Attention-Based Neural Network Emulators for Multi-Probe Data Vectors Part II: Assessing Tension Metrics

Understand

The next generation of cosmological surveys is expected to generate unprecedented high-quality data, consequently increasing the already substantial computational costs of Bayesian statistical methods.

• This will pose a significant challenge to analyzing theoretical models of cosmology.
• Additionally, new mitigation techniques of baryonic effects, intrinsic alignment, and other systematic effects will inevitably introduce more parameters, slowing down the convergence of Bayesian analyses.
• In this scenario, machine-learning-based accelerators are a promising solution, capable of reducing the computational costs and execution time of such tools by order of thousands.