Photometric classification of Hyper Suprime-Cam transients using machine learning
Abstract
Abstract The advancement of technology has resulted in a rapid increase in supernova (SN) discoveries. The Subaru/Hyper Suprime-Cam (HSC) transient survey, conducted from fall 2016 through spring 2017, yielded 1824 SN candidates. This gave rise to the need for fast type classification for spectroscopic follow-up and prompted us to develop a machine learning algorithm using a deep neural network with highway layers. This algorithm is trained by actual observed cadence and filter combinations such that we can directly input the observed data array without any interpretation. We tested our model with a dataset from the LSST classification challenge (Deep Drilling Field). Our classifier scores an area under the curve (AUC) of 0.996 for binary classification (SN Ia or non-SN Ia) and 95.3% accuracy for three-class classification (SN Ia, SN Ibc, or SN II). Application of our binary classification to HSC transient data yields an AUC score of 0.925. With two weeks of HSC data since the first detection, this classifier achieves 78.1% accuracy for binary classification, and the accuracy increases to 84.2% with the full dataset. This paper discusses the potential use of machine learning for SN type classification purposes.
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1657872
- Resource Type:
- Published Article
- Journal Name:
- Publications of the Astronomical Society of Japan
- Additional Journal Information:
- Journal Name: Publications of the Astronomical Society of Japan Journal Volume: 72 Journal Issue: 5; Journal ID: ISSN 0004-6264
- Publisher:
- Oxford University Press
- Country of Publication:
- Japan
- Language:
- English
Citation Formats
Takahashi, Ichiro, Suzuki, Nao, Yasuda, Naoki, Kimura, Akisato, Ueda, Naonori, Tanaka, Masaomi, Tominaga, Nozomu, and Yoshida, Naoki. Photometric classification of Hyper Suprime-Cam transients using machine learning. Japan: N. p., 2020.
Web. doi:10.1093/pasj/psaa082.
Takahashi, Ichiro, Suzuki, Nao, Yasuda, Naoki, Kimura, Akisato, Ueda, Naonori, Tanaka, Masaomi, Tominaga, Nozomu, & Yoshida, Naoki. Photometric classification of Hyper Suprime-Cam transients using machine learning. Japan. https://doi.org/10.1093/pasj/psaa082
Takahashi, Ichiro, Suzuki, Nao, Yasuda, Naoki, Kimura, Akisato, Ueda, Naonori, Tanaka, Masaomi, Tominaga, Nozomu, and Yoshida, Naoki. Fri .
"Photometric classification of Hyper Suprime-Cam transients using machine learning". Japan. https://doi.org/10.1093/pasj/psaa082.
@article{osti_1657872,
title = {Photometric classification of Hyper Suprime-Cam transients using machine learning},
author = {Takahashi, Ichiro and Suzuki, Nao and Yasuda, Naoki and Kimura, Akisato and Ueda, Naonori and Tanaka, Masaomi and Tominaga, Nozomu and Yoshida, Naoki},
abstractNote = {Abstract The advancement of technology has resulted in a rapid increase in supernova (SN) discoveries. The Subaru/Hyper Suprime-Cam (HSC) transient survey, conducted from fall 2016 through spring 2017, yielded 1824 SN candidates. This gave rise to the need for fast type classification for spectroscopic follow-up and prompted us to develop a machine learning algorithm using a deep neural network with highway layers. This algorithm is trained by actual observed cadence and filter combinations such that we can directly input the observed data array without any interpretation. We tested our model with a dataset from the LSST classification challenge (Deep Drilling Field). Our classifier scores an area under the curve (AUC) of 0.996 for binary classification (SN Ia or non-SN Ia) and 95.3% accuracy for three-class classification (SN Ia, SN Ibc, or SN II). Application of our binary classification to HSC transient data yields an AUC score of 0.925. With two weeks of HSC data since the first detection, this classifier achieves 78.1% accuracy for binary classification, and the accuracy increases to 84.2% with the full dataset. This paper discusses the potential use of machine learning for SN type classification purposes.},
doi = {10.1093/pasj/psaa082},
journal = {Publications of the Astronomical Society of Japan},
number = 5,
volume = 72,
place = {Japan},
year = {Fri Sep 04 00:00:00 EDT 2020},
month = {Fri Sep 04 00:00:00 EDT 2020}
}
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Works referenced in this record:
Application of convolutional neural networks for stellar spectral classification
journal, November 2019
- Sharma, Kaushal; Kembhavi, Ajit; Kembhavi, Aniruddha
- Monthly Notices of the Royal Astronomical Society, Vol. 491, Issue 2
Optical Spectra of Supernovae
journal, September 1997
- Filippenko, Alexei V.
