Cosmic Ray Muons Research Articles

Developments of a centimeter-level precise muometric wireless navigation system (MuWNS-V) and its first demonstration using directional information from tracking detectors

Various positioning techniques such as Wi-Fi positioning system have been proposed to use in situations where satellite navigation is unavailable. One such system, the muometric positioning system (muPS), was invented for navigation which operates in locations where even radio waves cannot reach such as underwater or underground. muPS takes advantage of a key feature of its probe, cosmic-ray muons, which travel straightforwardly at almost a speed of light in vacuum regardless of the matter they traverse. Similar to other positioning techniques, muPS is a technique to determine the position of a client’s muPS receiver within the coordinate defined by reference detectors. This can be achieved either by using time-of-flight (ToF) or angle of arrival (AoA) measurements. The latter configuration (AoA), called the Vector-muPS has recently been invented and the present paper describes the developments of the first prototype of a vector muometric wireless navigation system (MuWNS-V) with this new vector-muPS concept and its demonstration. With MuWNS-V, the reference tracker and the receiver ran wirelessly with fully independent readout systems, and a positioning accuracy of 3.9 cm (RMS) has been achieved. We also evaluated the outcome of measuring continuous indoor localization of a moving receiver with this prototype. Our results indicated that further improvements in positioning accuracy will be attainable by acquiring higher angular resolution of the reference trackers. It is anticipated that “sub-cm level” navigation will be possible for muPS which could be applied to many situations such as future autonomous mobile robot operations.

Momentum informed muon scattering tomography for monitoring spent nuclear fuels in dry storage cask

Development of an effective monitoring method for spent nuclear fuel (SNF) in a dry storage cask (DSC) is important to meet the increasing demand for dry storage investigations. The DSC investigation should provide information about the quantity of stored SNF, and quality assurance of materials should be possible without opening the cask. However, traditional nondestructive examination (NDE) methods such as x-rays are difficult to deploy for DSC investigation because a typical DSC is intentionally designed to shield against radiation. To address this challenge, cosmic ray muons (CRMs) are used as an alternative NDE radiation probe because they can easily penetrate an entire DSC system; however, a wide application of muons is often hindered due to the naturally low CRM flux (~104 muons/m2/min). This paper introduces a newly proposed imaging algorithm, momentum-informed muon scattering tomography (MMST), and presents how a limitation of the current muon scattering tomography technique has been addressed by measuring muon momentum. To demonstrate its functionality, a commercial DSC with 24 pressurized light water reactor fuel assemblies (FAs) and the MMST system were designed in GEANT4. Three noticeable improvements were observed for MMST system as a DSC investigation tool: (1) a signal stabilization, (2) an enhanced capability to differentiate various materials, and (3) statistically increased precision to identify and locate missing FAs. The results show that MMST improves the investigation accuracy from 79 to 98% when one FA is missing and 51% to 88% when one-half FA is missing. The advancement of the NDE technique using CRM for DSC verification is expected to resolve long-standing problems in increasing demand for DSC inspections and nuclear security.

Imaging technology based on the interaction between muon and material

Muon imaging technology, as an emerging detection method, is widely used in various fields. Muons can be classified into cosmic ray muons and accelerator muons based on their origins. Cosmic ray muons stand out for wide energy range, strong penetrating power and no artificial radiation. These characteristics make cosmic ray muon imaging technology adept at achieving nondestructive imaging of target objects. Presently, the commonly used imaging methods include scattering and transmission imaging technologies that leverage muon information for imaging. Additionally, muon and muonic secondary particle coincidence imaging technology utilizes information from secondary particles generated during the interaction between muons and target objects for imaging. The accelerator muon, distinguished by its high flux, strong monochromaticity, and adjustable energy, enables rapid and multidimensional imaging of target objects at various depths. Furthermore, it facilitates the analysis of material elements through muonic X-rays. This article provides insights into the production process and physical characteristics of muons, the fundamental principles of muon imaging technology, and its diverse applications across disciplines. It also explores the current development status and emerging trends in fields such as mineral resource exploration, archaeological studies, and nuclear safety.

