constraints on dark matter microphysics from dwarf galaxies · ethan nadler. the dark matter...
TRANSCRIPT
Constraints on Dark Matter Microphysics from Dwarf Galaxies
LIneA Webinar8/6/2020
Ethan Nadler
The Dark Matter Landscape
Credit: T. Tait
Buckley & Peter 2018
Microphysical dark matter properties affect structure formation on small scales
Dark Matter and Structure Formation
Dark Matter and Structure Formation
Planck Collaboration 2019
Planck Collaboration 2019
• Small scales contain information about a variety of dark matter physics: we are compelled to search there!
• What is the luminous content of the smallest halos?
The Galaxy–Halo Connection
Wechsler & Tinker 2018
?
Credit: J. Carlin
MW halo virial radius
Ultra-faint Milky Way satellite galaxies occupy the smallest luminous dark matter halos
Our Census of the Faintest Galaxies
The Milky Way Satellite Population
Credit: K. Bechtol
�60�
�30�
0�
+30�
+60�
Classical
SDSS
PS1
DES
DECam
HSC
ATLAS
GaiaAnt II
Aqr II
Boo IBoo II
Boo III
Boo IV
CVn ICVn II
CarCar II
Car III
Cen I
Cet II
Cet III
Col I
Com
Crt II
Dra
Dra II
Eri II
For
Gru IGru II
Her
Hor I
Hor II
Hyd II
Hyi ILMC
Leo I
Leo II
Leo IVLeo V
Peg III
Phe II
Pic I
Pic II
Psc IIRet II
Ret III
Sgr
Sgr II
Scl
Seg 1
Seg 2
Sex
SMC
Tri II
Tuc II
Tuc IIITuc IV
Tuc V
UMa I
UMa II
UMi
Vir IWil 1
Drlica-Wagner & Bechtol et al. 2020
The Milky Way Satellite Population
Missing Satellites?
“although there seem to be enough observed normal-sized galaxies to match the simulated size distribution, the number of dwarf galaxies is orders of magnitude lower than expected from simulation.” “We show that there is a match between the observed satellite counts
corrected by the detection efficiency of the Sloan Digital Sky Survey … and the number of luminous satellites predicted by CDM, assuming an empirical relation between stellar mass and halo mass. The “missing satellites problem”, cast in terms of number counts, is thus solved.”
“Astronomers couldn’t find enough satellite galaxies orbiting the Milky Way. Now they have the opposite problem, suggesting that our understanding of how galaxies get built is incomplete.”
🤕
• No missing satellites after correcting for observational completeness and extrapolating a standard stellar mass–halo mass relation
• Consistency has only been demonstrated at fixed modeling assumptions, and only for the brightest half of the observed satellites
No Missing Satellites?
Bullock & Boylan-Kolchin 2017Wetzel et al. 2016
7 7.5 8 8.5 9.0 9.5 10.0log(Mpeak/M�)
0
0.25
0.5
0.75
1.0
f gal
-18-15-12-9-6-30MV [mag]
1
10
50
100
N(<
MV)
-12 -9 -6 -3 0MV [mag]
