Paper detail

An Improved Fit to the Density Distribution in Supersonic Isothermal Turbulence

The density distribution of supersonic isothermal turbulence plays a critical role in many astrophysical systems. It is commonly approximated by a lognormal distribution with a variance of $σ_{s,{\rm V}}^2 \approx \ln(1 + b^2 M_{\rm V}^2),$ where $s \equiv \ln ρ/ρ_0,$ $M_{\rm V}$ is the rms volume-weighted Mach number, and $b$ is a parameter that depends on the driving mechanism, which can be solenoidal (divergence-free), compressive (curl-free), or a mix of both. However, this fit neglects the driving correlation time, $τ_{\rm a}$, which plays a key role when compressive driving is significant. Here we conduct turbulence simulations spanning a wide range of Mach numbers, driving mechanisms, and $τ_{\rm a}$ values. In the compressive case, $σ_{s,{\rm V}}^2$ is not well fit by the standard expression. Instead, it scales approximately linearly with $M_{\rm V},$ and its dependence on $τ_{\rm a}$ is $σ_{s,{\rm V}}^2 \approx M_{\rm V} [1 + \frac{2}{3}(1 + λ_{\rm a})Θ(1 + λ_{\rm a})]$, where $λ_{\rm a} \equiv \ln(τ_{\rm a}/τ_{\rm e})$, $τ_{\rm e}$ is the eddy turnover time, and $Θ$ is the Heaviside step function. Mixed-driven turbulence shows a weak dependence on $τ_{\rm a},$ and for solenoidally-driven turbulence, $σ_{s,{\rm V}}^2 \approx \frac{1}{3}M_{\rm V}$, which is consistent with the standard expression when $M_{\rm V} \lesssim 8.$ The volume-weighted mean and skewness also show systematic trends with $M_{\rm V}$ and $τ_{\rm a}$, deviating from lognormal expectations. The mass-weighted density distribution displays significant broadening and skewness in compressively-driven cases, especially at large $τ_{\rm a}/τ_{\rm e}$. These results provide a refined framework for modeling astrophysical turbulence.

preprint2026arXivOpen access

Signal facts

What is known right now

Open access4 authors1 topic

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.