star formation rates over a timescale

DErrick Carr
  • 1
  • 22 Jul '21

I want to get a star formation rate that is not instantaneous, but is more of a 500 Myr averaged SFH. I have an idea of what I could do to get that and just wanted to ask if this sounds like it would work.

  • Use the GFM_StellarFormationTime parameter to specify star particles born in the past 500 Myrs
  • Sum up the masses of all those star particles born in the past 500 Myrs
  • Divide by 500 Myrs to get a SFR in units of Msuns/year

Also, by "Instantaneous" Star formation rates, does the instantaneous mean stars born in just that snapshot? I don't think you can have truly instantaneous given it's in units of Msuns/yrs

Dylan Nelson
  • 23 Jul '21

That's correct, just note there are two possible masses you can sum which mean different things (PartType4/Masses and PartType4/GFM_InitialMass), be careful you use the one you want.

There is also an existing Star Formation Rates supplementary catalog you can compare with/use.

"Instantaneous" comes instead from the gas cells, and not the star particles. This is because every gas cell computes its current level of SFR.

DErrick Carr
  • 23 Jul '21

Thanks! Just to be clear though, that supplementary catalog is not accessible from the JupyterLab, right?

Kai Wang
  • 30 Apr '22

In the time-averaged star formation rate of Star Formation Rates supplementary catalog, how do you deal with gas recycling? For example, there is 1000 solar mass born and 200 solar mass lost due to stellar wind in the past 1Myr, so the final stellar particle weights 800 solar mass. Now, the resulted time-averaged star formation rate is 1000 solar mass/Myr or 800 solar mass/Myr in your calculation?

Dylan Nelson
  • 30 Apr '22

Hi Kai,

In all SFRs calculated based on the stars which have actually formed over the past X amount of time, we would use the GFM_InitialMass field instead of the Masses field (only the latter decreases with time due to stellar mass loss).

So 1000 Msun/Myr in your example.

Kai Wang
  • 30 Apr '22

Thanks! That is very helpful!

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