For the first time, the FRagment Separator (FRS) and the Multiple-Reflection Time-Of-Flight Mass-Spectrometer (MR-TOF-MS) particle identification (PID) systems at GSI have been coupled. This new ...approach adds to the standard FRS PID an additional unambiguous identification of the fragments and the possibility to identify and count long-lived isomeric states (>ms). For this purpose, single-event timestamp information given by a common clock was used to correlate both systems. Two methods were implemented to improve the signal-to-background ratio by more than a factor 2 in the high resolution mass spectrum obtained with the MR-TOF-MS for the 109In isotope. Moreover, the coupling of the systems allows an improvement in the on-line monitoring of the FRS-Ion Catcher (IC) efficiency and extraction time. In addition, range calculations were implemented in the on-line monitoring; a powerful tool for real-time optimization of stopped beam experiments.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
CUPID-Mo is a bolometric experiment to search for neutrinoless double-beta decay (
0
ν
β
β
) of
100
Mo
. In this article, we detail the CUPID-Mo detector concept, assembly and installation in the ...Modane underground laboratory, providing results from the first datasets. The CUPID-Mo detector consists of an array of 20
100
Mo
-enriched 0.2 kg
Li
2
MoO
4
crystals operated as scintillating bolometers at
∼
20
mK
. The
Li
2
MoO
4
crystals are complemented by 20 thin Ge optical bolometers to reject
α
events by the simultaneous detection of heat and scintillation light. We observe a good detector uniformity and an excellent energy resolution of 5.3 keV (6.5 keV) FWHM at 2615 keV, in calibration (physics) data. Light collection ensures the rejection of
α
particles at a level much higher than 99.9% – with equally high acceptance for
γ
/
β
events – in the region of interest for
100
Mo
0
ν
β
β
. We present limits on the crystals’ radiopurity:
≤
3
μ
Bq/kg
of
226
Ra
and
≤
2
μ
Bq/kg
of
232
Th
. We discuss the science reach of CUPID-Mo, which can set the most stringent half-life limit on the
100
Mo
0
ν
β
β
decay in half-a-year’s livetime. The achieved results show that CUPID-Mo is a successful demonstrator of the technology developed by the LUMINEU project and subsequently selected for the CUPID experiment, a proposed follow-up of CUORE, the currently running first tonne-scale bolometric
0
ν
β
β
experiment.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN ...technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.
Characterizing the chemical properties, morphologies, size, and quantities of microplastics (MPs) in water samples with high precision is critically important for understanding the environmental ...behaviors of MPs. Traditional detection methods, such as Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy point-by-point detection, provide worthy reference techniques but are time- and labor-consuming. We established a super time-saving and high-precision technique to characterize MPs using micro-Raman automatic particle identification (MR-API). Based on the identification of PS spheres, screen magnification, exposure time, and the number of scans are selected as crucial detection parameters for MR-API analysis, which highly affect the precision of the results. Detecting particles down to 1 μm requires magnification of the mosaic until the scale showed 200 μm. The recommended setting parameters were 83.33 or 100 ms exposure time, 20 scans, 7 mW laser power, and 1 μm image pixel size, suitable for polystyrene (PS), polypropylene (PP), polyethylene terephthalate (PET), polyethylene (PE), polyvinyl chloride (PVC), and polyamide (PA) particles detection. With the complete procedure of MR-API measurements, the recovery of MPs was 61.67–90.00 %. To validate the feasibility of the MR-API, the method was used to detect samples of known plastic types (mask leachates) and unknown plastic types (urban lake). A total of 4540 particles in the sample of mask leachates consuming 35 h 50 min 43 s, and 0.92 ± 0.49 % of particles were identified as MPs. The urban river sample efficiently identified PP, PET, PE, PVC, PS, EVA, and VC/VAC MPs using this method. The detected MPs size ranged from 8.3 to 5000 μm, saving 75.03 % and 58.38 % of the time compared to the conventional micro-FTIR and micro-Raman point-by-point methods, respectively. Therefore, this method is effective for detecting MPs in the environmental samples and has excellent prospects.
•MR-API method can effectively distinguish between MPs and non-MPs for water sample.•Screen magnification, exposure time and number of scan are key parameters of MR-API.•Compared with traditional method, the MR-API can save at least 58.38 % of the time.•The MR-API method can detecte MPs down to 8.3 μm in the environmental sample.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This article presents a novel machine learning approach for enhancing particle identification (PID) systems in high-energy physics (HEP) experiments. The proposed method utilizes a hybrid model that ...combines a deep neural network (DNN) and a random forest regressor (RFR), leveraging their complementary strengths. This approach achieves robust performance, leading to significantly improved particle discrimination and cleaner data for physics analysis. Our evaluation demonstrates a marked increase in PID system precision, highlighting the model's potential to optimize PID tasks in complex high-energy physics settings. By improving identification efficiency and reducing misidentification rates, this hybrid deep learning model offers valuable advancements for the field of particle physics.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the ...classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.
The scanning light ion microprobe in Uppsala – Status in 2022 Nagy, Gyula; Whitlow, Harry J.; Primetzhofer, Daniel
Nuclear instruments & methods in physics research. Section B, Beam interactions with materials and atoms,
12/2022, Volume:
533
Journal Article
Peer reviewed
Open access
The Scanning Light Ion Microprobe in Uppsala (SLIM-UP) was originally installed during 1989/90. Since then, the microprobe has undergone several minor and major modifications. The present ...configuration is a re-build of the SLIM-UP, that is now connected to the 5 MV tandem Pelletron® accelerator of the Tandem Laboratory, Uppsala University. We give an overview of the present status of the Uppsala microprobe facility, including a detailed description of the components and a recent resolution test. In addition, we present the most recent technical developments whereby, the system is able to quickly image large area samples, to reliably identify individual microparticles, and to analyse them separately. Optimal parameters for a certain system can be found by simple test measurements on dummy samples. Our test scenario comprises of Fe particles embedded in a light matrix, representing human tissue. We found a good compromise between the required analysis time and particle detection efficiency.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
28.
STOPGAP—A time-of-flight extension for the Belle II TOP barrel PID system Hartbrich, Oskar; Tamponi, Umberto; Varner, Gary S.
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
01/2024, Volume:
1058
Journal Article, Conference Proceeding
Peer reviewed
Open access
The Belle II barrel region is instrumented with the Time of Propagation (TOP) particle identification system. Due to its mechanical design, the individual TOP modules do not overlap, leaving a gap of ...around 2 cm between them in the azimuthal direction. This leads to a 6%–9% drop in acceptance, depending on the track’s momentum. We propose a solution to remedy these gaps by instrumenting them with fast silicon detectors to directly measure the time-of-flight of traversing particles. We present here a simulation study discussing the performance requirements and the possible sensor technologies, and we demonstrate that such a project could be realized with novel, fast monolithic CMOS sensors, or alternatively AC-LGAD sensors, both of which are expected to reach MIP timing resolutions of down to 50 ps or better.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
30.
A gaseous RICH detector for SiD or ILD Basso, Matthew J.; Cairo, Valentina Maria Martina; Damerell, Chris ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
12/2023, Volume:
1059
Journal Article
Peer reviewed
This paper describes a preliminary study of a gaseous Ring Imaging Cherenkov (RICH) system capable of discriminating between kaons and pions at high momenta — up to 50 GeV/c — and thus enhancing ...particle identification at future colliders. The system possesses a compact design, facilitating easy integration into existing detector concepts. Here, a study of the key contributions to the Cherenkov angle resolution is also presented.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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