Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 87 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 25 tok/s Pro
GPT-5 High 23 tok/s Pro
GPT-4o 112 tok/s Pro
Kimi K2 165 tok/s Pro
GPT OSS 120B 460 tok/s Pro
Claude Sonnet 4 29 tok/s Pro
2000 character limit reached

Expected dust grain size distributions in galaxies detected by ALMA at $z>7$ (1909.08264v2)

Published 18 Sep 2019 in astro-ph.GA

Abstract: The dust properties in high-redshift galaxies provide clues to the origin of dust in the Universe. Although dust has been detected in galaxies at redshift $z>7$, it is difficult to constrain the dominant dust sources only from the total dust amount. Thus, we calculate the evolution of grain size distribution, expecting that different dust sources predict different grain size distributions. Using the star formation time-scale and the total baryonic mass constrained by the data in the literature, we calculate the evolution of grain size distribution. To explain the total dust masses in ALMA-detected $z>7$ galaxies, the following two solutions are possible: (i) high dust condensation efficiency in stellar ejecta, and (ii) efficient accretion (dust growth by accreting the gas-phase metals in the interstellar medium). We find that these two scenarios predict significantly different grain size distributions: in (i), the dust is dominated by large grains ($a\gtrsim 0.1~\mu$m, where $a$ is the grain radius), while in (ii), the small-grain ($a\lesssim 0.01~\mu$m) abundance is significantly enhanced by accretion. Accordingly, extinction curves are expected to be much steeper in (ii) than in (i). Thus, we conclude that extinction curves provide a viable way to distinguish the dominant dust sources in the early phase of galaxy evolution.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube