A new fast scanning system for the measurement of large angle tracks in nuclear emulsions

Abstract

Nuclear emulsions have been widely used in particle physics to identify new particles through the observation of their decays thanks to their unique spatial resolution. Nevertheless, before the advent of automatic scanning systems, the emulsion analysis was very demanding in terms of well trained manpower. Due to this reason, they were gradually replaced by electronic detectors, until the '90s, when automatic microscopes started to be developed in Japan and in Europe. Automatic scanning was essential to conceive large scale emulsion-based neutrino experiments like CHORUS, DONUT and OPERA. Standard scanning systems have been initially designed to recognize tracks within a limited angular acceptance (θ 30 • ) where θ is the track angle with respect to a line perpendicular to the emulsion plane. In this paper we describe the implementation of a novel fast automatic scanning system aimed at extending the track recognition to the full angular range and improving the present scanning speed. Indeed, nuclear emulsions do not have any intrinsic limit to detect particle direction. Such improvement opens new perspectives to use nuclear emulsions in several fields in addition to large scale neutrino experiments, like muon radiography, medical applications and dark matter directional detection.

The Continuous Motion Technique for a New Generation of Scanning Systems

“…The CM technique was implemented within the LASSO framework 25 . The latter has a modular structure with a number of modules each having a definite role: the Stage Module controls stage movements and position monitoring; the Camera Module performs image acquisition with frame-grabber and camera; the Image Processing Module processes images in real-time using available GPU boards; the Tracker Module performs real-time reconstruction of microtracks; the Guide Module ensures reliable co-operation of all modules and governs the scanning process.…”

“…The track recognition procedure is a quite complex process executed by the LASSO software tracking module: all the steps of the algorithm for the microtrack reconstruction are described in ref. 25 . Then a dedicated offline software FEDRA 30 performs the track reconstruction in the full volume data: after the connection of microtracks across the plastic base (to form base tracks), which strongly reduces the number of fake tracks in a single film, a plate to plate alignment is done to connect base tracks in consecutive sheets and recognize the volume tracks.…”

“…Since 2011 the Naples OPERA group has carried out a dedicated R&D on automatic scanning 24 to improve the performance of the ESS developing the Large Angle Scanning System for OPERA framework (LASSO) 25 able to work up to 40 cm 2 /h on the current ESS hardware set-up and to measure tracks in emulsion in an extended angular range. In 2015 the ESS has been upgraded to the New Generation Scanning System (NGSS) 26 that can operate with high efficiency at the record speed of 84 cm 2 /h.…”

Supernova neutrino physics with a nuclear emulsion detector

“…A 3D reconstruction with nanometric accuracy is currently feasible. Moreover, the R&D for a new scanning system is ongoing to enable the analysis of ton-scale detectors on a time scale comparable with the exposure time [27,28,29]. The challenging task of detecting track lengths shorter than the diffraction limit -∼ 200 nm -is achieved adopting a two-step approach: (i) candidate selection with elliptical shape analysis, (ii) candidate validation with polarised light analysis.…”

Real-time tissue offset correction system for intravital multiphoton microscopy

“…For example, the scanning microscopes that are used to perform nuclear emulsion data acquisition for modern experiments such as the OPERA experiment (Acquafredda et al, 2009) yield data at the rate of approximately 2 GB/s, performing scanning at 84 cm 2 /h. Combined with the total emulsion area of 10 5 m 2 to be scanned, the real-time data processing with GPUs is one of the few possible solutions for effective data acquisition and analysis (Alexandrov et al, 2015).…”