2025 Joint ARGOS-TITAN-TOSCA workshop

Liste des Contributions

1. Introduction

Jean-Luc Starck (CosmoStat, CEA Paris-Saclay)

07/07/2025 10:00

30. Radio weak-lensing shear measurements using deep learning

Priyam Tripathi

07/07/2025 10:20

The limited shape measurement methods in the radio waveband are either computationally intensive or fail to achieve the accuracy required for future surveys. In this talk, I will present a supervised deep learning framework, dubbed DeepShape, that measures galaxy shapes with the necessary precision while minimizing computational expenses. DeepShape is made of two modules. The first module is a...

33. Generative model for shear inference

Ezequiel Centofanti

07/07/2025 10:45

Next-generation radio interferometers, such as the SKA, will observe the radio sky with unprecedented sensitivity and resolution. Their wide sky coverage will also enable weak lensing studies using radio data. Radio weak lensing not only complements optical observations, but also allows access to higher redshifts. However, traditional shear estimation methods—based on measuring the ellipticity...

32. A Decentralized Framework for Radio-Interferometric Image Reconstruction

Sunrise Wang

07/07/2025 11:10

A Decentralized Framework for Radio-Interferometric Image Reconstruction
Abstract The advent of large aperture arrays, such as the ones currently under construction for SKAO, allows for observing the Universe in the radio-spectrum at unprecedented resolution and sensitivity. To process the enormous amounts of data produced by these telescopes, scalable software pipelines are required. In this...

29. Plug-and-play weak lensing mass mapping with fast uncertainty quantification

Hubert Leterme (ENSICAEN)

07/07/2025 11:35

In this talk, I will present a plug-and-play (PnP) approach for estimating the dark matter distribution from weak gravitational lensing data, using noisy shear measurements. Our method is designed to provide accurate and efficient mass maps without the need to retrain deep learning models for each new galaxy survey or sky region. Instead, a single model is trained on simulated mass maps...

39. Discussion

07/07/2025 12:00

41. Mass mapping and cosmological inference with higher-order statistics

Andreas Tersenov

07/07/2025 14:30

In this talk, I will present ongoing work toward improving cosmological inference from weak lensing through a synergy of forward modeling, simulation-based inference (SBI), and higher-order statistics. First, I will discuss the impact of mass mapping algorithms on the accuracy and robustness of cosmological parameter estimation. I will then introduce a framework that combines SBI with the BNT...

38. Wavelet l1norm: A Theory-Driven Approach Beyond Two-Point Inference

Vilasini Tinnaneri Sreekanth

07/07/2025 14:55

Weak gravitational lensing is a key cosmological probe of the large-scale matter distribution, yet conventional two-point statistics are insufficient to capture the non-Gaussian features imprinted by nonlinear structure formation. This thesis develops a novel framework based on the wavelet ℓ1-norm to extract higher-order information from weak lensing convergence maps. Leveraging predictions...

28. Deep Denoising and Signal Restoration for Astrophysical Spectral Cubes: From Simulations to Real Data

Arnab Lahiri (FORTH)

07/07/2025 15:20

Spectral cube data obtained from instruments such as ALMA are fundamental for understanding the structures and dynamics of astrophysical objects. However, noise, beam convolutions, and other artifacts can mask important astrophysical features. This is more evident in high-redshift observations as large cosmological distances, high levels of noise and lower resolution beams may hinder signal...

31. Unsupervised Cloud Removal and Change Detection on Multi-Temporal Images via Unrolled Tensor Decomposition Network

Anasthasia Aidini

07/07/2025 16:05

The increasing availability of multi-temporal remote sensing data offers unprecedented opportunities in monitoring environmental changes induced by natural disasters. However, a common issue in satellite imagery is cloud cover and cloud shadows, which can hinder further analysis. Given the high-dimensionality of satellite image time series and the lack of cloud-free observations and ground...

