arXiv subjects

Željko Ivezić

Publications and source records attributed to Željko Ivezić.

At least 37 records · Page 2Linked to original sources

arXiv2023

Detecting long-period variability in SDSS Stripe 82 standards catalog

We report the results of a search for long-period ($100<P<600$ days) periodic variability in SDSS Stripe 82 standards catalog. The SDSS coverage of Stripe 82 enables such a search because there are on average 20 observations per band in $ugriz$ bands for about 1 million sources, collected over about 6 years, with a faint limit of $r\sim22$ mag and precisely calibrated 1-2% photometry. We calculated the periods of candidate variable sources in this sample using the Lomb-Scargle periodogram and considered the three highest periodogram peaks in each of the $gri$ filters as relevant. Only those sources with $gri$ periods consistent within 0.1% were later studied. We use the Kuiper statistic to ensure uniform distribution of data points in phased light curves. We present 5 sources with the spectra consistent with quasar spectra and plausible periodic variability. This SDSS-based search bodes well for future sensitive large-area surveys, such as the Rubin Observatory Legacy Survey of Space and Time, which, due to its larger sky coverage (about a factor of 60) and improved sensitivity ($\sim2$ mag), will be more powerful for finding such sources.

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arXiv2022

Satellite Constellation Avoidance with the Rubin Observatory Legacy Survey of Space and Time

We investigate a novel satellite avoidance strategy to mitigate the impact of large commercial satellite constellations in low-Earth orbit on the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We simulate the orbits of currently planned Starlink and OneWeb constellations ($\sim$40,000 satellites) to test how effectively an upgraded Rubin scheduler algorithm can avoid them, and assess how the overall survey is affected. Given a reasonably accurate satellite orbit forecast, we find it is possible to adjust the scheduler algorithm to effectively avoid some satellites. Overall, sacrificing 10% of LSST observing time to avoid satellites reduces the fraction of LSST visits with streaks by a factor of two. Whether such a mitigation will be required depends on the overall impact of streaks on science, which is not yet well quantified. This is due to a lack of adequate information about satellite brightness distributions as well as the impact of glints and low surface brightness residuals on alert purity and systematic errors in cosmological parameter estimation. A significant increase in the number of satellites or their brightness during Rubin Operations may make implementing this satellite avoidance strategy worthwhile.

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arXiv2022

Simulating the Legacy Survey of Space and Time stellar content with TRILEGAL

We describe a large simulation of the stars to be observed by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The simulation is based on the TRILEGAL code, which resorts to large databases of stellar evolutionary tracks, synthetic spectra, and pulsation models, added to simple prescriptions for the stellar density and star formation histories of the main structures of the Galaxy, to generate mock stellar samples through a population synthesis approach. The main bodies of the Magellanic Clouds are also included. A complete simulation is provided for single stars, down to the $r=27.5$ mag depth of the co-added wide-fast-deep survey images. A second simulation is provided for a fraction of the binaries, including the interacting ones, as derived with the BinaPSE module of TRILEGAL. We illustrate the main properties and numbers derived from these simulations, including: comparisons with real star counts; the expected numbers of Cepheids, long-period variables and eclipsing binaries; the crowding limits as a function of seeing and filter; the star-to-galaxy ratios, etc. Complete catalogs are accessible through the NOIRLab Astro Data Lab, while the stellar density maps are incorporated in the LSST metrics analysis framework (MAF).

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arXiv2022

MUSSES2020J: The Earliest Discovery of a Fast Blue Ultraluminous Transient at Redshift 1.063

In this Letter, we report the discovery of an ultraluminous fast-evolving transient in rest-frame UV wavelengths, MUSSES2020J, soon after its occurrence by using the Hyper Suprime-Cam (HSC) mounted on the 8.2 m Subaru telescope. The rise time of about 5 days with an extremely high UV peak luminosity shares similarities to a handful of fast blue optical transients whose peak luminosities are comparable with the most luminous supernovae while their timescales are significantly shorter (hereafter "fast blue ultraluminous transient," FBUT). In addition, MUSSES2020J is located near the center of a normal low-mass galaxy at a redshift of 1.063, suggesting a possible connection between the energy source of MUSSES2020J and the central part of the host galaxy. Possible physical mechanisms powering this extreme transient such as a wind-driven tidal disruption event and an interaction between supernova and circumstellar material are qualitatively discussed based on the first multiband early-phase light curve of FBUTs, although whether the scenarios can quantitatively explain the early photometric behavior of MUSSES2020J requires systematical theoretical investigations. Thanks to the ultrahigh luminosity in UV and blue optical wavelengths of these extreme transients, a promising number of FBUTs from the local to the high-z universe can be discovered through deep wide-field optical surveys in the near future.

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arXiv2021

The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy.

