arXiv subjects

Daniel M. Scolnic

Publications and source records attributed to Daniel M. Scolnic.

17 recordsLinked to original sources

arXiv2025

TITAN DR1: An Improved, Validated, and Systematically-Controlled Recalibration of ATLAS Photometry toward Type Ia Supernova Cosmology

ATLAS (Asteroid Terrestrial Last Alert System) is a time-domain survey using four telescopes, covering the entire sky. It has observed over 10,000 spectroscopically confirmed Type Ia supernovae (SNe~Ia), with thousands of cosmology-grade light curves (to be released as TITAN DR1). To prepare this massive, low-redshift dataset for cosmology, we evaluate and cross-calibrate ATLAS forced photometry using tertiary stars from the DES (Dark Energy Survey) Y6 release. The 5000 deg$^2$ DES footprint overlaps regions both in and out of the PS1 (Pan-STARRS DR1) footprint, allowing tests of the primary calibrator for the ATLAS Refcat2 catalog. Initial offsets are at the $\sim$40 mmag scale. To improve this we determine $Δ$ zeropoint offsets for two cases: (1) pixel-to-pixel offsets within individual CCDs (reduced from $\sim$8 to $\sim$4 mmag RMS) and (2) chip-to-chip offsets across the 9 CCDs and filters (reduced from $\sim$17 to $\sim$3 mmag RMS). We also identify the largest systematic uncertainty as a transmission-function color dependence, requiring shifts in the assumed ATLAS filters at the $\sim$30 mmag level if uncorrected. We validate our calibration using (a) CALSPEC standards, (b) an independent tertiary catalog, and (c) distance moduli of cross-matched SNe~Ia, all showing improved consistency. Overall, we estimate combined calibration-related systematics at the $\sim$5--10 mmag level, supporting competitive cosmological constraints with the TITAN SN~Ia dataset.

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arXiv2024

Reconnaissance with JWST of the J-region Asymptotic Giant Branch in Distance Ladder Galaxies: From Irregular Luminosity Functions to Approximation of the Hubble Constant

We study stars in the J-regions of the asymptotic giant branch (JAGB) of near-infrared color magnitude diagrams in the maser host NGC 4258 and 4 hosts of 6 Type Ia supernovae (SN Ia): NGC 1448, NGC 1559, NGC 5584, and NGC 5643. These clumps of stars are readily apparent near $1.0<F150W-F277W<1.5$ and $m_{F150W}$=22-25 mag with James Webb Space Telescope NIRCam photometry. Various methods have been proposed to assign an apparent reference magnitude for this recently proposed standard candle, including the mode, median, sigma-clipped mean or a modeled luminosity function parameter. We test the consistency of these by measuring intra-host variations, finding differences of up to $\sim$0.2 mag that significantly exceed statistical uncertainties. Brightness differences appear intrinsic, and are further amplified by the non-uniform shape of the JAGB luminosity function, also apparent in the LMC and SMC. We follow a 'many methods' approach to consistently measure JAGB magnitudes and distances to the SN Ia host sample calibrated by NGC 4258. We find broad agreement with distances measured from Cepheids, tip of the red giant branch (TRGB), and Miras. However, the SN host mean distance estimated via the JAGB method necessary to estimate $H_0$ differs by $\sim$0.19 mag amongst the above definitions, a result of different levels of luminosity function asymmetry. The methods yield a full range of $71-78$ km s$^{-1}$ Mpc$^{-1}$, i.e., a fiducial result of $H_0=74.7\pm2.1$ (stat) $\pm$2.3 (sys) ($\pm$3.1 if combined in quadrature) km s$^{-1}$ Mpc$^{-1}$, with systematic errors limited by the differences in methods. Future work may seek to further standardize and refine this promising tool, making it more competitive with established distance indicators.

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arXiv2021

The Foundation Supernova Survey: Photospheric Velocity Correlations in Type Ia Supernovae

