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author = {{Penny}, M.~T. and {Kerins}, E. and {Rattenbury}, N. and {Beaulieu}, J. -P. and {Robin}, A.~C. and {Mao}, S. and {Batista}, V. and {Calchi Novati}, S. and {Cassan}, A. and {Fouqu{\'e}}, P. and {McDonald}, I. and {Marquette}, J.~B. and {Tisserand}, P. and {Zapatero Osorio}, M.~R.},
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title = "{ExELS: an exoplanet legacy science proposal for the ESA Euclid mission - I. Cold exoplanets}",
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journal = {\mnras},
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keywords = {gravitational lensing: micro, planets and satellites: detection, stars: low-mass, planetary systems, Galaxy: bulge, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@ARTICLE{Penny2019,
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author = {{Penny}, Matthew T. and {Gaudi}, B. Scott and {Kerins}, Eamonn and {Rattenbury}, Nicholas J. and {Mao}, Shude and {Robin}, Annie C. and {Calchi Novati}, Sebastiano},
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title = "{Predictions of the WFIRST Microlensing Survey. I. Bound Planet Detection Rates}",
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journal = {\apjs},
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keywords = {gravitational lensing: micro, planets and satellites: detection, space vehicles: instruments, Astrophysics - Earth and Planetary Astrophysics},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@ARTICLE{Sormani2022,
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author = {{Sormani}, Mattia C. and {Sanders}, Jason L. and {Fritz}, Tobias K. and {Smith}, Leigh C. and {Gerhard}, Ortwin and {Sch{\"o}del}, Rainer and {Magorrian}, John and {Neumayer}, Nadine and {Nogueras-Lara}, Francisco and {Feldmeier-Krause}, Anja and {Mastrobuono-Battisti}, Alessandra and {Schultheis}, Mathias and {Shahzamanian}, Banafsheh and {Vasiliev}, Eugene and {Klessen}, Ralf S. and {Lucas}, Philip and {Minniti}, Dante},
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title = "{Self-consistent modelling of the Milky Way's nuclear stellar disc}",
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journal = {\mnras},
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keywords = {Galaxy: centre, Galaxy: kinematics and dynamics, Galaxy: structure, Astrophysics - Astrophysics of Galaxies},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@ARTICLE{Bachelet2024,
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author = {{Bachelet}, E. and {Hundertmark}, M. and {Calchi Novati}, S.},
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title = "{Estimating Microlensing Parameters from Observables and Stellar Isochrones with pyLIMASS}",
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journal = {\aj},
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keywords = {Gravitational microlensing, 672, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@ARTICLE{Johnson2020,
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author = {{Johnson}, Samson A. and {Penny}, Matthew and {Gaudi}, B. Scott and {Kerins}, Eamonn and {Rattenbury}, Nicholas J. and {Robin}, Annie C. and {Calchi Novati}, Sebastiano and {Henderson}, Calen B.},
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title = "{Predictions of the Nancy Grace Roman Space Telescope Galactic Exoplanet Survey. II. Free-floating Planet Detection Rates}",
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journal = {\aj},
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keywords = {Gravitational microlensing, Free floating planets, Space telescopes, Exoplanet detection methods, 672, 549, 1547, 489, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
title: 'SynthPop: A New Framework for Synthetic Milky Way Population Generation'
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tags:
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- Python
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- astronomy
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- milky way
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- population synthesis
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authors:
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- name: Jonas Kl\"{u}ter
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orcid: 0000-0002-3469-5133
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equal-contrib: true
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affiliation: 1
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- name: Macy J. Huston
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orcid: 0000-0003-4591-3201
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equal-contrib: true
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affiliation: 2
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- name: Abigail Aronica
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affiliation: 3
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- name: Samson A. Johnson
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orcid: 0000-0001-9397-4768
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affiliation: "3, 4"
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- name: Matthew Penny
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orcid: 0000-0001-7506-5640
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affiliation: 1
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- name: Marz Newman
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orcid: 0009-0002-1973-5229
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affiliation: 1
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- name: Farzaneh Zohrabi
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orcid: 0000-0003-2872-9883
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affiliation: 1
