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The Next Generation of Cosmological Measurements with Type Ia Supernovae

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arxiv 1903.05128 v2 pith:J35MTETA submitted 2019-03-12 astro-ph.CO

The Next Generation of Cosmological Measurements with Type Ia Supernovae

Dan Scolnic , Saul Perlmutter , Greg Aldering , Dillon Brout , Tamara Davis , Alex Filippenko , Ryan Foley , Renee Hlozek
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Rebekah Hounsell Saurabh Jha David Jones Pat Kelly Rick Kessler Alex Kim David Rubin Adam Riess Steven Rodney Justin Roberts-Pierel Christopher Stubbs Yun Wang Jacobo Asorey Arturo Avelino Chetan Bavdhankar Peter J. Brown Anthony Challinor Christophe Balland Asantha Cooray Suhail Dhawan Georgios Dimitriadis Cora Dvorkin Julien Guy Will Handley Ryan E. Keeley Jean-Paul Kneib Benjamin LHuillier Massimiliano Lattanzi Kaisey Mandel James Mertens Mickael Rigault Pavel Motloch Suvodip Mukherjee Gautham Narayan Andrei Nomerotski Lyman Page Levon Pogosian Giuseppe Puglisi Marco Raveri Nicolas Regnault Armin Rest Cesar Rojas-Bravo Masao Sako Feng Shi Srivatsan Sridhar Aritoki Suzuki Yu-Dai Tsai W. M. Wood-Vasey Yannick Copin Gong-Bo Zhao Ningfeng Zhu
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While Type Ia Supernovae (SNe Ia) are one of the most mature cosmological probes, the next era promises to be extremely exciting in the number of different ways SNe Ia are used to measure various cosmological parameters. Here we review the experiments in the 2020s that will yield orders of magnitudes more SNe Ia, and the new understandings and capabilities to constrain systematic uncertainties at a level to match these statistics. We then discuss five different cosmological probes with SNe Ia: the conventional Hubble diagram for measuring dark energy properties, the distance ladder for measuring the Hubble constant, peculiar velocities and weak lensing for measuring sigma8 and strong-lens measurements of H0 and other cosmological parameters. For each of these probes, we discuss the experiments that will provide the best measurements and also the SN Ia-related systematics that affect each one.

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Cited by 4 Pith papers

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    Simulation-based inference with a Gaussian process emulator trained on ~1300 POSSIS simulations enables rapid, robust kilonova parameter estimation that avoids MCMC biases from likelihood misspecification.

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    A simulation-based inference method with Gaussian process emulators trained on 1300 kilonova simulations recovers parameters accurately and rapidly while avoiding MCMC biases from likelihood misspecification.

  3. The Pantheon+ Analysis: The Full Dataset and Light-Curve Release

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    Pantheon+ releases 1701 light curves from 1550 spectroscopically confirmed Type Ia supernovae across 18 surveys for cosmological inference.

  4. SpecTel: A 10-12 meter class Spectroscopic Survey Telescope

    astro-ph.IM 2019-07 unverdicted novelty 5.0

    Recommends an 11.4 m spectroscopic survey telescope with 5 deg² FOV and 15,000 fibers for massively multiplexed spectroscopy to complement Gaia, LSST, Euclid, and WFIRST.