The ejecta velocities of type-Ia supernovae (SNe Ia), as measured by the Si II $λ6355$ line, have been shown to correlate with other supernova properties, including color and standardized luminosity. We investigate these results using the Foundation Supernova Survey, with a spectroscopic data release presented here, and photometry analyzed with the SALT2 light-curve fitter. We find that the Foundation data do not show significant evidence for an offset in color between SNe Ia with high and normal photospheric velocities, with $Δc = 0.005 \pm 0.014$. Our SALT2 analysis does show evidence for redder high-velocity SN Ia in other samples, including objects from the Carnegie Supernova Project, with a combined sample yielding $Δc = 0.017 \pm 0.007$. When split on velocity, the Foundation SN Ia also do not show a significant difference in Hubble diagram residual, $ΔHR = 0.015 \pm 0.049$ mag. Intriguingly, we find that SN Ia ejecta velocity information may be gleaned from photometry, particularly in redder optical bands. For high-redshift SN Ia, these rest-frame red wavelengths will be observed by the Nancy Grace Roman Space Telescope. Our results also confirm previous work that SN Ia host-galaxy stellar mass is strongly correlated with ejecta velocity: high-velocity SN Ia are found nearly exclusively in high-stellar-mass hosts. However, host-galaxy properties alone do not explain velocity-dependent differences in supernova colors and luminosities across samples. Measuring and understanding the connection between intrinsic explosion properties and supernova environments, across cosmic time, will be important for precision cosmology with SNe Ia.

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arXiv2020

Photometric Classification of 2315 Pan-STARRS1 Supernovae with Superphot

The classification of supernovae (SNe) and its impact on our understanding of the explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming wide-field time-domain surveys have increased the transient discovery rate far beyond our capacity to obtain even a single spectrum of each new event. We must therefore rely heavily on photometric classification, connecting SN light curves back to their spectroscopically defined classes. Here we present Superphot, an open-source Python implementation of the machine-learning classification algorithm of Villar et al., and apply it to 2315 previously unclassified transients from the Pan-STARRS1 Medium Deep Survey for which we obtained spectroscopic host-galaxy redshifts. Our classifier achieves an overall accuracy of 82%, with completenesses and purities of >80% for the best classes (SNe Ia and superluminous SNe). For the worst performing SN class (SNe Ibc), the completeness and purity fall to 37% and 21%, respectively. Our classifier provides 1257 newly classified SNe Ia, 521 SNe II, 298 SNe Ibc, 181 SNe IIn, and 58 SLSNe. These are among the largest uniformly observed samples of SNe available in the literature and will enable a wide range of statistical studies of each class.

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arXiv2020

SuperRAENN: A Semi-supervised Supernova Photometric Classification Pipeline Trained on Pan-STARRS1 Medium Deep Survey Supernovae

Automated classification of supernovae (SNe) based on optical photometric light curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin Observatory. Photometric classification can enable real-time identification of interesting events for extended multi-wavelength follow-up, as well as archival population studies. Here we present the complete sample of 5,243 "SN-like" light curves (in griz) from the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). The PS1-MDS is similar to the planned LSST Wide-Fast-Deep survey in terms of cadence, filters and depth, making this a useful training set for the community. Using this dataset, we train a novel semi-supervised machine learning algorithm to photometrically classify 2,315 new SN-like light curves with host galaxy spectroscopic redshifts. Our algorithm consists of a random forest supervised classification step and a novel unsupervised step in which we introduce a recurrent autoencoder neural network (RAENN). Our final pipeline, dubbed SuperRAENN, has an accuracy of 87% across five SN classes (Type Ia, Ibc, II, IIn, SLSN-I). We find the highest accuracy rates for Type Ia SNe and SLSNe and the lowest for Type Ibc SNe. Our complete spectroscopically- and photometrically-classified samples break down into: 62.0% Type Ia (1839 objects), 19.8% Type II (553 objects), 4.8% Type IIn (136 objects), 11.7% Type Ibc (291 objects), and 1.6% Type I SLSNe (54 objects). Finally, we discuss how this algorithm can be modified for online LSST data streams.

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arXiv2019

Constraining Temporal Oscillations of Cosmological Parameters Using Type Ia Supernovae

The existing set of type Ia supernovae (SNe Ia) is now sufficient to detect oscillatory deviations from the canonical $Λ$CDM cosmology. We determine that the Fourier spectrum of the Pantheon data set of spectroscopically well-observed SNe Ia is consistent with the predictions of $Λ$CDM. We also develop and describe two complementary techniques for using SNe Ia to constrain those alternate cosmological models that predict deviations from $Λ$CDM that are oscillatory in conformal time. The first technique uses the reduced $χ^2$ statistic to determine the likelihood that the observed data would result from a given model. The second technique uses bootstrap analysis to determine the likelihood that the Fourier spectrum of a proposed model could result from statistical fluctuations around $Λ$CDM. We constrain three oscillatory alternate cosmological models: one in which the dark energy equation of state parameter oscillates around the canonical value of $w_Λ = -1$, one in which the energy density of dark energy oscillates around its $Λ$CDM value, and one in which gravity derives from a scalar field evolving under an oscillatory coupling. We further determine that any alternate cosmological model that produces distance modulus residuals with a Fourier amplitude of $\simeq 36$ millimags is strongly ruled out, given the existing data, for frequencies between $\simeq 0.08\ \textrm{Gyr}^ {-1} h_{100}$ and $\simeq 80\ \textrm{Gyr}^ {-1} h_{100}$.

