Stochastic particle reflection from absorbing domain boundaries (#2281)

* added tunable particle reflection from absorbing domain boundaries

* extended picmi.py to allow setting boundary reflection coefficients and added a CI test for the reflection implementation

* allow R(E) to be specified, except for embedded boundaries

* changed approach for particle reflection, now the ParticleBoundaries object will hold the reflection coefficient; reflection from EBs not implemented

* added functionality to reflect from EB; still needs to be tested for accuracy

* added support for energy dependent reflection models for domain boundaries

* fixed at least one issue causing CI fails - building reflection model parsers for not physical particle containers

* switched reflection coefficients to be functions of the velocity component perpendicular to the boundary rather than energy

* reverted initial work on reflecting from EBs

* changed naming convention for new CI test for particle reflection

* switched useMPI back to 1 in test

* breaking changes while trying to sort out GPU issue

* fixed issue with CUDA compilation - hopefully :)

* various code improvements from PR review suggestions

* fix of major issues

* no need to parse the reflection models at every step

* skip particles that are already flagged for removal in ApplyBoundaryConditions

1 files changed, 19 insertions, 0 deletions

diff --git a/Python/pywarpx/picmi.py b/Python/pywarpx/picmi.py
index 1bb46e439..d3fa599d8 100644
--- a/Python/pywarpx/picmi.py
+++ b/Python/pywarpx/picmi.py
@@ -86,6 +86,15 @@ class Species(picmistandard.PICMI_Species):
         self.save_previous_position = kw.pop('warpx_save_previous_position', None)
         self.do_not_deposit = kw.pop('warpx_do_not_deposit', None)
 
+        # For particle reflection
+        self.reflection_model_xlo = kw.pop('warpx_reflection_model_xlo', None)
+        self.reflection_model_xhi = kw.pop('warpx_reflection_model_xhi', None)
+        self.reflection_model_ylo = kw.pop('warpx_reflection_model_ylo', None)
+        self.reflection_model_yhi = kw.pop('warpx_reflection_model_yhi', None)
+        self.reflection_model_zlo = kw.pop('warpx_reflection_model_zlo', None)
+        self.reflection_model_zhi = kw.pop('warpx_reflection_model_zhi', None)
+        # self.reflection_model_eb = kw.pop('warpx_reflection_model_eb', None)
+
         # For the scraper buffer
         self.save_particles_at_xlo = kw.pop('warpx_save_particles_at_xlo', None)
         self.save_particles_at_xhi = kw.pop('warpx_save_particles_at_xhi', None)
@@ -127,6 +136,16 @@ class Species(picmistandard.PICMI_Species):
                                              save_particles_at_eb = self.save_particles_at_eb,
                                              save_previous_position = self.save_previous_position,
                                              do_not_deposit = self.do_not_deposit)
+
+        # add reflection models
+        self.species.add_new_attr("reflection_model_xlo(E)", self.reflection_model_xlo)
+        self.species.add_new_attr("reflection_model_xhi(E)", self.reflection_model_xhi)
+        self.species.add_new_attr("reflection_model_ylo(E)", self.reflection_model_ylo)
+        self.species.add_new_attr("reflection_model_yhi(E)", self.reflection_model_yhi)
+        self.species.add_new_attr("reflection_model_zlo(E)", self.reflection_model_zlo)
+        self.species.add_new_attr("reflection_model_zhi(E)", self.reflection_model_zhi)
+        # self.species.add_new_attr("reflection_model_eb(E)", self.reflection_model_eb)
+
         pywarpx.Particles.particles_list.append(self.species)
 
         if self.initial_distribution is not None: