Reconstruction Of Energy Spectrum Research Articles

Inhomogeneous stripe phase and tunable Majorana zero modes in Rashba s-wave superconducting systems in the presence of in-plane Zeeman field

Based on the extended Bogoliubov–de Gennes theory, the inhomogeneous stripe order and Majorana bound states are demonstrated in s-wave superconducting systems with Rashba spin–orbit interaction when the in-plane Zeeman field is applied. For a fully open square sample, topological phase transitions can be driven by the Zeeman field, and the stripe phase with spatially oscillating order parameter shows up across a critical field strength. The topological channels arise in this phase, which can be utilized to create and manipulate Majorana zero modes. Interestingly, (quasi-)one-dimensional channels with diminished pairing amplitude can be formed in narrow arms of a square loop, accompanied by the reconstruction of energy spectra of the condensate and the realization of robust Majorana zero-energy states at the ends of channels. The associated evolution of topological phases and the location of Majorana zero modes are highly sensitive to the field direction. Moreover, the effects of the rectangular aspect-ratio and the off-centered hole as well as the surface defects on Majorana end modes are explored in Rashba asymmetric loops. In comparison, the field-dependent evolution processes of low-energy levels behave more complicated because the emergence of confined topological channels can be effectively tuned by the length and width of loop arms as well as the size and position of an introduced small indentation at the outer edge. Rich patterns of Majorana corner-like states are generated for such asymmetric systems. Our theoretical predictions may shed new light on the tunability of Majorana zero modes and provide useful guidance for future experiments and applications.

Application of neural networks for the reconstruction of supernova neutrino energy spectra following fast neutrino flavor conversions

Neutrinos can undergo fast flavor conversions (FFCs) within extremely dense astrophysical environments, such as core-collapse supernovae (CCSNe) and neutron star mergers (NSMs). In this study, we explore FFCs in a neutrino gas, revealing that when the FFC growth rate significantly exceeds that of the vacuum Hamiltonian, all neutrinos (regardless of energy) share a common survival probability dictated by the energy-integrated neutrino spectrum. We then employ physics-informed neural networks (PINNs) to predict the asymptotic outcomes of FFCs within such a multienergy neutrino gas. These predictions are based on the first two moments of neutrino angular distributions for each energy bin, typically available in state-of-the-art CCSN and NSM simulations. Our PINNs achieve errors as low as ≲6% and ≲18% for predicting the number of neutrinos in the electron channel and the relative absolute error in the neutrino moments, respectively. Published by the American Physical Society 2024

Methods of machine learning for the analysis of cosmic rays mass composition with the KASCADE experiment data

We study the problem of reconstruction of high-energy cosmic rays mass composition from the experimental data of extensive air showers. We develop several machine learning methods for the reconstruction of energy spectra of separate primary nuclei at energies 1–100 PeV, using the public data and Monte-Carlo simulations of the KASCADE experiment from the KCDC platform. We estimate the uncertainties of our methods, including the unfolding procedure, and show that the overall accuracy exceeds that of the method used in the original studies of the KASCADE experiment.

EAS Cherenkov LDF Analysis: CORSIKA Simulations for Tunka-133 and Chacaltaya Arrays

This study leverages CORSIKA simulations to analyze the Lateral Distribution Function (LDF) of Cherenkov photons in Extensive Air Showers (EAS) within the knee region of the cosmic ray energy spectrum (10^15 - 10^16 eV). Focusing on primary particles like helium, proton, oxygen, and iron nuclei at varying zenith angles (0˚, 20˚, and 45˚), we aimed to reconstruct Cherenkov photons' LDF using an Exponential Function model, tailored as a function of primary energy. Our approach involved a comparative analysis of simulated LDFs with experimental data from the Tunka-133 and Chacaltaya arrays. The results exhibit a high degree of concordance between simulated and observed data, affirming the validity of our method. We developed a set of approximation functions for different primary particles and zenith angles, enhancing our ability to identify the particle type in EAS events and accurately determine its energy. The primary contribution of our work lies in its potential to rapidly compile a comprehensive LDF pattern library, instrumental for analyzing real EAS array events and reconstructing the mass composition and primary cosmic ray energy spectrum. This advancement in CORSIKA-based simulation methods marks a significant stride in cosmic ray research, offering a robust tool for detailed EAS analysis.Highlights : Validation of Simulation Accuracy: Demonstrated high concordance between CORSIKA simulated LDFs and experimental data from Tunka-133 and Chacaltaya arrays. Enhanced Particle Identification: Development of approximation functions for various primary particles and zenith angles, improving accuracy in identifying particle types in EAS events. Advancement in Cosmic Ray Research: Potential to create a comprehensive LDF pattern library, significantly aiding in the reconstruction of mass composition and primary cosmic ray energy spectrum. Keywords : CORSIKA Simulations, Cherenkov LDF, EAS Analysis, Cosmic Ray Spectrum, Particle Identification