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arXiv2021

Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: a pioneering process of community-focused experimental design

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.

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arXiv2021

Photometric Cross-Calibration of the SDSS Stripe 82 Standard Stars catalogue with Gaia EDR3, and Comparison with Pan-STARRS1, DES, CFIS and GALEX catalogues

We extend the SDSS Stripe 82 Standard Stars Catalog with post-2007 SDSS imaging data. This improved version lists averaged SDSS ugriz photometry for nearly a million stars brighter than r~22 mag. With 2-3x more measurements per star, random errors are 1.4-1.7x smaller than in the original catalog, and about 3x smaller than for individual SDSS runs. Random errors in the new catalog are ~< 0.01 mag for stars brighter than 20.0, 21.0, 21.0, 20.5, and 19.0 mag in u, g, r, i, and z-bands, respectively. We achieve this error threshold by using the Gaia Early Data Release 3 (EDR3) Gmag photometry to derive gray photometric zeropoint corrections, as functions of R.A. and Declination, for the SDSS catalog, and use the Gaia BP-RP colour to derive corrections in the ugiz bands, relative to the r-band. The quality of the recalibrated photometry, tested against Pan-STARRS1, DES, CFIS and GALEX surveys, indicates spatial variations of photometric zeropoints <=0.01 mag (RMS), with typical values of 3-7 millimag in the R.A., and 1-2 millimag in the Declination directions, except for <~6 millimag scatter in the u-band. We also report a few minor photometric problems with other surveys considered here, including a magnitude-dependent ~0.01 mag bias between 16 < G_Gaia < 20 in the Gaia EDR3. Our new, publicly available catalog offers robust calibration of ugriz photometry below 1% level, and will be helpful during the commissioning of the Vera C. Rubin Observatory Legacy Survey of Space and Time.

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arXiv2021

THOR: An Algorithm for Cadence-Independent Asteroid Discovery

We present "Tracklet-less Heliocentric Orbit Recovery" (THOR), an algorithm for linking of observations of Solar System objects across multiple epochs that does not require intra-night tracklets or a predefined cadence of observations within a search window. By sparsely covering regions of interest in the phase space with "test orbits", transforming nearby observations over a few nights into the co-rotating frame of the test orbit at each epoch, and then performing a generalized Hough transform on the transformed detections followed by orbit determination (OD) filtering, candidate clusters of observations belonging to the same objects can be recovered at moderate computational cost and little to no constraints on cadence. We validate the effectiveness of this approach by running on simulations as well as on real data from the Zwicky Transient Facility (ZTF). Applied to a short, 2-week, slice of ZTF observations, we demonstrate THOR can recover 97.4% of all previously known and discoverable objects in the targeted ($a > 1.7$ au) population with 5 or more observations and with purity between 97.7% and 100%. This includes 10 likely new discoveries, and a recovery of an $e \sim 1$ comet C/2018 U1 (the comet would have been a ZTF discovery had THOR been running in 2018 when the data were taken). The THOR package and demo Jupyter notebooks are open source and available at https://github.com/moeyensj/thor.

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arXiv2021

The LSST DESC DC2 Simulated Sky Survey

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.

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arXiv2020

Proper motion measurements for stars up to $100$ kpc with Subaru HSC and SDSS Stripe 82

We present proper motion measurements for more than $0.55$ million main-sequence stars, by comparing astrometric positions of matched stars between the multi-band imaging datasets from the Hyper Suprime-Cam (HSC) Survey and the SDSS Stripe 82. In doing this we use $3$ million galaxies to recalibrate the astrometry and set up a common reference frame between the two catalogues. The exquisite depth and the nearly $12$ years of time baseline between HSC and SDSS enable high-precision measurements of statistical proper motions for stars down to $i\simeq 24$. A validation of our method is demonstrated by the agreement with the $Gaia$ proper motions, to the precision better than $0.1$ mas yr$^{-1}$. To retain the precision, we make a correction of the subtle effects due to the differential chromatic refraction in the SDSS images based on the comparison with the $Gaia$ proper motions against colour of stars, which is validated using the SDSS spectroscopic quasars. Combining with the photometric distance estimates for individual stars based on the precise HSC photometry, we show a significant detection of the net proper motions for stars in each bin of distance out to $100$ kpc. The two-component tangential velocities after subtracting the apparent motions due to our own motion display rich phase-space structures including a clear signature of the Sagittarius stream in the halo region of distance range $[10,\ 35]$ kpc. We also measure the tangential velocity dispersion in the distance range $5-20$ kpc and find that the data are consistent with a constant isotropic dispersion of $80\pm 10\ {\rm km/s}$. More distant stars appear to have random motions with respect to the Galactic centre on average.

