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Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

  • Volume 12Issue 12

  • ISSN: 0168-9002
  • 5 Year impact factor: 1.4
  • Impact factor: 1.5

Nuclear Instruments and Methods in Physics Research - section A (NIM-A) publishes papers on design, development and performance of scientific instruments including complex de… Read more

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Nuclear Instruments and Methods in Physics Research - section A (NIM-A) publishes papers on design, development and performance of scientific instruments including complex detector systems and large-scale facilities which utilize or study ionizing radiation. This scope includes the development of particle accelerators, particle beam sources, beam transport systems and target arrangements as well as the use of secondary phenomena and their enabling instruments such as neutron sources, synchrotron radiation sources and free electron lasers. It also includes all types of instrumentation for the detection and spectrometry of radiations from high energy processes and nuclear decays, as well as innovative instrumentation for nuclear reactors, nuclear security, nuclear medical diagnoses and therapy, astrophysics, planetary science, and environmental protection. Specialized electronics for these instruments as well as computerization of measurements and control systems in this area also find their place in NIM-A, as do new simulation codes and analysis tools*). Theoretical as well as experimental papers are accepted.

*) We receive an increasing number of submissions that are based exclusively on simulated data generated by standard codes such as ANSYS, Geant4, MAFIA, to name a few. Often the codes are used in a black-box manner to simulate relatively simple concepts and geometries without any validation of the results. Such submissions if found to fall short of our thresholds for originality and innovation may be rejected.
We face a similar situation related to the use of standard neural networks (deep learning) that are used to analyse all kinds of data (experimental or Monte-Carlo generated). Unless there is a clear motivation and a significant performance increase compared to a conventional analysis, such submissions may be rejected without starting the review process.

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