I created that dataset, and yes, the stars have ages that are in the future (gasoline uses stellar ages to determine feedback rates, so stars with ages in the future will not do any feedback, which I needed for the experiment that dataset came from). Sorry for the confusion.

On Mar 30, 2015 2:33 PM, "Desika Narayanan" <dnarayan@haverford.edu> wrote:
Hey Nathan,

This is great - thanks!

-d


On Mon, Mar 30, 2015 at 2:24 PM, Nathan Goldbaum <nathan12343@gmail.com> wrote:

On Mon, Mar 30, 2015 at 11:10 AM, Desika Narayanan <dnarayan@haverford.edu> wrote:
Hi All,

I'm trying to understand some of the stellar ages that the Tipsy example data (the isolated galaxy) at:


When I examine the formation time with the super-simple script:

http://paste.yt-project.org/show/5501/

I get: 

max star age:  100.000499852 Gyr

I thought normally the formation time was the current simulation time minus the stellar age for Tipsy outputs - am I interpreting this wrongly?



Hi Desika,

I encountered this before.  Take a look at the following section of the docs, which makes use of this dataset:


I don't have a copy of gasoline to confirm this, but the conclusion I came to is that the stars in the initial conditions for this simulation were given a creation time arbitrarily far in the future, generating spurious stellar ages.

If you instead define particle filters for formed stars like so:

def young_stars(pfilter, data):
    age = data.ds.current_time - data[pfilter.filtered_type, "creation_time"]
    filter = np.logical_and(age.in_units('Myr') <= 5, age >= 0)
    return filter

def old_stars(pfilter, data):
    age = data.ds.current_time - data[pfilter.filtered_type, "creation_time"]
    filter = np.logical_or(age.in_units('Myr') >= 5, age < 0)
    return filter

where I've arbitrarily chosen 5 Myr as the cutoff for old stars and young stars, you'll find that your results make more sense.
 
HTH,

Nathan

Thanks,
desika




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