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arXiv2020

Improving Damped Random Walk parameters for SDSS Stripe 82 Quasars with Pan-STARRS1

We use the Panoramic Survey Telescope and Rapid Response System 1 Survey (Pan-STARRS1, PS1) data to extend the Sloan Digital Sky Survey (SDSS) Stripe 82 quasar light curves. Combining PS1 and SDSS light curves provides a 15 yr baseline for 9248 quasars - 5 yr longer than prior studies that used only SDSS. We fit the light curves with the damped random walk (DRW) model model - a statistical description of their variability. We correlate the resulting DRW model parameters: asymptotic variability amplitude SF$_{\infty}$, and characteristic timescale $τ$, with quasar physical properties - black hole mass, bolometric luminosity, and redshift. Using simulated light curves, we find that a longer baseline allows us to better constrain the DRW parameters. After adding PS1 data, the variability amplitude is a stronger function of the black hole mass, and has a weaker dependence on quasar luminosity. In addition, the characteristic timescale $τ$ dependence on quasar luminosity is marginally weaker. We also make predictions for the fidelity of DRW model parameter retrieval when light curves will be further extended with Zwicky Transient Facility (ZTF) and the Rubin Observatory Legacy Survey of Space and Time (LSST) data. Finally, we show how updated DRW parameters offer an independent method of discovering changing-look quasar candidates (CLQSOs). The candidates are outliers in terms of differences in magnitude and scatter between SDSS and PS1 segments. We identify 40 objects (35 newly reported) with tenfold increase in variability timescale between SDSS and SDSS--PS1 data, which is due to a large change in brightness (over 0.5 mag) - characteristic for CLQSOs.

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arXiv2020

Predicting the Accuracy of Asteroid Size Estimation with Data from the Rubin Observatory Legacy Survey of Space and Time

Recent work has shown that the correlation between SDSS colors and optical albedo can be used to estimate asteroid sizes from optical data alone. We revisit a correlation between SDSS colors and optical albedo for asteroids, with the albedo derived using WISE-based size estimates. Moeyens, Myhrvold \& Ivezić (2020) showed that this correlation can be used to estimate asteroid sizes with optical data alone, with a precision of about 17\% relative to WISE-based size estimates. We present here several more sophisticated data-driven models for the variation of optical albedo with colors and estimate the contribution of SDSS photometric errors to the albedo and size estimate uncertainties. We use the results of our analysis to predict that LSST data will enable asteroid size precision of about 15\% relative to WISE-based size estimates. Compared to the accuracy of WISE-based size estimates of 15-20\%, the implied accuracy of optical size estimates, in the range 21-25\%, is thus only a factor of 1.3 to 1.4 worse. This size estimation accuracy is significantly better than commonly assumed for optical data and is due to accurate and homogeneous multi-band photometry delivered by modern digital sky surveys.

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arXiv2020

Mitigation of LEO Satellite Brightness and Trail Effects on the Rubin Observatory LSST

We report studies on the mitigation of optical effects of bright low-Earth-orbit (LEO) satellites on Vera C. Rubin Observatory and its Legacy Survey of Space and Time (LSST). These include options for pointing the telescope to avoid satellites, laboratory investigations of bright trails on the Rubin Observatory LSST camera sensors, algorithms for correcting image artifacts caused by bright trails, experiments on darkening SpaceX Starlink satellites, and ground-based follow-up observations. The original Starlink v0.9 satellites are g ~ 4.5 mag, and the initial experiment "DarkSat" is g ~ 6.1 mag. Future Starlink darkening plans may reach g ~ 7 mag, a brightness level that enables nonlinear image artifact correction to well below background noise. However, the satellite trails will still exist at a signal-to-noise ratio ~ 100, generating systematic errors that may impact data analysis and limit some science. For the Rubin Observatory 8.4-m mirror and a satellite at 550 km, the full width at half maximum of the trail is about 3" as the result of an out-of-focus effect, which helps avoid saturation by decreasing the peak surface brightness of the trail. For 48,000 LEOsats of apparent magnitude 4.5, about 1% of pixels in LSST nautical twilight images would need to be masked.

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arXiv2020

Photometric Redshifts with the LSST II: The Impact of Near-Infrared and Near-Ultraviolet Photometry

