# New Analytic Solutions for Galaxy Evolution: Gas, Stars, Metals and Dust in local Early-Type Galaxies and in their high-z Starforming Progenitors

## TL;DR

This paper introduces new analytic models for the evolution of gas, stars, metals, and dust in galaxies, enabling better understanding and prediction of galaxy formation and evolution, especially for early-type galaxies and their high-redshift progenitors.

## Contribution

The paper presents novel analytic solutions that self-consistently describe galaxy evolution, facilitating exploration of physical processes and improving theoretical models and simulations.

## Key findings

- Reproduces statistical relationships of early-type galaxies
- Disentangles roles of physical processes in galaxy formation
- Provides transparent predictions for high-redshift galaxy observations

## Abstract

We present a set of new analytic solutions aimed at self-consistently describing the spatially-averaged time evolution of the gas, stellar, metal, and dust content in an individual starforming galaxy hosted within a dark halo of given mass and formation redshift. Then, as an application, we show that our solutions, when coupled to specific prescriptions for parameter setting (inspired by in-situ galaxy-black hole coevolution scenarios) and merger rates (based on numerical simulations), can be exploited to reproduce the main statistical relationships followed by early-type galaxies and by their high-redshift starforming progenitors. Our analytic solutions allow to easily disentangle the diverse role of the main physical processes regulating galaxy formation, to quickly explore the related parameter space, and to make transparent predictions on spatially-averaged quantities. As such, our analytic solutions may provide a basis for improving the (subgrid) physical recipes presently implemented in theoretical approaches and numerical simulations, and can offer a benchmark for interpreting and forecasting current and future broadband observations of high-redshift starforming galaxies.