The Need for Speed: Escape velocity and dynamical mass measurements of the Andromeda galaxy

Abstract: Our nearest large cosmological neighbour, the Andromeda galaxy (M31), is a dynamical system, and an accurate measurement of its total mass is central to our understanding of its assembly history, the life-cycles of its satellite galaxies, and its role in shaping the Local Group environment. Here, we apply a novel approach to determine the dynamical mass of M31 using high velocity Planetary Nebulae (PNe), establishing a hierarchical Bayesian model united with a scheme to capture potential outliers and marginalize over tracers unknown distances. With this, we derive the escape velocity run of M31 as a function of galacto-centric distance, with both parametric and non-parametric approaches. We determine the escape velocity of M31 to be $470\pm{40}$ km s$^{-1}$ at a galacto-centric distance of 15 kpc, and also, derive the total potential of M31, estimating the virial mass and radius of the galaxy to be $0.8\pm{0.1}\times10^{12}\,M_\odot$ and $240\pm{10}$ kpc, respectively. Our M31 mass is on the low-side of the measured range, this supports the lower expected mass of the M31-Milky Way system from the timing and momentum arguments, satisfying the HI constraint on circular velocity between $10\lesssim R/\textrm{kpc}<35$, and agreeing with the stellar mass Tully-Fisher relation. To place these results in a broader context, we compare them to the key predictions of the $\Lambda{\rm CDM}$ cosmological paradigm, including the stellar-mass-halo-mass and the dark matter halo concentration-virial mass correlation, and finding it to be an outlier to this relation.

• The paper presents a novel hierarchical Bayesian method to measure Andromeda’s escape velocity and mass using high-velocity planetary nebulae data.
• It reports an escape velocity of 470±40 km/s at 15 kpc and a virial mass of 0.8±0.1×10^12 M⊙, refining previous estimates.
• The advanced methodology sets a new standard for dynamical analyses, enhancing our understanding of galaxy formation and local group interactions.

Modeling Escape Velocity and Dynamical Mass of the Andromeda Galaxy

The paper "The Need for Speed: Escape Velocity and Dynamical Mass Measurements of the Andromeda Galaxy" by P. R. Kafle et al. presents a comprehensive analysis of the dynamical mass and escape velocity measurements of the Andromeda galaxy (M31), utilizing a novel methodology combining high-velocity data from Planetary Nebulae (PNe) with hierarchical Bayesian modeling. This methodological advancement provides an improved technique in understanding the mass distribution and dynamics of M31, which is paramount for interpretations of galactic evolution within the Local Group.

The study employs a sample extracted from the current largest catalog of PNe for M31, with line-of-sight velocity data from spectra obtained using the Planetary Nebula Spectrograph. This dataset forms the basis for analyzing the high-velocity tail distribution to infer the escape velocity profile of M31 as a function of galacto-centric distance, based on the model formalism proposed by \cite{1990ApJ...353..486L} and extended using hierarchical Bayesian methods. The authors advance the original approach by incorporating improvements like the treatment of unknown distance and potential outliers, and employing both parametric and non-parametric techniques to the data.

Key results include the determination of the escape velocity of M31 at 15 kpc to be $470 \pm 40 \, \text{km/s}$, suggesting escape velocity decreases with distance. For the total mass estimation, the paper reports the virial mass and radius of M31 to be $0.8 \pm 0.1 \times 10^{12} \, M_\odot$ and $240 \pm 10 \, \text{kpc}$ respectively. These results place M31's mass on the low end of previous estimates, aligning with predictions from the timing and momentum arguments about the M31-Milky Way mass system and corroborating the stellar-mass–halo-mass relation.

The implications of these findings highlight the mass distribution's effect on understanding M31's assembly history and its interaction with the Milky Way, influencing theories about the dynamics of the Local Group. The paper further discusses the observed agreement and discrepancies of these results with predictions of the $\Lambda$CDM cosmology, specifically the dark matter halo concentration-mass and stellar-mass–halo-mass relations, indicating the potential need for refined cosmological models.

The methodology, relying on a hierarchical Bayesian approach and sophisticated statistical tools, sets a new standard for dynamical studies of nearby galaxies. This robust framework not only offers improved estimations for the mass profile of M31 but also opens avenues for its application in other galactic contexts where such data is available. Future developments in obtaining larger high-velocity samples could refine these techniques, consequently narrowing uncertainties in mass estimations and yielding greater insights into galaxy formation and evolution within cosmological frameworks.