Code for Bayesian Analysis

DerivKit — a robust Python toolkit for stable numerical derivatives

DeepSphere: a graph-based spherical CNN (TensorFlow)

Python code for learning cosmology using different methods and mock data

Flexible, fully bayesian stacking software for modelling of astronomical data sets

CosmicFishPie: Python Fisher Matrix code for Cosmological probes

Repository containing tutorials about how to use Cobaya for cosmological inference at PhD Schools

Correlation functions versus field-level inference in cosmology: example with log-normal fields

Mock CMB likelihood class for Cobaya sampler (https://github.com/CobayaSampler/cobaya), and several specific experiment examples

Collection of Jupyter notebooks demonstrating statistical methods for cosmological data analysis, including Bayesian inference & basic frequentist tools

Main tools and results from arxiv:

Interactive exploration of equivariant neural networks on homogeneous spaces, with a focus on the sphere S² as SO(3)/SO(2). From Lecture 8 of the Lie groups course with Quantum Formalism

JAX-powered Hi-Fi mocks

A Bayesian Python code to confront the quasar data set with models beyond the standard model of elementary particle physics and models beyond the $\Lambda$CDM standard cosmology.

The codes for computing the scale-dependent peak height function and the scale-dependent valley depth function of the cosmic-log density field.

The universe may operate as a self-executing algorithm where structure precedes matter. Reality’s “errors”—from cosmic anomalies to quantum correlations—are reflections of its code. Through holography, recursion, and informational self-replication, the cosmos continuously rewrites its own laws.

Flexible, fully bayesian stacking software for modelling of astronomical data sets

This essay presents a clear and intuitive overview of the full Siamese Universe framework. It explains how a shared quantum vacuum, a minimal phase desynchronization, and CPT symmetry together generate matter, structure, and cosmic complexity. A causal narrative linking physical principles and observable signatures.

Quadratic estimator algorithm to extract the weak gravitational lensing power spectrum from a shear catalog.