Move RICH sensor QE from npsim.py into epic geometry (optical surface EFFICIENCY property)

[wdconinc]

Motivation

The quantum efficiency (QE) curves for the DRICH SiPM and PFRICH HRPPD photocathode sensors are currently hardcoded as explicit lambda/efficiency tables in npsim.py. These are physical properties of the sensors and belong in the epic geometry repository alongside the rest of the detector description.

Key finding

optical_materials.xml in epic already defines SensorSurface_DRICH with a placeholder flat efficiency:

<opticalsurface name="SensorSurface_DRICH" model="glisur" finish="polished" type="dielectric_dielectric">
  <property name="EFFICIENCY" coldim="2" values="
    1*eV  1
    7*eV  1
    "/>
</opticalsurface>

This surface is already applied as a SkinSurface to each pss volume in DRICH_geo.cpp. The infrastructure is in place — we just need to replace the placeholder with real data.

Proposed design

Part 1 — epic (compact/optical_materials.xml)

• Replace the flat EFFICIENCY = 1.0 on SensorSurface_DRICH with real SiPM (S13361-3050NE-08) QE values, converting λ[nm] → E[eV] via E = 1239.84 / λ.
• Add a new SensorSurface_PFRICH with HRPPD photocathode QE values.
• Reference SensorSurface_PFRICH from compact/pid/pfrich.xml on the photocathode element.

Part 2 — npsim stacking action (OpticalPhotonEfficiencyStackingAction.h)

• Add a SensorSurface property (a surface name string).
• In initialize(), if SensorSurface is set, look up the named optical surface, read its EFFICIENCY from the G4MaterialPropertiesTable, convert photon energy back to wavelength, and populate the existing interpolation table (m_interp_lambda_values / m_efficiency).
• Keep LambdaValues + Efficiency as explicit fallback for backward compatibility.

Priority in initialize():

1. SensorSurface set → read QE from G4 optical surface MPT
2. LambdaValues + Efficiency set → use explicit tables (current behaviour)
3. LambdaMin/LambdaMax + Efficiency → linspace fallback (legacy hpDIRC path)

Part 3 — npsim.py

Replace hardcoded lambda/efficiency tables:

# Before (hardcoded in npsim):
{
  "name": "OpticalPhotonEfficiencyStackingAction",
  "parameter": {
    "LambdaValues": [315e-6, 325e-6, ...],  # 17 values
    "Efficiency":   [0.00, 0.04, ...],       # 17 values
    "LogicalVolume": "DRICH_(gas|aerogel)",
  }
},

# After (QE lives in epic):
{
  "name": "OpticalPhotonEfficiencyStackingAction",
  "parameter": {
    "SensorSurface": "SensorSurface_DRICH",
    "LogicalVolume":  "DRICH_(gas|aerogel)",
  }
},

Separation of concerns

Repository	Responsibility
epic	Sensor QE physics (what wavelengths does this photocathode detect?)
npsim	Simulation topology (which radiator volumes feed which sensor surface?)

npsim.py retains only the LogicalVolume regex — a simulation choice about where to kill photons early. The QE numbers themselves are geometry data.

Scope

• DRICH (SiPM) and PFRICH (HRPPD) are the primary targets.
• hpDIRC can be migrated in a follow-up once epic defines a SensorSurface_DIRC with the barPMT QE.
• The LambdaValues/Efficiency fallback must be retained until all detectors have migrated.