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- name: Alison L. Crisp
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orcid: 0000-0003-4310-3440
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affiliation: 3
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- name: Allison Chevis
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orcid: 0000-0003-2558-1748
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affiliation: 5
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affiliations:
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- name: Department of Physics \& Astronomy, Louisiana State University, Baton Rouge, LA 70803, USA
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index: 1
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- name: Astronomy Department, University of California, Berkeley, CA, 94720, USA
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index: 2
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- name: Department of Astronomy, The Ohio State University, Columbus, OH 43210, USA
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index: 3
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- name: NASA Jet Propulsion Laboratory, Pasadena, CA, 91109, USA
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index: 4
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- name: Department of Physics, Pennsylvania State University, State College, PA 16802, USA
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index: 5
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date: 02 December 2024
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bibliography: joss-paper.bib
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aas-doi: xx.xxxx/xxxxx
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aas-journal: xxxxxxx
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---
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# Summary
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SynthPop is a new open source, modular population synthesis Galactic modeling software to simulate catalogs of Milky Way stars along any sightline outward from the Sun.
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Motivated by a lack flexibility in existing Galactic models, SynthPop is coded entirely in python, can be run standalone or as an imported module, and is configured by json files that allow different model components to be switched out as desired.
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# Statement of need
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We have built SynthPop to address the need we perceived for a publicly available population synthesis code that can be easily modified, provides an interface that can be run via script, and ideally can allow comparisons between different models within a single framework. To achieve these goals, we built the package in python, which is likely the most widely used language in astronomy. This choice results in slower performance than a compiled language, but a minimal bar to code modification, and an easy way to import the package into other code. We have designed the package so that it can be modified either through the adjustment of parameter files or by adding new code modules to achieve results that are not enabled by existing tools.
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The primary driving use case for SynthPop is to provide synthetic stellar population catalogs for microlensing simulations (@Penny2013, @Penny2019, @Johnson2020).
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# Ongoing use
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Huston et al. (in prep.) will illustrate the development of a SynthPop Model version that matches well to data, and apply the model to the Roman Galactic Bulge Time Domain Survey to explore the Galactic distributions of anticipated microlensing event lenses and sources.
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This model version is also being used as the Galactic model input for gulls (@Penny2013, @Penny2019) and PyLIMASS (@Bachelet2024) by the Roman Galactic Exoplanet Survey Project Infrastructure Team for updated exoplanet mass yield estimates and field optimization (Terry et al., in prep.; Zohrabi et al., in prep.).
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# Acknowledgements
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We appreciate conversations with N. Koshimoto in implementing the (@Koshimoto2021) model and (@Sormani2022) nuclear stellar disk into SynthPop.
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We also thank the Roman Galactic Exoplanet Survey Project Infrastructure team members and others who helped improve the software through discussions, use during development, and feedback.
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J.K. acknowledges support from NASA award NNX16AC62G and the Gordon and Betty Moore Foundation award GBMF10467.
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M.J.H. acknowledges support from the Heising-Simons Foundation under grant No. 2022-3542.
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Early work on this software by M.J.H. and A.A. was supported by the Ohio State University Summer Undergraduate Research Program.
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S.A.J.’s work was supported by NASA Grant 80NSSC24M0022 and an appointment to the NASA Postdoctoral Program at the NASA Jet Propulsion Laboratory, administered by Oak Ridge Associated Universities under contract with NASA.
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M.T.P. acknowledges support from NASA awards NNX14AF63G, NNX16AC62G, 80NSSC24M0022, 80NSSC24K0881, and Louisiana Board of Regents Support Fund (RCS Award Contract Simple: LEQSF(2020-23)-RD-A-10).