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arXiv2019

WFIRST: Enhancing Transient Science and Multi-Messenger Astronomy

Astrophysical transients have been observed for millennia and have shaped our most basic assumptions about the Universe. In the last century, systematic searches have grown from detecting handfuls of transients per year to over 7000 in 2018 alone. As these searches have matured, we have discovered both large samples of "normal" classes and new, rare classes. Recently, a transient was the first object observed in both gravitational waves and light. Ground-based observatories, including LSST, will discover thousands of transients in the optical, but these facilities will not provide the high-fidelity near-infrared (NIR) photometry and high-resolution imaging of a space-based observatory. WFIRST can fill this gap. With its survey designed to measure the expansion history of the Universe with Type Ia supernovae, WFIRST will also discover and monitor thousands of other transients in the NIR, revealing the physics for these high-energy events. Small-scale GO programs, either as a supplement to the planned survey or as specific target-of-opportunity observations, would significantly expand the scope of transient science that can be studied with WFIRST.

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arXiv2019

LSST Target of Opportunity proposal for locating a core collapse supernova in our galaxy triggered by a neutrino supernova alert

A few times a century, a core collapse supernova (CCSN) occurs in our galaxy. When such galactic CCSNe happen, over 99\% of its gravitational binding energy is released in the form of neutrinos. Over a period of tens of seconds, a powerful neutrino flux is emitted from the collapsing star. When the exploding shock wave finally reaches the surface of the star, optical photons escaping the expanding stellar envelope leave the star and eventually arrive at Earth as a visible brightening. Crucially, although the neutrino signal is prompt, the time to the shock wave breakout can be minutes to many hours later. This means that the neutrino signal will serve as an alert, warning the optical astronomy community the light from the explosion is coming. Quickly identifying the location of the supernova on the sky and disseminating it to the all available ground and spaced-based instruments will be critical to learn as much as possible about the event. Some neutrino experiments can report pointing information for these galactic CCSNe. In particular, the Super-Kamiokande experiment can point to a few degrees for CCSNe near the center of our galaxy. A CCSN located 10 kpc from Earth is expected to result in a pointing resolution on the order of 3 degrees. LSST's field of view (FOV) is well matched to this initial search box. LSSTs depth is also uniquely suited for identifying CCSNe even if they fail or are obscured by the dust of the galactic plane. This is a proposal to, upon receipt of such an alert, prioritize the use of LSST for a full day of observing to continuously monitor a pre-identified region of sky and, by using difference imaging, identify and announce the location of the supernova.

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arXiv2018

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey

Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collaboration (DESC) has been tasked with deriving constraints on cosmological parameters from LSST data. Each of the cosmological probes for LSST is heavily impacted by the choice of observing strategy. This white paper is written by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy that will benefit all cosmological analyses with LSST. It is accompanied by the DESC DDF (Deep Drilling Fields) white paper (Scolnic et al.). We use a variety of metrics to understand the effects of the observing strategy on measurements of weak lensing, large-scale structure, clusters, photometric redshifts, supernovae, strong lensing and kilonovae. In order to reduce systematic uncertainties, we conclude that the current baseline observing strategy needs to be significantly modified to result in the best possible cosmological constraints. We provide some key recommendations: moving the WFD (Wide-Fast-Deep) footprint to avoid regions of high extinction, taking visit pairs in different filters, changing the 2x15s snaps to a single exposure to improve efficiency, focusing on strategies that reduce long gaps (>15 days) between observations, and prioritizing spatial uniformity at several intervals during the 10-year survey.