0
1
2
3
4
5
dN/d
MV
PS1
Observed
Predicted
1. Resimulate Milky Way- like halos from large cosmological volume.
2. Paint satellite galaxies onto subhalos using galaxy—halo model.
4. Calculate likelihood of observed satellites given galaxy—halo connection parameters.
3. Apply observational selection functions based on imaging data.
Mar
kov
Cha
in M
onte
Car
lo↵
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-12 -9 -6 -3 0MV [mag]
0
1
2
3
4
5
dN/d
MV
DES
Observed
Predicted
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Simulated LMC
M50<latexit sha1_base64="gV1REod6INZYF0m2I1PcPtZcxYU=">AAAB+XicbVDLSsNAFL2pr1pfUZduBovgqiRV0WXRjRuhgn1AG8JkOm2HTiZhZlIoIX/ixoUibv0Td/6NkzYLbT0wcDjnXu6ZE8ScKe0431ZpbX1jc6u8XdnZ3ds/sA+P2ipKJKEtEvFIdgOsKGeCtjTTnHZjSXEYcNoJJne535lSqVgknvQspl6IR4INGcHaSL5t90OsxwTz9CHz0ysn8+2qU3PmQKvELUgVCjR9+6s/iEgSUqEJx0r1XCfWXoqlZoTTrNJPFI0xmeAR7RkqcEiVl86TZ+jMKAM0jKR5QqO5+nsjxaFSszAwk3lOtezl4n9eL9HDGy9lIk40FWRxaJhwpCOU14AGTFKi+cwQTCQzWREZY4mJNmVVTAnu8pdXSbtecy9q9cfLauO2qKMMJ3AK5+DCNTTgHprQAgJTeIZXeLNS68V6tz4WoyWr2DmGP7A+fwBvspOG</latexit>
EN & Wechsler et al. 2020
• Gaia is revolutionizing our understanding of Milky Way halo properties: mass, concentration, assembly history
• We analyze halos that 1) resemble the MW in these properties, 2) experience a Gaia-Enceladus merger, and 3) have a realistic Large Magellanic Cloud analog
Simulating Milky Way Analogs
Mao, Williamson, Wechsler 2015Callingham et al. 2018
GE-like event
Gaia-Enceladus
Koppelman et al. 2018 Simulated MWs
MW
LMCGaia-Enceladus
Credit: Ralf Kaehler
EN, Y.-Y. Mao, G. Green, R. Wechsler 2019
Empirical modeling allows us to marginalize over theoretical uncertainties
Galaxy–Halo Connection Model
Mock Satellite Observations
simulated “LMC”
simulated “LMC”
Mock Satellite Observations
DES
Pan-STARRS
Mock Satellite Observations
simulated “LMC”
Allows for a rigorous statistical comparison to observations
Detection probability is constrained directly by photometric data
-9-6-30MV [mag]
1
5
10
20
N(<
MV)
DES
Observed Satellites
No LMC
Fiducial (with LMC)
-9-6-30MV [mag]
1
5
10
20
N(<
MV)
PS1
Observed Satellites
No LMC
Fiducial (with LMC)
Predicted Satellite Populations• Recent infall (within last 2 Gyr) of LMC system required to fit the data
• Predict 5 (DES) & 1 (PS1) LMC satellites, consistent with Gaia proper motions!
EN & Wechsler et al. 2020
107 108 109 1010 1011
Mpeak [M�]
102
104
106
108
M⇤
[M�]
DES Satellites
PS1 Satellites
Behroozi et al. 2013
Fiducial (with LMC)
�16
�12
�8
�4
0
4
MV
[mag
]
107 108 109 1010 1011
Mvir [M�]
7 7.5 8 8.5 9.0 9.5 10.0log(Mpeak/M�)
0
0.25
0.5
0.75
1.0
f gal
Resolution Limit
Fiducial (with LMC)
The Faint-End Galaxy–Halo Connection
No evidence for a galaxy formation cutoff due to reionization or dark matter physics
atomic cooling limit
observational threshold
-18-15-12-9-6-30MV [mag]
1
10
100
300
N(<
MV)
Without H2 Star Formation
With H2 Star Formation
All Known Satellites
DES + PS1 (weighted)
Fiducial (with LMC)
FIRE Simulations
3 4 5 6 7 8 9
log(M⇤/M�)
The Total MW Satellite Population
• Predict ~220 total MW satellites, 25% of which are LMC-associated
• Vera C. Rubin Observatory should discover ~100 new systems
• Constraints on faint-end slope and galaxy formation efficiency inform hydrodynamic simulations
Munshi et al. 2019
• Spectroscopic follow-up (e.g., on GSMTs) will be key
EN & Wechsler et al. 2020
Interplay with High-z Galaxy Formation
Weisz & Boylan-Kolchin 2017
• Combining the star formation histories of Local Group dwarfs with our abundance matching results will constrain the high-redshift luminosity function
Boylan-Kolchin et al. 2015
Interplay with Local Satellite Surveys
Geha et al. 2017
• Surveys of Milky Way-like satellite systems in the Local Universe are rapidly progressing
• The Satellites Around Galactic Analogs (SAGA) survey targets MW analogs within 20-40 Mpc
• Detailed work to jointly fit the MW and other systems in progress!
• MW satellite luminosity function is typical among SAGA, LV systems
The Faint-End Galaxy–Halo Connection
Wechsler & Tinker 2018
?
