Dark Matter Science in the Era of LSST

Bechtol, K.; Drlica-Wagner, A.; Abazajian, Kevork N.; Abidi, Muntazir; Adhikari, Susmita; Ali-Haı̈moud, Yacine; Annis, James; Ansarinejad, Behzad; Armstrong, R.; Asorey, J.; Baccigalupi, C.; Banerjee, Arka; Banik, Nilanjan; Bennett, C. L.; Beutler, Florian; Bird, Simeon; Birrer, Simon; Biswas, Rahul; Biviano, A.; Blazek, Jonathan; Boddy, Kimberly K.; Bonaca, Ana; Borrill, J.; Bose, Sownak; Bovy, Jo; Frye, Brenda; Brooks, Alyson; Buckley, Matthew R.; Buckley-Geer, E.; Bülbül, Esra; Burchat, P. R.; Burgess, C.P.; Calore, Francesca; Caputo, R.; Castorina, Emanuele; Chang, C.; Chapline, George; Charles, E.; Chen, Xingang; Clowe, Douglas; Cohen‐Tanugi, J.; Comparat, Johan; Croft, Rupert A. C.; Cuoco, A.; Cyr-Racine, Francis-Yan; D’Amico, Guido; Davis, Tamara M.; Dawson, William A.; Macorra, Axel de la; Valentino, Eleonora Di; Rivero, Ana Dı́az; Digel, S. W.; Dodelson, Scott; Doré, O.; Dvorkin, Cora; Eckner, Christopher; Ellison, J.; Erkal, Denis; Farahi, Arya; Fassnacht, Christopher D.; Ferreira, Pedro G.; Flaugher, B.; Foreman, Simon; Friedrich, Oliver; Frieman, Joshua A.; García-Bellido, J.; Gawiser, Eric; Gerbino, Martina; Giannotti, Maurizio; Gill, M. S.; Gluscevic, Vera; Golovich, Nathan; Gontcho, Satya Gontcho A; González‐Morales, Alma X.; Grin, Daniel; Gruen, D.; Hearin, Andrew P.; Hendel, David; Hezaveh, Yashar; Hirata, Christopher M.; Hložek, Renée; Horiuchi, Shunsaku; Jain, Bhuvnesh; Jee, M. James; Jeltema, T.; Kamionkowski, Marc; Kaplinghat, Manoj; Keeley, Ryan E.; Keeton, Charles R.; Khatri, Rishi; Koposov, Sergey E.; Koushiappas, Savvas M.; Kovetz, Ely D.; Lahav, O.; Lam, Casey; Lee, Chien‐Hsiu; Li, Ting S.; Liguori, M.; Lin, Tongyan; Lisanti, Mariangela; Loverde, Marilena; Lu, Jessica R.; Mandelbaum, Rachel; Mao, Yao-Yuan; McDermott, Samuel D.; McNanna, M.; Medford, Michael S.; Meerburg, P. Daniel; Meyer, M.; Mirbabayi, Mehrdad; Mishra-Sharma, Siddharth; Moniez, M.; More, Surhud; Moustakas, John; Muñoz, Julián B.; Murgia, S.; Myers, Adam D.; Nadler, Ethan O.; Necib, Lina; Newburgh, Laura; Newman, Jeffrey A.; Nord, B.; Nourbakhsh, Erfan; Nuss, E.; O’Connor, P.; Pace, Andrew B.; Padmanabhan, Hamsa; Palmese, A.; Peiris, Hiranya V.; Peter, Annika H. G.; Piacentni, Francesco; Plazas, A. A.; Polin, Daniel A.; Prakash, Abhishek; Prescod-Weinstein, Chanda; Read, Justin I.; Ritz, S.; Robertson, Brant; Rose, Benjamin; Rosenfeld, R.; Rossi, Graziano; Samushia, Lado; Sánchez, Javier; Sánchez‐Conde, Miguel A.; Schaan, Emmanuel; Sehgal, Neelima; Senatore, Leonardo; Seo, Hee-Jong; Shafieloo, Arman; Shan, Huanyuan; Shipp, Nora; Simon, Joshua D.; Simon, Sara M.; Slatyer, Tracy R.; Slosar, Anže; Sridhar, Srivatsan; Stebbins, Albert; Straniero, O.; Strigari, Louis E.; Tait, Tim M. P.; Tollerud, Erik; Troxel, M. A.; Tyson, J. A.; Uhlemann, Cora; Urenña-López, L. Arturo; Verma, Aprajita; Vilalta, Ricardo; Walter, Christopher W.; Wang, Meiyu; Watson, Scott; Wechsler, Risa H.; Wittman, David; Xu, Weishuang; Yanny, B.; Young, Sam; Yu, Hai-Bo; Zaharijaš, Gabrijela; Zentner, Andrew R.; Zuntz, Joe

doi:10.2172/1572253

Cited by 108 publications

(208 citation statements)

