I The delay of shock breakout due to circumstellar material evident in most type II supernovae (Förster et al. 2018, Nature )

F. Förster1,2,3*, T. J. Moriya4, J. C. Maureira1, J. P. Anderson5, S. Blinnikov6,7,8, F. Bufano9, G. Cabrera-Vives2,10, A. Clocchiatti2,11, T. de Jaeger12, P. A. Estévez2,13, L. Galbany14, S. González-Gaitán1,15, G. Gräfener16, M. Hamuy2,3, E. Hsiao17, P. Huentelemu13, P. Huijse2,12, H. Kuncarayakti18,19, J. Martínez1,2,3, G. Medina3, F. Olivares E.2,3, G. Pignata2,20, A. Razza3,5, I. Reyes2,13, J. San Martín1, R. C. Smith21, E. Vera1, A. K. Vivas21, A. de Ugarte Postigo22,23, S.-C. Yoon24,25, C. Ashall26, M. Fraser27, A. Gal-Yam28, E. Kankare29, L. Le Guillou30, P. A. Mazzali26,31, N. A. Walton32 and D. R. Young29

1) Center for Mathematical Modeling, University of Chile, Santiago, Chile. 2) Millennium Institute of , Santiago, Chile. 3) Department of Astronomy, University of Chile, Santiago, Chile. 4) Division of Theoretical Astronomy, National Astronomical Observatory of Japan, National Institutes of Natural Sciences, Tokyo, Japan. 5) European Southern Observatory, Santiago, Chile. 6) Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo, Tokyo, Japan. 7) Institute for Theoretical and Experimental Physics, Moscow, Russia. 8) All-Russia Research Institute of Automatics, Moscow, Russia. 9) INAF Catania Astrophysical Observatory, Catania, Italy. 10) Department of Computer Science, University of Concepción, Concepción, Chile. 11) Department of Physics and Astronomy, Universidad Católica de Chile, Santiago, Chile. 12) Department of Astronomy, University of California, Berkeley, Berkeley, USA. 13) Department of Electrical Engineering, University of Chile, Santiago, Chile. 14) Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA. 15) CENTRA, Instituto Técnico Superior, Universidade de Lisboa, Lisbon, Portugal. 16) Argelander-Institut fur Astronomie, Bonn, Germany. 17) Department of Physics, Florida State University, Tallahassee, FL, USA. 18) Finnish Centre for Astronomy with ESO, University of Turku, Turku, Finland. 19) Tuorla Observatory, Department of Physics and Astronomy, University of Turku, Turku, Finland. 20) Departamento de Ciencias Fisicas, Universidad Andres Bello, Santiago, Chile. 21) Cerro Tololo Interamerican Observatory, La Serena, Chile. 22) CSIC Instituto de Astrofísica de Andalucía, Granada, Spain. 23) Dark Centre, Niels Borh Institute, University of Copenhagen, Copenhagen, Denmark. 24) Department of Physics and Astronomy, Seoul National University, Seoul, Republic of Korea. 25) Monash Centre for Astrophysics, School of Physics and Astronomy, Monash University, Melbourne, Australia. 26) Astrophysics Research Institute, Liverpool John Moores University, Liverpool, UK. 27) School of Physics, O’Brien Centre for Science, University College Dublin, Dublin, Ireland. 28) Department of Particle Physics and Astrophysics, Weizmann Institute of Science, Rehovot, Israel. 29) Astrophysics Research Centre, School of Mathematics and Physics, Queens University Belfast, Belfast, UK. 30) Sorbonne Université, Université Paris Diderot, CNRS, IN2P3, UMR 7585, LPNHE, Paris, France. 31) Max-Planck-Institut fur Astrophysik, Garching bei Munchen, Germany. 32) Institute of Astronomy, University of Cambridge, Cambridge, UK. *e-mail: [email protected]

Type II supernovae (SNe II) originate from the explosion of hydrogen-rich supergiant massive stars. Their first electromagnetic signature is the shock breakout (SBO), a short-lived phenomenon that can last for hours to days depending on the density at shock emergence. We present 26 rising optical light curves of SN II candidates discovered shortly after explosion by the High Cadence Transient Survey and derive physical parameters based on hydrodynamical models using a Bayesian approach. We observe a steep rise of a few days in 24 out of 26 SN II candidates, indicating the systematic detection of SBOs in a dense circumstellar matter consistent with a mass loss rate of Ṁ > 10−4M⊙/yr or a dense atmosphere. This implies that the characteristic hour-timescale signature of stellar envelope SBOs may be rare in nature and could be delayed into longer-lived circumstellar material SBOs in most SNe II.

