I’ve run basic “B4d” example with “run1.mac” and “run2.mac” macros. I’ve read “Absorber_Edep” ntuple (from “B4.root”) as pandas dataframe (via uproot). “Absorber_Edep_cell” column was filled with zeros as if there was single cell over whole detector. How should sampling calorimeter manifest it’s multi-layered structure? Does 50 MeV electron not propagate to the second absorber?
Or “sampling” originally means, calorimeter measures spectrum?
A sampling calorimeter is one in which only part of the incident particle’s energy is converted into a readout signal. This contrasts with a total-energy calorimeter, in which all of the incident particle’s energy is converted to an active readout signal.
In this instance, the calorimeter consists of a stack of interleaved lead and plastic scintillator sheets. The incident particle initiates a shower in the first lead sheet.
Most of that shower is just absorbed in the lead material, but some of the secondaries escape out of the lead and pass through the scintillator. There, they produce some amount of light which can be read out. Then those secondaries enter the next lead sheet, and initiate or continue the showering process. This continues through all of the layers, until the original incident energy is fully absorbed.
The total light output of all the thin scintillator sheets is proportional to the incident energy, but would not be “equal” to the incident energy because of the absorber layers. A calibration is needed in order to convert the readout signal back into incident energy.
An advantage of a sampling calorimeter is that you may also read out each sampling layer (scintillator sheet) individually, and use the distribution (shower shape) for particle identification: an electron, a photon, or a hadron will produce different shower shapes for the same incident energy.