References 20 publications

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“…On the other hand, orbits also allow us to gain insight into how a galaxy acquires its satellite population. For example, it has been argued that the satellites lie preferentially on streams (Lynden-Bell & Lynden-Bell 1995), on a thin plane (Kroupa et al 2005), or that they have fallen in groups (Li & Helmi 2008), of which the LMC/SMC and their recently discovered satellites are direct proof (Bechtol et al 2015;Koposov et al 2015). The Gaia DR2 data will allow us to establish how real and important these associations are, and also whether the orbits found are consistent with the expectations from the concordance cosmological model.…”

Section: Introductionmentioning

confidence: 84%

GaiaData Release 2

Helmi¹,

Leeuwen²,

McMillan³

et al. 2018

A&A

552

197

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Context. Aims. The goal of this paper is to demonstrate the outstanding quality of the second data release of the Gaia mission and its power for constraining many different aspects of the dynamics of the satellites of the Milky Way. We focus here on determining the proper motions of 75 Galactic globular clusters, nine dwarf spheroidal galaxies, one ultra-faint system, and the Large and Small Magellanic Clouds. Methods. Using data extracted from the Gaia archive, we derived the proper motions and parallaxes for these systems, as well as their uncertainties. We demonstrate that the errors, statistical and systematic, are relatively well understood. We integrated the orbits of these objects in three different Galactic potentials, and characterised their properties. We present the derived proper motions, space velocities, and characteristic orbital parameters in various tables to facilitate their use by the astronomical community. Results. Our limited and straightforward analyses have allowed us for example to (i) determine absolute and very precise proper motions for globular clusters; (ii) detect clear rotation signatures in the proper motions of at least five globular clusters; (iii) show that the satellites of the Milky Way are all on high-inclination orbits, but that they do not share a single plane of motion; (iv) derive a lower limit for the mass of the Milky Way of 9.1-2.6+6.2 × 1011 M⊙ based on the assumption that the Leo I dwarf spheroidal is bound; (v) derive a rotation curve for the Large Magellanic Cloud based solely on proper motions that is competitive with line-of-sight velocity curves, now using many orders of magnitude more sources; and (vi) unveil the dynamical effect of the bar on the motions of stars in the Large Magellanic Cloud. Conclusions. All these results highlight the incredible power of the Gaia astrometric mission, and in particular of its second data release.

show abstract

Section: Introductionmentioning

confidence: 84%

GaiaData Release 2

Helmi¹,

Leeuwen²,

McMillan³

et al. 2018

A&A

552

197

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“…Using the IMACS spectrograph on the Magellan Baade Telescope, Li et al (2017) measured a velocity dispersion of σ = 6.9 +1.2 −0.9 km s −1 and inferred a mass-to-light ratio of 420 +210 −140 M L −1 , confirming Eri 2 is an UFD. The earliest observations indicated the possible presence of bright blue stars and a stellar cluster (Koposov et al 2015), and an age of ∼12 Gyr for the main population (Bechtol et al 2015). The Megacam imaging showed the blue stars were likely an intermediate-age population and confirmed the presence of a cluster-like overdensity.…”

Section: Introductionmentioning

confidence: 95%

“…Eri 2 was independently discovered by Koposov et al (2015) in public DES data and by Bechtol et al (2015) in DES internal data release Y1A1. Based on deep imaging with the Megacam on the Magellan Clay Telescope, an absolute magnitude M V = − 7.1 ± 0.3, a projected half-light radius R h,gal = 277 ± 14 pc, and a distance of ∼366 ± 17 kpc were determined (Crnojević et al 2016).…”