I. The High cadence Transient Survey (HiTS)

HiTS is a high cadence survey which used DECam to look for the elusive shock breakout in type II supernovae. In 2014 and 2015 it monitored >100 deg2, mostly in the g band, with a cadence of 2 and 1.6 hr, for 5 and 7 consecutive nights, respectively. Some scientific highlights are: ● 1st real time analysis of DECam data (Feb 2014) Fast physical ● Time series of LCs for progenitor, Store light Fast evaluation Bayesian parameter 125 detected (ATELs) spectra SNe+CSM telescope, redshift, curves for fast of model inference interpolation (Moriya+17,18) attenuation evaluation likelihoods feasible (MCMC) ● Envelope shock breakout models ruled out (Förster+16, ApJ) (emulation) ]

st 1 ● -

z Mass Energy Mass CSM Figure 3: Percentiles 5, 50 and 95 of the marginalized H

1 CNN real/bogus classifier (Cabrera-Vives+17, ApJ) d loss radius 1 - n m a c

b ● 1 b

- posterior probabilities of the wind acceleration parameter

s

Discovery of 18 very distant RR Lyrae (Medina+17,18, ApJ) g g r e ● [ vs the mass loss rate (error bars intersect at percentiles 50).

Discovery of ~10k new asteroids (Peña+18, AJ) ] 1 -

z -4 H

d 1 ● - Most SNe II require very large mass loss rates >10 Msun/yr n m

Public variability catalog of ~22M sources (Martínez+18, AJ) a c

1 b -

s r

● g r even after marginalizing over all the model parameters. e

This work (Förster+18, Nat. Ast.) [ 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 50 50 50 50 Days since explosion Days since explosion Days since explosion Days since explosion ] 1 - A redshift z b V H

d 1 - n m a c

b 1 - IV. Conclusions s g

g r e [

II. Physical characterization of HiTS type II ] 1 - z H

1 d - n m a c

b 1 -

supernova candidate light curves s

r ●

g

r We have found a sample of 26 SNe II in the HiTS sample, e [ 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 https://github.com/fforster/surveysim 50 50 50 most of them showing a fast early rise of only a few days. Days since explosion Days since explosion Days since explosion In this work we compiled HiTS SNe II light curves to ● A detailed model comparison suggests that a density estimate distributions of physical parameters (Figure 1): Figure 1: Parameter estimation schema profile consistent with large pre explosion mass loss rates ● We use grid of red supergiant + accelerated wind explosion (>10-4 M /yr) is required in 24 our of 26 SNe II. models compiled by Moriya et al. 2017, 2018, MNRAS. ⊙ ● This suggests that either large circumstellar material (CSM) ● Build a light curve synthesizer for any combination of III. Results densities are required in most SNe II briefly before physical parameters explosion, or that their progenitors have very extended ● Interpolate in the space of intrinsic (mass, energy, mass loss envelopes not predicted by theory. Early spectra could help rate, wind acceleration parameter) and extrinsic (host distinguish between these two scenarios. attenuation, redshift) physical parameters to build library ● We have obtained posterior distributions of physical ● This is an independent confirmation of the confined CSM of precomputed light curves. parameters for the 26 SNe II in the HiTS sample. scenario proposed for SN 2013fs (Yaron et al. 2017, Science), ● Build SN II photometric classifier that correctly predicts all ● The observed light curves are well reproduced by synthetic but we argue that most SNe II show this behavior. our spectroscopically classified SNe. light curves sampled from the posterior (Figure 2). ● ● -4 This result has important implications for large field of Do fast likelihood estimation for an observed light curve ● 24/26 SNe II require mass loss rates >10 M /yr, much ⊙ view and fast surveys such as ZTF or LSST. and a set of physical parameters. larger than expected for red supergiant stars (Figure 3). ● Use Markov Chain Monte Carlo sampler (emcee, Foreman- ● A sample of five SNe from the literature with well sampled Figure 2: Comparison between observed and synthetic Mackey et al. 2012) to infer the posterior distribution of erly light curves show a similar behavior. physical parameters. light curves sampled from the posterior distribution of

physical parameters. Dashed lines correspond to models with no circumstellar material.

F.F. Acknowledges financial support from CMM, MAS and CONICYT. We are grateful to the NLHPC for providing computing and storage capacity. We have used data from the Dark Energy Camera (DECam) which was constructed by the Dark Energy Survey collaborating institutions. Image credit: NAOJ.