Generating LSB-optimised synthetic images for simulated galaxies

TL;DR

This paper presents a new emission-biasing scheme in the SKIRT radiative transfer code that efficiently enhances low-surface-brightness galaxy image simulation by boosting photon emission from faint regions, improving depth without high computational costs.

Contribution

The authors introduce a novel biasing method based on smoothing lengths in radiative transfer simulations to better capture low-brightness galaxy outskirts.

Findings

Bias factors proportional to smoothing length extend LSB detection in simulations.

Method conserves energy through weight corrections despite biasing.

Significant improvement in synthetic galaxy imaging depth.

Abstract

We introduce an emission-biasing scheme in the SKIRT radiative transfer code that enables efficient generation of synthetic galaxy images optimized for low-surface-brightness (LSB) science. Standard Monte Carlo radiative transfer simulations achieve high signal-to-noise in bright regions but require prohibitively many photon packets to reach reliable depth in galaxy outskirts. By assigning stellar particles bias factors that scale with their smoothing lengths, our method boosts photon emission from low-density regions while conserving energy through weight corrections. Tests on a Milky-Way-like galaxy from the TNG50 cosmological simulation show that bias factors proportional to the smoothing length substantially extend the reliable LSB regime, providing an inexpensive improvement for deep synthetic imaging of simulated galaxies.