Testing a novel sensor design to jointly measure cosmic-ray neutrons, muons and gamma rays for non-invasive soil moisture estimation

Abstract. Cosmic-ray neutron sensing (CRNS) has emerged as a reliable method for soil moisture and snow estimation. However, the applicability of this method beyond research has been limited due to, among others, the use of relatively large and expensive sensors. This paper presents the tests conducted on a new scintillator-based sensor especially designed to jointly measure neutron counts, muons and total gamma rays. The neutron signal is first compared against two conventional gas-tube-based CRNS sensors at two locations. The estimated soil moisture is further assessed at four agricultural sites, based on gravimetric soil moisture collected within the sensor footprint. Muon fluxes are compared to the incoming neutron variability measured at a neutron monitoring station and total gammas counts are compared to the signal detected by a gamma ray spectrometer. The results show that the neutron dynamic detected by the new scintillator-based CRNS sensor is well in agreement with conventional CRNS sensors. The derived soil moisture also agreed well with the gravimetric soil moisture measurements. The muons and the total gamma rays simultaneously detected by the sensor show promising features to account for the incoming variability and for discriminating irrigation and precipitation events, respectively. Further experiments and analyses should be conducted, however, to better understand the accuracy and the added value of these additional data for soil moisture estimation. Overall, the new scintillator design shows to be a valid and compact alternative to conventional CRNS sensors for non-invasive soil moisture monitoring and to open the path to a wide range of applications.

KinKal: A Kinematic Kalman filter Track Fitting Package for the Mu2e Experiment

Many current physics experiments require precision reconstruction of low-energy particles. One example is the Mu2e experiment, which requires reconstructing an isolated 105 MeV electron with better than 500 KeV/c momentum resolution. Mu2e uses a low-mass straw tube tracker, and a CsI crystal calorimeter, to reconstruct tracks. In this paper, we present the design and performance of a track reconstruction algorithm optimized for Mu2e’s unusual requirements. The algorithm is based on the KinKal [1] kinematic Kalman filter track fit package. KinKal supports multiple track parameterizations, including one optimized for looping tracks, such as Mu2e signal tracks, and others optimized for straight or slightly-curved tracks, such as the high-momentum (>1 GeV/c) cosmic ray muons used to calibrate and align the Mu2e detectors. All KinKal track parameterizations include the track origin time, to correctly model correlations arising from measurements that couple time and space, such as the straw drift time or the calorimeter cluster time. KinKal employs magnetic field inhomogeneity and material effect correction algorithms with 10−4 fractional precision. The Mu2e fit uses Artificial Neural Net functions to discriminate background hits from signal hits, and to resolve the straw tube hit left-right ambiguity, while iterating the extended Kalman filter. The efficiency, accuracy, and precision of the Mu2e track reconstruction, as tested on detailed simulations of Mu2e data, are presented.

Fast muon simulation in the JUNO experiment with neural networks

Fast muon simulation in the JUNO experiment with neural networks

A muon high-resolution pseudorange measurement method: Application to muon navigation in confined spaces

Confined spaces such as polar regions, deep earth and deep ocean are crucial navigation scenarios where traditional navigation techniques have difficulty in obtaining external signals for positioning. The cosmic ray muons, which carry the spatial and energetic information, are easy to penetrate these confined spaces. Therefore, the unique muon characteristic provides a new perspective to estimate detector position, which can be considered using in confined spaces navigation. In this paper, a well-developed theory of muon navigation is established by combining a muon pseudorange measurement method. Moreover, an Equivalent Velocity Calculation Model (EVCM) and a Muon Sequence Matching Technology (MSMT) are proposed. The first model corrects flight pseudorange error caused by the relativistic energy loss and the second technology compensates the random error in pseudorange measurement. Further, a series of simulations are performed to analyze the muon events number which can be received by detector in different scenarios with the variations of zenith angle, detector area, varied detector plates gap, and muon flight distance. Meanwhile, the simulation results demonstrate that the muon navigation update rate every 10 minutes can reach 5.989 in confined spaces at 100 m, and further pseudorange error analysis indicates that the meter-level positioning accuracy can be acquired. Finally, we construct a muon coincidence measurement scheme and verify that the laws of the muon positioning system for high-energy muons are consistent with the simulation results.

