The efficient classification of different types of supernova is one of the most important problems for observational cosmology. However, spectroscopic confirmation of most objects in upcoming photometric surveys, such as the The Rubin Observatory Legacy Survey of Space and Time (LSST), will be unfeasible. The development of automated classification processes based on photometry has thus become crucial. In this paper we investigate the performance of machine learning (ML) classification on the final cosmological constraints using simulated lightcurves from The Supernova Photometric Classification Challenge, released in 2010. We study the use of different feature sets for the lightcurves and many different ML pipelines based on either decision tree ensembles or automated search processes. To construct the final catalogs we propose a threshold selection method, by employing a \emph{Bias-Variance tradeoff}. This is a very robust and efficient way to minimize the Mean Squared Error. With this method we were able to get very strong cosmological constraints, which allowed us to keep $\sim 75\%$ of the total information in the type Ia SNe when using the SALT2 feature set and $\sim 33\%$ for the other cases (based on either the Newling model or on standard wavelet decomposition).
Modeling the probability distribution for cosmological analysis with photometrically classified samples
Observatório do Valongo, Universidade Federal do Rio de Janeiro（瓦隆戈天文台，里约热内卢联邦大学）；Instituto de Física, Universidade Federal do Rio de Janeiro（物理研究所，里约热内卢联邦大学）
As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multi-band light-curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNova (SNN; Möller et al. 2019) trained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classificati…
In the era of large astronomical surveys, photometric classification of supernovae (SNe) has become an important research field due to limited spectroscopic resources for candidate follow-up and classification. In this work, we present a method to photometrically classify type Ia supernovae based on machine learning with redshifts that are derived from the SN light-curves. This method is implemented on real data from the SNLS deferred pipeline, a purely photometric pipeline that identifies SNe Ia at high-redshifts ($0.2<z<1.1$). Our method consists of two stages: feature extraction (obtaining …
We present the cosmological analysis of 752 photometrically-classified Type Ia Supernovae (SNe Ia) obtained from the full Sloan Digital Sky Survey II (SDSS-II) Supernova (SN) Survey, supplemented with host-galaxy spectroscopy from the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). Our photometric-classification method is based on the SN typing technique of Sako et al. (2011), aided by host galaxy redshifts (0.05<z<0.55). SNANA simulations of our methodology estimate that we have a SN Ia typing efficiency of 70.8%, with only 3.9% contamination from core-collapse (non-Ia) SNe. We demon…
The present paper analyses the quasar clustering using the two-point correlation function (2pCF) and the largest existing sample of photometrically selected quasars: the SDSS NBCKDE catalogue (from the SDSS DR6). A new technique of random catalogue generation was developed for this purpose, that allows to take into account the original homogeneity of the survey without knowledge of its imaging mask. When averaged over photometrical redshifts 0.8<z_phot<2.2 the 2pCF of photometrically selected quasars is found to be approximated well with the power law w(θ)=(θ/θ_0)^{-α} with θ_0=4".5+/-1".4, α=…
We use 1169 Pan-STARRS supernovae (SNe) and 195 low-$z$ ($z < 0.1$) SNe Ia to measure cosmological parameters. Though most Pan-STARRS SNe lack spectroscopic classifications, in a previous paper (I) we demonstrated that photometrically classified SNe can be used to infer unbiased cosmological parameters by using a Bayesian methodology that marginalizes over core-collapse (CC) SN contamination. Our sample contains nearly twice as many SNe as the largest previous SN Ia compilation. Combining SNe with Cosmic Microwave Background (CMB) constraints from Planck, we measure the dark energy equation of…
The Pan-STARRS (PS1) Medium Deep Survey discovered over 5,000 likely supernovae (SNe) but obtained spectral classifications for just 10% of its SN candidates. We measured spectroscopic host galaxy redshifts for 3,147 of these likely SNe and estimate that $\sim$1,000 are Type Ia SNe (SNe Ia) with light-curve quality sufficient for a cosmological analysis. We use these data with simulations to determine the impact of core-collapse SN (CC SN) contamination on measurements of the dark energy equation of state parameter, $w$. Using the method of Bayesian Estimation Applied to Multiple Species (BEAM…
