Greg Aldering, Lawrence Berkeley National Lab
Flux Calibration for Measuring Dark Energy with SNe Ia

October 3, 2019 (9:00 AM - 9:20 AM)

PDF, 15.89 MB
Co-authors: David Rubin, Daniel Kusters, Saul Perlmutter, Marek Kowalkski
A solution to the issue of wavelength-neutral flux calibration is central to the success of current and future measurements of the dark energy equation of state based on SNe Ia. This talk will discuss work on flux calibration for the Nearby Supernova Factory dataset, including the use of existing spectrophotometric standard stars, the need for detailed testing of instrument and software to control systematics, and progress towards establishing a laboratory-referenced wavelength-neutral flux calibration using the Supernova CALlibration Apparatus.
Anita Bahmanyar, University of Toronto
Constraining Cosmology with Galaxy Peculiar Velocities Using SNe Ia

October 4, 2019 (11:10 AM - 11:30 AM)

PDF, 0.86 MB
Co-authors: Renee Hlozek, Rahul Biswas
Galaxy peculiar velocities are correlated with the clustering of matter which would give us a tool to study the distribution of matter in the Universe. Supernovae Type Ia inherit peculiar velocity of their host galaxies, which can be used to study large-scale structure as they are better distance indicators than galaxy Tully-Fisher method. LSST will detect a large number of supernovae that can be used for this study. We illustrate the power of LSST to constrain the growth of structure at intermediate redshift, complementing low-redshift studies of supernovae. Predictions of how precise measurements of peculiar velocities need to be to constrain cosmological parameters can motivate higher observing cadences for LSST which would result in better distance estimations. We will discuss the impact of proposed cadences of the Deep Drilling Fields (DDF) and Wide Fast Deep (WFD) surveys on peculiar velocity science and how well we can measure $fsigma_8$. We will discuss challenges of photometric surveys for peculiar velocity studies in terms of redshift estimation and classification. Lastly, We will place LSST constraints in the broader cosmological context.
Martin Briday, CNRS/IN2P3
Comparing Type Ia Supernovae environmental tracers

October 3, 2019 (4:00 PM - 4:20 PM)

PDF, 12.72 MB
Co-authors: Mickael Rigault, Romain Graziani
Type Ia Supernovae (SNeIa) are standards candles that enable us to measure the recent expansion rate of the Universe. However, their true nature remains unknown, and potential astrophysical dependences of SNeIa that may vary between redshift and/or survey may bias cosmological measurements if not properly accounted for. Last decades studies have shown several relations between SNeIa properties and those of their host galaxy. Yet, the correct way to account for the astrophysical effects remains uncertain as various teams find various results — sometime even discrepant — when using various tracers. We propose to compare these different environmental analyses methods previously used in light of their ability to accurately trace fondamental SN astrophysical parameters, and notably the progenitor age. We show, as expected, that host colors and Halpha-based specific star formation rate are better age indicator than, say, morphology. More importantly we show that these known accuracy variations actually explain the discrepancy between the SN magnitude step observed when using different environmental tracers
Dillon Brout, UPenn
Photometric SNIa Cosmology without Core Collapse Spectral Time Series

October 4, 2019 (9:00 AM - 9:20 AM)

PDF, 2.11 MB
Co-authors: Daniel Scolnic
Photometric supernova cosmology has thus far been accomplished using detailed and costly spectral time series templates of non-Ia supernovae. I will discuss the ability of photometric color templates of known core collapse events to develop a training dataset for photometric typing that perform equally well on both simulated and real datasets.
Sam Dixon, UC Berkeley/LBNL
Using SNEMO to Prepare for Future Supernova Surveys

October 2, 2019 (2:20 PM - 2:40 PM)

PDF, 1.46 MB
Type Ia supernovae continue to be one of the best tools for measuring cosmological distances. However, photometric studies of supernovae are currently limited in their use for cosmology by as yet unmodeled dispersion in standardized magnitudes. I'll discuss SNEMO, a new empirical model of Type Ia supernova spectral time series that captures more of the spectral diversity responsible for this remaining dispersion than can be captured by traditional light-curve-based SED models. I'll also present new tools for simulating spectroscopic and photometric observations using SNEMO as the underlying SED model. Using these tools, we explore new analyses that are uniquely enabled by this model, including evaluations of our ability to find spectroscopic twins and to probe population evolution with redshift. These analyses will be an important piece of the puzzle in assessing the cosmological impact of various survey strategies for upcoming projects like WFIRST and LSST.
Ryan Foley, UC Santa Cruz
Breaking through the Nearby Barrier (Foundation)

