학술논문

Sparse Representation for Signal Reconstruction in Calorimeters Operating in High Luminosity
Document Type
Periodical
Source
IEEE Transactions on Nuclear Science IEEE Trans. Nucl. Sci. Nuclear Science, IEEE Transactions on. 64(7):1942-1949 Jul, 2017
Subject
Nuclear Engineering
Bioengineering
Deconvolution
Signal reconstruction
Minimization
Linear programming
Covariance matrices
Amplitude estimation
calorimetry
high-luminosity colliders
optimal filters (OFs)
sparse representation (SR)
Language
ISSN
0018-9499
1558-1578
Abstract
A calorimeter signal reconstruction method, based on sparse representation (SR) of redundant data, is proposed for energy reconstruction in particle colliders operating in high-luminosity conditions. The signal overlapping is first modeled as an underdetermined linear system, leading to a convex set of feasible solutions. The solution with the smallest number of superimposed signals (the SR) that represents the recorded data is obtained through the use of an interior-point (IP) optimization procedure. From a signal processing point-of-view, the procedure performs a source separation, where the information of the amplitude of each convoluted signal is obtained. In the simulation results, a comparison of the proposed method with standard signal reconstruction one was performed. For this, a toy Monte Carlo simulation was developed, focusing in calorimeter front-end signal generation only, where the different levels of pileup and signal-to-noise ratio were used to qualify the proposed method. The results show that the method may be competitive in high-luminosity environments.