- Annual Review of Astronomy and Astrophysics, Vol. 35, Issue 1
First Release of High-redshift Superluminous Supernovae from the Subaru HIgh-Z SUpernova CAmpaign (SHIZUCA). II. Spectroscopic Properties
journal, March 2019
- Curtin, Chris; Cooke, Jeff; Moriya, Takashi J.
- The Astrophysical Journal Supplement Series, Vol. 241, Issue 2
Type Ia Supernovae in the First Few Days: Signatures of Helium Detonation versus Interaction
journal, July 2018
- Maeda, Keiichi; Jiang, Ji-an; Shigeyama, Toshikazu
- The Astrophysical Journal, Vol. 861, Issue 2
First Release of High-Redshift Superluminous Supernovae from the Subaru HIgh- Z SUpernova CAmpaign (SHIZUCA). I. Photometric Properties
journal, March 2019
- Moriya, Takashi J.; Tanaka, Masaomi; Yasuda, Naoki
- The Astrophysical Journal Supplement Series, Vol. 241, Issue 2
The relative specific Type Ia supernovae rate from three years of ASAS-SN
journal, January 2019
- Brown, J. S.; Stanek, K. Z.; Holoien, T. W-S
- Monthly Notices of the Royal Astronomical Society, Vol. 484, Issue 3
The delay of shock breakout due to circumstellar material evident in most type II supernovae
journal, September 2018
- Förster, F.; Moriya, T. J.; Maureira, J. C.
- Nature Astronomy, Vol. 2, Issue 10
The Prism Multi-Object Survey (Primus). i. Survey Overview and Characteristics
journal, October 2011
- Coil, Alison L.; Blanton, Michael R.; Burles, Scott M.
- The Astrophysical Journal, Vol. 741, Issue 1
The Gemini–North Multi‐Object Spectrograph: Performance in Imaging, Long‐Slit, and Multi‐Object Spectroscopic Modes
journal, May 2004
- Hook, I. M.; Jørgensen, Inger; Allington‐Smith, J. R.
- Publications of the Astronomical Society of the Pacific, Vol. 116, Issue 819
Accurate abundance patterns of solar twins and analogs: Does the anomalous solar chemical composition come from planet formation?
journal, November 2009
- Ramírez, I.; Meléndez, J.; Asplund, M.
- Astronomy & Astrophysics, Vol. 508, Issue 1
R-band light-curve properties of Type Ia supernovae from the (intermediate) Palomar Transient Factory
journal, December 2018
- Papadogiannakis, S.; Goobar, A.; Amanullah, R.
- Monthly Notices of the Royal Astronomical Society, Vol. 483, Issue 4
PHOTOMETRIC REDSHIFT AND CLASSIFICATION FOR THE XMM -COSMOS SOURCES
journal, December 2008
- Salvato, M.; Hasinger, G.; Ilbert, O.
- The Astrophysical Journal, Vol. 690, Issue 2
THE FMOS-COSMOS SURVEY OF STAR-FORMING GALAXIES AT z ∼ 1.6. III. SURVEY DESIGN, PERFORMANCE, AND SAMPLE CHARACTERISTICS
journal, September 2015
- Silverman, J. D.; Kashino, D.; Sanders, D.
- The Astrophysical Journal Supplement Series, Vol. 220, Issue 1
Superluminous Supernovae
journal, March 2018
- Moriya, Takashi J.; Sorokina, Elena I.; Chevalier, Roger A.
- Space Science Reviews, Vol. 214, Issue 2
Evolutionary population synthesis: models, analysis of the ingredients and application to high-z galaxies
journal, September 2005
- Maraston, C.
- Monthly Notices of the Royal Astronomical Society, Vol. 362, Issue 3
The Cosmic Energy Inventory
journal, December 2004
- Fukugita, Masataka; Peebles, P. J. E.
