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Color laws

The following empirical laws allow us to model the reddening of light as it travels to us. The law you use should depend on the type of data you have and the goal of its use. CCM89 is very common for use in removing extinction from stellar observations, but CAL00, for instance, is suited for galaxies with massive stars. Look through the citations and documentation for each law to get a better idea of what sort of physics it targets.

Usage

Color laws are constructed and then used as a function for passing wavelengths. Wavelengths are assumed to be in units of angstroms.

julia> CCM89(Rv=3.1)(4000)
1.464555702942584

These laws can be applied across higher dimension arrays using the . operator

julia> CCM89(Rv=3.1).([4000, 5000])
2-element Array{Float64,1}:
 1.464555702942584
 1.1222468788993019

these laws return magnitudes, which we can apply directly to flux by mulitplication with a base-2.5 logarithmic system (because astronomers are fun):

\[f = f \cdot 10 ^ {-0.4A_v\cdot mag}\]

To make this easier, we provide a convenience redden and deredden functions for applying these color laws to flux measurements.

julia> wave = range(4000, 5000, length=4)
4000.0:333.3333333333333:5000.0

julia> flux = 1e-8 .* wave .+ 1e-2
0.01004:3.3333333333333333e-6:0.01005

julia> redden.(CCM89, wave, flux; Av=0.3)
4-element Array{Float64,1}:
 0.006698646015454752
 0.006918253926353551
 0.007154659823737299
 0.007370491272731541

julia> deredden.(CCM89(Rv=3.1), wave, ans; Av=0.3) ≈ flux
true

Advanced Usage

The color laws also have built-in support for uncertainties using Measurements.jl.

julia> using Measurements

julia> CCM89(Rv=3.1).([4000. ± 10.5, 5000. ± 10.2])
2-element Array{Measurement{Float64},1}:
 1.4646 ± 0.0033
 1.1222 ± 0.003

and also support units via Unitful.jl and its subsidiaries. Notice how the output type is now Unitful.Gain.

julia> using Unitful, UnitfulAstro

julia> mags = CCM89(Rv=3.1).([4000u"angstrom", 0.5u"μm"])
2-element Array{Gain{Unitful.LogInfo{:Magnitude,10,-2.5},:?,Float64},1}:
 1.4645557029425837 mag
 1.1222468788993019 mag

You can even combine the two above to get some really nice workflows exploiting all Julia has to offer! This example shows how you could redden some OIR observational data with uncertainties in the flux density.

julia> using Measurements, Unitful, UnitfulAstro

julia> wave = range(0.3, 1.0, length=5)u"μm"
(0.3:0.175:1.0) μm

julia> err = randn(length(wave))
5-element Array{Float64,1}:
  0.2972879845354616
  0.3823959677906078
 -0.5976344767282311
 -0.01044524463737564
 -0.839026854388764

julia> flux = @.(300 / ustrip(wave)^4 ± err)*u"Jy"
5-element Array{Quantity{Measurement{Float64},𝐌*𝐓⁻²,Unitful.FreeUnits{(Jy,),𝐌*𝐓⁻²,nothing}},1}:
  37037.04 ± 0.3 Jy
  5893.14 ± 0.38 Jy
  1680.61 ± -0.6 Jy
 647.598 ± -0.01 Jy
   300.0 ± -0.84 Jy

julia> redden.(CCM89, wave, flux; Av=0.3)
5-element Array{Quantity{Measurement{Float64},𝐌*𝐓⁻²,Unitful.FreeUnits{(Jy,),𝐌*𝐓⁻²,nothing}},1}:
    22410.8 ± 0.18 Jy
    4229.74 ± 0.27 Jy
    1337.12 ± 0.48 Jy
 554.3349 ± 0.0089 Jy
     268.31 ± 0.75 Jy

Parametric Extinction Laws

These laws are all parametrized by the selective extinction Rv. Mathematically, this is the ratio of the total extinction by the reddening

\[R_V = \frac{A_V}{E(B-V)}\]

and is loosely associated with the size of the dust grains in the interstellar medium.

Index:

Clayton, Cardelli and Mathis (1989)

DustExtinction.CCM89 — Type
CCM89(;Rv=3.1)

Clayton, Cardelli and Mathis (1989) dust law.

Returns E(B-V) in magnitudes at the given wavelength relative to the extinction at 5494.5 Å. The default support is [1000, 33333]. Outside of that range this will return 0. Rv is the selective extinction and is valid over [2, 6]. A typical value for the Milky Way is 3.1.

References

Clayton,Cardelli and Mathis (1989)

source

O'Donnell 1994

DustExtinction.OD94 — Type
OD94(;Rv=3.1)

O'Donnell (1994) dust law.