Recent cosmological analyses (e.g., JLA, Pantheon) of Type Ia Supernova (SNIa) have propagated systematic uncertainties into a covariance matrix and either binned or smoothed the systematic vectors in redshift space. We demonstrate that systematic error budgets of these analyses can be improved by a factor of $\sim1.5\times$ with the use of unbinned and unsmoothed covariance matrices. To understand this, we employ a separate approach that simultaneously fits for cosmological parameters and additional self-calibrating scale parameters that constrain the size of each systematic. We show that the…
We present the results of a study of selection criteria to identify Type Ia supernovae photometrically in a simulated mixed sample of Type Ia supernovae and core collapse supernovae. The simulated sample is a mockup of the expected results of the Dark Energy Survey. Fits to the MLCS2k2 and SALT2 Type Ia supernova models are compared and used to help separate the Type Ia supernovae from the core collapse sample. The Dark Energy Task Force Figure of Merit (modified to include core collapse supernovae systematics) is used to discriminate among the various selection criteria. This study of varying…
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 f…
The rate evolution of subluminous Type Ia Supernovae is presented using data from the Supernova Legacy Survey. This sub-sample represents the faint and rapidly-declining light-curves of the observed supernova Ia (SN Ia) population here defined by low stretch values (s<0.8). Up to redshift z=0.6, we find 18 photometrically-identified subluminous SNe Ia, of which six have spectroscopic redshift (and three are spectroscopically-confirmed SNe Ia). The evolution of the subluminous volumetric rate is constant or slightly decreasing with redshift, in contrast to the increasing SN Ia rate found for th…
The Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z = 0.5 and z = 2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans ~11,000 square degrees and probes a volume of 80(Gpc/h)^3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometric…
We investigate the identification of hydrogen-poor superluminous supernovae (SLSNe I) using a photometric analysis, without including an arbitrary magnitude threshold. We assemble a homogeneous sample of previously classified SLSNe I from the literature, and fit their light curves using Gaussian processes. From the fits, we identify four photometric parameters that have a high statistical significance when correlated, and combine them in a parameter space that conveys information on their luminosity and color evolution. This parameter space presents a new definition for SLSNe I, which can be u…
Photometric classification of supernovae detected by the Zwicky Transient Facility using noise augmentation
Humboldt-Universität zu Berlin（柏林洪堡大学）；Deutsches Elektronen-Synchrotron（德国电子同步辐射加速器中心）；Leibniz-Institut für Astrophysik Potsdam (AIP)（波茨坦阿基米德天体物理研究所）；European Southern Observatory（欧洲南方天文台）；University of Washington（华盛顿大学）；Trinity College Dublin, The University of Dublin（都柏林三一学院）；California Institute of Technology（加州理工学院）；National Central University（中央大学）；Lancaster University（兰卡斯特大学）；Institute of Space Sciences (ICE, CSIC)（空间科学研究所）；Institut d’Estudis Espacials de Catalunya (IEEC)（加泰罗尼亚空间研究院）
We present a sample of 485 photometrically identified Type Ia supernova candidates mined from the first three years of data of the CFHT SuperNova Legacy Survey (SNLS). The images were submitted to a deferred processing independent of the SNLS real-time detection pipeline. Light curves of all transient events were reconstructed in the g_M, r_M, i_M and z_M filters and submitted to automated sequential cuts in order to identify possible supernovae. Pure noise and long-term variable events were rejected by light curve shape criteria. Type Ia supernova identification relied on event characteristic…
Improvement in the precision of measurements of cosmological parameters with Type Ia Supernovae (SNIa) is expected to come from large photometrically identified (photometric) SN samples. Here we re-analyse the SDSS photometric SN sample, with roughly 700 high-quality, likely but unconfirmed SNIa light-curves, to develop new analysis tools aimed at evaluating systematic uncertainties on the dark energy equation-of-state parameter $w$. Since we require a spectroscopically measured host galaxy redshift for each SN, we determine the associated selection efficiency of host galaxies in order to simu…
