can test our calibration process with various simulations and ultimately isolate the sources of residual shear biases in order to improve our methods. In this work, we build on the Roman HLIS image simulation pipeline in Troxel et al. 2021 to incorporate several new realistic processing-pipeline updates necessary to more accurately process the imaging data and calibrate the shear. We show the first results of this calibration for six deg$^2$ of the simulated reference HLIS using Metacalibration and compare these results to measurements on more simple, faster Roman-like image simulations. In both cases, we neglect the impact of blending of objects. We find that in the simplified simulations, Metacalibration can calibrate shapes to be within $m=(-0.01\pm 0.10)$%. When applied to the current most-realistic version of the simulations, the precision is much lower, with estimates of $m=(-1.34\pm 0.67)$% for joint multi-band single-epoch measurements and $m=(-1.13\pm 0.60)$% for multi-band coadd measurements. These results are all consistent with zero within 1-2$\sigma$, indicating we are currently limited by our simulated survey volume. Further work on testing the shear calibration methodology is necessary at higher precision to reach the level of the Roman requirements, in particular in the presence of blending. Current results demonstrate, however, that the Metacalibration method can work on undersampled space-based Roman imaging data at levels comparable to the requirements of current weak lensing surveys., Comment: updated to published version

Shear estimation bias from galaxy detection and blending identification is now recognized as an issue for ongoing and future weak lensing surveys. Currently, the empirical approach to correcting for this bias involves numerically shearing every observed galaxy and rerunning the detection and selection process. In this work, we provide an analytical correction for this bias that is accurate to subpercent level and far simpler to use. With the interpretation that smoothed image pixel values and galaxy properties are projections of the image signal onto a set of basis functions, we analytically derive the linear shear responses of both the pixel values and the galaxy properties (i.e., magnitude, size and shape) using the shear responses of the basis functions. With these derived shear responses, we correct for biases from shear-dependent galaxy detection and galaxy sample selection. With the analytical covariance matrix of measurement errors caused by image noise on pixel values and galaxy properties, we correct for the noise biases in galaxy shape measurement and the detection/selection process to the second-order in noise. The code used for this paper can carry out the detection, selection, and shear measurement for ~1000 galaxies per CPU second. The algorithm is tested with realistic image simulations, and we find, after the analytical correction (without relying on external image calibration) for the detection/selection bias of about $-4\%$, the multiplicative shear bias is $-0.12 \pm 0.10\%$ for isolated galaxies; and $-0.3 \pm 0.1\%$ for blended galaxies with Hyper Suprime-Cam observational condition., Comment: 23 pages, 22 figures, Accepted in MNRAS

This work uses hierarchical logistic Gaussian processes to infer true redshift distributions of samples of galaxies, through their cross-correlations with spatially overlapping spectroscopic samples. We demonstrate that this method can accurately estimate these redshift distributions in a fully Bayesian manner jointly with galaxy-dark matter bias models. We forecast how systematic biases in the redshift-dependent galaxy-dark matter bias model affect redshift inference. Using published galaxy-dark matter bias measurements from the Illustris simulation, we compare these systematic biases with the statistical error budget from a forecasted weak gravitational lensing measurement. If the redshift-dependent galaxy-dark matter bias model is mis-specified, redshift inference can be biased. This can propagate into relative biases in the weak lensing convergence power spectrum on the 10% - 30% level. We, therefore, showcase a methodology to detect these sources of error using Bayesian model selection techniques. Furthermore, we discuss the improvements that can be gained from incorporating prior information from Bayesian template fitting into the model, both in redshift prediction accuracy and in the detection of systematic modeling biases., 17 pages, 8 figures, 4 tables, Accepted to MNRAS Nov 2019

The generation-defining Vera C. Rubin Observatory will make state-of-the-art measurements of both the static and transient universe through its Legacy Survey for Space and Time (LSST). With such capabilities, it is immensely challenging to optimize the LSST observing strategy across the survey's wide range of science drivers. Many aspects of the LSST observing strategy relevant to the LSST Dark Energy Science Collaboration, such as survey footprint definition, single visit exposure time and the cadence of repeat visits in different filters, are yet to be finalized. Here, we present metrics used to assess the impact of observing strategy on the cosmological probes considered most sensitive to survey design; these are large-scale structure, weak lensing, type Ia supernovae, kilonovae and strong lens systems (as well as photometric redshifts, which enable many of these probes). We evaluate these metrics for over 100 different simulated potential survey designs. Our results show that multiple observing strategy decisions can profoundly impact cosmological constraints with LSST; these include adjusting the survey footprint, ensuring repeat nightly visits are taken in different filters and enforcing regular cadence. We provide public code for our metrics, which makes them readily available for evaluating further modifications to the survey design. We conclude with a set of recommendations and highlight observing strategy factors that require further research., Comment: 49 pages, 17 figures

