[Users] Meeting Minutes 2020-06-04 [fixed links]

[Ian Hinder]

On 8 Jun 2020, at 14:48, Ian Hinder <ian.hinder at manchester.ac.uk<mailto:ian.hinder at manchester.ac.uk>> wrote:



On 4 Jun 2020, at 16:39, Bill Gabella <b.gabella at vanderbilt.edu<mailto:b.gabella at vanderbilt.edu>> wrote:

** [ZE] NRPyPN we use two punctures for initial data in ETK.  Looking
for low ecc BBH intial data parameter solvers.  Wrote one based on
literature.  Option in Two Punctures that you sepcify the 8 input params
and outputs the initial data, P_t and P_r.  If close to ecc =0, as close
as Post-Newtonian allows.  ES-Good enough params or need to iterate?
ZE-Paper by Ramos-Buades et al. https://arxiv.org/abs/1810.00036 .  They
say with one iteration can drop ecc to order 1/10^3 .  RH-Good to have
the notebook in the utils folder for Two Punctures.  ZE-Tedious, but the
C version is not too hard and integrate with Two Punctures.  RH-Very low
eccentricity requires man iterations, a glitch shows that ecc energy
goes up.  Scheme gives back P_t and P_r.  PN in C does iteration zero,
but not later ones.  RH&ZE-Iteration greater than 1 is not in NRPyPN but
RH's student has been doing that.  RH-I will reach out to principals and
discuss this.  Does two orbits and sees what to update, and then
re-submits itself, and want ecc < 1e-6 .  First bit is all eccentricity
reduction.  ZE-Found typos in the original paper.  dE_GW/dt was very
different than other groups use.  RH-Recevied their Mathematica
notebook, so hopefully better than the paper.

Some links to NRPyPN, Low-eccentricity Post-Newtonian BBH initial data
parameters (for Two Punctures):
https://nbviewer.jupyter.org/github/zachetienne/nrpytutorial/blob/master/NRPyPN/NRPyPN.ipynb
https://github.com/zachetienne/nrpytutorial/tree/master/NRPyPN   (source
codes)

Hi,

I developed an infrastructure for obtaining low-eccentricity parameters for BBH.  It is implemented and freely-available in SimulationTools for Mathematica.  See https://bitbucket.org/simulationtools/simulationtools/src/master/EccentricityReduction.m.  I haven't used it in a while, but can't think why it wouldn't still work.  It lacks documentation - if someone is interested in using it or developing it further, I can see if I can find some time to write up some docs.

You can use it to generate an initial guess from PN (QuasiCircularParametersFromPostNewtonian[{m_, q_, chi1_, chi2_, om_}]) for any aligned-spin case (you can probably use chi_z for precessing cases).  This will give you the separation, orbital angular momentum (r * py) and radial linear momentum (px).  You then run a simulation with these parameters for a few orbits, and analyse the results.  The method uses the time derivative of the radial separation for its eccentricity estimator. You use BinaryEccentricityFromSeparationDerivative, passing it the separation as a function of time (which you can get from ReadBinarySeparation), and a time window in which to measure the eccentricity.  You can get a suitable window from EccentricityFitWindow, which calculates it using a simple heuristic from the initial orbital frequency to give two orbits.  You can then use ReduceEccentricity with the results of BinaryEccentricityFromSeparationDerivative which gives you updated TwoPunctures parameters.

There are a number of higher level functions designed to fit this into an automated workflow.  I was using it with SimFactory 3, which supports the idea of post-simulation scripts and "termination reasons".  I had it set up so that when Cactus terminates during an eccentricity reduction run, it would run a script (https://bitbucket.org/simulationtools/simulationtools/src/master/Scripts/AnalyseEccentricity) which would call SimulationTools to estimate the next separation and radial momentum (I chose to keep the angular momentum L fixed, since that corresponds to fixed omega at 0 PN (maybe 1 PN?)).  The post-simulation script is https://bitbucket.org/ianhinder/simfactory3/src/master/simfactory/etc/appdb/scripts/post-simulation, and it has a number of heuristics for what to do in different cases.

There are a lot of parts to this system, but it used to run extremely well, and was fully automated, and was used to produce many production simulations, including the very high spin simulations used in https://arxiv.org/abs/1810.10585, with chi_z = 0.9 and mass ratios up to 5.

I forgot to mention the crucial part!  For those simulations, it's very challenging to get the eccentricity down; typically I could only get it down to ~1e-3, but that is usually enough.  For simple cases, like equal mass, non-spinning, if you are at a large separation (e.g. 15 orbits), the method was able to iterate the eccentricity down to something like 1e-6.

--
Ian Hinder
Research Software Engineer
University of Manchester, UK

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