We present measurements of the pseudo-equivalent width of the Fe II,$λ$5018 absorption feature in the spectra of 12 Type IIP supernovae (SNe II) in low luminosity ($M>-17$) dwarf host galaxies. The Fe II,$λ$5018 line has been suggested to be a useful diagnostic of the metallicity of the SN progenitor stars. The events in our sample were discovered photometrically by the Pan-STARRS Survey for Transients (PSST), and classified spectroscopically by us. Comparing our sample to 24 literature SNe II, we find that those in low luminosity hosts have significantly weaker Fe II features, with a probabil…
We present broadband photometric and polarimetric observations of two type II supernovae (SNe) 2013hj and 2014G. SN 2014G is a spectroscopically classified type IIL event, which we also confirm photometrically as its light curve show characteristic features (plateau slope of 2.55 mag (100 d)$ ^{-1} $ in V-band and duration of $ \sim77 $d) of a generic IIL SN. On the other hand SN 2013hj also shows high plateau decline rate of $ 1.5 $ mag (100 d)$ ^{-1} $ in V-band, similar to SNe IIL, but marginally lower than SNe IIL template light curves. Our high cadence photometric observations of SNe 2013…
We use the wide-field capabilities of the 2dF fibre positioner and the AAOmega spectrograph on the Anglo-Australian Telescope (AAT) to obtain redshifts of galaxies that hosted supernovae during the first three years of the Supernova Legacy Survey (SNLS). With exposure times ranging from 10 to 60 ksec per galaxy, we were able to obtain redshifts for 400 host galaxies in two SNLS fields, thereby substantially increasing the total number of SNLS supernovae with host galaxy redshifts. The median redshift of the galaxies in our sample that hosted photometrically classified Type Ia supernovae (SNe I…
We present GHOST, a database of 16,175 spectroscopically classified supernovae and the properties of their host galaxies. We have developed a host galaxy association method using image gradients that achieves fewer misassociations for low-z hosts and higher completeness for high-z hosts than previous methods. We use dimensionality reduction to identify the host galaxy properties that distinguish supernova classes. Our results suggest that the hosts of SLSNe, SNe Ia, and core collapse supernovae can be separated using host brightness information and extendedness measures derived from the host's…
In this work, we propose the use of Kernel Principal Component Analysis (KPCA) combined with k = 1 nearest neighbour algorithm (1NN) as a framework for supernovae (SNe) photometric classification. The classification is entirely based on information within the spectroscopic confirmed sample and each new light curve is classified one at a time. This allows us to update the principal component (PC) parameter space if a new spectroscopic light curve is available while also avoids the need of re-determining it for each individual new classification. We applied the method to different instances of t…
We present a new photometric identification technique for SN 1991bg-like type Ia supernovae (SNe Ia), i.e. objects with light-curve characteristics such as later primary maxima and absence of secondary peak in redder filters. This method is capable of selecting out this sub-group from the normal type Ia population. Furthermore, we find that recently identified peculiar sub-types such as SNe Iax and super-Chandrasekhar SNe Ia have similar photometric characteristics as 91bg-like SNe Ia, namely the absence of secondary maxima and shoulders at longer wavelengths, and can also be classified with o…
We present measurements of the rates of high-redshift Type Ia supernovae derived from the Subaru/XMM-Newton Deep Survey (SXDS). We carried out repeat deep imaging observations with Suprime-Cam on the Subaru Telescope, and detected 1040 variable objects over 0.918 deg$^2$ in the Subaru/XMM-Newton Deep Field. From the imaging observations, light curves in the observed $i'$-band are constructed for all objects, and we fit the observed light curves with template light curves. Out of the 1040 variable objects detected by the SXDS, 39 objects over the redshift range $0.2 < z < 1.4$ are classified as…
We present supernova rate measurements at redshift 0.1-1.0 from the Stockholm VIMOS Supernova Survey (SVISS). The sample contains 16 supernovae in total. The discovered supernovae have been classified as core collapse or type Ia supernovae (9 and 7, respectively) based on their light curves, colour evolution and host galaxy photometric redshift. The rates we find for the core collapse supernovae are 3.29 (-1.78,-1.45)(+3.08,+1.98) x 10^-4 yr^-1 Mpc^-3 h70^3 (with statistical and systematic errors respectively) at average redshift 0.39 and 6.40 (-3.12,-2.11)(+5.30,+3.65) x 10^-4 yr^-1 Mpc^-3 h7…
