Small-scale structure Annika Peter CCAPP The Ohio State University - PowerPoint PPT Presentation

Small-scale structure Annika Peter CCAPP The Ohio State University

Microphysics Macrophysics Baryons Dark matter Maybe some mediators

Example: Cold Dark Matter (CDM) Micromodel: Cold, collisionless, totally stable P(k) (typically Mpc^3 units) WIMP: Slight speed, late kinetic decoupling Springel+ 2008 k (wavenumber; typically 1/Mpc units)

Example: Cold Dark Matter (CDM) 2 predictions 1. Scale-free hierarchy of 2. Dense halos structure Springel+ 2008 NFW 1997

Example: Cold Dark Matter (CDM) 2 predictions 1. Scale-free hierarchy of 2. Dense halos structure Springel+ 2008 NFW 1997

Model variants NB: M ~ λ 3 P(k) (typically Mpc^3 units) Non-standard inflation (Erickcek, Scott) k (wavenumber; typically 1/Mpc units)

Model variants 1. Different small-scale 2. Underdense or halo hierarchy overdense relative to CDM AP+ 2013 Schewtschenko+ 2014

Model variants 1. Different small-scale 2. Underdense or halo hierarchy overdense relative to CDM AP+ 2013 Schewtschenko+ 2014

Probes 1. Linear scale 2. Non-linear: counts 3. Non-linear: density (I won’t talk about novel constraints like enhanced annihilation or microlensing from ultra- compact minihalos from non-standard thermal histories---interesting, but I have no time)

Linear(ish): Lyman- α forest Linear$scales$ a$$ Viel+$2013$

Non-linear: halo counts Visible tracers SDSS, GAMA Ultrafaint Carlin,…AP+ 2016 Dooley, AP+ 2016b More on this in a few slides…

Non-linear: halo counts Invisible tracers Lensed AGN Anomalous time delays Flux ratio anomalies

Non-linear: halo counts Among methods, can we achieve 10 4 M ¤ ? Invisible tracers Lensed galaxies Astrometric perturbations

Non-linear: density Vera Rubin Image credit: NOAO Rubin+ 1980

Non-linear: density Halo density ßà ßà halo counting CDM-no baryons Sqrt( GM(r)/r) Boylan-Kolchin+ 2012 Strigari+2010 from Walker +2009 & Mateo+2008

Challenges and opportunities

Challenges: baryons mess stuff up Garrison-Kimmel+ 2017 Governato+ 2012

Opportunities 1. Simulations lead to better mapping among microphysics, phenomenological parameters, and observables. Stellar mass (M ¤ ) Core size vs. CDM Halo mass (M ¤ ) Creasey+ 2016; see also Elbert+2016, Dooley, AP+ 2016a Manoj’s talk!

Opportunities 1. Simulations lead to better mapping among microphysics, phenomenological parameters, and observables. Semi-analytic modeling of WDM ETHOS Vogelsberger+ 2016, Cyr-Racine+ 2016 Pullen, Benson & Moustakas 2014

Opportunities 2. Wealth of data for finding faint things in and out of the Local Group. Ultrafaint dwarf at 10 Mpc!!! Peter/Kochanek LBT survey DES; Tucana III Local Group Davis, Nierenberg, AP+ in prep. Luque+ 2016

Opportunities 2. Wealth of data for finding faint things in and out of the Local Group. Ultrafaint dwarf at 10 Mpc!!! Peter/Kochanek LBT survey DES; Tucana III Local Group MADCASH; Sand+; reanalysis of SDSS; Dragonfly; DECals; HSC; amateur astronomers…. Future: LSST, WFIRST,... Davis, Nierenberg, AP+ in prep. Luque+ 2016

Opportunities 3. Substructure lensing is becoming a real statistical tool. Pre-2017: 7 suitable systems CCAPP fellow Anna Nierenberg 2017: dozens (new methods + new DES discoveries) Nierenberg, …AP+ 2017

Opportunities 4. Creative new astronomical signatures. Wide binaries probe subhalos Clusters BCG max Kim, AP, Wittman 2016 Penarrubia+ 2016

Map from particle to astro space (and back again) Halo scale on which weirdness shows up “There's gold in them thar dark matter phase space hills.” ---Matt Buckley Coupling w/SM M. Buckley & AP, in prep.

The technology and data are here: $ Microphysics Macrophysics Baryons Dark matter Maybe some mediators

Extra slides

Opportunities 3. Substructure lensing is becoming a real statistical tool. ALMA dusty galaxies Vegetti+ 2014 Hezaveh+ 2012