Optimization of the regularization parameter in the Dual Annealing method used for the reconstruction of energy spectrum of electron beam generated by the AQURE mobile accelerator

IntroductionThe shape of the energy spectrum is an essential component of any electron beam Monte Carlo model. Due to specialized equipment and the long measurement time for the direct methods for determining the energy spectrum, attractive alternatives are backward spectrum reconstructions from the measured data. One such approach is solving the first-degree Fredholm integral equation with appropriate regularization. It makes it possible to calculate the depth distribution as the sum of the distributions from monoenergetic beams. This study aims to determine the optimal value of the regularization parameter for the problem of determining the spectrum of the electron beam produced by a mobile accelerator used during intraoperative radiotherapy. Material and methodsThe Geant4 package was used to generate the distributions of deep doses for monoenergetic beams for two models with different degrees of complexity, i.e. simple (theoretical) and full (for the mobile accelerator). The dose distributions for four different shapes of energy spectrum (for each model) were obtained similarly. They were established as the reference data for further calculations. The Dual Annealing optimization method was used to obtain the reconstructed spectrum. The multiple optimizations that differ by the regularization parameter (ranging from 0 to 1) were performed. For each reconstruction, similarity indicators of the energy spectrum and the dose distribution to the referenced data were calculated to determine the optimal regularization parameters. ResultsOptimal regularization parameters determined by similarity indicators for the spectrum and the dose distribution differ for geometry models considered in the study. The regularization parameter for the simple geometry ranged from 0.03 to 0.05, while for full geometry, they were from 0.05 to 0.06. The results for conventional linear accelerators found in the literature range from 0.5 to 1.1. ConclusionThe Dual Annealing optimization method can be effectively used to solve the Fredholm equation with Tikhonov regularization to reconstruct an electron beam's energy spectrum. The regularization parameter value depends on the beam-forming system. Its value for the mobile accelerator considered in the study ranges from 0.05 to 0.06, depending on the nominal beam energy value.

A fast simulation model of 2-D photoelectron track images for gaseous X-ray polarimetry

Gaseous polarimetry applies in soft X-ray polarization detection, typically like the Gas Pixel detector (GPD) and the micropattern time projection chamber (TPC). The polarization phase angles resolve from photoelectron track trajectories for both of them. The photoelectron track images derived from read-out pixels or strips are the key to determining the performance of the polarimetry. Gaseous X-ray polarimetry is regularly optimized and diagnosed by the Geant4 associated with Garfield++ and finite element analysis software (full simulation). Although the results are more realistic by the full simulation, the sample generation is low efficiency, especially for large gain values of the multiplier stage. The 2-D photoelectron track images regularly generate by a gaussian smear of initial ionization electrons at present. However, discrepancies exist in the modulation curves, resulting in fuzzy diagnoses and optimization of polarimetry. In this study, a fast simulation framework is constructed, the reconstruction of polarization phase angles and energy spectrum of the samples obtained from the fast simulation are consistent with those from experiments and the full simulation, and the deviation of modulation factor is within 2% for both situations of the GPD and TPC. In addition, the fast simulation greatly improves the sample generation efficiency. These results illustrate the fast simulation model is relative accuracy and high efficiency, which provides a useful tool for gaseous X-ray polarimetry.

Using low voltage ionization chamber (LVIC) in current mode for energy spectrum reconstruction: Experiments and validation.

Due to the International Thermonuclear Experimental Reactor (ITER) radiative environment, in particular during high D-T power phase, classic x-ray detectors, such as semiconductor diodes, might be too fragile and are thus not viable. Instead, robust detectors, such as gas-filled detectors, are nowadays considered. The Low Voltage Ionization Chamber (LVIC) is one of the most promising candidates for x-ray measurement during the ITER nuclear phase. A complete model of the detector, recently developed at IRFM (Intitute for Research on Magnetic Fusion), now requires experimental validation. Experimental testing at the IRFM laboratory of an ITER industrial LVIC prototype and comparison with modeling are presented. In particular, an original approach to extract information on the x-ray spectrum from current-mode LVIC measurement is validated experimentally.

