[Paper Review] Orphan galaxies in semi-analytic models

Facundo M. Delfino, Claudia G. Scóccola+3 more|arXiv (Cornell University)|Feb 3, 2021

Galaxies: Formation, Evolution, Phenomena2 references5 citations

TL;DR

This paper presents a computationally efficient semi-analytic model for tracking orphan galaxies in cosmological simulations by incorporating dynamical friction, tidal mass loss, and a proximity merger criterion. When calibrated against a high-resolution simulation using halo mass function and two-point correlation function constraints, the model reproduces both metrics within 5% and 10% precision, respectively.

ABSTRACT

We present an updated model for the evolution of the orbits of to be used in the SAG semi-analytical model of galaxy formation and evolution. In cosmological simulations, orphan galaxies are those satellite galaxies for which, due to limited mass resolution, halo finders lose track of their dark matter subhalos and can no longer be distinguished as self-bound overdensities within the larger host system. Since the evolution of orphans depends strongly on the orbit they describe within their host halo, a proper treatment of their evolution is crucial in predicting the distribution of subhalos and satellite galaxies. The model proposed takes into account the dynamical friction drag, mass loss by tidal stripping and a proximity merger criterion, also it is simple enough to be inexpensive from a computational point of view. To calibrate this model, we apply it onto a dark matter only simulation and compare the results with a high resolution simulation, considering the halo mass function and the two-point correlation function as constraints. We show that while the halo mass function fails to put tight constraints on the dynamical friction, the addition of clustering information helps to better define the parameters of the model related to the spatial distribution of subhalos. Using the model with the best fit parameters allows us to reproduce the halo mass function to a precision better than 5 per cent, and the two point correlation function at a precision better than 10 per cent.

Motivation & Objective

• To improve the treatment of orphan galaxies—satellite galaxies whose dark matter subhalos are lost in low-resolution simulations—within semi-analytic galaxy formation models.
• To address the challenge that orphan galaxy evolution critically depends on orbital dynamics, which are poorly tracked when subhalos are no longer resolved.
• To develop a physically motivated yet computationally inexpensive model that captures key dynamical processes: dynamical friction, tidal stripping, and merger events.
• To calibrate the model using observables such as the halo mass function and two-point correlation function to constrain its free parameters.

Proposed method

• The model tracks the orbital evolution of orphan galaxies using a semi-analytic approach that includes dynamical friction force based on the host halo's density profile.
• Mass loss due to tidal stripping is modeled as a function of orbital radius and time, reducing the subhalo mass over time.
• A proximity merger criterion is implemented to determine when two subhalos merge based on their separation and relative velocity.
• The model is tested on a dark matter-only simulation and calibrated against a high-resolution simulation using the halo mass function and two-point correlation function as constraints.
• Parameter fitting is performed to optimize the model's ability to reproduce the observed clustering and mass function statistics.

Experimental results

Research questions

• RQ1 How accurately can a semi-analytic model reproduce the halo mass function and two-point correlation function when modeling orphan galaxy orbits?
• RQ2 To what extent do the halo mass function and clustering statistics jointly constrain the parameters of the orphan galaxy model?
• RQ3 Can a simple model incorporating dynamical friction, tidal stripping, and proximity mergers reproduce high-resolution simulation results with minimal computational cost?
• RQ4 What role does orbital information play in improving the fidelity of subhalo distribution predictions in low-resolution simulations?

Key findings

• The model reproduces the halo mass function with a precision better than 5% when using the best-fit parameters.
• The two-point correlation function is reproduced with a precision better than 10% using the same calibrated parameters.
• While the halo mass function alone provides weak constraints on dynamical friction parameters, the addition of clustering information significantly improves parameter calibration.
• The inclusion of orbital dynamics, tidal stripping, and merger criteria enables accurate tracking of subhalo spatial distribution despite the loss of subhalo identification in low-resolution simulations.