October 2, 2019 (10:00 AM - 10:15 AM)

PDF, 10.88 MB
Co-authors: Foundation Supernova Survey, Swope Supernova Survey, UC Santa Cruz Transient Team
Constraints on the Hubble constant and the dark energy equation-of-state parameter are currently both limited by the nearby (z < 0.1) sample of Type Ia supernovae (SNe Ia), the analysis tools informed by a nearby sample, and unconstrained SN physics best investigated with nearby, bright SNe. I will present the next-generation SN sample with photometry from the Foundation Supernova Survey and the Swope Supernova Survey (~500 high-fidelity light curves) and corresponding spectroscopy (>5000 spectra) stored in the Kaepora relational database. With these data, we are (1) updating the low-z Hubble-flow sample, anchoring cosmological analyses, (2) significantly increasing the number of possible Cepheid calibrators, and (3) determining the explosion properties (and corresponding observables) that cause intrinsic scatter. In addition to presenting these data and tool, I will present highly significant differences in the spectra of SNe Ia with positive and negative Hubble residuals.
Philippe Gris, LPC/IN2P3/CNRS
LSST Observing Strategy and Supernovae

October 2, 2019 (11:15 AM - 11:30 AM)

PDF, 1.9 MB
Co-authors: Nicolas Regnault
Recent assessment of LSST observing strategies has shown that it may be possible to observe O(10^5) well-measured type Ia supernovae after ten years. This opens up new opportunities for supernovae cosmology such as anisotropies studies or measurements of galaxy peculiar velocity. This presentation will be a summary of the latest developments regarding interplay between observing strategies and supernovae science. It will be shown that the close relation between strategy parameters and quality of the supernovae light curves provides guidance on the best observing strategy for supernovae cosmology.
Samuel R Hinton, University of Queensland
A supernovae cosmology pipeline to streamline analyses

October 3, 2019 (11:50 AM - 12:10 PM)

PDF, 1.76 MB
Co-authors: DES Collaboration
The current state of supernovae cosmology involves utilising a variety of disparate tools written in different programming languages. As such, past analyses pipelines have required a huge labour overhead as researchers manually invoke programs, translate output and manipulate files by hand. Pippin is designed to simplify this process, by wrapping various tools used in supernovae cosmology pipelines into a configurable task-based system to allow simplistic execution and monitoring of an entire analysis pipeline.
Isobel Hook, Lancaster University
Photometric classification of transients using a simulated 4MOST spectroscopic training sample

October 4, 2019 (9:20 AM - 9:40 AM)

PDF, 1.23 MB
Co-authors: Jon Carrick
Although the next generation of large supernova surveys will generate enormous numbers of supernovae, spectroscopic follow-up resources will be limited, and it will not be possible to obtain spectroscopic classification for all the supernovae. The TiDES survey that is currently being planned with the 4MOST instrument is well-suited to spectroscopic follow-up of transients discovered by LSST, and their host galaxies. However, the live spectra from 4MOST-TiDES will be a subset of all LSST transients and will be limited to brighter objects (with a limit of about m=22.5 mag). We are carrying out simulations to test the effectiveness of such a sample of spectra as a training sample for photometric classification of the bulk of LSST transients. Our initial simulations are carried out using snmachine (Lochner et al 2016) machine-learning algorithms. We present results of tests that are being carried out with the ultimate goal of optimising the use of 4MOST spectroscopic time for Type Ia SN cosmology.
Rebekah Hounsell, University of Pennsylvania

October 2, 2019 (11:45 AM - 12:00 PM)

PDF, 15.69 MB
Co-authors: DES collaboration
Using data from the DES-SN program we perform an analysis on a complete sample of nearby core-collapse supernovae (CC SN). Within this talk I describe the procedures for identifying the CC SN candidates and the construction of a new set of light-curve and spectral templates, which will enable improvements in photometric SN classification as well as studies of biases in photometric SN Ia cosmological measurements by CC SN contamination
Saurabh W Jha, Rutgers University
SN Ia Distances in the Infrared

October 2, 2019 (3:20 PM - 3:40 PM)