This is identical to the Clayton, Cardelli and Mathis (1989) dust law, except for different coefficients used in the optical (3030.3 Å to 9090.9 Å).

References

O'Donnell (1994)

See Also

CCM89

source

Calzetti et al. (2000)

DustExtinction.CAL00 — Type
CAL00(;Rv=4.05)

Calzetti et al. (2000) Dust Law.

Returns E(B-V) in magnitudes at the given wavelength. λ is the wavelength in Å and has support over [1200, 22000]. Outside of that range this will return 0.

Calzetti et al. (2000) developed a recipe for dereddening the spectra of galaxies where massive stars dominate the radiation output. They found the best fit value for such galaxies was 4.05±0.80.

References

Calzetti et al. (2000)

source

Valencic, Clayton, & Gordon (2004)

Gordon, Cartledge, & Clayton (2009)

Fitzpatrick (1999)

DustExtinction.F99 — Type
F99(;Rv=3.1)

Fitzpatrick (1999) dust law. Returns E(B-V) in magnitudes at the given wavelength relative to the extinction. This model applies to the UV and optical to NIR spectral range. The default support is [1000, 33333] Å. Outside of that range this will return

  1. Rv is the selective extinction and is valid over [2, 6]. A typical value for

the Milky Way is 3.1.

References

Fitzpatrick (1999)

source

Fitzpatrick (2004)

DustExtinction.F04 — Type
F04(;Rv=3.1)

Fitzpatrick (2004) dust law. Returns E(B-V) in magnitudes at the given wavelength relative to the extinction. This model applies to the UV and optical to NIR spectral range. The default support is [1000, 33333] Å. Outside of that range this will return

  1. Rv is the selective extinction and is valid over [2, 6]. A typical value for

the Milky Way is 3.1. Equivalent to the F99 model with an updated NIR Rv dependence See also Fitzpatrick & Massa (2007, ApJ, 663, 320)

References

Fitzpatrick (2004)

source

Fitzpatrick (2019)

DustExtinction.F19 — Type
F19(;Rv=3.1)

Fitzpatrick (2019) dust law.

Returns E(B-V) in magnitudes at the given wavelength relative to the extinction. This model applies to the UV and optical to NIR spectral range. The default support is [1149, 33333] Å. Outside of that range this will return

  1. Rv is the selective extinction and is valid over [2, 6]. A typical value for

the Milky Way is 3.1.

Fitzpatrick, Massa, Gordon et al. (2019, ApJ, 886, 108) model. Based on a sample of stars observed spectroscopically in the optical with HST/STIS.

References

Fitzpatrick (2019)

source

Maiz Apellaniz et al. (2014)

DustExtinction.M14 — Type
M14(;Rv=3.1)

Maiz Apellaniz et al (2014) Milky Way & LMC R(V) dependent model.

Returns E(B-V) in magnitudes at the given wavelength relative to the extinction. The published UV extinction curve is identical to Clayton, Cardelli, and Mathis (1989, CCM). Forcing the optical section to match smoothly with CCM introduces a non-physical feature at high values of R5495 around 3.9 inverse microns; see section 5 in Maiz Apellaniz et al. (2014) for more discussion. For that reason, we provide the M14 model only through 3.3 inverse microns, the limit of the optical in CCM. Outside of that range this will return 0. Rv is the selective extinction and is valid over [2, 6]. A typical value for the Milky Way is 3.1. R5495 = A(5485)/E(4405-5495) Spectral equivalent to photometric R(V).

References

Maiz Apellaniz et al. (2014)

source

API/Reference

DustExtinction.redden — Function
redden(::ExtinctionLaw, wave, flux; Av=1)
redden(::Type{ExtinctionLaw}, wave, flux; Av=1, law_kwargs...)

Redden the given flux using the given extinction law at the given wavelength.

If wave is <:Real then it is expected to be in angstrom and if it is <:Unitful.Quantity it will be automatically converted. Av is the total extinction value. The extinction law can be a constructed struct or a Type. If it is a Type, law_kwargs will be passed to the constructor.

Examples

julia> wave = 3000; flux = 1000;

julia> redden(CCM89, wave, flux; Rv=3.1)
187.38607779757183

julia> redden(CCM89(Rv=3.1), wave, flux; Av=2)
35.11354215235764

See Also

deredden

source
DustExtinction.deredden — Function
deredden(::ExtinctionLaw, wave, flux; Av=1)
deredden(::Type{ExtinctionLaw}, wave, flux; Av=1, law_kwargs...)

