The orbital PDF: general inference of the gravitational potential from steady-state tracers

Han, Jiaxin; Wang, Wenting; Cole, Shaun; Frenk, Carlos S.

doi:10.1093/mnras/stv2707

Cited by 25 publications

(49 citation statements)

References 30 publications

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“…In a steady-state halo, the density profile is fully determined by the distribution of orbits of the particles, because the distribution of particles around their orbits is fixed by the travel time at each position (Han et al 2016). If subhaloes follow a similar distribution of orbits to that of the particles, they would naturally form the same spatial profile as that of the DM particles.…”

Section: The Spatial Pdf Of Accreted Objectsmentioning

confidence: 99%

A unified model for the spatial and mass distribution of subhaloes

Han

Cole

Frenk

et al. 2016

Mon. Not. R. Astron. Soc.

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140

162

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Section: The Spatial Pdf Of Accreted Objectsmentioning

confidence: 99%

A unified model for the spatial and mass distribution of subhaloes

Han

Cole

Frenk

et al. 2016

Mon. Not. R. Astron. Soc.

Self Cite

140

162

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“…In a previous paper (Han et al 2016a), we developed the orbital Probability Distribution Function (oPDF) method to infer the underlying mass distribution or halo potential, which only assumes that tracers are well phase mixed and relaxed, and the underlying potential is spherical. This clean method allowed us to further investigate how the two assumptions hold when it is applied to Aquarius haloes (Han et al 2016b).…”

Section: Introductionmentioning

confidence: 99%

“…To study stellar tracers, we use an additional sample of haloes from a set of hydrodynamical simulations of the Local Group. In Han et al (2016a) and Wang et al (2015), the star particles are selected from N-body simulations using the particle-tagging technique (Cooper et al 2010). In this work, we instead use stars directly produced from the hydrodynamical simulations.…”

Section: Introductionmentioning

confidence: 99%

“…Results from these hydrodynamical simulations are compared to their corresponding dark matter only runs to study the influence of baryonic physics in dynamical modelling. Han et al (2016a) and Wang et al (2015) have reported that both statistical and systematic errors tend to be aligned along a direction of anticorrelation between halo mass and concentration parameters even when the statistical errors are controlled to be much smaller than the systematic uncertainties. It has been argued that this is probably due to an underestimate of statistical errors.…”

Section: Introductionmentioning

confidence: 99%

“…The method of Han et al (2016a) is briefly summarized in Section 3. Results based on the large sample of haloes from the Millennium II simulation and based on star particles in hydrodynamical simulations is presented in Sections 4 and 5, respectively.…”

Section: Introductionmentioning

confidence: 99%

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What to expect from dynamical modelling of galactic haloes

Wang

Han

Cole

et al. 2017

Monthly Notices of the Royal Astronomical Society

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Many dynamical models of the Milky Way halo require assumptions that the distribution function of a tracer population should be independent of time (i.e., a steady state distribution function) and that the underlying potential is spherical. We study the limitations of such modelling by applying a general dynamical model with minimal assumptions to a large sample of galactic haloes from cosmological N -body and hydrodynamical simulations. Using dark matter particles as dynamical tracers, we find that the systematic uncertainties in the measured mass and concentration parameters typically have an amplitude of 25% to 40%. When stars are used as tracers, however, the systematic uncertainties can be as large as a factor of 2 − 3. The systematic uncertainties are not reduced by increasing the tracer sample size and vary stochastically from halo to halo. These systematic uncertainties are mostly driven by underestimated statistical noise caused by correlated phase-space structures that violate the steady state assumption. The number of independent phase-space structures inferred from the uncertainty level sets a limiting sample size beyond which a further increase no longer significantly improves the accuracy of dynamical inferences. The systematic uncertainty level is determined by the halo merger history, the shape and environment of the halo. Our conclusions apply generally to any spherical steady-state model.

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The mass of our Milky Way

Wang¹,

Han²,

Cautun³

et al. 2020

Sci. China Phys. Mech. Astron.

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112

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We perform an extensive review of the numerous studies and methods used to determine the total mass of the Milky Way. We group the various studies into seven broad classes according to their modeling approaches. The classes include: i) estimating Galactic escape velocity using high velocity objects; ii) measuring the rotation curve through terminal and circular velocities; iii) modeling halo stars, globular clusters and satellite galaxies with the Spherical Jeans equation and iv) with phase-space distribution functions; v) simulating and modeling the dynamics of stellar streams and their progenitors; vi) modeling the motion of the Milky Way, M31 and other distant satellites under the framework of Local Group timing argument; and vii) measurements made by linking the brightest Galactic satellites to their counterparts in simulations. For each class of methods, we introduce their theoretical and observational background, the method itself, the sample of available tracer objects, model assumptions, uncertainties, limits and the corresponding measurements that have been achieved in the past. Both the measured total masses within the radial range probed by tracer objects and the extrapolated virial masses are discussed and quoted. We also discuss the role of modern numerical simulations in terms of helping to validate model assumptions, understanding systematic uncertainties and calibrating the measurements. While measurements in the last two decades show a factor of two scatters, recent measurements using Gaia DR2 data are approaching a higher precision. We end with a detailed discussion of future developments in the field, especially as the size and quality of the observational data will increase tremendously with current and future surveys. In such cases, the systematic uncertainties will be dominant and thus will necessitate a much more rigorous testing and characterization of the various mass determination methods.

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The orbital PDF: general inference of the gravitational potential from steady-state tracers

Cited by 25 publications

References 30 publications

A unified model for the spatial and mass distribution of subhaloes

A unified model for the spatial and mass distribution of subhaloes

What to expect from dynamical modelling of galactic haloes

The mass of our Milky Way

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