Accurate photometric redshift (photo-$z$) estimates are essential to the cosmological science goals of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). In this work we use simulated photometry for mock galaxy catalogs to explore how LSST photo-$z$ estimates can be improved by the addition of near-infrared (NIR) and/or ultraviolet (UV) photometry from the Euclid, WFIRST, and/or CASTOR space telescopes. Generally, we find that deeper optical photometry can reduce the standard deviation of the photo-$z$ estimates more than adding NIR or UV filters, but that additional filters are the only way to significantly lower the fraction of galaxies with catastrophically under- or over-estimated photo-$z$. For Euclid, we find that the addition of ${JH}$ $5σ$ photometric detections can reduce the standard deviation for galaxies with $z>1$ ($z>0.3$) by ${\sim}20\%$ (${\sim}10\%$), and the fraction of outliers by ${\sim}40\%$ (${\sim}25\%$). For WFIRST, we show how the addition of deep ${YJHK}$ photometry could reduce the standard deviation by ${\gtrsim}50\%$ at $z>1.5$ and drastically reduce the fraction of outliers to just ${\sim}2\%$ overall. For CASTOR, we find that the addition of its ${UV}$ and $u$-band photometry could reduce the standard deviation by ${\sim}30\%$ and the fraction of outliers by ${\sim}50\%$ for galaxies with $z<0.5$. We also evaluate the photo-$z$ results within sky areas that overlap with both the NIR and UV surveys, and when spectroscopic training sets built from the surveys' small-area deep fields are used.

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arXiv2019

Morphological Star-Galaxy Separation

We discuss the statistical foundations of morphological star-galaxy separation. We show that many of the star-galaxy separation metrics in common use today (e.g. by SDSS or SExtractor) are closely related both to each other, and to the model odds ratio derived in a Bayesian framework by Sebok (1979). While the scaling of these algorithms with the noise properties of the sources varies, these differences do not strongly differentiate their performance. We construct a model of the performance of a star-galaxy separator in a realistic survey to understand the impact of observational signal-to-noise ratio (or equivalently, 5-sigma limiting depth) and seeing on classification performance. The model quantitatively demonstrates that, assuming realistic densities and angular sizes of stars and galaxies, 10% worse seeing can be compensated for by approximately 0.4 magnitudes deeper data to achieve the same star-galaxy classification performance. We discuss how to probabilistically combine multiple measurements, either of the same type (e.g., subsequent exposures), or differing types (e.g., multiple bandpasses), or differing methodologies (e.g., morphological and color-based classification). These methods are increasingly important for observations at faint magnitudes, where the rapidly rising number density of small galaxies makes star-galaxy classification a challenging problem. However, because of the significant role that the signal-to-noise ratio plays in resolving small galaxies, surveys with large-aperture telescopes, such as LSST, will continue to see improving star-galaxy separation as they push to these fainter magnitudes.

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arXiv2019

LSST Narrowband Filters

In this white paper, we present the scientific cases for adding narrowband optical filters to the Large Synoptic Survey Telescope (LSST). LSST is currently planning to observe the southern sky in 6 broadband optical filters. Three of the four LSST science themes would benefit from adding narrowband filter observations. We discuss the technical considerations of using narrowband filters with the LSST and lay out the scientific impact that would result on the study of AGB stars, emission line nebula (e.g., supernova remnants and planetary nebulae), photometric redshifts of galaxies, and the determination of stellar parameters.

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arXiv2019

Future Uses of the LSST Facility: Input from the LSST Project Science Team

In this white paper, we discuss future uses of the LSST facility after the planned 10-year survey is complete. We expect the LSST survey to profoundly affect the scientific landscape over the next ten years, and it is likely that unexpected discoveries may drive its future scientific program. We discuss various operations and instrument options that could be considered for an extended LSST mission beyond ten years.

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arXiv2019

ATM: An Open-Source Tool for Asteroid Thermal Modeling

We publicly release ATM, a Python package designed to model asteroid flux measurements to estimate an asteroid's size, surface temperature distribution, and emissivity. The full multi-dimensional posterior pdf is found using Markov Chain Monte Carlo. Data files with $\sim$ 2.5 million WISE flux measurements for $\sim$ 150,000 asteroids and additional MPC data are also included with the package, as well as Python Jupyter Notebooks with examples of analysis. The entirety of the analysis presented here, including all the figures, tables, and catalogs, can be easily reproduced with these publicly released Notebooks. We show that ATM can match the best-fit size estimates for well-observed asteroids published in 2016 by the NEOWISE team (Mainzer et al. 2016) with a sub-percent bias and a scatter of only 6%. We estimate that the accuracy of WISE-based asteroid size estimates is approximately in the range of 15-20% for most objects. We also study optical data collected by the Sloan Digital Sky Survey (SDSS) and show that correlations of optical colors and WISE-based best-fit model parameters indicate robustness of the latter. Our analysis also gives support to the claim by Harris & Drube (2014) that candidate metallic asteroids can be selected using the best-fit temperature parameter and infrared albedo. We investigate a correlation between SDSS colors and optical albedo derived using WISE-based size estimates and show that this correlation can be used to estimate asteroid sizes with optical data alone, with a precision of about 21% relative to WISE-based size estimates. After accounting for systematic errors, the difference in accuracy between infrared and optical color-based size estimates becomes less than a factor of two. (abridged)

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