The cyclotron radiation emission spectroscopy (CRES) technique pioneered by Project 8 measures electromagnetic radiation from individual electrons gyrating in a background magnetic field to construct ...a highly precise energy spectrum for beta decay studies and other applications. The detector, magnetic trap geometry and electron dynamics give rise to a multitude of complex electron signal structures which carry information about distinguishing physical traits. With machine learning models, we develop a scheme based on these traits to analyze and classify CRES signals. Proper understanding and use of these traits will be instrumental to improve cyclotron frequency reconstruction and boost the potential of Project 8 to achieve world-leading sensitivity on the tritium endpoint measurement in the future.
Objective: We developed and implemented two predictor-corrector methods for the classification of two-channel EEG data into sleep stages. Approach: The sequence of sleep stages over the night is ...modeled by a Markov chain of first and second order, resulting in an informative prior distribution for the new state, given the distribution of the current one. The correction step is realized by applying a Bayes classifier using the (preprocessed) data and this prior. The preprocessing step consists of a frequency analysis, a log transformation and a dimensionality reduction via principal component analysis. Main results: The software automatically generates sleep profiles in which it detects wakeful phases as well as the different sleep stages with error rates of 16.5%-31.9% (n = 8, healthy subjects, mean age ± SD: 39 ± 8.1 years, five females), where we compared our results to those of a certified polysomnographic technologist, who used a full polysomnograph and rated according to the American Academy of Sleep Medicine (AASM) criteria. Significance: The method presented relies on considerably less information than visual scoring and is done automatically. Furthermore, the error is comparable to visual scoring, where the inter-rater variability lies around 82%. Therefore, it has the potential to lessen the overheads associated with sleep diagnostics.
Replicating the mechanical behavior of human bones, especially cancellous bone tissue, is challenging. Typically, conventional bone models primarily consist of polyurethane foam surrounded by a solid ...shell. Although nearly isotropic foam components have mechanical properties similar to cancellous bone, they do not represent the anisotropy and inhomogeneity of bone architecture. To consider the architecture of bone, models were developed whose core was additively manufactured based on CT data. This core was subsequently coated with glass fiber composite. Specimens consisting of a gyroid-structure were fabricated using fused filament fabrication (FFF) techniques from different materials and various filler levels. Subsequent compression tests showed good accordance between the mechanical behavior of the printed specimens and human bone. The unidirectional fiberglass composite showed higher strength and stiffness than human cortical bone in 3-point bending tests, with comparable material behaviors being observed. During biomechanical investigation of the entire assembly, femoral prosthetic stems were inserted into both artificial and human bones under controlled conditions, while recording occurring forces and strains. All of the artificial prototypes, made of different materials, showed analogous behavior to human bone. In conclusion, it was shown that low-cost FFF technique can be used to generate valid bone models and selectively modify their properties by changing the infill.
Abstract
Cyclotron radiation emission spectroscopy (CRES) is a modern approach for determining charged particle energies via high-precision frequency measurements of the emitted cyclotron radiation. ...For CRES experiments with gas within the fiducial volume, signal and noise dynamics can be modelled by a hidden Markov model. We introduce a novel application of the Viterbi algorithm in order to derive informational limits on the optimal detection of cyclotron radiation signals in this class of gas-filled CRES experiments, thereby providing concrete limits from which future reconstruction algorithms, as well as detector designs, can be constrained. The validity of the resultant decision rules is confirmed using both Monte Carlo and Project 8 data.
Abstract Cyclotron Radiation Emission Spectroscopy (CRES) is a technique for precision measurement of the energies of charged particles, which is being developed by the Project 8 Collaboration to ...measure the neutrino mass using tritium beta-decay spectroscopy. Project 8 seeks to use the CRES technique to measure the neutrino mass with a sensitivity of 40 meV, requiring a large supply of tritium atoms stored in a multi-cubic meter detector volume. Antenna arrays are one potential technology compatible with an experiment of this scale, but the capability of an antenna-based CRES experiment to measure the neutrino mass depends on the efficiency of the signal detection algorithms. In this paper, we develop efficiency models for three signal detection algorithms and compare them using simulations from a prototype antenna-based CRES experiment as a case-study. The algorithms include a power threshold, a matched filter template bank, and a neural network based machine learning approach, which are analyzed in terms of their average detection efficiency and relative computational cost. It is found that significant improvements in detection efficiency and, therefore, neutrino mass sensitivity are achievable, with only a moderate increase in computation cost, by utilizing either the matched filter or machine learning approach in place of a power threshold, which is the baseline signal detection algorithm used in previous CRES experiments by Project 8.