Spectroscopic autoradiography of alpha particles using a parallel ionization multiplier gaseous detector

Geoscience is a field of study where nuclear instruments find their place for conducting specific measurements of radioactivity, usually to improve the monitoring of natural processes using naturally-occurring radioactive tracers, but also for the nuclear industry linked to the mining sector. In geological samples, the location and identification of the minerals bearing radioactivity at the thin-section scale remains a major challenge as the detection limit of the usual elementary microprobe techniques is far higher than the concentration of most of the natural radioactive decay products. The location of each decay product, as in the case of uranium-238 series in a geomaterial is interesting for relating radionuclide concentrations to mineralogy. The present study aims to provide spectroscopic autoradiography analysis method for measuring the initial energy of alpha particles with a parallel ionization multiplier gaseous detector. This spectroscopic autoradiography method was successfully used to reproduce the alpha spectra from a 238U decay chain on a geological sample at the thin-section scale. The characteristics of this measurement are an energy spectrum resolution of 17.2% (FWHM) at 4647 keV and a spatial resolution of at least 50 μm. Even if the efficiency of energy spectrum reconstruction is low (4.4%) compared to the efficiency of a simple autoradiograph (50%), this novel measurement approach offers the opportunity to select areas on an autoradiograph to perform an energy spectrum analysis within that area. This opens up possibilities for the detailed analysis of heterogeneous geological samples containing natural alpha emitters such as uranium-238 and radium-226.

Estimation of energy and angle of incident protons from three-dimensional track profiles on CR-39 detectors

The aim of this study was to establish a new method for estimating the energy and angle of incident protons based on the three-dimensional profile of nuclear tracks. An inverse growth approach was developed to obtain the latent track from the etched track pit. The energy and angle of the incident protons can be estimated by determining the critical point (end point of the particle trajectory). The estimated incident energies and angles were in good agreement with the pre-set values for the simulated and experimental data. Compared with the pre-set values, the deviation of the energies and angles for 1–3 MeV protons were within ±0.3 MeV and ±5.0°, respectively. This study provides a valuable reference for extracting energy and angle information from 3-D profiles of a nuclear track, and is expected to be beneficial in reconstruction of energy spectra.

Reconstruction of energy spectrum of runaway electrons in nanosecond-pulse discharges in atmospheric air

This paper presents an experimental investigation into the runaway electron spectrum with a gas diode composed of a rough spherical cathode and plane anode under the excitation of a nanosecond-pulse generator in atmospheric air. The runaway electron beams are measured by a collector covered with aluminum foil with a thickness from 0 μm (mesh grid) to 50 μm. The energy spectrum is calculated by an improved Tikhonov regularization called the maximum entropy method. The experimental results show that the transition state of the discharge consisted of multiple streamer channels stretched from the cathode with glow-like plasma uniformly distributed over the anode. The number of runaway electrons measured by the collector is in the order of 1010 in atmospheric pressure air with a gap spacing of 5 mm and applied voltages of 70–130 kV. The cathode with a rough surface creates a more inhomogeneous electric field and larger emission site for the runaway electrons around the cathode, providing conditions for the coexistence of filamentary streamer and diffuse discharge. The reconstructed spectra show that the energy distribution of the runaway electrons presents a single-peak profile with energies from eU m/2–2eU m/3 (U m is maximal voltage across the gap).

Accurate reconstruction of soft X-ray energy spectrum in detector response matrix

In this paper, we report the design of a Monte Carlo simulation for the energy spectrum measurement system based on the ladder-absorption method. Herein, the detector response matrix can be calculated using the detector responses to several monochromatic X-ray beams. A novel soft X-ray spectrum unfolding method based on the two-step reverse iteration (TSRI) algorithm is applied to acquire the primary spectrum. This paper provides examples of the use of TSRI, and the unfolded energy spectra for the soft X-ray beams show excellent agreement with the references. The unfolded energy spectra obtained using the TSRI exhibit better accuracy than those obtained from the commonly used unfolding code GRAVEL.

A new energy spectrum reconstruction method for time-of-flight diagnostics of high-energy laser-driven protons.

The Time-of-Flight (TOF) technique coupled with semiconductorlike detectors, as silicon carbide and diamond, is one of the most promising diagnostic methods for high-energy, high repetition rate, laser-accelerated ions allowing a full on-line beam spectral characterization. A new analysis method for reconstructing the energy spectrum of high-energy laser-driven ion beams from TOF signals is hereby presented and discussed. The proposed method takes into account the detector's working principle, through the accurate calculation of the energy loss in the detector active layer, using Monte Carlo simulations. The analysis method was validated against well-established diagnostics, such as the Thomson parabola spectrometer, during an experimental campaign carried out at the Rutherford Appleton Laboratory (UK) with the high-energy laser-driven protons accelerated by the VULCAN Petawatt laser.