42. Antenna Array Optimization for Radio Interferometry: Towards a Machine Learning-Guided Approach

Manal BENSAHLI (CosmoStat, CEA Paris-Saclay)

07/07/2025 16:30

The quality of images produced by a radio interferometer strongly depends on the geometric layout of the individual antennas. Enhancing the UV-plane coverage through an optimal configuration improves the synthesized beam shape and enables a more accurate reconstruction of the sky, with reduced artefacts.
In this work, we investigate several strategies for optimizing antenna placements using...

43. Improving Weak Gravitational Lensing Using Kinematic Information from Galaxies

Jordy Ram

07/07/2025 16:50

In this talk, we introduce the concept of kinematic lensing to infer the intrinsic galaxy shapes
and their deformation due to the matter distribution in the line of sight. Traditional weak
lensing, in which the intrinsic galaxy shape is unknown, uses a significant number of galaxies
in order to make an estimate of the galaxy shear. However, the shape noise will remain a
source of variance...

40. Discussions

07/07/2025 17:10

34. Inertial Non-Convex Optimization Algorithms Meet Neural Network-Based Inverse Problems

Jalal Fadili (ENSICAEN)

08/07/2025 10:00

In this talk, I will focus on non-convex minimization problems via inertial second-order (in-time) dynamics and how they can prove valuable when solving inverse problems with neural network-based methods.
I will first discuss several theoretical and practical issues fo these algorithms, including convergence, convergence rates and trap avoidance properties.
I will then turn to discussing how...

35. Detection of Fast Radio Bursts using hybrid neural architecture

Sara El Bouch (OCA)

08/07/2025 10:30

FRBs-millisecond-duration radio pulses from distant galaxies-offer unique insights but remain challenging to detect due to overwhelming radio frequency interference. Traditional detection methods and conventional machine learning techniques struggle with extreme class imbalance and data volume challenges. Our solution treats FRB detection as an open-set anomaly detection problem, leveraging a...

37. UNIONS: First Cosmic Shear Constraints from 3000 deg² of Northern Sky

Cail Daley (CEA)

08/07/2025 11:00

The Ultraviolet Near-Infrared Optical Northern Survey (UNIONS) is a multi-band optical survey that will cover over 4800 deg² of northern sky. Combining data from three wide-field Hawaiian telescopes (CFHT, Pan-STARRS, and Subaru), UNIONS' sky coverage and excellent image quality makes it an ideal dataset for weak lensing studies, providing cosmological constraints that are both independent of...

36. Overview of the ESA Euclid mission in the context of ESA Science today

Valeria Pettorino (ESA)

08/07/2025 12:00

Abstract : After a brief introduction of the ESA Science programme I will focus on an overview of the ESA Euclid mission: I will describe mission objectives, challenges, main milestones so far, the first data release and next steps.
I will also mention a few ESA programmes dedicated to interns, graduate students, and postdocs.

bio:
I am a physicist, and I work as Euclid Project...

25. Learnlet for component separation of noisy data

Dr Victor Bonjean (FORTH)

08/07/2025 14:30

21 cm data analysis

Blind source separation (BSS) plays a pivotal role in modern astrophysics by enabling the extraction of scientifically meaningful signals from multi-frequency observations. Traditional BSS methods, such as those relying on fixed wavelet dictionaries, enforce sparsity during component separation, but may fall short when faced with the inherent complexity of real astrophysical signals. In this...

26. Foreground cleaning strategies for HI 21 cm signal extraction

Dr Sia Gkogkou (FORTH)

08/07/2025 14:55

21 cm data analysis

Neutral hydrogen (HI) intensity mapping is a powerful probe of cosmological parameters, the epoch of reionization, and the dark ages. However, extracting the HI signal is challenging due to astrophysical foregrounds that are over four orders of magnitude stronger. This work evaluates various blind source separation and fitting methods for reconstructing the HI signal under different telescope...

27. Higher order statistics for HI intensity mapping

Pauline Gorbatchev

08/07/2025 15:20

21 cm data analysis

HI intensity mapping is a promising tool for probing large-scale structure, but at late times the 21cm signal becomes strongly non-Gaussian due to nonlinear gravitational evolution and astrophysical effects. Standard two-point statistics like the angular power spectrum fail to capture this non-Gaussian information, potentially limiting their ability to constrain cosmological parameters. We...

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