Constraints on (Fuzzy) Dark Matter Microphysics from Dwarf Galaxies - Ethan Nadler Less Travelled Path of Dark Matter (ICTS) 11/12/2020
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Constraints on (Fuzzy) Dark Matter Microphysics from Dwarf Galaxies Ethan Nadler Less Travelled Path of Dark Matter (ICTS) 11/12/2020
Dark Matter and Structure Formation Microphysical dark matter properties affect structure formation on small scales Buckley & Peter 2018
Our Census of the Faintest Galaxies MW halo virial radius Ultra-faint Milky Way satellite galaxies occupy the smallest luminous dark matter halos Credit: J. Carlin
The Milky Way Satellite Population Classical CVn II Boo III Boo I Com SDSS CVn I Boo II Leo II +60 PS1 Vir I Leo V Wil 1 UMa I Boo IV Leo IV Seg 1 DES Leo I UMi Dra II Crt II Sex DECam Her +30 UMa II Dra HSC Hyd II Cen I ATLAS Gaia Ant II 0 Sgr Car III Car II Tri II Sgr II Car LMC Pic II Col I 30 Hyi I Seg 2 Peg III Pic I SMC Ret III Psc II Ret II Tuc II Tuc V Hor I Aqr II Gru II Eri II Tuc IV Gru I Hor II 60 Cet III Phe II Tuc III For Cet II Scl Drlica-Wagner & Bechtol et al. 2020
There is No Missing Satellites Problem • No missing satellites problem after correcting for incomplete observations and extrapolating standard stellar mass–halo mass relations • Consistency has only been demonstrated at fixed modeling assumptions, and only for the brightest half of the Milky Way satellite population Bullock & Boylan-Kolchin 2017 Wetzel et al. 2016
1. Resimulate Milky Way- like halos from large cosmological volume. 1.0 2. Paint satellite galaxies 100 ↵ AAAB7XicbVBNS8NAEJ3Ur1q/qh69LBbBU0mqoMeiF48V7Ae0oUy2m3btZhN2N0IJ/Q9ePCji1f/jzX/jts1BWx8MPN6bYWZekAiujet+O4W19Y3NreJ2aWd3b/+gfHjU0nGqKGvSWMSqE6BmgkvWNNwI1kkUwygQrB2Mb2d++4kpzWP5YCYJ8yMcSh5yisZKrR6KZIT9csWtunOQVeLlpAI5Gv3yV28Q0zRi0lCBWnc9NzF+hspwKti01Es1S5COcci6lkqMmPaz+bVTcmaVAQljZUsaMld/T2QYaT2JAtsZoRnpZW8m/ud1UxNe+xmXSWqYpItFYSqIicnsdTLgilEjJpYgVdzeSugIFVJjAyrZELzll1dJq1b1Lqq1+8tK/SaPowgncArn4MEV1OEOGtAECo/wDK/w5sTOi/PufCxaC04+cwx/4Hz+AIzPjxw= gal 50 B onto subhalos using AAAB/HicbVBNS8NAEN3Ur1q/oj16CRbBU0mqoMeiF48V7Ae0IWy2m3TpbhJ2J2II8a948aCIV3+IN/+N2zYHbX0w8Hhvhpl5fsKZAtv+Nipr6xubW9Xt2s7u3v6BeXjUU3EqCe2SmMdy4GNFOYtoFxhwOkgkxcLntO9Pb2Z+/4FKxeLoHrKEugKHEQsYwaAlz6yPFAsF9vIR0EfIQ8yLwjMbdtOew1olTkkaqETHM79G45ikgkZAOFZq6NgJuDmWwAinRW2UKppgMsUhHWoaYUGVm8+PL6xTrYytIJa6IrDm6u+JHAulMuHrToFhopa9mfifN0whuHJzFiUp0IgsFgUptyC2ZklYYyYpAZ5pgolk+laLTLDEBHReNR2Cs/zyKum1ms55s3V30Whfl3FU0TE6QWfIQZeojW5RB3URQRl6Rq/ozXgyXox342PRWjHKmTr6A+PzB8RalX4= AAAB8nicbVDLSgMxFM3UV62vqks3wSK4KjNV0GWpG5cV7AOmQ8mkmTY0kwzJHaEM/Qw3LhRx69e482/MtLPQ1gOBwzn3knNPmAhuwHW/ndLG5tb2Tnm3srd/cHhUPT7pGpVqyjpUCaX7ITFMcMk6wEGwfqIZiUPBeuH0Lvd7T0wbruQjzBIWxGQsecQpASv5g5jAhBKRtebDas2tuwvgdeIVpIYKtIfVr8FI0TRmEqggxviem0CQEQ2cCjavDFLDEkKnZMx8SyWJmQmyReQ5vrDKCEdK2ycBL9TfGxmJjZnFoZ3MI5pVLxf/8/wUotsg4zJJgUm6/ChKBQaF8/vxiGtGQcwsIVRzmxXTCdGEgm2pYkvwVk9eJ91G3buqNx6ua81WUUcZnaFzdIk8dIOa6B61UQdRpNAzekVvDjgvzrvzsRwtOcXOKfoD5/MHcyGRXA== 0.75 N (< MV ) M50 galaxy—halo model. 10 fgal AAAB+XicbVDLSsNAFL2pr1pfUZduBovgqiRV0WXRjRuhgn1AG8JkOm2HTiZhZlIoIX/ixoUibv0Td/6NkzYLbT0wcDjnXu6ZE8ScKe0431ZpbX1jc6u8XdnZ3ds/sA+P2ipKJKEtEvFIdgOsKGeCtjTTnHZjSXEYcNoJJne535lSqVgknvQspl6IR4INGcHaSL5t90OsxwTz9CHz0ysn8+2qU3PmQKvELUgVCjR9+6s/iEgSUqEJx0r1XCfWXoqlZoTTrNJPFI0xmeAR7RkqcEiVl86TZ+jMKAM0jKR5QqO5+nsjxaFSszAwk3lOtezl4n9eL9HDGy9lIk40FWRxaJhwpCOU14AGTFKi+cwQTCQzWREZY4mJNmVVTAnu8pdXSbtecy9q9cfLauO2qKMMJ3AK5+DCNTTgHprQAgJTeIZXeLNS68V6tz4WoyWr2DmGP7A+fwBvspOG 0.5 AAAB73icbVDLSgNBEOz1GeMr6tHLYBA8hd0o6DHoxYsQwTwgWcLsZDYZMo91ZlYIS37CiwdFvPo73vwbJ8keNLGgoajqprsrSjgz1ve/vZXVtfWNzcJWcXtnd2+/dHDYNCrVhDaI4kq3I2woZ5I2LLOcthNNsYg4bUWjm6nfeqLaMCUf7DihocADyWJGsHVSu2vYQODeXa9U9iv+DGiZBDkpQ456r/TV7SuSCiot4diYTuAnNsywtoxwOil2U0MTTEZ4QDuOSiyoCbPZvRN06pQ+ipV2JS2aqb8nMiyMGYvIdQpsh2bRm4r/eZ3UxldhxmSSWirJfFGccmQVmj6P+kxTYvnYEUw0c7ciMsQaE+siKroQgsWXl0mzWgnOK9X7i3LtOo+jAMdwAmcQwCXU4Bbq0AACHJ7hFd68R+/Fe/c+5q0rXj5zBH/gff4A8YOP5w== M Markov Chain Monte Carlo 0.25 1 0 0 -3 -6 -9 -12 -15 -18 7 7.5 8 8.5 9.0 9.5 10.0 MV [mag] log(Mpeak/M ) 3. Apply observational selection functions based on imaging data. Simulated LMC 4. Calculate likelihood of DES PS1 5 5 Observed Observed observed satellites 4 Predicted 4 Predicted given galaxy—halo 3 3 dN/dMV dN/dMV 2 2 connection parameters. 1 1 0 0 -12 -9 -6 -3 0 -12 -9 -6 -3 0 MV [mag] MV [mag] EN & Wechsler et al. 2020
Transfer function Fit the Milky Way satellite population with subhalo mass function suppression, marginalizing over galaxy–halo connection and MW halo properties: Subhalo mass function Satellite luminosity function Current satellite observations are sensitive to ~25% suppression in subhalo abundance relative to CDM EN & Drlica-Wagner et al. 2020
Fuzzy Dark Matter Subhalo Mass Function interference due to macroscopic de Broglie wavelength → cutoff in abundance of low-mass halos
Fuzzy Dark Matter Subhalo Mass Function Order of magnitude uncertainty in FDM SHMF!
