Galaxies as stochastic systems: why the next breakthrough in galaxy evolution requires one hundred million spectra
Sandro Tacchella, Vasily Belokurov, Harry T. J. Bevins, Roberto Maiolino, Hiranya V. Peiris, Lucia Pozzetti, Mark T. Sargent

TL;DR
Understanding galaxy evolution as a stochastic process requires analyzing vast ensembles of galaxy spectra, demanding a future large-scale spectroscopic survey with hundreds of millions of observations to constrain physical mechanisms.
Contribution
The paper proposes a hierarchical inference framework for galaxy evolution using large-scale spectroscopic data, emphasizing the need for a new survey capable of capturing millions of galaxy spectra across redshifts.
Findings
Galaxy evolution can be modeled as a stochastic process with hyper-parameters.
A survey of approximately 10^8 galaxies is necessary to constrain these hyper-parameters.
Such data will enable comparisons to simulations and improve understanding of galaxy physics.
Abstract
Each galaxy is observed only once along its life, making galaxy evolution fundamentally an inverse statistical problem: time-dependent physics must be inferred from ensembles of single-epoch snapshots. To move beyond descriptive scaling relations toward physical regulation mechanisms of star formation, quenching, chemical enrichment and black hole growth, galaxies must be treated as realizations of a stochastic process whose hyper-parameters (e.g., correlation timescales, burstiness, duty cycles) are inferred hierarchically. This demands both depth and scale: continuum S/N sufficient for absorption-line ages and chemistry, and samples far larger than those in SDSS, DESI, 4MOST or MOONS, which provide either depth or size but not both across . Once the relevant axes of mass, redshift, environment, structure and evolutionary phase are populated, the requirement naturally rises from…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Galaxies: Formation, Evolution, Phenomena · Scientific Research and Discoveries