CDM WDM
Lovell et al. 2011
Dark Matter Constraints
CDM WDM
Dark Matter Constraints
free-streaming due to large primordial velocity dispersion → cutoff in abundance of low-mass halos
Bullock & Boylan-Kolchin 2017Pacucci et al. 2013
DM Physics and the Minimum Halo Mass
collisional damping due to DM–SM interactions → cutoff in abundance of low-mass halos
DM Physics and the Minimum Halo Mass
Green et al. 2004 Diemand et al. 2005
even “CDM” has a small-scale cutoff!
linear matter power spectrum (sub)halo mass function
interference due to macroscopic de Broglie wavelength → cutoff in abundance of low-mass halos
Armengaud et al. 2017
Du 2019
DM Physics and the Minimum Halo Mass
EN & Drlica-Wagner et al. 2020
Fit the Milky Way satellite population with subhalo mass function suppression, marginalizing over galaxy–halo connection uncertainties and Milky Way halo properties:
Transfer function
Subhalo mass function
Satellite luminosity function
Current satellite observations are sensitive to ~25% suppression in subhalo abundance relative to CDM
Dark Matter Constraints• Our Milky Way satellite analysis yields the strongest astrophysical constraints
to date on a variety of dark matter properties and particle models
• For thermal relic WDM: mWDM > 6.5 keV (95% confidence), comparable to limits from the Lyman-alpha forest, strong gravitational lensing, and stellar stream perturbations (with largely distinct systematics)
• This is the opposite of searching under a lamppost!
EN & Drlica-Wagner et al. 2020
Warm Dark Matter Constraints
• Our analysis excludes nearly all remaining parameter space for resonantly-produced sterile neutrino dark matter
• The sterile neutrino interpretation of the 3.5 keV X-ray line is ruled out at >> 99% confidence
• Interpretation: the dark matter free-streaming length must be smaller than the sizes of the halos that host ultra-faint dwarf galaxies
EN & Drlica-Wagner et al. 2020
0.1 1 5 10 30 50k [h Mpc�1]
0.05
0.25
0.5
0.75
1.0
Pco
llis
ional/P
CD
M
mWDM = 0.3 keV
mWDM = 1.2 keV
mWDM = 4.7 keV
�0 = 10�27 cm2
�0 = 10�28 cm2
�0 = 10�29 cm2
mWDM = 0.3 keV
mWDM = 1.2 keV
mWDM = 4.7 keV
�0 = 10�27 cm2
�0 = 10�28 cm2
�0 = 10�29 cm2
1016 1014 1012 1010 108
M [M�]• 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
• Minimum observed halo mass yields analytic cross section limit
EN, V. Gluscevic, K. Boddy, R. Wechsler 2019
Interacting Dark Matter Constraints
Hubble rateMomentum transfer rate
Interacting Dark Matter Constraints
EN & Drlica-Wagner et al. 2020
K. Maamari et al. in prep
Preliminary
Interacting Dark Matter Constraints
• Implies that the DM de Broglie wavelength is smaller than the sizes of ultra-faint dwarfs
Fuzzy Dark Matter Constraints• Our analysis robustly rules out
fuzzy dark matter masses below 10-21 eV, with very conservative modeling assumptions
• Can be interpreted as a lower limit on the ultra-light axion mass assuming negligible self and Standard Model couplings
EN & Drlica-Wagner et al. 2020
• Dark radiation that decays to DM after BBN (“late-forming DM”) suppresses power on small scales
• MW satellites yields an order-of-magnitude improvement on the transition redshift lower bound:
Late-Forming Dark Matter Constraints
S. Das & EN in prep.
• Cutoff in halo abundance is set by the LFDM transition redshift
Preliminary
0
20
40
60
80
N(>
Vpea
k)
w10
w100
w200
w500
CDM
20 25 30 35 40 45
Vpeak [km s�1]
0
0.5
1.0
NSI
DM/N
CD
M
• Our framework also constrains DM properties that suppress subhalo abundances at late times (e.g. DM self-interactions, decays)
• Self-interactions: Sensitivity to SIDM cross sections of ~1 cm2/g at low velocity scales (stay tuned!)
EN, A. Banerjee, S. Adhikari, Y.-Y. Mao, R. Wechsler 2020
Constraining Late-time DM Physics
1 cm2/g for v < 500 km/s
• Decays: Sensitivity to decaying DM with a lifetime of ~10 Gyr, which has been claimed to alleviate the Hubble tension (stay tuned!)
• Our framework also constrains DM properties that suppress subhalo abundances at late times (e.g. DM self-interactions, decays)
S. Mau et al. in prep
Constraining Late-time DM Physics
Preliminary
Vattis et al. 2019
Outlook
• These constraints will continue to improve with advances in (currently conservative) galaxy–halo modeling and LSST satellite discoveries
• Our analysis informs a variety of DM properties (free-streaming scale, de Broglie wavelength, coupling to the Standard Model) and particle models (sterile neutrinos, generalized WIMPs, ultra-light axions)
• Joint modeling of small-scale structure probes is an important area for future work, starting with satellites, streams, and strong lenses
• The lack of a cutoff in the abundance of observable ultra-faint galaxies down to halo masses of ~108 M☉ yields stringent constraints on the galaxy—halo connection and dark matter physics
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
DES & Pan-STARRS Survey Selection Functions
• Rigorous satellite search over ~75% of the sky
• Masks for dusty regions, background galaxies, etc.