- The Astrophysical Journal, Vol. 616, Issue 2
Hyper Suprime-Cam: Filters
journal, June 2018
- Kawanomoto, Satoshi; Uraguchi, Fumihiro; Komiyama, Yutaka
- Publications of the Astronomical Society of Japan, Vol. 70, Issue 4
Photometric redshifts from SDSS images using a convolutional neural network
journal, December 2018
- Pasquet, Johanna; Bertin, E.; Treyer, M.
- Astronomy & Astrophysics, Vol. 621
Measuring type ia Supernova Populations of Stretch and Color and Predicting Distance Biases
journal, May 2016
- Scolnic, D.; Kessler, R.
- The Astrophysical Journal, Vol. 822, Issue 2
Automated Transient Identification in the dark Energy Survey
journal, August 2015
- Goldstein, D. A.; D’Andrea, C. B.; Fischer, J. A.
- The Astronomical Journal, Vol. 150, Issue 3
Avocado: Photometric Classification of Astronomical Transients with Gaussian Process Augmentation
journal, December 2019
- Boone, Kyle
- The Astronomical Journal, Vol. 158, Issue 6
The DEIMOS 10K Spectroscopic Survey Catalog of the COSMOS Field
journal, May 2018
- Hasinger, G.; Capak, P.; Salvato, M.
- The Astrophysical Journal, Vol. 858, Issue 2
The Keck Low-Resolution Imaging Spectrometer
journal, April 1995
- Oke, J. B.; Cohen, J. G.; Carr, M.
- Publications of the Astronomical Society of the Pacific, Vol. 107
Nearby supernova rates from the Lick Observatory Supernova Search - II. The observed luminosity functions and fractions of supernovae in a complete sample: Nearby supernova rates from LOSS - II
journal, March 2011
- Li, Weidong; Leaman, Jesse; Chornock, Ryan
- Monthly Notices of the Royal Astronomical Society, Vol. 412, Issue 3
Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant
journal, September 1998
- Riess, Adam G.; Filippenko, Alexei V.; Challis, Peter
- The Astronomical Journal, Vol. 116, Issue 3
Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC)
journal, July 2019
- Kessler, R.; Narayan, G.; Avelino, A.
- Publications of the Astronomical Society of the Pacific, Vol. 131, Issue 1003
The Rise Time of Type Ia Supernovae from the Supernova Legacy Survey
journal, September 2006
- Conley, A.; Howell, D. A.; Howes, A.
- The Astronomical Journal, Vol. 132, Issue 4
Random Forests for Photometric Redshifts
journal, March 2010
- Carliles, Samuel; Budavári, Tamás; Heinis, Sébastien
- The Astrophysical Journal, Vol. 712, Issue 1
FOCAS: The Faint Object Camera and Spectrograph for the Subaru Telescope
journal, December 2002
- Kashikawa, Nobunari; Aoki, Kentaro; Asai, Ryo
- Publications of the Astronomical Society of Japan, Vol. 54, Issue 6
Shock Breakout in type ii Plateau Supernovae: Prospects for High-Redshift Supernova Surveys
journal, March 2011
- Tominaga, N.; Morokuma, T.; Blinnikov, S. I.
- The Astrophysical Journal Supplement Series, Vol. 193, Issue 1
Shock Breakout in Core‐Collapse Supernovae and Its Neutrino Signature
journal, July 2003
- Thompson, Todd A.; Burrows, Adam; Pinto, Philip A.
- The Astrophysical Journal, Vol. 592, Issue 1
Relative frequencies of Type Ia and Type II supernovae in the chemical evolution of the Galaxy, LMC and SMC
journal, December 1995
- Tsujimoto, T.; Nomoto, K.; Yoshii, Y.
- Monthly Notices of the Royal Astronomical Society, Vol. 277, Issue 3
SN 2016jhj at redshift 0.34: extending the Type II supernova Hubble diagram using the standard candle method
journal, September 2017
- de Jaeger, T.; Galbany, L.; Filippenko, A. V.
- Monthly Notices of the Royal Astronomical Society, Vol. 472, Issue 4
Morpheus : A Deep Learning Framework for the Pixel-level Analysis of Astronomical Image Data
journal, May 2020
- Hausen, Ryan; Robertson, Brant E.
