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CHANGELOG.md

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Change Log

Future (To-Do)

  • General
    • Add fit/interpolated GW spectra from Chen19 into SAM modules.
  • Explicit evolution/hardening models for
    • comprehensive stellar scattering using arbitrary stellar distributions
    • eccentric binary evolution
    • triple MBH interactions
  • Comparisons with observations (particularly EM) to calibrate synthesized populations
    • accurate catalogs of 'direct' MBH mass measurements from the local universe
    • approximate catalogs of 'indirect' MBH mass measurements from populations of AGN/quasars
    • AGN/Quasar luminosity functions
    • constraints on kpc--Mpc scale galaxy and AGN mergers
    • constraints on sub-kpc separation binary AGN based on EM candidates (and upper-limits)

Current

v1.6 - 2024/05/01

  • DEPRECATIONS:

    • holodeck.librarian.py ==> holodeck.librarian.lib_tools
      • Rename submodule. All components remain the same. All lib_tools elements are now also imported into the librarian namespace. i.e. elements like holodeck.librarian.lib_tools._Param_Space will now be accessible via holodeck.librarian._Param_Space.
    • Library filenames:
      • Standard library simulation files will now be saved to the 'library_sims' subdirectory, and filenames 'library__p######.npz'. Combined library files will now be 'sam-library.hdf5'.
      • 'Domain' simulation files will be saved to the 'domain_sims' subdirectory, and filenames 'domain__p######.npz'. Combined domain files will now be 'sam-domain.hdf5'.

  • BUGS:

    • Semi-Analytic Models
      • Semi_Analytic_Model._dynamic_binary_number_at_fobs_inconsistent was not checking for systems that had already coalesced. Only effected GW-only evolution using the python version of the calculation.

  • DEFAULTS:

    • Semi-Analytic Models
      • Semi_Analytic_Models instances now use galaxy merger-rates (instead of galaxy pair-fractions and merger-times) by default. To use GPF+GMT SAMs, the user must pass in at least a GPF instance manually.

  • General Changes

    • Semi-Analytic Models (holodeck.sams)

      • Improve accuracy of dynamic binary number calculation for consistent evolution models.

    • holodeck.librarian

      • Added functionality to construct 'domain' sets of simulations, to explore each parameter in a parameter-space one at a time.
      • NOTE: Standard library files will now be called "sam-library.hdf5" instead of "sam_lib.hdf5"

v1.5.2 - 2024/04/12

  • DEPRECATIONS
    • host_relations.py: remove the mamp parameter and MASS_AMP attributes in the MMBulge relationships, and use mamp_log10 and MASS_AMP_LOG10 exclusively.

v1.5 - 2024/03/29

  • Deprecated relations.py.
    • Material from this file has mostly been moved to host_relations.py. The components for galaxy/halo density/velocity profiles have been moved to galaxy_profiles.py. Stellar-mass vs. halo-mass relations are still in host_relations.py.
    • All of the same material can temporarily still be accessed/imported from relations.py, and it will log/print a deprecation warning.
  • M-Mbulge relations now use separate bulge-fractions.
    • All subclasses of _MMBulge_Relation now utilize separate bulge-fraction instances, implemented as subclasses of the new holodeck.host_relations._Bulge_Frac class.
    • The overall API remains unchanged (users can still perform conversions from total stellar-mass mstar to black-hole masses mbh), but internally conversions from total stellar-mass to stellar bulge-mass are performed by the bulge-fraction instances, and then stellar bulge-masses are converted to black-hole masses by the M-Mbulge instances.
    • The API for M-Mbulge relations has also been cleaned up and unified.
    • Two _Bulge_Frac subclasses have been implememted:
      • BF_Constant which is a single, fixed bulge-fraction value. This maintains the behavior that was previously performed within _MMBulge_Relation.
      • BF_Sigmoid is a new implementation that transitions from one bulge-fraction value at asymptotically low stellar-masses, up to a second bulge-fraction at and above a fixed characteristic stellar mass. The 'width' or 'steepness' of the transition can also be varied.

Past

v0.2 - 2022/03/28

  • Binary Evolution (evolution.py)
    • Now tracking hardening rates in evolution.
    • Simple implementation of some binary hardening models, both physical and phenomenological (i.e. power-law like).
    • Modules for Dynamical Friction, Stellar Scattering, and GW hardening.
  • Logistical and Internals
    • Added submodule for logging (log.py)
    • Added submodule for plotting (plot.py)
    • Added submodule for observational data and relations (observations.py)
    • New, and also improvements to old, notebooks for testing and demonstration purposes. Addition of more unit tests and test scripts.
    • Extensive additions to utility / mathematical / numerical functions (utils.py).
    • Improved README.md, and started adding basics to holodeck paper manuscript.
  • Populations
    • Cleaned up of observationally-based populations (pop_observational.py)
    • Unified implementation of MBH-galaxy relationships (relations.py)
    • Significant cleanup and upgrades in Semi-Analytic Models based populations (sam.py)
      • Developed methodology for sampling discrete binaries from continuous distributions (in coordination with kalepy modules)

v0.1 - 2021/08/15

  • Basic GW spectra can be generated using simple versions of population synthesis based on:
    • A finite, discrete population of binaries from the Illustris simulations
    • Continuous distributions from semi-analytic modeling
    • Continuous distributions from semi-analytic modeling, with Illustris merger rates, calibrated to local galaxy observations.
  • A class-based implementation is used in a way to facilitate subclassing (i.e. extensibility).
  • Only the simplest models for binary evolution (i.e. fixed time-delays and GW emission) are currently included.
  • Continuous population distributions can be easily interfaced with the kalepy package to facilitate discrete sampling. Even without formal discrete sampling, proper GW (foreground and background) statistics can be approximated.
  • Cosmology class (subclass of astropy.cosomology) providing convenience functions and more rapid calculations on arrays (via interpolation).