Public repository of the Cosmic Linear Anisotropy Solving System (master for the most recent version of the standard code; GW_CLASS to include Cosmic Gravitational Wave Background anisotropies; classnet branch for acceleration with neutral networks; ExoCLASS branch for exotic energy injection; class_matter branch for FFTlog)
I am using the scf model as implemented in CLASS in MontePython. For long runs, the frequent sampling of the model's parameter space seems to cause a memory leak and the run aborts with Signal 9.
Tweaking the upper and lower bounds and sigma values of those parameters seem to ameliorate the problem but it still persists especially for long runs. I was wondering if you are aware of such an issue or of possible solutions.
Here's some of the input from CLASS side:
Omega_fld = 0
Omega_scf = -0.1
Omega_Lambda = 0
# the mean values of scf parameters used in MontePython:
scf_parameters = 4.0, 2.0, 1e2, 1e2, 1e2, 1
# Other settings:
attractor_ic_scf = no
scf_tuning_index = 0
Please let me know if further details were needed.
Dear experts,
I am using the scf model as implemented in CLASS in MontePython. For long runs, the frequent sampling of the model's parameter space seems to cause a memory leak and the run aborts with Signal 9. Tweaking the upper and lower bounds and sigma values of those parameters seem to ameliorate the problem but it still persists especially for long runs. I was wondering if you are aware of such an issue or of possible solutions. Here's some of the input from CLASS side:
Please let me know if further details were needed.
Thank you, Amin