PDF, 13.36 MB
Co-authors: TBD
I will discuss the current state of and future prospects for SN Ia distances from near-infrared photometry. I will present applications to the Hubble constant and dark energy equation of state. I will highlight what we can expect from WFIRST and what we need to do now to prepare.
David O Jones, UC Santa Cruz
Progress and Challenges with Photometrically Classified SNIa

October 3, 2019 (1:50 PM - 2:10 PM)

PDF, 3.56 MB
Co-authors: Daniel Scolnic, Ryan Foley, Rick Kessler
The ability to measure robust cosmological constraints from samples of Type Ia supernovae (SNe Ia) without spectroscopic classifications is key to the next generation of cosmological constraints from DES, LSST and WFIRST. I will discuss lessons learned from some of the recent measurements of cosmological parameters from the Pan-STARRS photometrically classified SN Ia sample and the continuing challenges that we face in understanding and marginalizing over core-collapse (CC) SN contamination.
Lisa G Kelsey, University of Southampton
The Effect of Local Environment on SNIa in the Dark Energy Survey

October 3, 2019 (3:40 PM - 4:00 PM)

PDF, 5.57 MB
Co-authors: Mat Smith, Mark Sullivan, Phil Wiseman
Type Ia supernovae (SNe Ia) are vital cosmological probes as standardisable candles, due to their brightness and low intrinsic luminosity dispersion. They have been used to reveal the accelerating expansion of the universe, and place constraints on the cosmological parameters. However, there remains a puzzling ∼0.15mag dispersion in their peak magnitudes that is not understood. This has prompted a search for further light curve corrections. Recent studies have found that the corrected brightness correlates with the stellar mass of the supernova host galaxy. After standardisation, SN Ia in high-mass, passive hosts are brighter than those in lower-mass, star-forming regions. It has been suggested that the stellar mass acts as a proxy for the galactic characteristics and supernova progenitor and could be utilised as an additional light curve correction parameter. Here, we compare local and global properties of the host galaxies of the Dark Energy Survey 3-year spectroscopically confirmed SNe Ia, with a redshift range of 0.05 < z < 0.85. We perform photometric measurements of the host and local aperture photometry within a fixed proper distance radius centred around the locations of the supernovae in griz filter bands. Spectral Energy Distribution (SED) fitting is then applied to both the global and local photometry, from which we calculate the host galaxy star formation rate, stellar mass, and rest-frame U-V colour. We compare these quantities against the SN Ia corrected luminosity to find the most effective host galaxy correction to use in cosmological analysis.
William D Kenworthy, Johns Hopkins University
Hubble Tension: Local Structure Doesn’t Impact Measurement of H0

October 4, 2019 (11:30 AM - 11:50 AM)

PDF, 1.7 MB
Co-authors: Dan Scolnic, Adam Riess
We use the largest sample to date of spectroscopic SN Ia distances and redshifts to look for evidence in the Hubble diagram of large scale outflows caused by local voids suggested to exist at z<0.15. Our sample combines data from the Pantheon sample with the Foundation survey and the most recent release of lightcurves from the Carnegie Supernova Project to create a sample of 1295 SNe over a redshift range of 0.01<z<2.26. We make use of an inhomogeneous and isotropic Lemaitre-Tolman-Bondi metric to model a void in the SN Ia distance-redshift relation. We conclude that the SN luminosity distance-redshift relation is inconsistent at the 4-5 sigma confidence level with large local underdensities (|delta| > 20%, where the density contrast delta = Delta rho /rho) proposed in some galaxy count studies, and find no evidence of a change in the Hubble constant corresponding to a void with a sharp edge in the redshift range 0.023<z<0.15. With empirical precision of sigma_H_0 = 0.60%, we conclude that the distance ladder measurement is not affected by local density contrasts, in agreement with cosmic variance of sigma_H_0 = 0.42% predicted from simulations of large-scale structure. Given that uncertainty in the distance ladder value is sigma_H_0=2.2%, this does not affect the Hubble tension. We derive a 5 sigma constraint on local density contrasts on scales larger than 69 megaparsec h^-1 of delta < 27%. The presence of local structure does not appear to impede the possibility of measuring the Hubble constant to 1% precision
Richard Kessler, University of Chicago
BBC Hubble diagram corrected for selection effects and contamination

October 3, 2019 (11:30 AM - 11:50 AM)