We explore synergies between the space-based Wide-Field Infrared Survey Telescope (WFIRST) and the ground-based Rubin Observatory Legacy Survey of Space and Time (LSST). In particular, we consider a scenario where the currently envisioned survey strategy for WFIRST's High Latitude Survey (HLS), i.e., 2000 square degrees in four narrow photometric bands is altered in favor of a strategy that combines rapid coverage of the LSST area (to full LSST depth) in one band. We find that a 5-month WFIRST survey in the W-band can cover the full LSST survey area providing high-resolution imaging for >95% of the LSST Year 10 gold galaxy sample. We explore a second, more ambitious scenario where WFIRST spends 1.5 years covering the LSST area. For this second scenario we quantify the constraining power on dark energy equation of state parameters from a joint weak lensing and galaxy clustering analysis, and compare it to an LSST-only survey and to the Reference WFIRST HLS survey. Our survey simulations are based on the WFIRST exposure time calculator and redshift distributions from the CANDELS catalog. Our statistical uncertainties account for higher-order correlations of the density field, and we include a wide range of systematic effects, such as uncertainties in shape and redshift measurements, and modeling uncertainties of astrophysical systematics, such as galaxy bias, intrinsic galaxy alignment, and baryonic physics. Assuming the 5-month WFIRST wide scenario, we find a significant increase in constraining power for the joint LSST+WFIRST wide survey compared to LSST Y10 (FoM(Wwide)= 2.4 FoM(LSST)) and compared to LSST+WFIRST HLS (FoM(Wwide)= 5.5 FoM(HLS)).

Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multi-purpose 10-year optical survey of the southern hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the Solar System, exploring the transient optical sky, and mapping the Milky Way. The survey's massive data throughput will be transformational for many other astrophysics domains and Rubin's data access policy sets the stage for a huge potential users' community. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue., Submitted as the opening paper of the Astrophysical Journal Focus Issue on Rubin LSST cadence and survey strategy

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep (WFD) area of approximately 300 deg^2 as well as a deep drilling field (DDF) of approximately 1 deg^2. We simulate 5 years of the planned 10-year survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the dataset to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic testbed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time-domain cosmology., 39 pages, 19 figures, version accepted for publication in ApJS

Modifications of the matter power spectrum due to baryonic physics are one of the major theoretical uncertainties in cosmological weak lensing measurements. Developing robust mitigation schemes for this source of systematic uncertainty increases the robustness of cosmological constraints, and may increase their precision if they enable the use of information from smaller scales. Here we explore the performance of two mitigation schemes for baryonic effects in weak lensing cosmic shear: the PCA method and the halo-model approach in \textsc{HMcode}. We construct mock tomographic shear power spectra from four hydrodynamical simulations, and run simulated likelihood analyses with \textsc{CosmoLike} assuming LSST-like survey statistics. With an angular scale cut of $\ell_{\rm max} 10\ h^{-1}\mathrm{Mpc}$. We investigate variants of the PCA method and improve the bias mitigation through PCA by accounting for the noise properties in the data via Cholesky decomposition of the covariance matrix. Our improved PCA method allows us to retain more statistical constraining power while effectively mitigating baryonic uncertainties even for a broad range of baryonic physics scenarios., 29 pages, 19 figures, accepted to MNRAS

Variable stars with well-calibrated period-luminosity relationships provide accurate distance measurements to nearby galaxies and are therefore a vital tool for cosmology and astrophysics. While these measurements typically rely on samples of Cepheid and RR-Lyrae stars, abundant populations of luminous variable stars with longer periods of $10 - 1000$ days remain largely unused. We apply machine learning to derive a mapping between lightcurve features of these variable stars and their magnitude to extend the traditional period-luminosity (PL) relation commonly used for Cepheid samples. Using photometric data for long period variable stars in the Large Magellanic cloud (LMC), we demonstrate that our predictions produce residual errors comparable to those obtained on the corresponding Cepheid population. We show that our model generalizes well to other samples by performing a blind test on photometric data from the Small Magellanic Cloud (SMC). Our predictions on the SMC again show small residual errors and biases, comparable to results that employ PL relations fitted on Cepheid samples. The residual biases are complementary between the long period variable and Cepheid fits, which provides exciting prospects to better control sources of systematic error in cosmological distance measurements. We finally show that the proposed methodology can be used to optimize samples of variable stars as standard candles independent of any prior variable star classification., Comment: 14 pages, 10 figures, 1 table, updated to match the version accepted by the MNRAS

