112 citations · 145 across the 3 of their papers we have counts for
7 papers
A Photon Burst Clears the Earliest Dusty Galaxies: Modelling Dust in High-redshift Galaxies from ALMA to JWST
Daichi Tsuna, Yurina Nakazato, Tilman Hartwig
The generation and evolution of dust in galaxies are important tracers for star formation, and can characterize the rest-frame ultraviolet to infrared emission from the galaxies. I…
The Galaxy Assembly and Interaction Neural Networks (GAINN) for high-redshift JWST observations
Lillian Santos-Olmsted, Kirk Barrow, Tilman Hartwig
We present the Galaxy Assembly and Interaction Neural Networks (GAINN), a series of artificial neural networks for predicting the redshift, stellar mass, halo mass, and mass-weight…
Population III X-ray Binaries and their Impact on the Early Universe
Nina S. Sartorio, A. Fialkov, T. Hartwig +8
The first population of X-ray binaries (XRBs) is expected to affect the thermal and ionization states of the gas in the early Universe. Although these X-ray sources are predicted t…
Machine learning detects multiplicity of the first stars in stellar archaeology data
Tilman Hartwig, Miho N. Ishigaki, Chiaki Kobayashi +2
In unveiling the nature of the first stars, the main astronomical clue is the elemental compositions of the second generation of stars, observed as extremely metal-poor (EMP) stars…
Unveiling the contribution of Pop III stars in primeval galaxies at redshift
Shafqat Riaz, Tilman Hartwig, Muhammad A. Latif
Detection of the first stars has remained elusive so-far but their presence may soon be unveiled by upcoming JWST observations. Previous studies have not investigated the entire po…
Comparing simulated Milky Way satellite galaxies with observations using unsupervised clustering
Li-Hsin Chen, Tilman Hartwig, Ralf S. Klessen +1
We develop a new analysis method that allows us to compare multi-dimensional observables to a theoretical model. The method is based on unsupervised clustering algorithms which ass…