Deredden the given flux using the given extinction law at the given wavelength.

If wave is <:Real then it is expected to be in angstrom and if it is <:Unitful.Quantity it will be automatically converted. Av is the total extinction value. The extinction law can be a constructed struct or a Type. If it is a Type, law_kwargs will be passed to the constructor.

Examples

julia> wave = 3000; flux = 187.386;

julia> deredden(CCM89, wave, flux; Rv=3.1)
999.9995848273642

julia> deredden(CCM89(Rv=3.1), wave, flux; Av=2)
5336.573541539394

See Also

redden

source
DustExtinction.ExtinctionLaw — Type
DustExtinction.ExtinctionLaw

The abstract super-type for dust extinction laws. See the extended help (??DustExtinction.ExtinctionLaw from the REPL) for more information about the interface.

Extended Help

Interface

Here's how to make a new extinction law, called MyLaw

  • Create your struct. We strongly recommend using Parameters.jl to facilitate creating keyword argument constructors if your model is parameterized, which allows convenient usage with redden and deredden. 
struct MyLaw <: DustExtinction.ExtinctionLaw end
  • (Optional) Define the limits. This will default to (0, Inf). Currently, this is used within the DustExtinction.checkbounds function and in the future will be used for plotting recipes.
DustExtinction.bounds(::Type{<:MyLaw}) = (min, max)
  • Define the law. You only need to provide one function which takes wavelength as angstrom. If your law is naturally written for inverse-micron, there is a helper function aa_to_invum.
(::MyLaw)(wavelength::Real)
  • (Optional) enable Unitful.jl support by adding this function. If you are building a new law within DustExtinction.jl you can add your law to the code-gen list inside DustExtinction.jl/src/DustExtinction.jl.
(l::MyLaw)(wavelength::Unitful.Quantity) = l(ustrip(u"angstrom", wavelength)) * u"mag"
source
DustExtinction.bounds — Function
DustExtinction.bounds(::ExtinctionLaw)::Tuple
DustExtinction.bounds(::Type{<:ExtinctionLaw})::Tuple

Get the natural wavelengths bounds for the extinction law, in angstrom

source

Fittable Extinction Laws

Fitzpatrick & Massa (1990)

DustExtinction.FM90 — Type
FM90(;c1=0.10, c2=0.70, c3=3.23, c4=0.41, x0=4.60, gamma=0.9)
FM90(coeffs, x0=4.60, gamma=0.9)

Fitzpatrick & Massa (1990) generative model for ultraviolet dust extinction. The default values are the published values for the Milky Way average.

Parameters

  • c1 - y-intercept of linear term
  • c2 - slope of liner term
  • c3 - amplitude of 2175 Å bump
  • c4 - amplitude of FUV rise
  • x0 - centroid of 2175 Å bump
  • gamma - width of 2175 Å bump

If λ is a Unitful.Quantity it will be automatically converted to Å and the returned value will be UnitfulAstro.mag.

Examples

julia> model = FM90(c1=0.2, c2=0.7, c3=3.23, c4=0.41, x0=4.6, gamma=0.99);

julia> model(1500)
5.2521258452800135

julia> FM90()(1500)
5.152125845280013

julia> FM90(c1=0.2, c2=0.7, c3=3.23, c4=0.41, x0=4.6, gamma=0.99).([1000, 1200, 1800])
3-element Array{Float64,1}:
 12.562237969522851
  7.769215017329513
  4.890128210972148

Extended Help

The model has form $c_1 + c_2x + c_3D(x; \gamma, x_0) + c_4 F(x)$ where $x$ is the wavenumber in inverse microns, $D(x)$ is a Drude profile (modified Lorentzian) used to model the 2175 Å bump with the scale-free parameters $x_0$ (central wavenumber) and $\gamma$ (damping coefficient), and $F(x)$, a piecewise function for the far-UV. Note that the coefficients will change the overall normalization, possibly changing the expected behavior of reddening via the parameter $A_V$.

References

Fitzpatrick & Massa (1990)

source

Mixture Extinction Laws

Gordon et al. (2016)

DustExtinction.G16 — Type
G16(;Rv=3.1, f_A=1.0)

Gordon et al. (2016) Milky Way, LMC, & SMC R(V) and f_A dependent model

Returns E(B-V) in magnitudes at the given wavelength relative to the extinction. This is mixture model between the F99 R(V) dependent model (component A) and the G03_SMCBar model (component B) The default support is [1000, 33333] Å. Outside of that range this will return 0. Rv is the selective extinction and is valid over [2, 6]. A typical value for the Milky Way is 3.1.

References

Gordon et al. (2016)

source