Image reconstruction algorithm for momentum dependent muon scattering tomography

Nondestructive radiography using cosmic ray muons has been used for decades to monitor nuclear reactor and spent nuclear fuel storage. Because nuclear fuel assemblies are highly dense and large, typical radiation probes such as x-rays cannot penetrate these target imaging objects. Although cosmic ray muons are highly penetrative for nuclear fuels as a result of their relatively high energy, the wide application of muon tomography is limited because of naturally low cosmic ray muon flux. This work presents a new image reconstruction algorithm to maximize the utility of cosmic ray muon in tomography applications. Muon momentum information is used to improve imaging resolution, as well as muon scattering angle. In this work, a new convolution was introduced known as M-value, which is a mathematical integration of two measured quantities: scattering angle and momentum. It captures the objects’ quantity and density in a way that is easy to use with image reconstruction algorithms. The results demonstrate how to reconstruct images when muon momentum measurements are included in a typical muon scattering tomography algorithm. Using M-value improves muon tomography image resolution by replacing the scattering angle value without increasing computation costs. This new algorithm is projected to be a standard nondestructive radiography technique for spent nuclear fuel and nuclear material management.

Muon Flux Variations Measured by Low‐Cost Portable Cosmic Ray Detectors and Their Correlation With Space Weather Activity

AbstractWe present a comparison of the measured cosmic ray (CR) muon fluxes from two identical portable low‐cost detectors at different geolocations and their sensitivity to space weather events in real time. The first detector is installed at Mount Wilson Observatory, CA, USA (geomagnetic cutoff rigidity Rc ∼ 4.88 GV), and the second detector is running on the downtown campus of Georgia State University in Atlanta, GA, USA (Rc ∼ 3.65 GV). The variation of the detected muon fluxes is compared to the changes in the interplanetary solar wind parameters at the L1 Lagrange point and geomagnetic indexes. In particular, we have investigated the muon flux behavior during three major interplanetary shock events and geomagnetic disturbances that occurred during July and August of 2022. To validate the interpretation of the measured muon signals, we compare the muon fluxes to the measurement from the Oulu neutron monitor (NM, Rc ∼ 0.8 GV). The results of this analysis show that the muon detector installed at Mount Wilson Observatory demonstrates a stronger correlation with a high‐latitude NM. Both detectors typically observe a muon flux decrease during the arrival of interplanetary shocks and geomagnetic storms. Interestingly, the decrease could be observed several hours before the onset of the first considered interplanetary shocks at L1 at 2022‐07‐23 02:28:00 UT driven by the high‐speed Coronal Mass Ejection and related geomagnetic storm at 2022‐07‐23 03:59:00 UT. This effort represents an initial step toward establishing a global network of portable low‐cost CR muon detectors for monitoring the sensitivity of muon flux changes to space and terrestrial weather parameters.

New the Design and Measurements of the Portable Cosmic Ray Muons Detector (CRMD) for an Observatory

New the Design and Measurements of the Portable Cosmic Ray Muons Detector (CRMD) for an Observatory