- The Astrophysical Journal Supplement Series, Vol. 248, Issue 1
THE COSMOS2015 CATALOG: EXPLORING THE 1 < z < 6 UNIVERSE WITH HALF A MILLION GALAXIES
journal, June 2016
- Laigle, C.; McCracken, H. J.; Ilbert, O.
- The Astrophysical Journal Supplement Series, Vol. 224, Issue 2
The HSC-SSP Transient Survey: Implications from Early Photometry and Rise Time of Normal Type Ia Supernovae
journal, March 2020
- Jiang, Ji-an; Yasuda, Naoki; Maeda, Keiichi
- The Astrophysical Journal, Vol. 892, Issue 1
Machine-learning selection of optical transients in the Subaru/Hyper Suprime-Cam survey
journal, October 2016
- Morii, Mikio; Ikeda, Shiro; Tominaga, Nozomu
- Publications of the Astronomical Society of Japan, Vol. 68, Issue 6
The Complete Calibration of the Color–Redshift Relation (C3R2) Survey: Survey Overview and Data Release 1
journal, May 2017
- Masters, Daniel C.; Stern, Daniel K.; Cohen, Judith G.
- The Astrophysical Journal, Vol. 841, Issue 2
Uncertain time-series similarity: return to the basics
journal, July 2012
- Dallachiesa, Michele; Nushi, Besmira; Mirylenka, Katsiaryna
- Proceedings of the VLDB Endowment, Vol. 5, Issue 11
Enrichment of the Hot Intracluster Medium: Observations
journal, November 2018
- Mernier, F.; Biffi, V.; Yamaguchi, H.
- Space Science Reviews, Vol. 214, Issue 8
Superluminous supernovae at redshifts of 2.05 and 3.90
journal, October 2012
- Cooke, Jeff; Sullivan, Mark; Gal-Yam, Avishay
- Nature, Vol. 491, Issue 7423
Photometric Supernova Classification with Machine Learning
journal, August 2016
- Lochner, Michelle; McEwen, Jason D.; Peiris, Hiranya V.
- The Astrophysical Journal Supplement Series, Vol. 225, Issue 2
SN 2005ap: A Most Brilliant Explosion
journal, October 2007
- Quimby, Robert M.; Aldering, Greg; Wheeler, J. Craig
- The Astrophysical Journal, Vol. 668, Issue 2
PHOTOMETRIC TYPE Ia SUPERNOVA CANDIDATES FROM THE THREE-YEAR SDSS-II SN SURVEY DATA
journal, August 2011
- Sako, Masao; Bassett, Bruce; Connolly, Brian
- The Astrophysical Journal, Vol. 738, Issue 2
A hybrid type Ia supernova with an early flash triggered by helium-shell detonation
journal, October 2017
- Jiang, Ji-an; Doi, Mamoru; Maeda, Keiichi
- Nature, Vol. 550, Issue 7674
The Supernova Legacy Survey 3-year sample: Type Ia supernovae photometric distances and cosmological constraints
journal, November 2010
- Guy, J.; Sullivan, M.; Conley, A.
- Astronomy & Astrophysics, Vol. 523
A strong ultraviolet pulse from a newborn type Ia supernova
journal, May 2015
- Cao, Yi; Kulkarni, S. R.; Howell, D. Andrew
- Nature, Vol. 521, Issue 7552
ANN z : Estimating Photometric Redshifts Using Artificial Neural Networks
journal, April 2004
- Collister, Adrian A.; Lahav, Ofer
- Publications of the Astronomical Society of the Pacific, Vol. 116, Issue 818
RAPID: Early Classification of Explosive Transients Using Deep Learning
journal, September 2019
- Muthukrishna, Daniel; Narayan, Gautham; Mandel, Kaisey S.
- Publications of the Astronomical Society of the Pacific, Vol. 131, Issue 1005
The many flavours of photometric redshifts
journal, June 2018
- Salvato, Mara; Ilbert, Olivier; Hoyle, Ben
- Nature Astronomy, Vol. 3, Issue 3
The rate of core Collapse Supernovae to Redshift 2.5 from the Candels and Clash Supernova Surveys
journal, November 2015
- Strolger, Louis-Gregory; Dahlen, Tomas; Rodney, Steven A.
- The Astrophysical Journal, Vol. 813, Issue 2
First Cosmology Results Using SNe Ia from the Dark Energy Survey: Analysis, Systematic Uncertainties, and Validation
journal, April 2019
- Brout, D.; Scolnic, D.; Kessler, R.