PDF, 2.2 MB
Young-Lo Kim, CNRS/IN2P3/IP2I Lyon
SEDMachine for SN Cosmology: Typing and Redshifts for SNe

October 2, 2019 (9:30 AM - 9:45 AM)

PDF, 10.83 MB
Co-authors: Mickael Rigault
Redshift and classification for Type Ia supernova (SN Ia) are currently crucial to build the Hubble diagram and study the peculiar velocities of nearby galaxies. However, it is challenging to acquire all of the necessary SN Ia information discovered by current and future time-domain surveys, which (will) find hundreds of new SNe every week. Here we present the SEDMachine, a very-low resolution and fully automated integral field spectrograph (IFS) dedicated to classify transients discovered by the ZTF survey. Since the SEDMachine is an IFS, it collects more than just the transient spectra. It also observes the transient vicinity and thereby almost always its host galaxy. In this talk, we will present the SEDMachine, the automated pipeline «pysedm», the IFS performances and our current work on automatic extraction of transient redshift, together with its typing.
Kaisey S Mandel, University of Cambridge
A new hierarchical Bayesian model for SN Ia optical and NIR data

October 2, 2019 (3:40 PM - 4:00 PM)

PDF, 11.7 MB
I will describe a new, extended hierarchical Bayesian statistical model for SN Ia optical and infrared time series data. Hierarchical Bayes offers a principled approach for coherent inference and uncertainty quantification for individual SNe and their population. This is done by probabilistically modelling the generative processes underlying the observed data, including multiple random and physical effects and systematic uncertainties, such as measurement error, host galaxy dust, and intrinsic variations of the latent spectral energy distribution, correlated across time and wavelength. I will describe applications of the model to SN Ia optical and near-infrared datasets.
Florian Mondon, LPC/IN2p3
Cosmological biases from new variability detected in SNIa

October 2, 2019 (2:40 PM - 3:00 PM)

PDF, 3.66 MB
Co-authors: Pierre-François Leget, Emmanuel Gangler
Distances measured using Type Ia supernovae (SNIa) are an excellent way of constraining the equation of state of the dark energy. However, the brightnesses of these SNIa have variabilities due to internal mechanisms or environmental effects that have to be accounted for. Empirical models of the SNIa spectral energy distribution can be employed to standardize these objects. One of the most efficient of such models is the Spectral Adaptative Light-curve Template 2 (SALT2) developed by Guy et al. (2007). This model uses a standardization based on stretch and color, which are the best known sources of variability in SNIa. A new model called SUpernova Generator And Reconstructor (SUGAR) was proposed by Léget et al. (submitted), who showed with the help of the data from the Nearby Supernova Factory, that two new sources of variability have to be taken into account. In this presentation, we aim to check the impact of these new variabilities on cosmological analysis by fitting supernovae light curves with SUGAR and by using these parameters for standardization. Furthermore, we also intend to analyse the impact of SUGAR in the correlation between Hubble residuals and host galaxy properties.
Anais Möller, CNRS / LPC Clermont-Ferrand
SuperNNova: statistical soundness of ML classifiers and SNIa cosmology

October 4, 2019 (10:00 AM - 10:20 AM)

PDF, 7.62 MB
In this era of photometric SNIa cosmology, when using machine learning classifiers, a high accuracy algorithm is not enough, it is equally important to show that it is statistically sound. In this talk, I will present SuperNNova, an open source Neural Network framework that is able to obtain photometric samples with purities similar to those of spectroscopically selected samples, <2% contamination, as well to provide a Bayesian interpretation. I will present what we have learnt from applying SuperNNova to simulated and real data and the extensive tests we devised to estimate its robustness. I will emphasize the importance of properly calibrated classification probabilities and the additional information that provide epistemic uncertainties when dealing with representativeness issues and out-of-distribution events.
Gautham S Narayan, University of Illinois
Improving SNIa Cosmological Studies with Host-galaxy Information

October 3, 2019 (2:40 PM - 3:00 PM)

PDF, 8.52 MB
Co-authors: Alex Gagliano (UIUC), Andrew Engel (UIUC)
Host galaxy information can help a photometric SNIa cosmology analysis by improving classification performance, as well as improving photometric redshift and distance estimates. I will detail our efforts to use SDSS, PS1 and DES data, either in the form of derived features, such as photometry and shape information, or directly using the postage stamps, to infer the correlations between supernovae of different kinds and their host environments. These correlations can be used to improve classifiers and alert broker systems, as well as update SNIa light curve fitters, and I will describe our efforts towards this end.
Christina Peters, Dunlap Institute for Astronomy & Astrophysics, University of Toronto
Simulating Data for Validation of Photometric Supernova Cosmology