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Early work by M.T.P. was performed in part under contract with the Jet Propulsion Laboratory (JPL) funded by NASA through the Sagan Fellowship Program executed by the NASA Exoplanet Science Institute.
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M.N. acknowledges support from NASA award 80NSSC24K0881.
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A.L.C. and F.Z. acknowledge support from NASA grant 80NSSC24M0022.
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A.C.'s work was supported by the National Science Foundation under Grant Number 1852454.
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Portions of this research were conducted with high performance computational resources provided by Louisiana State University ([http://www.hpc.lsu.edu](http://www.hpc.lsu.edu)).
Copy file name to clipboardExpand all lines: docs/source/configuration.rst
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@@ -100,7 +100,7 @@ example::
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"l_set_type":"list",
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"b_set":[-1,0,1],
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"b_set_type":"list",
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"solid_angle": 1e-2,
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"solid_angle": 1e-2,
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"solid_angle_unit": "deg^2"
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}
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**mass_lims**: range of initial stellar masses to produce
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**N_mc_totmass**: number of stars to use to estimate number of stars needed per slice
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**N_mc_totmass**: number of random points to sample to estimate average density in a slice
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**lost_mass_option**: method to estimate correction for mass loss
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**lost_mass_option**: method to estimate correction for mass loss with four integer options:
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* 1: For each population, a test batch of N_av_mass stars is generated and evolved to estimate the total initial stellar mass required to meet the desired present day total stellar mass. These values are saved for all sightlines run with the initialized populations.
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* 2: For each population a test batch of N_av_mass stars is generated and evolved to estimate the total initial stellar mass required to meet the desired present day total stellar mass. These value is re-calculated for each sightline run.
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* 3: Initially treat the population density as an initial mass density, then add or remove stars as needed.
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* 4: Use the precomputed value given by either "av_mass_corr" or "n_star_corr" in each population file to scale the required total initial stellar mass needed to achieve the desired present day total stellar mass.
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**N_av_mass**: number of stars to use to estimate average evolved stellar mass
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**extinction_law_kwargs**: dictionary containing:
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* **name**: name of extinction law module
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* **R_V**: total to selective extinction ratio [note: only used in select extinction laws, will be ignored if input for others]
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* **<kwargs>**: any kwargs required or optional for the selected module
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[Note: multi-evolution class options are available]
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**R_V**: total to selective extinction ratio [note: only used in select extinction laws]
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example::
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},
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"extinction_law_kwargs":
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[
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{"name":"SODC"}
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],
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"R_V":2.5
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{"name":"SODC", "R_V":2.5}
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]
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},
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ISOCHRONE_INTERPOLATION
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**chosen_bands**: list of filters to include for synthetic photometry
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For the MIST evolution module, the following filters are available:
**eff_wavelengths**: dictionary specifying effective wavelength for each chosen filter [Note: use option {"json_file":"AAA_effective_wavelengths.json"} to load these from a pre-existing file]
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**obs_mag**: boolean option to generate observed magnitudes (generates absolute magnitudes if set to false)
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**opt_iso_props**: optional stellar properties to save, with original column names from isochrones
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For MIST isochrone stellar property options, see `their documentation here <https://waps.cfa.harvard.edu/MIST/README_tables.pdf>`_
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**col_names**: columns names for output for the columns determined in **opt_iso_props**
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example::
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**output_filename_pattern**: string describing naming system for output files. Accessible values are model_base_name (str), model_name (str), l_deg (float), b_deg(float), solid_angle (float), date (datetime.date object), time (datetime.time object).
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**output_file_type**: list containing output file type and dictionary for additional kwargs
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**output_file_type**: list containing output file type and dictionary for additional kwargs, saved via pandas or astropy. valid options: csv, json, html, xml, excel, hdf5, feather, parquet, stata, pickle, sql, fits, vot
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**overwrite**: boolean option to overwrite existing output files of the same name
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