- The Astrophysical Journal, Vol. 874, Issue 2
Rapidly Evolving Transients from the Hyper Suprime-Cam SSP Transient Survey
journal, May 2020
- Tampo, Yusuke; Tanaka, Masaomi; Maeda, Keiichi
- The Astrophysical Journal, Vol. 894, Issue 1
Machine learning in APOGEE: Unsupervised spectral classification with
journal, April 2018
- Garcia-Dias, Rafael; Prieto, Carlos Allende; Almeida, Jorge Sánchez
- Astronomy & Astrophysics, Vol. 612
The History of the Cosmic Supernova Rate Derived from the Evolution of the Host Galaxies
journal, August 2000
- Kobayashi, Chiaki; Tsujimoto, Takuji; Nomoto, Ken’ichi
- The Astrophysical Journal, Vol. 539, Issue 1
AAOmega: a scientific and optical overview
conference, September 2004
- Saunders, Will; Bridges, Terry; Gillingham, Peter
- SPIE Astronomical Telescopes + Instrumentation, SPIE Proceedings
The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC: Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals
journal, October 2019
- Malz, A. I.; Hložek, R.; Allam, T.
- The Astronomical Journal, Vol. 158, Issue 5
The Cosmic Evolution Survey (COSMOS): Overview
journal, September 2007
- Scoville, N.; Aussel, H.; Brusa, M.
- The Astrophysical Journal Supplement Series, Vol. 172, Issue 1
Hyper Suprime-Cam: Camera dewar design
journal, September 2017
- Komiyama, Yutaka; Obuchi, Yoshiyuki; Nakaya, Hidehiko
- Publications of the Astronomical Society of Japan, Vol. 70, Issue SP1
LSST: From Science Drivers to Reference Design and Anticipated Data Products
journal, March 2019
- Ivezić, Željko; Kahn, Steven M.; Tyson, J. Anthony
- The Astrophysical Journal, Vol. 873, Issue 2
Photometric redshifts for Hyper Suprime-Cam Subaru Strategic Program Data Release 1
journal, October 2017
- Tanaka, Masayuki; Coupon, Jean; Hsieh, Bau-Ching
- Publications of the Astronomical Society of Japan, Vol. 70, Issue SP1
Unity: Confronting Supernova Cosmology’S Statistical and Systematic Uncertainties in a Unified Bayesian Framework
journal, November 2015
- Rubin, D.; Aldering, G.; Barbary, K.
- The Astrophysical Journal, Vol. 813, Issue 2
On the evolution of the cosmic supernova rates
journal, June 1998
- Madau, Piero; Della Valle, Massimo; Panagia, Nino
- Monthly Notices of the Royal Astronomical Society, Vol. 297, Issue 1
Measuring Dark Energy Properties with Photometrically Classified Pan-STARRS Supernovae. II. Cosmological Parameters
journal, April 2018
- Jones, D. O.; Scolnic, D. M.; Riess, A. G.
- The Astrophysical Journal, Vol. 857, Issue 1
The volumetric rate of normal type Ia supernovae in the local Universe discovered by the Palomar Transient Factory
journal, March 2019
- Frohmaier, C.; Sullivan, M.; Nugent, P. E.
- Monthly Notices of the Royal Astronomical Society, Vol. 486, Issue 2
SALT2: using distant supernovae to improve the use of type Ia supernovae as distance indicators
journal, February 2007
- Guy, J.; Astier, P.; Baumont, S.
- Astronomy & Astrophysics, Vol. 466, Issue 1
Finding strong gravitational lenses in the Kilo Degree Survey with Convolutional Neural Networks
journal, August 2017
- Petrillo, C. E.; Tortora, C.; Chatterjee, S.
- Monthly Notices of the Royal Astronomical Society, Vol. 472, Issue 1
A Modified Magnitude System that Produces Well-Behaved Magnitudes, Colors, and Errors Even for Low Signal-to-Noise Ratio Measurements
journal, September 1999
- Lupton, Robert H.; Gunn, James E.; Szalay, Alexander S.