October 3, 2019 (11:10 AM - 11:30 AM)

Co-authors: A. I. Malz, R. Hlozek
Supernova Cosmology Inference with Probabilistic Photometric Redshifts (scippr) is a model that tries to answer the question: How does one perform cosmological analysis on a hetereogenous population of supernovae without certainty in either the specific type of object or the redshift of both the object and its potential host? The biggest difference between scippr and standard approaches to SN Ia cosmology is the fact that the traditional Hubble diagram of z and mu(z) is absent. Instead, the input data are probability distributions over redshift and distance modulus, which could be generated from light curve points and host galaxy fluxes/colors. Developing codes that produce these probability distributions is an active area of research in the community; however, such codes are not currently available. Thus, in order to do a proof of concept for scippr, it is necessary to simulate our input data. In this talk, I will outline the forward model we use for the simulations. I will discuss the assumptions that were necessary (for example: cosmology and relative proportions of supernova types) and the improvements that can be made (for example: improving our understanding where non-Ia SNe end up on a Hubble diagram) in order to create more accurate probability distributions for various types of SNe in redshift and distance modulus.
Justin Pierel, University of South Carolina
Turning Gravitationally Lensed Supernovae into Cosmological Probes

October 4, 2019 (2:00 PM - 2:20 PM)

PDF, 5.47 MB
Co-authors: Steven Rodney
Recently, there have been two landmark discoveries of gravitationally lensed supernovae: the first multiply-imaged SN, "Refsdal", and the first Type Ia SN resolved into multiple images, SN iPTF16geu. Fitting the multiple light curves of such objects can deliver measurements of the lensing time delays, which are the difference in arrival times for the separate images. These measurements provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Over the next decade, accurate time delay measurements will be needed for the tens to hundreds of lensed SNe to be found by wide-field time-domain surveys such as LSST and WFIRST. We have developed an open source software package for simulations and time delay measurements of multiply-imaged SNe, including an improved characterization of the uncertainty caused by microlensing. We describe simulations using the package that suggest a before-peak detection of the leading image enables a more accurate and precise time delay measurement (by ~1 and ~2 days, respectively), when compared to an after-peak detection. We also conclude that fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data, but that employing a Gaussian Process Regression (GPR) technique is sufficient for determining the uncertainty due to microlensing.
Kara Ponder, UC Berkeley
The Nearby Supernova Factory - Science and Data Overview

October 2, 2019 (9:45 AM - 10:00 AM)

PDF, 2.56 MB
Co-authors: The Nearby Supernova Factory.
The Nearby Supernova Factory (SNfactory) has obtained optical integral-field spectroscopy for over 1000 supernovae, including spectrophotometric time series for over 300 Type Ia Supernovae (SNe Ia) predominantly in the smooth Hubble flow. We will show some statistics and illustrative validation tests from our most recent data reduction, which are the result of implementing corrections for a number of subtle instrument and software effects. We will then provide an overview of a few recent science analyses obtained from these data, such as improved non-linear standardization and exploration of several different facets of the dust extinction problem.
Brodie Popovic, Duke University
A Re-analysis of the SDSS Photometric SN Sample

October 3, 2019 (1:30 PM - 1:50 PM)

PDF, 1.67 MB
Co-authors: Dan Scolnic
Future progress in improving the precision of measurements of cosmological parameters with Type Ia Supernovae (SNIa) will come from large photometric SN samples. Here we revisit the SDSS photometric SN sample, with roughly 850 high-quality, likely but unidentified SNIa light-curves to develop new tools for analyses of photometric SN samples. We simulate realistic catalogs of host galaxies and cross-match them against the real data sample in order to identify and account for systematics unique to photometric samples. These systematics include the correlations of host galaxy parameters with SNIa luminosity, host galaxy selection, and different classification libraries such as PLASTICC. Overall, we show the key systematic uncertainties unique to photometric samples are on the order of 1%, which requires continued study but will be an important but surmountable issue for future experiments with DES, LSST and WFIRST
Wahidur Rahman, Imperial College London
A Bayesian Approach to Selection Effects Modelling