• 17/18 (DES), 19/31 (PS1) satellites recovered by two search algorithms
• Selection functions from catalog-level searches for simulated satellites
Drlica-Wagner & Bechtol et al. 2020
0
1
2
3
log 1
0(r
/pc)
8 < D < 16 kpc
Cet IIDra II
Ret IISeg 1
Tri II
Tuc III
16 < D < 32 kpc
Boo II
Boo III
ComGru II
Seg 2
Tuc IITuc IV
Tuc V
UMa II
Wil 1
32 < D < 64 kpc
�10.0 �7.5 �5.0 �2.5 0.0MV
0
1
2
3
log 1
0(r
/pc)
Aqr IIBoo I
Crt II
Dra
Gru I
Hor I Hor IIPhe II
Pic I
Ret III
Sgr II
Sex
UMa I
UMi
Vir I
64 < D < 128 kpc
�10.0 �7.5 �5.0 �2.5 0.0MV
Boo IVCVn I
CVn IICet III
Col IHer
Leo II
Leo IV
Leo V
Peg III
Psc II
128 < D < 256 kpc
�10.0 �7.5 �5.0 �2.5 0.0MV
Eri II
256 < D < 512 kpc
0.0
0.2
0.4
0.6
0.8
1.0
Det
ecti
onE
�ci
ency
DES
Observational Selection Functions
Drlica-Wagner & Bechtol et al. 2020
0
1
2
3
log 1
0(r
/pc)
8 < D < 16 kpc
Cet IIDra II
Ret IISeg 1
Tri II
Tuc III
16 < D < 32 kpc
Boo II
Boo III
ComGru II
Seg 2
Tuc IITuc IV
Tuc V
UMa II
Wil 1
32 < D < 64 kpc
�10.0 �7.5 �5.0 �2.5 0.0MV
0
1
2
3
log 1
0(r
/pc)
Aqr IIBoo I
Crt II
Dra
Gru I
Hor I Hor IIPhe II
Pic I
Ret III
Sgr II
Sex
UMa I
UMi
Vir I
64 < D < 128 kpc
�10.0 �7.5 �5.0 �2.5 0.0MV
Boo IVCVn I
CVn IICet III
Col IHer
Leo II
Leo IV
Leo V
Peg III
Psc II
128 < D < 256 kpc
�10.0 �7.5 �5.0 �2.5 0.0MV
Eri II
256 < D < 512 kpc
0.0
0.2
0.4
0.6
0.8
1.0
Det
ecti
onE
�ci
ency
PS1
Observational Selection Functions
Drlica-Wagner & Bechtol et al. 2020
Satellites of the LMC
Predict 5 (1) currently observed LMC-associated satellites in DES (PS1), consistent with Gaia PMs!
Also see Patel et al. 2020!
Kallivayalil et al. 2018
EN & Wechsler et al. 2020
↵ = �1.430+0.020�0.015
0.1
0.2
�M
�M = 0.004+0.093�0.000
7.6
8.0
8.4
M50
M50 = 7.51+0.21�0.00
0.8
1.6
B
B = 0.93+0.59�0.33
0.25
0.50
0.75
�ga
l
�gal = 0.03+0.32�0.00
40
80
A
A = 37+36�25
0.5
1.0
1.5
�lo
gR
�log R = 0.63+0.28�0.30
�1.48�1.44�1.40↵
0.8
1.6
n
0.1 0.2�M
7.6 8.0 8.4M50
0.8 1.6B
0.25 0.50 0.75�gal
40 80A
0.5 1.0 1.5�log R
0.8 1.6n
n = 1.07+0.38�0.57
Faint-end slope consistent with global luminosity function
Luminosity scatter < 0.2 dex
Minimum halo mass corresponding to observed satellites < 3 x108 M☉
Disruption consistent with FIRE sims
Galaxy occupation fraction consistent with step function
Measurement of amplitude, scatter, slope of galaxy-halo size relation
EN & Wechsler et al. 2020
Dark Matter Constraints
cutoff in galaxy occupation
mass scale of suppression due to dark matter physics
EN & Drlica-Wagner et al. 2020