The reliability of Type Ia supernovae (SNIa) may be limited by the imprint of their galactic origins. To investigate the connection between supernovae and their host characteristics, we developed an improved method to estimate the stellar population age of the host as well as the local environment around the site of the supernova. We use a Bayesian method to estimate the star formation history and mass weighted age of a supernova's environment by matching observed spectral energy distributions to a synthesized stellar population. Applying this age estimator to both the photometrically and spec…
We present a ground-based near-infrared search for lensed supernovae behind the massive cluster Abell 1689 at z=0.18, one of the most powerful gravitational telescopes that nature provides. Our survey was based on multi-epoch $J$-band observations with the HAWK-I instrument on VLT, with supporting optical data from the Nordic Optical Telescope. Our search resulted in the discovery of five high-redshift, $0.671<z<1.703$, photometrically classified core-collapse supernovae with magnifications in the range $Δm$ = $-0.31$ to $-1.58$ mag, as calculated from lensing models in the literature. Thanks …
We use stacked spectra of the host galaxies of photometrically identified type Ia supernovae (SNe Ia) from the Dark Energy Survey (DES) to search for correlations between Hubble diagram residuals and the spectral properties of the host galaxies. Utilising full spectrum fitting techniques on stacked spectra binned by Hubble residual, we find no evidence for trends between Hubble residuals and properties of the host galaxies that rely on spectral absorption features ($< 1.3σ$), such as stellar population age, metallicity, and mass-to-light ratio. However, we find significant trends between the H…
Université Paris-Saclay（巴黎萨克雷大学）；CNRS/IN2P3（法国国家科学研究中心/核物理与粒子物理研究所）；Université Clermont Auvergne（克莱蒙奥弗涅大学）；Swinburne University of Technology（斯威本科技大学）
We describe how the Fink broker early supernova Ia classifier optimizes its ML classifications by employing an active learning (AL) strategy. We demonstrate the feasibility of implementation of such strategies in the current Zwicky Transient Facility (ZTF) public alert data stream. We compare the performance of two AL strategies: uncertainty sampling and random sampling. Our pipeline consists of 3 stages: feature extraction, classification and learning strategy. Starting from an initial sample of 10 alerts (5 SN Ia and 5 non-Ia), we let the algorithm identify which alert should be added to the…
Current and future cosmological analyses with Type Ia Supernovae (SNe Ia) face three critical challenges: i) measuring redshifts from the supernova or its host galaxy; ii) classifying SNe without spectra; and iii) accounting for correlations between the properties of SNe Ia and their host galaxies. We present here a novel approach that addresses each challenge. In the context of the Dark Energy Survey (DES), we analyze a SNIa sample with host galaxies in the redMaGiC galaxy catalog, a selection of Luminous Red Galaxies. Photo-$z$ estimates for these galaxies are expected to be accurate to $σ_{…
The Pan-STARRS1 (PS1) survey has obtained imaging in 5 bands (grizy_P1) over 10 Medium Deep Survey (MDS) fields covering a total of 70 square degrees. This paper describes the search for apparently hostless supernovae (SNe) within the first year of PS1 MDS data with an aim of discovering new superluminous supernovae (SLSNe). A total of 249 hostless transients were discovered down to a limiting magnitude of M_AB ~ 23.5, of which 76 were classified as Type Ia SNe. There were 57 SNe with complete light curves that are likely core-collapse SNe (CCSNe) or SLSNe and 12 of these have had spectra take…
We use a sample of 1338 spectroscopically confirmed and photometrically classified Type Ia Supernovae (SNe Ia), sourced from the CSP, CfA, SDSS-II, and SNLS supernova samples, to examine the relationships between SNe Ia and the galaxies that host them. Our results provide confirmation with improved statistical significance that SNe Ia, after standardization, are on average more luminous in massive hosts (significance $\rm > 5 σ$), and decline more rapidly in massive hosts (significance $\rm > 9σ$) and in hosts with low specific star formation rates (significance $\rm > 8σ$). We study the varia…