Section: Introductionmentioning

confidence: 99%

The MUSE-Faint survey

Zoutendijk

Brinchmann

Boogaard

et al. 2020

A&A

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Aims. It has been shown that the ultra-faint dwarf galaxy Eridanus 2 may host a stellar cluster in its centre. If this cluster is shown to exist, it can be used to set constraints on the mass and abundance of massive astrophysical compact halo objects (MACHOs) as a form of dark matter. Previous research has shown promising expectations in the mass range of 10−100 M⊙, but lacked spectroscopic measurements of the cluster. We aim to provide spectroscopic evidence regarding the nature of the putative star cluster in Eridanus 2 and to place constraints on MACHOs as a constituent of dark matter. Methods. We present spectroscopic observations of the central square arcminute of Eridanus 2 from MUSE-Faint, a survey of ultra-faint dwarf galaxies with the Multi Unit Spectroscopic Explorer on the Very Large Telescope. We derived line-of-sight velocities for possible member stars of the putative cluster and for stars in the centre of Eridanus 2. We discuss the existence of the cluster and determine new constraints for MACHOs using the Fokker–Planck diffusion approximation. Results. Out of 182 extracted spectra, we identify 26 member stars of Eridanus 2, seven of which are possible cluster members. We find intrinsic mean line-of-sight velocities of 79.7+3.1−3.8 km s−1 and 76.0+3.2−3.7 km s−1 for the cluster and the bulk of Eridanus 2, respectively, as well as intrinsic velocity dispersions of < 7.6 km s−1 (68% upper limit) and 10.3+3.9−3.2 km s−1, respectively. This indicates that the cluster most likely exists as a distinct dynamical population hosted by Eridanus 2 and that it does not have a surplus of dark matter over the background distribution. Among the member stars in the bulk of Eridanus 2, we find possible carbon stars, alluding to the existence of an intermediate-age population. We derived constraints on the fraction of dark matter that can consist of MACHOs with a given mass between 1 and 105 M⊙. For dark matter consisting purely of MACHOs, the mass of the MACHOs must be less than ∼7.6 M⊙ and ∼44 M⊙ at a 68- and 95% confidence level, respectively.

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“…opened the floodgates, and within two years the known population of Milky Way satellite galaxies more than doubled (Belokurov et al 2006(Belokurov et al , 2007Sakamoto & Hasegawa 2006;Zucker et al 2006a,b;Irwin et al 2007;Walsh et al 2007). Over the following decade, new discoveries continued at a rapid pace in SDSS and other surveys (e.g., Belokurov et al 2008Belokurov et al , 2009Belokurov et al , 2010Bechtol et al 2015;, 2016Kim & Jerjen 2015;Kim et al 2015a;Koposov et al 2015aKoposov et al , 2018Laevens et al 2015a,b;Martin et al 2015;Homma et al 2016Homma et al , 2018Torrealba et al 2016bTorrealba et al , 2018, such that the Milky Way satellite census has now doubled yet again (Figure 1). Thanks to significant investments of telescope time in deep imaging and spectroscopy of the newly discovered objects, along with accompanying theoretical modeling, we now have a general understanding of the properties of these systems and their place in galaxy evolution and cosmology.…”

Section: Introductionmentioning

confidence: 99%

The Faintest Dwarf Galaxies

Simon

2019

Annu. Rev. Astron. Astrophys.

477

383

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The lowest luminosity ([Formula: see text] L[Formula: see text]) Milky Way satellite galaxies represent the extreme lower limit of the galaxy luminosity function. These ultra-faint dwarfs are the oldest, most dark matter–dominated, most metal-poor, and least chemically evolved stellar systems known. They therefore provide unique windows into the formation of the first galaxies and the behavior of dark matter on small scales. In this review, we summarize the discovery of ultra-faint dwarfs in the Sloan Digital Sky Survey in 2005 and the subsequent observational and theoretical progress in understanding their nature and origin. We describe their stellar kinematics, chemical abundance patterns, structural properties, stellar populations, orbits, and luminosity function, as well as what can be learned from each type of measurement. We conclude the following: ▪ In most cases, the stellar velocity dispersions of ultra-faint dwarfs are robust against systematic uncertainties such as binary stars and foreground contamination. ▪ The chemical abundance patterns of stars in ultra-faint dwarfs require two sources of r-process elements, one of which can likely be attributed to neutron star mergers. ▪ Even under conservative assumptions, only a small fraction of ultra-faint dwarfs may have suffered significant tidal stripping of their stellar components. ▪ Determining the properties of the faintest dwarfs out to the virial radius of the Milky Way will require very large investments of observing time with future telescopes. Finally, we offer a look forward at the observations that will be possible with future facilities as the push toward a complete census of the Local Group dwarf galaxy population continues.

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Dark Matter Science in the Era of LSST

Cited by 108 publications

References 20 publications

GaiaData Release 2

GaiaData Release 2

The MUSE-Faint survey

The Faintest Dwarf Galaxies

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