| Full text | |
| Author(s): |
Fortino, G. F.
;
Zamora, J. C.
;
Tamayose, L. E.
;
Hirata, N. S. T.
;
Guimaraes, V
Total Authors: 5
|
| Document type: | Journal article |
| Source: | NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SP; v. 1031, p. 7-pg., 2022-05-11. |
| Abstract | |
An algorithm for digital signal analysis using convolutional neural networks (CNN) was developed in this work. The main objective of this algorithm is to make the analysis of experiments with active target time projection chambers more efficient. The code is divided in three steps: baseline correction, signal deconvolution and peak detection and integration. The CNNs were able to learn the signal processing models with relative errors of less than 6%. The analysis based on CNNs provides the same results as the traditional deconvolution algorithms, but considerably more efficient in terms of computing time (about 65 times faster). This opens up new possibilities to improve existing codes and to simplify the analysis of the large amount of data produced in active target experiments. (AU) | |
| FAPESP's process: | 18/04965-4 - Study of structure and nuclear reactions induced by exotic nuclei using active targets |
| Grantee: | Juan Carlos Zamora Cardona |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 19/07767-1 - Nuclear reactions with weakly-bound or cluster-structured radioactive and stable nuclei |
| Grantee: | Leandro Romero Gasques |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 16/17612-7 - Dynamics of many-body systems IV |
| Grantee: | Arnaldo Gammal |
| Support Opportunities: | Research Projects - Thematic Grants |