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Iterative Emulation is the Sincerest Form of Parameter Estimation

13 Jan 2020, 20:00 UTC
Iterative Emulation is the Sincerest Form of Parameter Estimation
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Title: Cosmological parameter estimation via iterative emulation of likelihoodsAuthors: Marcos Pellejero-Ibañez, Raul E. Angulo, Giovanni Aricó, Matteo Zennaro, Sergio Contreras, Jens StückerFirst Author’s Institution: Donostia International Physics Center (DIPC), Donostia-San Sebastián, SpainStatus: Open access on arXiv
Say you want to make the perfect soufflé. You know how fluffy it should be, but you don’t know how many eggs and sticks of butter you need. You could try a whole bunch of different combinations, but this would take forever (and waste a lot of ingredients on bad soufflés). Your sous-chef decides to help you out: you tell them about some of your previous attempts and how the souffle turned out, and they build you a predictor. You can now tell the predictor any amount of eggs and butter, and it estimates how fluffy the soufflé will be!This is the principle behind an emulator, which has become popular for estimating cosmological quantities. Today’s paper presents a new way of using emulators iteratively to perform this estimation even faster. This will get fairly technical, so put your apron on and prepare to get your hands dirty.

MCMC? More like MCM-See-ya-later!Let’s translate cooking to cosmology. Now say you’ve measured a galaxy power spectrum (a.k.a. ...

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