Data products and software released by our members and projects. Please contact Katya (kateryna.vovk@ipmu.jp) if you would like your data or software to be included on this page.

Observational Data

Hyper Suprime-Cam (data access)
The latest public release (third release) of HSC-SSP includes over 600 square degrees of deep multi-color data served through dedicated databases and user interfaces.

Software

Galight
A Python-based open-source package that performs two-dimensional model fitting of optical and near-infrared images to characterize the light distribution of galaxies with components including a disk, bulge, bar, and quasar.

Yomikata
Yomikata uses context to resolve ambiguous words in Japanese (Demo).

CosmoMMF
A julia based code that identifies clusters, filaments, walls, and voids using a modified version of the NEXUS algorithm, developed as part of Sunseri et al. 2022.

LUCiD (arxiv:2602.24129)
LUCiD (Light-based Unified Calibration and trackIng Differentiable simulation) is a high-performance, end-to-end differentiable simulation framework for optical particle detectors, such as Cherenkov and scintillator neutrino detectors. It enables gradient-based optimization of calibration parameters and particle reconstruction using automatic differentiation.

PhotonSim (arxiv:2602.24129)
A GEANT4-based C++ application that simulates optical photon generation (Cherenkov and scintillation) from particle interactions in monolithic detector volumes. It produces the photon samples used to build the surrogate models in LUCiD.

Simulation

The HalfDome Cosmological Simulations
The HalfDome Cosmological Simulations are tailored to the joint analysis of ongoing and upcoming cosmological surveys.

IllustrisTNG in the HSC-SSP (arxiv:2308.14793)
Synthetic images of galaxies from the IllustrisTNG simulations made using dust radiative transfer post-processing with SKIRT. The images are designed to match the observational characteristics of the Hyper Suprime-Cam Subaru Strategic Program. Both “HSC-realistic” and noise-free, high-resolution versions of the images are available. Galleries: HSC-realistic mocks, idealized mocks

kappaTNG (arxiv:2010.09731)
A suite of mock weak lensing maps based on the cosmological hydrodynamic simulations IllustrisTNG (TNG300-1), suitable for studying the effects of baryons on weak lensing.

MassiveNuS (arxiv:1711.10524)
A suite of 100 cosmological massive neutrino simulations (+ 1 massless model), with snapshots, halo catalogues, merger trees, and CMB and weak lensing convergence maps.

Teaching Materials

Lectures, hands-on notebooks, and hack projects from the AstroAI Asian (A3) Network Summer Schools on machine learning for astrophysics.

A3Net Summer School 2026 (Taipei, school page)
Statistical modeling and machine learning foundations (Tomomi Sunayama, Ting-Wen Lan); deep learning and neural network architectures (Kazuhiro Terao); generative models (Daniela Breitman); symmetries, specialized architectures, and transformers (Vera Maiboroda); hack projects.

A3Net Summer School 2025 (Seoul, school page)
Statistical modeling and machine learning (Adrian Bayer); introduction to deep learning (Sungwook E. Hong); generative models (Carol Cuesta-Lazaro); symmetries and specialized neural architectures (Vera Maiboroda); research application examples; hack projects.

A3Net Summer School 2024 (Osaka, school page)
Statistical modeling and shallow machine learning (Makoto Uemura); deep learning basics (Leander Thiele); symmetries and specialized neural architectures (Michelle Ntampaka); generative models (Kana Moriwaki); hack projects.