Inverse reconstruction of energy spectra of clinical electron beams using the generalized simulated annealing method

In radiotherapy, the electron spectrum should be considered for accurate dose calculation. There are mainly three approaches to obtain the central axis electron energy spectrum, namely: (i) radiation source modeling; (ii) direct measurement and (iii) inverse reconstruction. To determine the electron spectra, it is proposed to use the inverse reconstruction approach. Inverse reconstruction consists in deriving the electron spectra from measured depth dose distributions. Since inverse reconstruction is a poorly conditioned problem the Tikhonov regularization is implemented to avoid the nonphysical oscillations inherent to this problem. Generalized simulated annealing method is used for minimizing the Tikhonov function in order to find the electron spectra. The effectiveness of the spectral reconstruction is verified by the gamma index criterion. Gamma Index defines the degree of agreement between two depth-dose distributions based on predefined tolerances in terms of distance-to-agreement (DTA) and difference dose (DD). Results show a good agreement between provided (measured in a water phantom) and reproduced (simulated from a reconstructed spectrum) depth dose curves within the gamma index tolerance level defined by >95% passing rate with 1% difference dose/1 mm distance to agreement. In addition, it is possible to evidence an acceptable agreement between provided and reproduced dose profiles according to >95% with 2%/2 mm for every beam, excepting the lowest energy beam. Therefore, it is concluded that generalized simulated annealing is able to reconstruct central-axis electron spectra incident on water phantom surface within restrictive limits of gamma index clinical acceptance.

Neutron spectroscopy with soft computing: development of a computational code based on Support Vector Machine (SVM) for reconstruction of neutron energy spectrum

This paper presents a developed computational code based on Support Vector Machine (SVM) for reconstruction of energy spectrum of neutron source. To reconstruct unknown energy spectrum using known neutron pulse height distribution, the developed machine is trained by known neutron pulse height distribution of detector and corresponding energy spectrum of neutron source. Validation and testing are the next steps to verify the validity of the calculations done with the developed computational code. The calculated neutron pulse height distributions due to randomly generated energy spectrum using MCNPX-ESUT (MCNPX-Energy engineering of Sharif University of Technology) computational code are used as input data of the developed computational code for reconstruction of energy spectrum of neutron source. The considered energy spectrums of neutron source are output data. In the present study, the simulation of neutron pulse height distribution of 241Am-9Be neutron source in the NE-213 liquid organic scintillator is performed using MCNPX-ESUT computational code. In the constructed matrix form of Fredholm integral equation, the effective response matrix is usually close to singular or badly scaled and its condition number is so high. The solution of inverse problem in which the matrix has high condition number does not give accurate results. The motivation of the present study is the development of computational coded based on soft computing algorithm for reconstruction of energy spectrum of the neutron source with high accuracy. To this end, the computational code based on Support Vector Machine (SVM) is developed, where there is no need to solve the inverse problems. The unfolded energy spectra of 241Am-9Be neutron sources using the developed computational code have an excellent agreement with the reference spectrum provided by ISO. A comparison between the results of present study and results of developed computational code based on Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) is performed.

Current Status and New Challenges of The Tunka Radio Extension

The Tunka Radio Extension (Tunka-Rex) is an antenna array spread over an area of about 1 km2. The array is placed at the Tunka Advanced Instrument for cosmic rays and Gamma Astronomy (TAIGA) and detects the radio emission of air showers in the band of 30 to 80 MHz. During the last years it was shown that a sparse array such as Tunka-Rex is capable of reconstructing the parameters of the primary particle as accurate as the modern instruments. Based on these results we continue developing our data analysis. Our next goal is the reconstruction of cosmic-ray energy spectrum observed only by a radio instrument. Taking a step towards it, we develop a model of aperture of our instrument and test it against hybrid TAIGA observations and Monte-Carlo simulations. In the present work we give an overview of the current status and results for the last five years of operation of Tunka-Rex and discuss prospects of the cosmic-ray energy estimation with sparse radio arrays.

Time-of-flight spectrometry of ultra-short, polyenergetic proton bunches.