The Locust simulation package is a new C++ software tool developed to simulate the measurement of time-varying electromagnetic fields using RF detection techniques. Modularity and flexibility allow ...for arbitrary input signals, while concurrently supporting tight integration with physics-based simulations as input. External signals driven by the Kassiopeia particle tracking package are discussed, demonstrating conditional feedback between Locust and Kassiopeia during software execution. An application of the simulation to the Project 8 experiment is described. Locust is publicly available at https://github.com/project8/locust_mc.
Abstract
Cyclotron Radiation Emission Spectroscopy (CRES) is a
technique for measuring the kinetic energy of charged particles
through a precision measurement of the frequency of the cyclotron
...radiation generated by the particle's motion in a magnetic
field. The Project 8 collaboration is developing a next-generation
neutrino mass measurement experiment based on CRES. One approach is
to use a phased antenna array, which surrounds a volume of tritium
gas, to detect and measure the cyclotron radiation of the resulting
β-decay electrons. To validate the feasibility of this method,
Project 8 has designed a test stand to benchmark the performance of
an antenna array at reconstructing signals that mimic those of
genuine CRES events. To generate synthetic CRES events, a novel
probe antenna has been developed, which emits radiation with
characteristics similar to the cyclotron radiation produced by
charged particles in magnetic fields. This paper outlines the
design, construction, and characterization of this Synthetic
Cyclotron Antenna (SYNCA). Furthermore, we perform a series of
measurements that use the SYNCA to test the position reconstruction
capabilities of the digital beamforming reconstruction technique. We
find that the SYNCA produces radiation with characteristics closely
matching those expected for cyclotron radiation and reproduces
experimentally the phenomenology of digital beamforming simulations
of true CRES signals.
Abstract The objective of the cyclotron radiation emission spectroscopy (CRES) technology is to build precise particle energy spectra. This is achieved by identifying the start frequencies of charged ...particle trajectories which, when exposed to an external magnetic field, leave semi-linear profiles (called tracks) in the time–frequency plane. Due to the need for excellent instrumental energy resolution in application, highly efficient and accurate track reconstruction methods are desired. Deep learning convolutional neural networks (CNNs) - particularly suited to deal with information-sparse data and which offer precise foreground localization—may be utilized to extract track properties from measured CRES signals (called events) with relative computational ease. In this work, we develop a novel machine learning based model which operates a CNN and a support vector machine in tandem to perform this reconstruction. A primary application of our method is shown on simulated CRES signals which mimic those of the Project 8 experiment—a novel effort to extract the unknown absolute neutrino mass value from a precise measurement of tritium β − -decay energy spectrum. When compared to a point-clustering based technique used as a baseline, we show a relative gain of 24.1% in event reconstruction efficiency and comparable performance in accuracy of track parameter reconstruction.
An innovative epidermal surface treatment based on
188
Re has been recently developed for squamous cell carcinomas of the skin. The planning and delivery of the treatment requires an accurate ...knowledge of the source activity and thus proper calibration of activity meters. However, reference sources for calibration purposes are not always available, as in the case of short-lived radionuclides. The aim of this work is to determine the calibration factors for
188
Re by comparison of measurements with an independently calibrated HPGe spectrometer. Calibration factors were experimentally determined for two different activity meters, a Capintec CRC15 and a MecMurphil MP-DC. This study was conducted on a Rhenium-188 compound produced by OncoBeta
®
GmbH for Rhenium-SCT
®
therapy. The final calibration factors, relative to
137
Cs, for the MecMurphil MP-DC were: 4.35 ± 0.06 for point-like sources and 4.48 ± 0.09 for 5 mL solutions. While the final calibration factors for the Capintec CRC15 were: 4.12 ± 0.07 for point-like sources and 4.60 ± 0.10 for 5 mL solutions. With the presented method, we managed to determine calibration factors with an uncertainty below 3%.
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Dostopno za:
BFBNIB, DOBA, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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