HI, CO, and Dust in the Perseus Cloud

TL;DR

This study refines the understanding of hydrogen gas distribution in the Perseus cloud by analyzing gas and dust emission data, revealing significant optically-thick HI gas and dust evolution effects that impact gas mass estimates.

Contribution

It introduces a calibrated tau353-NH relationship and estimates the optical depth of HI and the CO-to-H2 conversion factor in the Perseus cloud, highlighting the importance of dust evolution and optical depth corrections.

Findings

Optically-thick HI gas constitutes about 60% of total HI.

The average tauHI around the cloud is approximately 0.92.

The XCO factor is estimated to be around 1.0x10^20 cm^-2 K^-1 km^-1 s.

Abstract

Comparison analyses between the gas emission data (HI 21cm line and CO 2.6 mm line) and the Planck/IRAS dust emission data (optical depth at 353 GHz tau353 and dust temperature Td) allow us to estimate the amount and distribution of the hydrogen gas more accurately, and our previous studies revealed the existence of a large amount of optically-thick HI gas in the solar neighborhood. Referring to this, we discuss the neutral hydrogen gas around the Perseus cloud in the present paper. By using the J-band extinction data, we found that tau353 increases as a function of the 1.3-th power of column number density of the total hydrogen (NH), and this implies dust evolution in high density regions. This calibrated tau353-NH relationship shows that the amount of the HI gas can be underestimated to be ~60% if the optically-thin HI method is used. Based on this relationship, we calculated optical depth of the 21 cm line (tauHI), and found that <tauHI> ~ 0.92 around the molecular cloud. The effect of tauHI is still significant even if we take into account the dust evolution. We also estimated a spatial distribution of the CO-to-H2 conversion factor (XCO), and we found its average value is <XCO> ~ 1.0x10^20 cm-2 K-1 km-1 s. Although these results are inconsistent with some previous studies, these discrepancies can be well explained by the difference of the data and analyses methods.