October 3, 2019 (10:50 AM - 11:10 AM)

PDF, 5.82 MB
Co-authors: David van Dyk, Wahidur Rahman, Timothy Makinen, Vicent Chen, Evan Tey
A Bayesian Approach to Selection Effects Modelling
Nicolas Regnault, CNRS/IN2P3
New calibration methods

October 3, 2019 (9:40 AM - 10:00 AM)

PDF, 2.97 MB
Adam Riess, STScI/JHU
Expansion of the Universe, Faster Than We Thought

October 4, 2019 (1:40 PM - 2:00 PM)

PDF, 15.46 MB
Co-authors: SH0ES Team (Scolnic, Macri, Casertano, Yuan, Huang, Hoffman, Filippenko)
Mickael Rigault, CNRS/IN2P3
Environmental bias and H0 tension

October 3, 2019 (4:20 PM - 4:40 PM)

PDF, 13.91 MB
Type Ia supernova are powerful cosmological distance indicators that enable us to measure the expansion history of the Universe. Using SNe Ia distances, scientists discovered the accelerating expansion of the Universe, leading to a Nobel prize and a broad focus on understanding the underlying cause of this acceleration. SNe Ia distances are also key to measuring the Hubble Constant, the current expansion rate of the Universe and a key cosmological parameter. Interestingly, the SNe Ia measurements of H0 are ~4 sigma away from the those derived from CMB temperature anisotropy measurements from Planck. This highly discussed tension could be a sign of new physics, such as a new family of neutrinos. However, I will discuss how recent studies of SNe Ia in the nearby Universe indicate two separate populations of SNe Ia with different peak luminosities. These differences in the underlying SNe Ia population could introduce a bias in the derived H0 and be the true cause of the tension with CMB measurements.
Benjamin Rose, STScI
Initial Evaluation of SNEMO Light Curve Standardization

October 2, 2019 (2:00 PM - 2:20 PM)

PDF, 7.18 MB
To determine if the SuperNova Empirical Model (SNEMO) can improve Type Ia supernova (SN Ia) standardization, we perform an initial evaluation and compare our results to those when using the more common place SALT2. We fit several large photometric data sets using both models and then pass the results to the Bayesian hierarchical model UNITY1.2, which estimates the Tripp-standardization coefficients, including a host stellar mass term as a proxy for unknown astrophysical systematics. Our work indicates that, when fitting with the seven-principal-component variant, SNEMO7, only a small fraction of existing SN Ia have light curves that can constrain the additional five parameters over SALT2. Alternatively, the two principal-components of SNEMO2 are constrainable, on par with SALT2. This reduction was much smaller for the Carnegie Supernova Project data set, which generally has the highest signal to noise and time sampling, implying that SNEMO7’s parameters are measurable with sufficiently good light curves. However, an insufficient number of SN Ia have this light-curve quality to enable measurements of cosmological parameters. Since SNEMO2 can be used with the same SN Ia as SALT2, and the additional parameters of SNEMO7 do more completely explain SN Ia, further investigation of SNEMO with three to six principal components is therefore required.
David Rubin, University of Hawaii
High-Redshift SNe with Subaru and HST

October 2, 2019 (10:45 AM - 11:00 AM)

PDF, 8.03 MB
High-redshift type Ia supernovae are crucial for constraining any time variation in dark energy. I will present the SN discoveries from the See Change supernova survey with Hubble, and from the first semester of the SUbaru Supernovae with Hubble Infrared (SUSHI) program. I will discuss the data quality, calibration, and cosmological analysis of the samples.
Masao Sako, University of Pennsylvania
Dark Energy Survey

October 2, 2019 (10:15 AM - 10:30 AM)

PDF, 33.09 MB
Clare Saunders, LPHNE, France
SNeIa from the Subaru Strategic Program

October 2, 2019 (11:00 AM - 11:15 AM)

PDF, 1.18 MB
The Subaru Strategic Program is a survey designed to observe Type Ia supernovae in the high redshift region above z~0.8, filling in an underpopulated segment of the Hubble diagram. Starting in November 2016, the HyperSuprimeCam (HSC) on the 8.2m Subaru telescope has been used to carry out an ultra-deep rolling search on the COSMOS field, while upcoming time will be dedicated to the SXDS field. Additionally, observations of supernovae at redshifts above z~1.1 are supplemented by an IR measurement with the HST Wide Field Camera 3. This allows the supernova color to be constrained when only one supernova-frame optical band can be observed by HSC. Spectroscopic followup is used to secure the redshifts of the supernova hosts. I will discuss the photometric analysis pipeline and the preliminary results from the completed half of this survey.
Daniel Scolnic, Duke University
Intrinsic scatter issues

