GalaPy

Wed, 01 May 2024 00:00:00 +0000

Role: lead author & maintainer. Stack: C++ compute core exposed through a Python API; hybrid parallelisation (vectorised array programming, shared-memory concurrency, distributed-memory message passing).

GalaPy simulates the panchromatic emission of galaxies from X-rays to radio and performs Bayesian spectral-energy-distribution fitting. Models are generated on the fly rather than interpolated from a template library, which is what allows a peak throughput of almost 1000 SEDs per second on a single core — the fastest SED-generation tool of its kind.

The library is designed around an object-oriented architecture that keeps it portable with minimal memory overhead, and it scales from a laptop to an HPC allocation without changing the user-facing API. Recent additions include parallel sampling for Bayesian inference and a fully analytical, panchromatic AGN component.

Since release, GalaPy has been adopted by groups across Europe, Asia and South America, for work ranging from nearby resolved galaxies to JWST high-redshift candidates. Its role in my wider programme is described in my .

Presented in Astronomy & Astrophysics 685, A161 (2024) — see — with the computational design detailed in Astronomy and Computing 55, 101079 (2026): .

Galaxy formation and evolution

Wed, 29 Jul 2026 00:00:00 +0000

A second major axis is galaxy formation and evolution across cosmic time. With collaborators at SISSA I have analysed the spectral properties of high-redshift galaxies using theoretical models of star formation and dust processes.

This led to GalaPy, a public code that simulates the panchromatic emission of galaxies from X-rays to radio, offering full SED modelling, Bayesian inference, and a computationally efficient implementation. It is the fastest SED-generation tool of its kind, with a peak performance of almost 1000 SEDs per second on a single core, thanks to a hybrid C++/Python architecture that generates models on the fly rather than relying on templates.

Since its release GalaPy has gained users across Europe, Asia and South America, and has been adopted for studies ranging from nearby resolved galaxies to JWST high-redshift candidates. In a recent paper I presented the computational design of the code in detail: its object-oriented architecture, a hybrid parallelisation strategy combining vectorised array programming, shared-memory concurrency and distributed-memory message passing, and the optimisations that keep it portable with minimal memory overhead. That work also introduced two new capabilities — parallel sampling for Bayesian inference, and a fully analytical panchromatic AGN component.

Currently: GalaPy is developing along two directions. I am co-supervising a Ph.D. student implementing panchromatic line emission in GalaPy SEDs, covering both the physics of emission lines and the sampling strategies needed for efficient inference. Meanwhile growing adoption for JWST and ALMA data is driving further computational optimisation and validated spectroscopic fitting beyond the current photometric mode.

Key papers: ·

Software:

SED Modelling |

GalaPy

Galaxy formation and evolution