Performance evaluation of cosmic ray muon trajectory estimation algorithms

Muons, being elementary particles with minimal interaction with nuclear materials and abundant at sea level, have sparked interest in utilizing them for imaging various applications, such as mining [Borselli et al., Sci. Rep. 12, 22329 (2022)], volcano imaging [Nagamine et al., Nucl. Instrum. Meth. A, 356, 585(1995)], and underground tunnel detection [Guardincerri et al., Pure Appl. Geophys. 174, 2133 (2017)]. Recently, their use in nuclear nonproliferation and safeguard verification has gained attention, particularly in cargo screening for nuclear waste smuggling [Baesso et al., J. Instrum. 9, C10041 (2014)], source localization [L. J. Schultz et al., Nucl. Instrum. Meth. A 519, 687 (2004)], and locating nuclear fuel debris in reactors [Borozdin et al., Phys. Rev. Let. 109, 152501 (2012)]. However, the resolution of muon image reconstruction techniques is limited due to multiple Coulomb scattering (MCS) within the target object. To achieve robust muon tomography, it is crucial to develop efficient and flexible physics-based algorithms that can model the MCS process accurately and estimate the most probable trajectory of muons as they pass through the target object. To address this limitation, in this study, a novel algorithmic approach utilizing the Bayesian probability theory and Gaussian approximation of MCS is chosen. Different energy levels, materials, and target sizes were considered in the evaluations. The results demonstrate that the Generalized Muon Trajectory Estimation (GMTE) algorithm offers significant improvements over currently used algorithms. Across all test scenarios, the GMTE algorithm demonstrated ∼50% and 38% increase in precision compared to Straight Line Path (SLP) and Point of Closest Approach (PoCA) algorithms, respectively. Furthermore, it exhibited 10%–35% and 10%–15% increases in muon flux utilization for high and medium Z materials, respectively, compared to the PoCA algorithm. In conclusion, the extensive simulations confirm the enhanced performance and efficiency of the GMTE algorithm, offering improved resolution and reduced measurement time for cosmic ray muon imaging compared to the current SLP and PoCA algorithms.

Geant4 simulation study of low-Z material detection using muon tomography

Traditional X-ray scanning systems for cargo use ionising radiation which can be harmful to operators and the environment and requires shielding. Fully passive muon tomography is a promising alternative or a complementary approach to X-ray scanners. Muon tomography is a non-invasive technique that uses naturally occurring cosmic-ray muons and their scattering in various materials to create images of cargo in trucks or containers without applying ionising radiation. Muons are high-energy particles that are produced when primary cosmic rays collide with the Earth's atmosphere. These muons can penetrate through thick materials, such as concrete or metal, and are therefore useful for detecting hidden objects, including contraband. Muon tomography is expected to be used for detection of a wide range of materials, including metals, plastics, and organic materials like drugs or cigarettes, as well as weapons and explosives. In this work we have used the GEANT4 toolkit to simulate the performance of muon tomography in identifying the contraband hidden inside the legal cargo. We have used the Point of Closest Approach (PoCA) reconstruction algorithm to reconstruct the three-dimensional image of a loaded truck.

Nuclear material accountancy using momentum-informed muon scattering tomography

Screening cargo and vehicles to prevent proliferation of unauthorized nuclear and radioactive materials is essential to prevent threats to domestic and international security. Cosmic ray muons attracted attention as a potential next-generation radiographic technique to discover illicit transportation of nuclear and radioactive materials at borders or secure facilities. Unique features of cosmic muons—a high energy and deep penetration depth—enable them to be utilized for radiation probes, especially for large and dense materials. In muon scattering tomography, physical characteristics of target materials are estimated by measuring both incoming and outgoing muon trajectories using muon detectors. To reconstruct 3D tomographic images of target objects, a Point of Closest Approach (PoCA) algorithm is typically used to locate a scattering position, and the scattering angle values are used to map material density. However, high-resolution material mapping is often limited due to the absence of muon momentum information because the expected muon scattering angle depends on two variables: material atomic number and muon momentum. Despite the importance of measuring muon momentum, it is still challenging without deploying large and expensive muon spectrometers. Therefore, a mean muon momentum, 3 to 4 GeV/c, is often used to represent the entire cosmic ray muon spectrum. In this paper, we present a new momentum-informed muon scattering tomography (MST) approach for nuclear material accountancy based on a recently devised fieldable muon spectrometer. This approach uses a new imaging algorithm that improves the current PoCA algorithm by encoding momentum into the scattering angle. In our new algorithm, all muon measurements have a categorized momentum level with a scattering angle. We demonstrate the functionality and performance of momentum-informed MST using computational simulations. The results show that the image resolution is significantly improved, and this approach allows for visually differentiating nuclear materials from non-nuclear materials.

