Stellar initial mass functions describe the distribution of initial masses that stars are born with. This package aims to implement and provide interfaces for working with initial mass functions, including but not limited to evaluating and sampling from published distributions. See the linked documentation above for more details.
Published IMFs we include are
Salpeter1955(mmin::Real=0.4, mmax::Real=Inf)
Chabrier2001BPL(mmin::Real=0.08, mmax::Real=Inf)
Chabrier2001LogNormal(mmin::Real=0.08, mmax::Real=Inf)
Chabrier2003(mmin::Real=0.08, mmax::Real=Inf)
Chabrier2003System(mmin::Real=0.08, mmax::Real=Inf)
Kroupa2001(mmin::Real=0.08, mmax::Real=Inf)
These all return subtypes of Distributions.ContinuousUnivariateDistribution
and have many of the typical methods from Distributions.jl
defined for them. These include
- pdf, logpdf
- cdf, ccdf
quantile(d, x::Real), quantile(d,x::AbstractArray), quantile!(y::AbstractArray, d, x::AbstractArray)
- rand
- minimum, maximum, extrema
- mean, median, var, skewness, kurtosis (some of the higher moments don't work for
mmax=Inf
with instances ofBrokenPowerLaw
)
Note that var
, skewness
, and kurtosis
are not currently defined for instances of LogNormalBPL
, such as those returned by the Chabrier2003
function.
Many other functions that work on Distributions.ContinuousUnivariateDistribution
will also work transparently on these AbstractIMF
instances.
Continuous broken-power-law distributions (such as those used in Chabrier 2001 and Kroupa 2001) are provided through a new BrokenPowerLaw
type. The lognormal distribution for masses m<1.0
with a power law extension for higher masses as given in Chabrier 2003 is provided by a new LogNormalBPL
type. Simpler models (e.g., Salpeter1955
and Chabrier2001LogNormal
) are implemented using built-in distributions from Distributions.jl
in concert with their truncated
function.
Efficient samplers are implemented for the new types BrokenPowerLaw
and LogNormalBPL
such that batched calls (e.g., rand(Chabrier2003(),1000)
) are more efficient than single calls (e.g., d=Chabrier2003(); [rand(d) for i in 1:1000]
). These samplers can be created explicitly by calling Distributions.sampler(d)
, with d
being a BrokenPowerLaw
or LogNormalBPL
instance.
InitialMassFunctions.jl
follows Julia's recommended versioning strategy, where breaking changes prior to version 1.0 will result in a bump of the minor version (e.g., 0.1.x |> 0.2.0) whereas feature additions and bug patches will increment the patch version (0.1.0 |> 0.1.1).