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arXiv2018

Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Deep Drilling Fields and other Special Programs

We review the measurements of dark energy enabled by observations of the Deep Drilling Fields and the optimization of survey design for cosmological measurements. This white paper is the result of efforts by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy for the DDFs that will benefit all cosmological analyses with LSST. It is accompanied by the DESC-WFD white paper (Lochner et al.). We argue for altering the nominal deep drilling plan to have $>6$ month seasons, interweaving $gri$ and $zy$ observations every 3 days with 2, 4, 8, 25, 4 visits in $grizy$, respectively. These recommendations are guided by metrics optimizing constraints on dark energy and mitigation of systematic uncertainties, including specific requirements on total number of visits after Y1 and Y10 for photometric redshifts (photo-$z$) and weak lensing systematics. We specify the precise locations for the previously-chosen LSST deep fields (ELAIS-S1, XMM-LSS, CDF-S, and COSMOS) and recommend Akari Deep Field South as the planned fifth deep field in order to synergize with Euclid and WFIRST. Our recommended DDF strategy uses $6.2\%$ of the LSST survey time. We briefly discuss synergy with white papers from other collaborations, as well as additional mini-surveys and Target-of-Opportunity programs that lead to better measurements of dark energy.

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arXiv2018

PS1-13cbe: The Rapid "Turn on" of a Seyfert 1

We present a nuclear transient event, PS1-13cbe, that was first discovered in the Pan-STARRS1 survey in 2013. The outburst occurred in the nucleus of the galaxy SDSS J222153.87+003054.2 at $z = 0.12355$, which was classified as a Seyfert 2 in a pre-outburst archival Sloan Digital Sky Survey (SDSS) spectrum. PS1-13cbe showed the appearance of strong broad H$α$ and H$β$ emission lines and a non-stellar continuum in a Magellan spectrum taken 57 days after the peak of the outburst that resembled the characteristics of a Seyfert 1. These broad lines were not present in the SDSS spectrum taken a decade earlier and faded away within two years, as observed in several late-time MDM spectra. We argue that the dramatic appearance and disappearance of the broad lines and factor of $\sim 8$ increase in the optical continuum is most likely caused by variability in the pre-existing accretion disk than a tidal disruption event, supernova, or variable obscuration. The timescale for the turn-on of the optical emission of $\sim 70$ days observed in this transient is among the shortest observed in a "changing look" active galactic nucleus.

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arXiv2017

Type Ia Supernova Distances at z > 1.5 from the Hubble Space Telescope Multi-Cycle Treasury Programs: The Early Expansion Rate

We present an analysis of 15 Type Ia supernovae (SNe Ia) at redshift z > 1 (9 at 1.5 < z < 2.3) recently discovered in the CANDELS and CLASH Multi-Cycle Treasury programs using WFC3 on the Hubble Space Telescope. We combine these SNe Ia with a new compilation of 1050 SNe Ia, jointly calibrated and corrected for simulated survey biases to produce accurate distance measurements. We present unbiased constraints on the expansion rate at six redshifts in the range 0.07 < z < 1.5 based only on this combined SN Ia sample. The added leverage of our new sample at z > 1.5 leads to a factor of ~3 improvement in the determination of the expansion rate at z = 1.5, reducing its uncertainty to ~20%, a measurement of H(z=1.5)/H0=2.67 (+0.83,-0.52). We then demonstrate that these six measurements alone provide a nearly identical characterization of dark energy as the full SN sample, making them an efficient compression of the SN Ia data. The new sample of SNe Ia at z > 1 usefully distinguishes between alternative cosmological models and unmodeled evolution of the SN Ia distance indicators, placing empirical limits on the latter. Finally, employing a realistic simulation of a potential WFIRST SN survey observing strategy, we forecast optimistic future constraints on the expansion rate from SNe Ia.

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arXiv2016

Host Galaxy Identification for Supernova Surveys

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey.

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arXiv2016

SDSS-II Supernova Survey: An Analysis of the Largest Sample of Type Ia Supernovae and Correlations with Host-Galaxy Spectral Properties

Using the largest single-survey sample of Type Ia supernovae (SNe Ia) to date, we study the relationship between properties of SNe Ia and those of their host galaxies, focusing primarily on correlations with Hubble residuals (HR). Our sample consists of 345 photometrically-classified or spectroscopically-confirmed SNeIa discovered as part of the SDSS-II Supernova Survey (SDSS-SNS). This analysis utilizes host-galaxy spectroscopy obtained during the SDSS-I/II spectroscopic survey and from an ancillary program on the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) that obtained spectra for nearly all host galaxies of SDSS-II SN candidates. In addition, we use photometric host-galaxy properties from the SDSS-SNS data release (Sako et al. 2014) such as host stellar mass and star-formation rate. We confirm the well-known relation between HR and host-galaxy mass and find a 3.6σ significance of a non-zero linear slope. We also recover correlations between HR and host-galaxy gas-phase metallicity and specific star-formation rate as they are reported in the literature. With our large dataset, we examine correlations between HR and multiple host-galaxy properties simultaneously and find no evidence of a significant correlation. We also independently analyze our spectroscopically-confirmed and photometrically-classified SNe Ia and comment on the significance of similar combined datasets for future surveys.