Exploring the relationship between space weather parameters and cosmic ray muons observed at high cut-off rigidity site: A correlation, artificial neural network, and spectral analysis

The objective of this study was to examine the relationship between cosmic rays (CR) and various solar activity parameters, including the interplanetary magnetic field (B), solar radio emission flux at 10.7 cm (F10.7), solar wind speed (V), solar wind density (N), solar wind pressure (P), and the variance of the interplanetary magnetic field vector (σF). The CR data collected from 2007 to 2013 were obtained using a muon detector situated at King Abdulaziz University (KAAU) in Jeddah, Saudi Arabia, with a rigidity cutoff of 14.8 GV. To explore the correlation between the CR data and the selected parameters, three distinct methods were employed: regression analysis, artificial neural network (ANN), and power spectral analysis.Regression analysis revealed significant positive correlations between CR muons and plasma pressure (R = 0.1, p < 0.05), as well as solar wind speed (R = 0.1, p < 0.05). On the other hand, negative correlations were observed between CRs and radio flux (R = 0.75, p < 0.05), as well as interplanetary magnetic field (R = 0.1, p < 0.05). However, no significant correlations were found between CRs and plasma density or the variance of the interplanetary magnetic field vector (p > 0.05). Furthermore, multivariable correlation analyses were conducted to explore the relationship between CR muons and the considered parameters, resulting in only marginal improvement.For comparison purposes, data from the King Abdulaziz City for Science and Technology (KACST) muon detector in Riyadh, Saudi Arabia (with a rigidity cutoff of 14.4 GV), as well as CR data from Oulu NM (with a rigidity cutoff of 0.3 GV), were utilized for the same period as the KAAU data. The correlation results indicated that the relationships between the CR data from the three detectors and some of the considered parameters were consistent. However, the strength of the correlations and the magnitudes of the slopes exhibited variations.ANN procedures were also employed to compare the efficiency of neural network analysis in forecasting CR muons based on solar activity parameters. The Multilayer Perceptron (MLP) Module trained using the backpropagation learning algorithm was utilized to build a neural network model and assess its accuracy. The results indicated that the ANN method provided slightly more accurate predictions compared to regression analysis.Finally, Fast Fourier Transform (FFT) analyses were conducted to examine the presence of periodicities between the CRs and the variables under consideration. The analysis revealed several shared periodicities, including cycles spanning 270–277 days, 146–158 days, 89–95 days, 66–73 days, and 21–31 days.

Laser scanner and UAV digital photogrammetry as support tools for cosmic-ray muon radiography applications: an archaeological case study from Italy

The use of light detection and ranging technologies, i.e. terrestrial laser scanner (TLS), airborne laser scanner (ALS) and mobile laser scanner (MLS), together with the unmanned aerial vehicles digital photogrammetry (UAV-DP) and satellite data are proving to be fundamental tools to carry out reliable muographic measurement campaigns. The main purpose of this paper is to propose a workflow to correctly plan and exploit these types of data for muon radiography aims. To this end, a real case study is presented: searching for hidden tombs in the Etruscan necropolis of Palazzone (Umbria, Italy). A high-resolution digital elevation model (DEM) and three-dimensional models of the ground surface/sub-surface of the study area were created by merging data obtained using different survey methods to achieve the most accurate three-dimensional environment. Indeed, the simulated muon flux transmission used to infer relative transmission values, and the estimated density distribution, depends on the reliability of the three-dimensional reconstructed ground surface model. The aim of this study is to provide knowledge on the use of TLS and UAV-DP data and GPS-acquired points within the transmission-based muography process and how these data could improve or worsen the muon imaging results. Moreover, this study confirmed that muography applications require a multidisciplinary approach.

