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Stellar feedback drives the baryon deficiency in low-mass galaxies

Haoran Yu, Enci Wang, Zeyu Chen, Céline Péroux, Hu Zou, Zhicheng He, Huiyuan Wang, Cheqiu Lyu, Cheng Jia, Chengyu Ma, Xu Kong

Abstract

Stellar feedback, as a key process regulating the baryon cycle, is thought to greatly redistribute baryonic material inside and outside the dark matter halos (DMHs), however the observational evidences are lacking. Through stacking analyses of ~400,000 galaxy spectra from Dark Energy Spectroscopic Instrument (DESI), we find star formation driven cool outflows in Mg II absorption line. Assuming only gravity acts on the launched gas, our calculations reveal that outflows from low mass galaxies (log M*<10) are capable of escaping beyond the DMHs, which aligns well with our finding in the circumgalactic medium (CGM) absorption along the minor-axes of galaxies using background quasars. This research offers indirect evidence that stellar feedback drives the low baryon retention rate in low-mass haloes, implicating that baryonic processes within galaxies are connected with the diffuse matter beyond the DMHs.

Stellar feedback drives the baryon deficiency in low-mass galaxies

Abstract

Stellar feedback, as a key process regulating the baryon cycle, is thought to greatly redistribute baryonic material inside and outside the dark matter halos (DMHs), however the observational evidences are lacking. Through stacking analyses of ~400,000 galaxy spectra from Dark Energy Spectroscopic Instrument (DESI), we find star formation driven cool outflows in Mg II absorption line. Assuming only gravity acts on the launched gas, our calculations reveal that outflows from low mass galaxies (log M*<10) are capable of escaping beyond the DMHs, which aligns well with our finding in the circumgalactic medium (CGM) absorption along the minor-axes of galaxies using background quasars. This research offers indirect evidence that stellar feedback drives the low baryon retention rate in low-mass haloes, implicating that baryonic processes within galaxies are connected with the diffuse matter beyond the DMHs.

Paper Structure

This paper contains 18 sections, 12 equations, 11 figures.

Figures (11)

  • Figure 1: Outflow properties of samples with $0.6<z<1.7$ on the $M_*$-$\rm SFR$ diagram.(A) The distribution of samples, where colors of the hexagons indicate the total galaxy count per bin (including adjacent bins for stacking). Grey hexagons are excluded from color mapping due to insufficient neighboring bins, but the sample within them are used in the stacking of adjacent inner bins. Some of the stacked spectra are plotted over the hexagons with the two vertical dashed lines indicating the rest-frame wavelengths of Mg ii$\lambda$2796 and Mg ii$\lambda$2803, highlighting the prevalence of blueshifted outflow absorption features. The inset illustrates the stacked spectrum derived from galaxies within the black contour. (B) The map of outflow equivalent width ($\rm EW_{out}$). (C) The map of mean outflow velocity ($v_{\rm out}$). (D) The map of mass outflow rate ($\dot{M}_{\rm out}$). (E) The map of mass-loading factor ($\eta\equiv \dot{M}_{\rm out}/\mathrm{SFR}$), where the values are derived from the stacked spectra.
  • Figure 2: Redshift evolution of outflow properties. (A)$v_{\rm out}$ as a function of $\log M_*$. The samples are divided into three bins by redshift. The blue, green and yellow points represent the samples with $0.6\leq z<0.9$, $0.9\leq z<1.2$ and $1.2\leq z < 1.7$, respectively. The open symbols denote Mg ii outflow velocity measurements Weiner09Bordoloi14 from the literature. The value of each point is derived with a composite spectrum of 10,000 spectra, with the shaded area indicating 1$\sigma$ uncertainties from bootstrapping analysis. The dashed line is the best-fit relation, see Equation \ref{['eq:vout']}. (B)$v_{\rm out}$ as a function of $\log \rm SFR$. (C)$\dot{M}_{\rm out}$ as a function of $\log M_*$. The shaded area indicates 1$\sigma$ uncertainties propagated from the uncertainty in $\rm EW_{out}$ derived from bootstrap sampling and the uncertainty in estimating H i column density from $\rm EW_{out}$. (D)$\dot{M}_{\rm out}$ as a function of $\log \rm SFR$. The dashed line is the best-fit relation, see Equation \ref{['eq:mout']}.
  • Figure 3: The mass-loading factor as a function of outflow velocity, distinguishing energy-driven and momentum-driven outflow regimes. The data points colored by redshift are taken from the left panel of Figure \ref{['fig:evolution']}. To mitigate potential contamination from AGN activity in massive galaxies, we exclude data points with $M_*>10^{10}\,\rm M_\odot$. The solid and dash-dotted lines show best-fit models assuming fixed power-law exponents of $-2$ (energy-driven scenario) and $-1$ (momentum-driven scenario), respectively.
  • Figure 4: The (A) The velocity decay of outflows. The diagonal crosses represent the observed outflow velocities, which are obtained through Equation \ref{['eq:vout']} according to the given $M_*$ of galaxies. The four curves with increasing launching velocity represent velocity decay of outflows in galaxies with stellar mass of $10^{9.3}\,\rm M_\odot$, $10^{9.6}\,\rm M_\odot$, $10^{10.0}\,\rm M_\odot$ and $10^{10.4}\,\rm M_\odot$. (B) The EW(Mg ii) in the 20-150 kpc CGM surrounding galaxies derived using background quasars. The green (red) symbols represents CGM at the minor (major)-axes of the galaxy (see methods).
  • Figure S1: Sample parameter distribution.(A)$\log M_*$-$z$ distribution. The inner and outer black contours enclose 68% and 95% of the sample, respectively. For visual clarity, only 10% of the points falling outside the outer contour are plotted. (B)$\log M_*$-$\log \rm SFR$ distribution. The blue, green and yellow contours indicate the distribution of samples with $0.6<z<0.9$, $0.9<z<1.2$ and $1.2<z<1.7$, respectively. Similar to the black contours, these enclose 68% and 95% of the corresponding redshift subsamples.
  • ...and 6 more figures