search

martinmestre / stream-fit

Fitting orbits, streams and Milky Way potentials to model a large range of observables including stellar streams, rotation curve and the stars at the Galactic centre.
0 stars 0 forks source link

Manuscript ready to be shared with co-authors #12

Open martinmestre opened 1 year ago

martinmestre commented 1 year ago

Hi co-authors @Charly-Arguelles @danielcarpintero @ankrut

Finally I can share the manuscript to be edited by you. As not all of you use git, I will upload everything to overleaf so that you can edit. I will not edit while you do so. After you finish editing I will download the source files back again to this repo in order to commit the final version. If you want to take a quick look at the paper now, please see here

@ankrut, your formulas and suggestions have been very important in the origin of this project (in those pandemic days) when coping with the RAR model, so you are invited to participate if you want. No problem if you don't want to be author, we will acknowledge your help in the paper. Please let me know your decision.

Best. Martín

ankrut commented 1 year ago

I had a quick look at the paper and it looks nice. I am glad to hear my formulas were helpful 😃

Of course, I would like to participate in the paper and provide further help.

I have few questions/remarks so far:

Is there already an overleaf link? Btw you can link/connect an overleaf project with a github repo. But I think it must be an independent non-public repo (no subfolder or similar). Then you don't need to sync everything manually. Unfortunately, in the free version overleaf does not keep the git history. Though this is what I remember one year ago or so when I was experimenting with the github feature. Maybe there was some progress in meanwhile.

danielcarpintero commented 1 year ago

Martín:

Please upload the paper to Overleaf at your earlier convenience.

Regards,

Daniel

El jue, 28 sept 2023 a las 15:51, Andreas Krut @.***>) escribió:

I had a quick look at the paper and it looks nice. I am glad to hear my formulas were helpful 😃

Of course, I would like to participate in the paper and provide further help.

I have few questions/remarks so far:

  • There is a link to the repo (pipeline_paper folder). At the moment this repo is private and at some point it should be made public so people can access the files. Keep in mind that everything in this repo will be then publicly available.
  • for the chi^2 you used 100 points along the polynomial in the given domain. The number of 100 seems arbitrary. I am not familiar with fitting tidal streams. So maybe would be good to give a short justification of the chosen number.

Is there already an overleaf link? Btw you can link/connect an overleaf project with a github repo. But I think it must be an independent non-public repo (no subfolder or similar). Then you don't need to sync everything manually. Unfortunately, in the free version overleaf does not keep the git history. Though this is what I remember one year ago or so when I was experimenting with the github feature. Maybe there was some progress in meanwhile.

— Reply to this email directly, view it on GitHub https://github.com/martinmestre/stream-fit/issues/12#issuecomment-1739844904, or unsubscribe https://github.com/notifications/unsubscribe-auth/ATTASC733A6OAI62473UCX3X4XBLPANCNFSM6AAAAAA5J5N5QM . You are receiving this because you were mentioned.Message ID: @.***>

martinmestre commented 1 year ago

Hi @ankrut, sorry for the delay, tomorrow I have a group talk and forgot to answer you. Great that you want to participate. In fact, you have already participated with your guide in the RAR model :) The overleaf link is the following: https://www.overleaf.com/7983258894vfhpdjmtnjsc Please write in the overleaf chat any suggestions to be made. The selection 100 points is arbitrary. The key point is to have a dense sample of the domain in order that the chi^2 is equivalent to an L2 norm in function space. You are right that all the repo will become open, that is the idea so that everyone can reproduce our results, although we will think a bit more about it. Best.