October 2, 2019 (4:00 PM - 4:20 PM)

PDF, 4.23 MB
Mathew Smith, University of Southampton
Understanding the "mass step" in the DES3YR sample and beyond

October 3, 2019 (3:00 PM - 3:20 PM)

PDF, 17.34 MB
Co-authors: R. Kessler (University of Chicago), D. Scolnic (Duke), M. Sullivan (University of Southampton) on behalf of the DES Collaboration
Since the discovery of a correlation between host galaxy stellar mass and SN Ia brightness (after correction for stretch and colour), this relationship is routinely used in determining the cosmological parameters, ensuring that SN remain the principal probes of the accelerating Universe. However, this correction is not physically motivated, and thus potentially susceptible to systematic uncertainties. Contradicting previous results, the DES3YR sample found no evidence of a correlation between SNIa luminosity and stellar mass. In a full analysis of of the DES3YR "mass step", we show that this result is principally driven by the use of a 5D mu-bias correction when determining the distance to each event, compared to previous analyses, which consider a redshift-only correction. Using a 1D correction we recover a statistically significant mass step, consistent with previous results. This difference an be explained through the strong underlying correlation between host galaxy stellar mass and SN Ia "stretch", which is interpreted, in the 5D correction, to be the source of any "mass step". Uncovering the relationship between stellar mass, SNIa luminosity, stretch and colour is critical to unlock the true nature of the SNe Ia "mass step", and ensure that estimates on the equation-of-state of Dark Energy from all SNe Ia surveys are unbiased.
Nao Suzuki, Kavli IPMU, University of Tokyo
Reducing Systematic Errors for SNIa Cosmology

October 3, 2019 (9:20 AM - 9:40 AM)

PDF, 3.88 MB
Reducing the systematic error is the primary task for the future of SNIa cosmology. The two major sources of the systematic errors are 1) photometric system and 2) spectral templates. For photometric systems, we propose to replace white dwarf models by blackbody stars and eliminate errors from the models. We also introduce a virtual filter system so that we can minimize the errors. For spectral templates, we combine archived spectra and well calibrated photometry and reduce errors. We also use SNIbc to reduce the contaminations. We discuss the future prospects of SNIa cosmology based on Subaru HSC Transient Survey.
Elizabeth Swann, Institute of Cosmology and Gravitation
The Time Domain Extragalactic Survey

October 2, 2019 (11:30 AM - 11:45 AM)

PDF, 92.63 MB
Co-authors: The TiDES Team
The Large Synoptic Survey Telescope (LSST) will revolutionise our understanding of the extragalactic variable sky by discovering millions of transient detections per night. The key to fully exploiting this sample will be rapid spectroscopic classification of transients, combined with a systematic and well-controlled follow-up strategy. The Time-Domain Extragalactic Survey (TiDES) has secured a quarter million fibre hours on 4MOST (4-metre Multi-Object Spectroscopic Telescope) to follow up LSST transients and their host galaxies (Swann et al. 2019). TiDES is predicted to classify ~30,000 Type Ia supernovae (SNe Ia) and obtain redshift for ~50,000 hosts, this will be the largest spectroscopic sample of SNe Ia and their hosts ever collected. We will discuss our current simulations as well as our requirements for how photometric classification methods must evolve to ensure we can optimise our spectroscopic target selection for SNe Ia cosmology.
Maria Vincenzi, Institute of Cosmology and Gravitation
Cosmological biases from supernova photometric classification

October 4, 2019 (9:40 AM - 10:00 AM)

PDF, 4.95 MB
Co-authors: Mark Sullivan
The design and analysis of time-domain sky surveys requires the ability to simulate accurate and realistic populations of core collapse supernova (SN) events. Using a new library of core collapse SNe of different sub-types, we simulated a set of contaminated photometric SN samples, exploring different luminosity functions, rates and their redshift dependencies. We then test several independently-trained photometric classifiers and quantify the effects on the results of cosmological parameters estimation.