Reconstructing Galaxy Cluster Mass Maps using Score-based Generative Modeling

TL;DR

This paper introduces a score-based generative model that reconstructs galaxy cluster mass maps from mock observational data, accurately capturing the density profiles and structures across scales, demonstrating the potential for detailed astrophysical analysis.

Contribution

The paper presents a novel diffusion-based approach for reconstructing galaxy cluster density maps conditioned on observational data, improving accuracy and generalization over previous methods.

Findings

Accurately reconstructs radial density profiles of galaxy clusters.

Achieves near-unity bias and cross-correlation coefficients in spectral analysis.

Demonstrates the model's ability to distinguish clusters of different masses.

Abstract

We present a novel approach to reconstruct gas and dark matter projected density maps of galaxy clusters using score-based generative modeling. Our diffusion model takes in mock SZ and X-ray images as conditional inputs, and generates realizations of corresponding gas and dark matter maps by sampling from a learned data posterior. We train and validate the performance of our model by using mock data from a cosmological simulation. The model accurately reconstructs both the mean and spread of the radial density profiles in the spatial domain, indicating that the model is able to distinguish between clusters of different mass sizes. In the spectral domain, the model achieves close-to-unity values for the bias and cross-correlation coefficients, indicating that the model can accurately probe cluster structures on both large and small scales. Our experiments demonstrate the ability of score models to learn a strong, nonlinear, and unbiased mapping between input observables and fundamental density distributions of galaxy clusters. These diffusion models can be further fine-tuned and generalized to not only take in additional observables as inputs, but also real observations and predict unknown density distributions of galaxy clusters.