Japanese Cosmic Dawn/Epoch of Reionization Science with the Square Kilometre Array

Abstract

Cosmic reionization is known to be a major phase transition of the gas in the Universe. Since astronomical objects formed in the early Universe, such as the first stars, galaxies and black holes, are expected to have caused cosmic reionization, the formation history and properties of such objects are closely related to the reionization process. In spite of the importance of exploring reionization, our understandings regarding reionization is not sufficient yet. Square Kilometre Array (SKA) is a next-generation large telescope that will be operated in the next decade. Although several programs of next-generation telescopes are currently scheduled, the SKA will be the unique telescope with a potential to directly observe neutral hydrogen up to z~30, and provide us with valuable information on the Cosmic Dawn (CD) and the Epoch of Reionization (EoR). The early science with the SKA will start in a few years; it is thus the time for us to elaborate a strategy for CD/EoR Science with the SKA. The purpose of this document is to introduce Japanese scientific interests in the SKA project and to report results of our investigation.

14 pages, 12 figures, Japan SKA consortium (SKA-JP) Cosmic Dawn/Epoch of Reionization Science book

Cited by in corpus (7)

• Constraining the EoR model parameters with the 21cm bispectrum
• Detectability of 21cm-signal during the Epoch of Reionization with 21cm-Lyman-$\alpha$ emitter cross-correlation. I
• Exploring the cosmic dawn and epoch of reionization with 21cm line
• Bubble mapping with the Square Kilometer Array -- I. Detecting galaxies with Euclid, JWST, WFIRST and ELT within ionized bubbles in the intergalactic medium at z>6
• Detectability of 21cm-signal during the Epoch of Reionization with 21cm-Lyman-α emitter cross-correlation. II. Foreground contamination
• Detectability of 21cm signal during the Epoch of Reionization with 21cm-Lyman-$\alpha$ emitter cross-correlation. III. Model dependence
• Predicting 21cm-line map from Lyman $\alpha$ emitter distribution with Generative Adversarial Networks