- The Astronomical Journal, Vol. 118, Issue 3
SYSTEMATIC UNCERTAINTIES ASSOCIATED WITH THE COSMOLOGICAL ANALYSIS OF THE FIRST PAN-STARRS1 TYPE Ia SUPERNOVA SAMPLE
journal, October 2014
- Scolnic, D.; Rest, A.; Riess, A.
- The Astrophysical Journal, Vol. 795, Issue 1
A Measurement of the Rate of Type Ia Supernovae at Redshift z ≈ 0.1 from the First Season of the SDSS‐II Supernova Survey
journal, July 2008
- Dilday, Benjamin; Kessler, Richard; Frieman, Joshua A.
- The Astrophysical Journal, Vol. 682, Issue 1
Chemodynamical Simulations of the Milky way Galaxy
journal, February 2011
- Kobayashi, Chiaki; Nakasato, Naohito
- The Astrophysical Journal, Vol. 729, Issue 1
Hydrogen-poor superluminous stellar explosions
journal, June 2011
- Quimby, R. M.; Kulkarni, S. R.; Kasliwal, M. M.
- Nature, Vol. 474, Issue 7352
Simulations of the WFIRST Supernova Survey and Forecasts of Cosmological Constraints
journal, October 2018
- Hounsell, R.; Scolnic, D.; Foley, R. J.
- The Astrophysical Journal, Vol. 867, Issue 1
The Complete Light-curve Sample of Spectroscopically Confirmed SNe Ia from Pan-STARRS1 and Cosmological Constraints from the Combined Pantheon Sample
journal, May 2018
- Scolnic, D. M.; Jones, D. O.; Rest, A.
- The Astrophysical Journal, Vol. 859, Issue 2
Cosmological Parameter Uncertainties from Salt-Ii type ia Supernova Light Curve Models
journal, August 2014
- Mosher, J.; Guy, J.; Kessler, R.
- The Astrophysical Journal, Vol. 793, Issue 1
Exploring the Expansion History of the Universe
journal, March 2003
- Linder, Eric V.
- Physical Review Letters, Vol. 90, Issue 9
Measurements of Ω and Λ from 42 High‐Redshift Supernovae
journal, June 1999
- Perlmutter, S.; Aldering, G.; Goldhaber, G.
- The Astrophysical Journal, Vol. 517, Issue 2
The Hyper Suprime-Cam SSP transient survey in COSMOS: Overview
journal, May 2019
- Yasuda, Naoki; Tanaka, Masaomi; Tominaga, Nozomu
- Publications of the Astronomical Society of Japan, Vol. 71, Issue 4
Standard Solar Composition
journal, January 1998
- Grevesse, N.; Sauval, A. J.
- Space Science Reviews, Vol. 85, Issue 1/2, p. 161-174
Machine-learning-based Brokers for Real-time Classification of the LSST Alert Stream
journal, May 2018
- Narayan, Gautham; Zaidi, Tayeb; Soraisam, Monika D.
- The Astrophysical Journal Supplement Series, Vol. 236, Issue 1
Deep Recurrent Neural Networks for Supernovae Classification
journal, March 2017
- Charnock, Tom; Moss, Adam
- The Astrophysical Journal, Vol. 837, Issue 2
The Peculiar SN 2005hk: Do Some Type Ia Supernovae Explode as Deflagrations?
journal, April 2007
- Phillips, M. M.; Li, Weidong; Frieman, Joshua A.
- Publications of the Astronomical Society of the Pacific, Vol. 119, Issue 854
Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples
journal, August 2014
- Betoule, M.; Kessler, R.; Guy, J.
- Astronomy & Astrophysics, Vol. 568
The type Ia supernova SNLS-03D3bb from a super-Chandrasekhar-mass white dwarf star
journal, September 2006
- Andrew Howell, D.; Sullivan, Mark; Nugent, Peter E.
- Nature, Vol. 443, Issue 7109
DASH: Deep Learning for the Automated Spectral Classification of Supernovae and Their Hosts
journal, November 2019
- Muthukrishna, Daniel; Parkinson, David; Tucker, Brad E.
- The Astrophysical Journal, Vol. 885, Issue 1
The on-site quality-assurance system for Hyper Suprime-Cam: OSQAH†
journal, September 2017
- Furusawa, Hisanori; Koike, Michitaro; Takata, Tadafumi
- Publications of the Astronomical Society of Japan, Vol. 70, Issue SP1