collresolve is a library designed to provide collision analysis and handling for N-body codes.
The library has interfaces for the following languages:
- C/C++
- Fortran
- Python
The installation of the C/C++/Fortran library using the standard ./configure
, make
and make install
commands.
The repository does not provide the configure
script. If installing directly from the repository, the file must be created first. The easiest way to do this is executing autoreconf --install
command which will create the configure
script and its dependencies. This command requires the GNU autoconf tool. In this situation, the commands to execute are:
autoreconf --install
./configure
make
make install
As for other packages, you may want to execute ./configure --help
to see which options are available and tune that command to your needs, e.g. by changing the location where the library will be installed using the --prefix=PATH
option.
If the library has been installed in a non-standard part, then the paths to the header files and library object files must be provided to the compiler and linker calls. Hereafter, we assume that the base location of the library is PREFIX
, which is the value of the --prefix
argument to ./configure
call.
The public interface of the library for the C/C++ languages is provided in the collresolve.h
file. In case the path must be provided, then the argument -IPREFIX/include
must be added to the compiler commands of files that make use of collresolve.h
.
To use the library, the argument -lcollresolve
is to be provided to the linking command. In case the library is in a non-standard directory, the path can be provided using -LPREFIX/lib
argument.
The Fortran interface is tailored to use with the mercury
package.
From a checkout of the repository, the Python module can be easily built and installed by the executing the following commands:
python setup.py build
python setup.py install
In case the library is to be installed for the current user only, then the --user
argument can be provided to the install
command.
This will put the Python module in a location where is it readily available. No further action is needed.
To use most of the library, a configuration object must be created and set first. The configuration object contains essential parameters for the calls, such as the collision model to determine the outcome of collisions and the unit system in use. The object must not be accessed directly, but the functions collresolve_conf_*
should be used instead to alter its state.
An example of usage of the library is provided in the example.py
file.
To use the library with the mercury
, the following modifications to the code of the latter are needed. When compiling the code, the additional flags described above to link the executable to the library are required.
In the mce_coll
subroutine, near the end, in lieu of the part
c
c Do the collision (inelastic merger)
call mce_merg (jcen,i,j,nbod,nbig,m,xh,vh,s,stat,elost,
% nsetup)
the code should be changed to something like
if (opt(2).eq.2 .and. i.gt.1 .and. j.gt.1) then
model = 4
nres = 2
regime = collresolve_resolve(model, m(i) / K2, m(j) / K2,
% rphys(i), rphys(j), xh(:,i), xh(:,j), vh(:,i), vh(:,j), nres,
% mres, rres, pres, vres)
if (regime .lt. 0) then
! An error occurred
! Do not do anything.
else if (mres(1) .lt. 1.d-3 / (1047.d0 * 317.8d0)) then
stat(i) = -2
stat(j) = -2
xh(:,j) = -xh(:,j)
vh(:,j) = -vh(:,j)
else if (mres(2) .lt. 1.d-3 / (1047.d0 * 317.8d0)) then
m(i) = mres(1) * K2
rphys(i) = rres(1)
xh(:,i) = pres(:,1)
vh(:,i) = vres(:,1)
stat(j) = -2
xh(:,j) = -xh(:,j)
vh(:,j) = -vh(:,j)
else
m(i) = mres(1) * K2
m(j) = mres(2) * K2
rphys(i) = rres(1)
rphys(j) = rres(2)
xh(:,i) = pres(:,1)
xh(:,j) = pres(:,2)
vh(:,i) = vres(:,1)
vh(:,j) = vres(:,2)
end if
else
c
c Do the collision (inelastic merger)
call mce_merg (jcen,i,j,nbod,nbig,m,xh,vh,s,stat,elost,
% nsetup)
end if
with the following new variables at the beginning of the subroutine
real*8 mres(3),rres(3),pres(3,3),vres(3,3)
integer nres,model,regime,collresolve_resolve
There are a few items to be noted with the above code:
- The library is only called when the flag about using the "fragmentation" mode in the parameters file is enabled. This allows to easily perform comparison run with mercury's standard merging algorithm with having to re-compile the code.
- The value of the
model
variable should be adjusted to which model the library is to use to resolve the collisions. The possible values are given in thecollresolve_model
enummeration incollresolve.h
. The value provided in this code snippet,4
, tells the library to use Cambioni et al. (2019) model. - It implements a minimum mass cutoff for the remnants, with a value to 1/1000 of an Earth mass (the factor 1047 * 317.8 being the conversion to solar mass that Mercury uses as the mass unit).
While the above codes sets the correct radii on return, these will be ignored in a standard version of the mercury
package. In effect, this will assume a constant density for each body. In case the model 4 (Cambioni et al. 2019) is used, a further modification is needed so that the bodies have a consistent radius with the bodies that were used to generate the model. To achieve this, the code setting the physical radius in mce_init
should be changed from rphys(j)=hill(j)/a(j)*(temp/rho(j))**THIRD
to rphys(j) = collresolve_radius(4, m(j) / K2)
while adding real*8 collresolve_radius
in the definitions of that subroutine. This will make mercury use the library's mass-radius relation for all bodies (both at the beginning of the simulation and after a collision), except for the central body. In effect, this makes the d
parameter in the input file useless.
The library is licensed under version 2.0 of the Apache License, see the LICENSE
file for the full terms and conditions.
If you use this library in a scientific work that lead to publication, we would like you to acknowledge the following article:
- Emsenhuber, A., Cambioni S., Asphaug, E., Gabriel, T. S. J., Schwartz, S. R., and Furfaro, R. (2020). Realistic On-the-fly Outcomes of Planetary Collisions. II. Bringing Machine Learning to N-body Simulations. The Astrophysical Journal, 891(1), 6. doi:10.3847/1538-4357/ab6de5 bib:2020ApJ...891....6E
If you use the LS2012
model, you should also cite:
- Leinhardt, Z. M. and Stewart, S. T. (2012). Collisions between Gravity-dominated Bodies. I. Outcome Regimes and Scaling Laws. The Astrophysical Journal, 745(1), 79. doi:10.1088/0004-637X/745/1/79 bib:2012ApJ...745...79L
If you use the SL2012
model, you should also cite the same publication as for LS2012
, and:
- Stewart, S. T. and Leinhardt, Z. M. (2012). Collisions between Gravity-dominated Bodies. II. The Diversity of Impact Outcomes during the End Stage of Planet Formation. The Astrophysical Journal, 751(1), 32. doi:10.1088/0004-637X/751/1/32 bib:2012ApJ...751...32S
- Genda, H., Kokubo, E., and Ida, S. (2012). Merging Criteria for Giant Impacts of Protoplanets. The Astrophysical Journal, 744(2), 137. doi:10.1088/0004-637X/744/2/137 bib:2012ApJ...744..137G
If you use the C2019
model, you should also cite:
- Cambioni, S., Asphaug, E., Emsenhuber, A., Gabriel, T. S. J., Furfaro, R., and Schwartz, S. R. (2019). Realistic On-the-fly Outcomes of Planetary Collisions: Machine Learning Applied to Simulations of Giant Impacts. The Astrophysical Journal, 875(1), 40. doi:10.3847/1538-4357/ab0e8a bib:2019ApJ...875...40C