We present spectroscopy from the first three seasons of the Dark Energy Survey Supernova Program (DES-SN). We describe the supernova spectroscopic program in full: strategy, observations, data reduction, and classification. We have spectroscopically confirmed 307 supernovae, including 251 type Ia supernovae (SNe Ia) over a redshift range of $0.017 < z < 0.85$. We determine the effective spectroscopic selection function for our sample, and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. We also provide a full overview of the strategy, obser…
Normal or transitional? The evolution and properties of two type Ia supernovae in the Virgo cluster
University of Copenhagen（哥本哈根大学）；INAF, Osservatorio Astronomico di Capodimonte（意大利国家天体物理研究所，卡波迪蒙特天文台）；University of Queensland（昆士兰大学）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Institute for Astronomy, University of Hawaii（夏威夷大学天体物理研究所）；Kavli Institute for Theoretical Physics, University of California, Santa Barbara（加州大学圣塔芭芭拉分校，卡弗里理论物理研究所）；Las Cumbres Observatory（拉斯坎伯斯天文台）；David A. Dunlap Department of Astronomy and Astrophysics, University of Toronto（多伦多大学，大卫A·邓普林天文学与天体物理学系）
Measurements of the dark energy equation-of-state parameter, $w$, have been limited by uncertainty in the selection effects and photometric calibration of $z<0.1$ Type Ia supernovae (SNe Ia). The Foundation Supernova Survey is designed to lower these uncertainties by creating a new sample of $z<0.1$ SNe Ia observed on the Pan-STARRS system. Here, we combine the Foundation sample with SNe from the Pan-STARRS Medium Deep Survey and measure cosmological parameters with 1,338 SNe from a single telescope and a single, well-calibrated photometric system. For the first time, both the low-$z$ and high…
Supernovae (SNe) embedded in dense circumstellar material (CSM) may show prominent emission lines in their early-time spectra ($\leq 10$ days after the explosion), owing to recombination of the CSM ionized by the shock-breakout flash. From such spectra ("flash spectroscopy"), we can measure various physical properties of the CSM, as well as the mass-loss rate of the progenitor during the year prior to its explosion. Searching through the Palomar Transient Factory (PTF and iPTF) SN spectroscopy databases from 2009 through 2014, we found 12 Type II SNe showing flash-ionized (FI) signatures in th…
Theoretical and observational cosmology have enjoyed a number of significant successes over the last two decades. Cosmic microwave background measurements from the Wilkinson Microwave Anisotropy Probe and Planck, together with large-scale structure and supernova (SN) searches, have put very tight constraints on cosmological parameters. Type Ia supernovae (SNIa) played a central role in the discovery of the accelerated expansion of the Universe, recognised by the Nobel Prize in Physics in 2011. The last decade has seen an enormous increase in the amount of high quality SN observations, with SN …
We use a sample of 809 photometrically classified type Ia supernovae (SNe Ia) discovered by the Dark Energy Survey (DES) along with 40415 field galaxies to calculate the rate of SNe Ia per galaxy in the redshift range $0.2 < z <0.6$. We recover the known correlation between SN Ia rate and galaxy stellar mass across a broad range of scales $8.5 \leq \log(M_*/\mathrm{M}_{\odot}) \leq 11.25$. We find that the SN Ia rate increases with stellar mass as a power-law with index $0.63 \pm 0.02$, which is consistent with previous work. We use an empirical model of stellar mass assembly to estimate the a…
We use the first compilation of 72 core-collapse supernovae (SNe) from the Palomar Transient Factory (PTF) to study their observed subtype distribution in dwarf galaxies compared to giant galaxies. Our sample is the largest single-survey, untargeted, spectroscopically classified, homogeneous collection of core-collapse events ever assembled, spanning a wide host-galaxy luminosity range (down to M_r ~ -14 mag) and including a substantial fraction (>20%) of dwarf (M_r >= -18 mag) hosts. We find more core-collapse SNe in dwarf galaxies than expected and several interesting trends emerge. We use d…
The observed brightness of Type Ia supernovae is affected by gravitational lensing caused by the mass distribution along the line of sight, which introduces an additional dispersion into the Hubble diagram. We look for evidence of lensing in the SuperNova Legacy Survey 3-year data set. We investigate the correlation between the residuals from the Hubble diagram and the gravitational magnification based on a modeling of the mass distribution of foreground galaxies. A deep photometric catalog, photometric redshifts, and well established mass luminosity relations are used. We find evidence of a l…
