CWRU PAT Coffee Agenda

Tuesdays 10:30 - 11:30 | Fridays 11:30 - 12:30

+2 A new general relativistic contribution to Mercury's perihelion advance.

jtd55 +1 kxp265 +1

+1 Machine learning cosmological structure formation.

mro28 +1

+1 Constraining screened fifth forces with the electron magnetic moment.

oxg34 +1

+1 Compactified Cosmological Simulations of the Infinite Universe. - [UPDATED]

cxt282 +1

Showing votes from 2018-02-13 11:30 to 2018-02-16 12:30 | Next meeting is Tuesday Aug 5th, 10:30 am.

users

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astro-ph.CO

  • Machine learning cosmological structure formation.- [PDF] - [Article]

    Luisa Lucie-Smith, Hiranya V. Peiris, Andrew Pontzen, Michelle Lochner
     

    We train a machine learning algorithm to learn cosmological structure formation from N-body simulations. The algorithm infers the relationship between the initial conditions and the final dark matter haloes, without the need to introduce approximate halo collapse models. We gain insights into the physics driving halo formation by evaluating the predictive performance of the algorithm when provided with different types of information about the local environment around dark matter particles. The algorithm learns to predict whether or not dark matter particles will end up in haloes of a given mass range, based on spherical overdensities. We show that the resulting predictions match those of spherical collapse approximations such as extended Press-Schechter theory. Additional information on the shape of the local gravitational potential is not able to improve halo collapse predictions; the linear density field contains sufficient information for the algorithm to also reproduce ellipsoidal collapse predictions based on the Sheth-Tormen model. We investigate the algorithm's performance in terms of halo mass and radial position and perform blind analyses on independent initial conditions realisations to demonstrate the generality of our results.

astro-ph.HE

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astro-ph.GA

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astro-ph.IM

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gr-qc

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hep-ph

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hep-th

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hep-ex

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quant-ph

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other

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