The cosmological utility of galaxy cluster catalogues is primarily limited by our ability to calibrate the relation between halo mass and observable mass proxies such as cluster richness, X-ray luminosity or the Sunyaev-Zeldovich signal. Projection effects are a particularly pernicious systematic effect that can impact observable mass proxies; structure along the line of sight can both bias and increase the scatter of the observable mass proxies used in cluster abundance studies. In this work, we develop an empirical method to characterize the impact of projection effects on redMaPPer cluster catalogues. We use numerical simulations to validate our method and illustrate its robustness. We demonstrate that modeling of projection effects is a necessary component for cluster abundance studies capable of reaching $\approx 5\%$ mass calibration uncertainties (e.g. the Dark Energy Survey Year 1 sample). Specifically, ignoring the impact of projection effects in the observable--mass relation --- i.e. marginalizing over a log-normal model only --- biases the posterior of the cluster normalization condition $S_8 \equiv \sigma_8 (\Omega_{\rm m}/0.3)^{1/2}$ by $\Delta S_8 =0.05$, more than twice the uncertainty in the posterior for such an analysis., Comment: 16 pages, 11 figures

The Nancy Grace Roman Space Telescope (Roman) mission is expected to launch in the mid-2020s. Its weak lensing program is designed to enable unprecedented systematics control in photometric measurements, including shear recovery, point-spread function (PSF) correction, and photometric calibration. This will enable exquisite weak lensing science and allow us to adjust to and reliably contribute to the cosmological landscape after the initial years of observations from other concurrent Stage IV dark energy experiments. This potential requires equally careful planning and requirements validation as the mission prepares to enter its construction phase. We present a suite of image simulations based on GalSim that are used to construct a complex, synthetic Roman weak lensing survey that incorporates realistic input galaxies and stars, relevant detector non-idealities, and the current reference five-year Roman survey strategy. We present a first study to empirically validate the existing Roman weak lensing requirements flowdown using a suite of 12 matched image simulations, each representing a different perturbation to the wavefront or image motion model. These are chosen to induce a range of potential static and low- and high-frequency time-dependent PSF model errors. We analyze the measured shapes of galaxies from each of these simulations and compare them to a reference, fiducial simulation to infer the response of the shape measurement to each of these modes in the wavefront model. We then compare this to existing analytic flowdown requirements, and find general agreement between the empirically derived response and that predicted by the analytic model., Matches accepted version; substantial additions to appendices

We present the galaxy shear catalog that will be used for the three-year cosmological weak gravitational lensing analyses using data from the Wide layer of the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP) Survey. The galaxy shapes are measured from the $i$-band imaging data acquired from 2014 to 2019 and calibrated with image simulations that resemble the observing conditions of the survey based on training galaxy images from the Hubble Space Telescope in the COSMOS region. The catalog covers an area of 433.48 deg$^2$ of the northern sky, split into six fields. The mean $i$-band seeing is 0.59 arcsec. With conservative galaxy selection criteria (e.g., $i$-band magnitude brighter than 24.5), the observed raw galaxy number density is 22.9 arcmin$^{-2}$, and the effective galaxy number density is 19.9 arcmin$^{-2}$. The calibration removes the galaxy property-dependent shear estimation bias to a level: $|\delta m|1$ degree scales and will require mitigation during the inference of cosmological parameters using cosmic shear measurements., Comment: 39 pages, 31 figures, 5 tables; PASJ (in press)

The Fiber Optic Broad-band Optical Spectrometer (FOBOS) is a high-priority spectroscopic facility concept for the W. M. Keck Observatory. Here, we provide an update on the FOBOS conceptual design. FOBOS will deploy 1800 fibers across the 20-arcminute field-of-view of the Keck II Telescope. Starbugs fiber positioners will be used to deploy individual fibers as well as fiber-bundle arrays (integral field units, IFUs). Different combinations of active single fibers or IFUs can be selected to carry light to one of three mounted spectrographs, each with a 600-fiber pseudoslit. Each spectrograph has four wavelength channels, enabling end-to-end instrument sensitivity greater than 30% from 0.31-1.0 µm at a spectral resolution of R ~ 3500. With its high fiber density on a large telescope and modest field-of-view, FOBOS is optimized to obtain deep spectroscopy for large samples. In single- fiber mode, it will deliver premier spectroscopic reference sets for maximizing the information (e.g., photometric redshifts) that can be extracted from panoramic imaging surveys obtained from the forthcoming Rubin and Roman Observatories. Its IFUs will map emission from the circumgalactic interface between forming galaxies and the intergalactic medium at z ~ 2–3, and lay the path for multiplexed resolved spectroscopy of high-z galaxies aided by ground-layer and multi-object adaptive optics. In the nearby universe, its high sampling density and combination of single-fiber and IFU modes will revolutionize our understanding of the M31 disk and bulge via stellar populations and kinematics. Finally, with a robust and intelligent target and program allocation system, FOBOS will be a premier facility for follow-up of rare, faint, and transient sources that can be interleaved into its suite of observing programs. With a commitment to delivering science-ready data products, FOBOS will enable unique and powerful combinations of focused, PI-led programs and community-driven observing campaigns that promise major advances in cosmology, galaxy formation, time-domain astronomy, and stellar evolution.