Research on rapid imaging with cosmic ray muon scattering tomography

Cosmic ray muons tomography is a non-destructive imaging technique that uses the natural radiation of cosmic ray muons to create tomographic images of objects. This article presents a novel imaging algorithm that effectively utilizes experimental measurement data to achieve rapid and clear imaging of cosmic ray muons. A clear image can be obtained with only 20 min of measurement time and approximately 200 effective muons. However, the current detection flux is only about 0.044 cm^{-2} min^{-1}, which is significantly lower than the natural cosmic ray flux of about 1 cm^{-2} min^{-1}.

Application of Geant4 simulation in measurement of cosmic-ray muon flux and studies of muon-induced background

Application of Geant4 simulation in measurement of cosmic-ray muon flux and studies of muon-induced background

The effect of shielding material density in muon tomography

In recent years, the use of high-penetrate cosmic-ray muons has been used in many applications to investigate the internal structure and composition of large material. The muon attenuation is based on multiple Coulomb scattering. This study was aimed to investigate the effect of massive shielding material composition in muon tomography. Muon with various energies between 1 MeV to 100 MeV was used as a source located directly above the shielding material with different density and composition. The output of scattered muon was scored in 2 and 5 km after the material. The simulation was performed using particle and heavy ion transport system (PHITS) software developed by Japan Atomic Energy Agency. The attenuation and scattering of the muon depends predominantly on the shielding material density. The muon energy and flux was decreased with increasing depth of the muon detector. This muon tomography can be applied in investigating the structure and internal composition of unknown materials such as volcanic structures in Indonesia.

Simulation of RPC responses in mini-Iron Calorimeter for cosmic ray muon studies

A Prototype of the Iron Calorimeter for the India-based Neutrino Observatory is currently running in Madurai, India. This consists of twenty large area single gap Resistive Plate Chambers (RPCs) of size, ∼ 185 cm × 175 cm sandwiched between 11 layers of iron plates of thickness 5.6 cm. The total size of the mini-Iron Calorimeter(mini-ICAL) is 4 m × 4 m × 1.2 m and having a weight of 85 tons is a (1/600) scaled-down version of the ICAL detector of INO [1]. The detector is magnetized using iron plates and two sets of copper coils, each coil has 18 turns. The central region of the mini-ICAL, where the RPCs are placed, has a nearly uniform magnetic field of 1.4 T, similar to the magnetic field in the final ICAL detector. This prototype serves as the basis for the design of the demonstrators, which closely mimics the characteristics of a future ICAL. This detector is built to test the final electronics in the fringe field of the magnet and also to develop the experience to construct the ICAL detector. The mini-ICAL has been operational since 2018 and collects cosmic muon data with different configurations of RPC, and electronics, which are continuously changing for various R&D efforts. Dedicated efforts are made in parallel to measure the momentum and azimuthal angle of μ+ and μ- independently, which could be an important input to the cosmic neutrino event generators. To improve the precision of those measurements a dedicated simulation effort was made, particularly in the digitisation of the RPC signal for a real detector simulation, where efficiency, noise rate, strip multiplicity, etc. were matched with the real data collected during runs at mini-ICAL.

Muon energy reconstruction for applications in neutrino astronomy in the DUNE far detector

DUNE (Deep Underground Neutrino Experiment) is a proposed long-baseline neutrino oscillation experiment located in the United States. The main physics objectives of DUNE are to measure neutrino oscillations and interactions, search for nucleon decay, observe supernova neutrino bursts and beyond Standard Model (BSM) effects. The DUNE far detector will be located 4850 feet underground at the Sanford Underground Research Facility in Lead, South Dakota. It will house the world's largest liquid-argon time projection chambers (TPC). The DUNE far detector can detect high-energy leptons that arise from interactions of cosmogenic neutrinos and search for neutrinos originating from the decay of weakly-interactive massive particles (WIMPs) annihilations occurring inside the Sun. Selecting upward-going muons reduces the background from cosmic-ray muons. The muon energy is estimated from the electromagnetic showers accompanying the muon, a technique that allows energy reconstruction up to a few hundred TeV.