Material effect of inner-detectors on the performances of the BESⅢ Electromagnetic Calorimeter （EMC） is investigated. The BESⅢ Time-Of-Flight counters （TOF） have been utilized to improve the energy resolution and detection efficiency for photons after a careful energy calibration. A matching algorithm between TOF and EMC energy deposits is developed, and the effects of beam-related background are discussed. The energy resolution is improved and the photon detection efficiency can be increased by the combined measurement of EMC and TOF detectors.
A multilayered perceptrons＇ neural network technique has been applied in the particle identification at BESIII. The networks are trained in each sub-detector level. The NN output of sub-detectors can be sent to a sequential network or be constructed as PDFs for a likelihood. Good muon-ID, electron-ID and hadron-ID are obtained from the networks by using the simulated Monte Carlo samples.