To examine incidence and characteristics of women who developed secondary breast cancer after uterine cancer.This is a population-based retrospective cohort study utilizing the National Cancer Institute's Surveillance, Epidemiology, and End Result Program from 1973 to 2013. Women with uterine cancer who did not have synchronous or a history of breast cancer were followed after their uterine cancer diagnosis (N = 236,561). A time-dependent competing risk analysis was performed to examine cumulative incidences and clinico-pathological characteristics of those who subsequently developed breast cancer.There were 7110 (3.0%) women who developed secondary breast cancers after uterine cancer with 5-, 10-, and 20-year cumulative incidence rates of 1.5, 2.8, and 4.7%, respectively. The increase in the rate of secondary breast cancer was particularly high in the first 3 years after a uterine cancer diagnosis (annual percent change [APC] 4.9), followed by 3-7 years (APC 1.6) after diagnosis (P 0.001). The median time to develop secondary breast cancer was 6.4 years. Older women had significantly shorter time intervals between uterine and breast cancer diagnoses (3.7 years for aged 71, 5.9 for aged 64-71, 7.6 for aged 56-63, and 9.4 for aged 56, P 0.001). In a multivariable analysis, older age, White race, married status, endometrioid, serous, and mixed histology types, and early-stage tumors remained as independent factors of developing secondary breast cancer (all, P 0.05).Tumor factors with endometrioid and serous histology types and early-stage disease were the factors associated with secondary breast cancer after uterine cancer diagnosis. Older women had shorter time to develop secondary breast cancer.

Data Challenge 1 (DC1) is the first synthetic dataset produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST dataset. DC1 is comprised of $r$-band observations of 40 deg$^{2}$ to 10-year LSST depth. We present each stage of the simulation and analysis process: a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; b) reduction using a development version of the LSST Science Pipelines; and c) matching to the input cosmological catalog for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star-galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: i) survey properties have an impact of 50\% of the statistical uncertainty for the scales and models used in DC1 ii) a selection to eliminate artifacts in the catalogs is necessary to avoid biases in the measured clustering; iii) the presence of bright objects has a significant impact (2- to 6-$\sigma$) in the estimated power spectra at small scales ($\ell > 1200$), highlighting the impact of blending in studies at small angular scales in LSST, Comment: 21 pages, 21 figures. Accepted at MNRAS

Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3$\times$2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modeling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude ($Q_1$) generally reflects the strength of baryon feedback. With the upper limit of $Q_1$ prior being bound by the Illustris feedback scenarios, we reach $\sim 20\%$ improvement in the constraint of $S_8=\sigma_8(\Omega_{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3$\times$2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative $Q_1$ prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than $2 \sigma$., Comment: 22 pages, 18 figures, 2 tables. accepted to MNRAS. A brief video summary of this paper is available at https://www.youtube.com/watch?v=QbeNwk5papU

Forthcoming space-based observations will require high-quality point-spread function (PSF) models for weak gravitational lensing measurements. One approach to generating these models is using a wavefront model based on the known telescope optics. We present an empirical framework for validating such models to confirm that they match the actual PSF to within requirements by comparing the models to the observed light distributions of isolated stars. We apply this framework to Tiny Tim, the standard tool for generating model PSFs for the Hubble Space Telescope (HST), testing its models against images taken by HST's Advanced Camera for Surveys in the Wide Field Channel. We show that Tiny Tim's models, in the default configuration, differ significantly from the observed PSFs, most notably in their sizes. We find that the quality of Tiny Tim PSFs can be improved through fitting the full set of Zernike polynomial coefficients which characterise the optics, to the point where the practical significance of the difference between model and observed PSFs is negligible for most use cases, resulting in additive and multiplicative biases both of order approximately 4e-4. We also show that most of this improvement can be retained through using an updated set of Zernike coefficients, which we provide., Comment: 26 pages, 12 figures, code included. Accepted for publication by MNRAS