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arXiv2015

Two Type Ia Supernovae at Redshift ~2 : Improved Classification and Redshift Determination with Medium-band Infrared Imaging

We present two supernovae (SNe) discovered with the Hubble Space Telescope (HST) in the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS), an HST multi-cycle treasury program. We classify both objects as Type Ia SNe and find redshifts of z = 1.80+-0.02 and 2.26 +0.02 -0.10, the latter of which is the highest redshift Type Ia SN yet seen. Using light curve fitting we determine luminosity distances and find that both objects are consistent with a standard Lambda-CDM cosmological model. These SNe were observed using the HST Wide Field Camera 3 infrared detector (WFC3-IR), with imaging in both wide- and medium-band filters. We demonstrate that the classification and redshift estimates are significantly improved by the inclusion of single-epoch medium-band observations. This medium-band imaging approximates a very low resolution spectrum (lambda/delta lambda ~ 100) which can isolate broad spectral absorption features that differentiate Type Ia SNe from their most common core collapse cousins. This medium-band method is also insensitive to dust extinction and (unlike grism spectroscopy) it is not affected by contamination from the SN host galaxy or other nearby sources. As such, it can provide a more efficient - though less precise - alternative to IR spectroscopy for high-z SNe.

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arXiv2015

Reconsidering the Effects of Local Star Formation On Type Ia Supernova Cosmology

Recent studies found a correlation with $\sim$3 sigma significance between the local star formation measured by GALEX in Type Ia supernova (SN Ia) host galaxies and the distances or dispersions derived from these SNe. We search for these effects by using data from recent cosmological analyses to greatly increase the SN Ia sample; we include 179 GALEX-imaged SN Ia hosts with distances from the JLA and Pan-STARRS SN Ia cosmology samples and 157 GALEX-imaged SN Ia hosts with distances from the Riess et al. (2011) H$_0$ measurement. We find little evidence that SNe Ia in locally star-forming environments are fainter after light curve correction than SNe Ia in locally passive environments. We find a difference of only 0.000$\pm$0.018 (stat+sys) mag for SNe fit with SALT2 and 0.029$\pm$0.027 (stat+sys) mag for SNe fit with MLCS2k2 (R$_V$ = 2.5), which suggests that proposed changes to recent measurements of H$_0$ and w are not significant and numerically smaller than the parameter measurement uncertainties. We find the greatly reduced significance of these distance modulus differences compared to Rigault et al. (2013) and Rigault et al. (2015) result from two improvements with fairly equal effects, our larger sample size and the use of JLA and Riess et al. (2011) sample selection criteria. Without these improvements, we recover the results of Rigault et al. (2015). We find that both populations have more similar dispersion in distance than found by Rigault et al. (2013), Rigault et al. (2015), and Kelly et al. (2015), with slightly smaller dispersion for locally passive SNe Ia fit with MLCS, the opposite of the effect seen by Rigault et al. (2015) and Kelly et al. (2015). We caution that measuring local SNe Ia environments in the future may require a higher-resolution instrument than GALEX and that SN sample selection has a significant effect on local star formation biases.

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arXiv2013

Color Dispersion and Milky Way Reddening Among Type Ia Supernovae

Past analyses of Type Ia Supernovae (SNe Ia) have identified an irreducible scatter of 5-10% in distance widely attributed to an intrinsic dispersion in luminosity. Another, equally valid, source of this scatter is intrinsic dispersion in color. Misidentification of the true source of this scatter can bias both the retrieved color-luminosity relation and cosmological parameter measurements. The size of this bias depends on the magnitude of the intrinsic color dispersion relative to the distribution of colors that correlate with distance. We produce a realistic simulation of a misattribution of intrinsic scatter, and find a negative bias in the recovered color-luminosity relation, beta, of dbeta -1.0 (~33%) and a positive bias in the equation of state parameter, w, of dw +0.04 (~4%). We re-analyze current published data sets with the assumptions that the distance scatter is predominantly the result of color. Unlike previous analyses, we find that the data are consistent with a Milky Way reddening law R_V=3.1, and that a Milky Way dust model better predicts the asymmetric color-luminosity trends than the conventional luminosity scatter hypothesis. We also determine that accounting for color variation reduces the correlation between various Host galaxy properties and Hubble residuals by ~20%.

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