A common approach for spectrum determination of polyenergetic proton bunches from laser-ion acceleration experiments is based on the time-of-flight (TOF) method. However, spectra obtained using this method are typically given in relative units or are estimated based on some prior assumptions on the energy distribution of the accelerated ions. In this work, we present a new approach using the TOF method that allows for an absolute energy spectrum reconstruction from a current signal acquired with a sub-nanosecond fast and 10 µm thin silicon detector. The reconstruction is based on solving a linear least-squares problem, taking into account the response function of the detection system. The general principle of signal generation and spectrum reconstruction by setting up an appropriate system response matrix is presented. Proof-of-principle experiments at a 12 MV Tandem accelerator using different nanosecond-short (quasi-)monoenergetic and polyenergetic proton bunches at energies up to 20 MeV were successfully performed. Within the experimental uncertainties of 2.4% and 12.1% for energy and particle number, respectively, reconstructed energy distributions were found in excellent agreement with the spectra calculated using Monte Carlo simulations and measured by a magnetic spectrometer. This TOF method can hence be used for absolute online spectrometry of laser-accelerated particle bunches.

Initial result of neutron energy spectrum reconstruction using multi-foil activation method in KSTAR

For the purpose of the fusion power measurement accuracy improvement in KSTAR, multi-foil activation method has been applied on KSTAR neutron activation system (NAS). In order to increase the spectral coverage, in addition to indium and silicon samples which have been routinely used to measure fusion power of deuterium plasma and triton burnup respectively, 3 other sample materials, aluminum, niobium, and nickel are selected based on the calculation of expected activity and γ-ray counts. Due to the limited accessibility in counting station during the plasma experiment, and in order to maximize γ-ray counting statistics each sample material is irradiated one by one during the 2016 KSTAR campaign. In this reason, the analysis is carried out under the assumption that neutron emission characteristics on each plasma discharge do not change. MAXED unfolding code has been used in order to reconstruct the default spectrum which is calculated by MCNP5. This initial reconstruction result will be used as criterion for selection of additional appropriate reaction and optimization of strategies of sample irradiation and γ-ray counting.

Potential reduction interior point algorithm unfolding of neutron energy spectrum measured by recoil proton method**supported by Fundamental Research Funds for Central Universities (2016XS61), and Opening Foundation of State Key Laboratory of Intense Pulsed Radiation Simulation and Effect.

A reconstruction algorithm for unfolding neutron energy spectra has been developed, based for the first time on the potential reduction interior point algorithm. This algorithm can be easily applied to neutron energy spectrum reconstruction in the recoil proton method. We transform the neutron energy spectrum unfolding problem into a typical nonnegative linear complementarity problem. The recoil proton energy spectrum and response matrix at angles of 0° and 30° are generated by the Geant4 simulation toolkit. Several different neutron energy test spectra are also employed. It is found that this unfolding algorithm is stable and provides efficient, accurate results.

Space-Time Correlations and Dynamic Coupling in Turbulent Flows

Space-time correlation is a staple method for investigating the dynamic coupling of spatial and temporal scales of motion in turbulent flows. In this article, we review the space-time correlation models in both the Eulerian and Lagrangian frames of reference, which include the random sweeping and local straining models for isotropic and homogeneous turbulence, Taylor's frozen-flow model and the elliptic approximation model for turbulent shear flows, and the linear-wave propagation model and swept-wave model for compressible turbulence. We then focus on how space-time correlations are used to develop time-accurate turbulence models for the large-eddy simulation of turbulence-generated noise and particle-laden turbulence. We briefly discuss their applications to two-point closures for Kolmogorov's universal scaling of energy spectra and to the reconstruction of space-time energy spectra from a subset of spatial and temporal signals in experimental measurements. Finally, we summarize the current understanding of space-time correlations and conclude with future issues for the field.

Estimation of the energy spectrums of reflections in pulse Doppler weather radars. Part 2. Extreme performance

This is the second paper in a series of papers dedicated to the peculiarities of estimation of the continuous energy spectra of random processes of different nature, which are determined by their samples at discrete moments of time. In this paper we analyze extreme performance of the reconstruction of continuous energy spectra, in particular, the ones of interperiod fluctuations of reflections from meteorological objects in pulse Doppler weather radars under the hypothetical conditions of a priori known covariance matrix of the analyzed processes. The reasons, which cause known disadvantages of classical (nonparametric) spectral estimation (SE) methods for energy spectrums shape reconstruction, are discussed. We have considered known and suggested criteria, using which the extreme performance of classical SE methods and parametric superresolution ones has been quantitatively compared. It has been demonstrated that the extreme performance of SE methods contains important but not comprehensive information. In order to choose a SE method appropriate for operation under real-world conditions, this information should be used together with information on a corresponding method’s adaptive performance under a priori unknown statistical characteristics of input effects.