Fuzzy Dark Matter Constraints • Fuzzy dark matter lighter than 10-21 eV is robustly ruled out by MW satellite observations • Strongly disfavors FDM models that solve the core/cusp problem • Sets a lower limit on ULA mass for negligible self-interactions EN & Drlica-Wagner et al. 2020
Fuzzy Dark Matter Constraints • Fuzzy dark matter lighter than 10-21 eV is robustly ruled out by MW satellite observations • Strongly disfavors FDM models that solve the core/cusp problem • Subhalo evolution with ULA-like self-interactions is an important area for simulation work! EN & Drlica-Wagner et al. 2020
Late-Forming Dark Matter Constraints • Dark radiation that transitions to CDM (“late-forming dark matter”) suppresses power on small scales • Cutoff in halo abundance is set by the LFDM transition redshift • From MW satellites, dark radiation can transition to CDM no later than 1 week after the Big Bang: Das & EN 2020
Combining Small-Scale Structure Probes • Lyman-α forest, strong gravitational lensing, and stellar streams yield Preliminary similar dark matter constraints • Joint models of small-scale probes are key to break degeneracies and robustly detect non-CDM physics • In progress: combined constraints using MW satellite abundances and strong gravitational lensing EN, S. Birrer, D. Gilman et al. in prep.
Outlook • The lack of a cutoff in the abundance of Milky Way satellites down to halo masses of ~108 M☉ yields stringent constraints on dark matter physics • These constraints will continue to improve with next-generation data from the Vera C. Rubin Observatory (LSST) and simulation advances • Fuzzy dark mater lighter than 10 eV -21 is robustly ruled out despite SHMF uncertainty (for ULAs, simulations with self-interactions are crucial) • Joint modeling of small-scale structure probes is an important area for future work, starting with satellites, stellar streams, and strong lenses
Thanks! Susmita Adhikari, Arka Banerjee, Keith Bechtol, Kimberly Boddy, Subinoy Das, Alex Drlica-Wagner, Vera Gluscevic, Greg Green, Yao-Yuan Mao, Sidney Mau, Mitch McNanna, Risa Wechsler
Galaxy–Halo Connection Model Empirical modeling allows us to marginalize over theoretical uncertainties EN, Y.-Y. Mao, G. Green, R. Wechsler 2019
Dark Matter Constraints cutoff in galaxy occupation mass scale of suppression due to dark matter physics EN & Drlica-Wagner et al. 2020
Warm Dark Matter Constraints • Nearly all viable parameter space for resonantly-produced sterile neutrino dark matter is ruled out • The sterile neutrino interpretation of the 3.5 keV X-ray line is ruled out at >> 99% confidence • The dark matter free-streaming length must be smaller than the sizes of the halos that host ultra- faint dwarf galaxies (~10 kpc) EN & Drlica-Wagner et al. 2020
Interacting Dark Matter Constraints • Collisional damping due to DM– baryon scattering at early times suppresses power on small scales • Mass of the smallest halo allowed to form corresponds to the size of the horizon when Momentum Hubble rate transfer rate • Minimum observed halo mass sets cross section limit EN, V. Gluscevic, K. Boddy, R. Wechsler 2019
Interacting Dark Matter Constraints EN & Drlica-Wagner et al. 2020
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