Journal of the Korean Physical Society最新文献

The design of neutrino experiments and the analysis of neutrino data rely on precise computations of neutrino oscillations and scattering processes in general. Motivated by this, we developed a unified software package that calculates the expected number and energy spectrum of neutrino events in the liquid scintillation detector taking into account the neutrino flux at production, the oscillations of neutrinos during propagation and their interactions in the detectors. We also implemented the calculation of neutrino flux from nuclear reactors, the Sun, and radioactive isotopes to explorer various experimental setups using a single package. This software package is validated by reproducing the result of calculations and observations in other publications. We also demonstrate the feasibility of this package by calculating the sensitivity of a liquid scintillation detector, currently in planning, to the sterile neutrinos. This work is expected to be utilized to identify the physics potential and optimize the design of future neutrino experiments.

By analyzing the chemical composition of soil samples and effectively removing spontaneous radionuclides of cesium isotopes from the samples using the direct method and AMP, the MDA value is measured and compared with the direct method, and how much it can be reduced is analyzed and evaluated. A standard soil sample was made by diluting 37 kBq/kg of 134Cs aqueous solution in distilled water to prepare 500, 1000, 2500, and 5000 Bq/kg of aqueous solution at the Institute of Standard Science. As a result of AMP pretreatment using soil samples and reducing the loss of cesium isotopes that may occur during chemical pretreatment using AMP reagents, a satisfactory result of an average of 89.5% was obtained. As a result of measuring the standard soil sample after calibration, a very satisfactory result could be derived with a difference of at least 0 to 5 Bq/kg from the standard sample. In addition, the efficiency measurements in the three methods (direct method, AMP) after correction showed uncertainty within 3% compared to Monte Carlo values, which matched well. Several factors, such as background, sample measurement time, and recovery rate, affect the MDA value, especially when the radioactivity concentration is above 2500 Bq/kg, by shortening the measurement time, MDA values can be reduced. As the amount of sample increased, the efficiency decreased clearly due to the self-absorption effect. Therefore, it was confirmed that the higher the soil type and component ratio, the more the radioactive concentration was affected.

The puzzle of how cooperation arises in social dilemmas has been a central question in evolutionary game theory. Traditional studies have delineated direct and indirect reciprocity as distinct avenues for fostering cooperative behavior. Direct reciprocity hinges on recurrent interactions with the same individual, whereas indirect reciprocity involves leveraging information about the conduct of other participants. This study investigates strategy evolution within the iterated Prisoner’s Dilemma framework, focusing on a finite population and utilizing a refined Moran process. We explore the effectiveness of various strategies for discriminators, considering both repeated encounters with identical partners and the availability of public action records, to facilitate the emergence of cooperation. Our analysis reveals that the order of the performances of discriminator strategies depends on the cost-to-benefit ratio of cooperation. Discriminators utilizing indirect information from initial encounters generally outperform others, except in cases where the benefits significantly surpass the costs, a condition under which the conventional Tit-for-Tat approach prevails.

The current study endeavors to fabricate a lead-free bismuth-based layered multifunctional material denoted as CaBiGdNbVO₉ (CBGNVO), achieved through synthesis and characterization. X-ray diffraction analysis indicates a polycrystalline nature for the developed system, exhibiting orthorhombic crystal symmetry. Structural parameters obtained are a = 14.5781 Å, b = 27.3108 Å, c = 3.7148 Å, and V = 1479.01 Å³. Electron microscopic examination reveals compactness and uniform distribution of grains of similar sizes across the pellet sample surface. Electrical data analysis, encompassing relative permittivity, loss tangent, and impedance as functions of temperature and frequency, elucidates dielectric relaxation and conduction mechanisms within the material. These findings suggest the potential suitability for various applications, such as temperature sensors and bandwidth regulation. Examination of electronic charge carriers reveals a short-range order, validated through complex modulus and impedance spectrum analysis. A comprehensive investigation into resistive, capacitive, and microstructural characteristics provides valuable insights, positioning the material as a viable electronic component for device fabrication.

Adiabatic quantum computation is a paradigmatic model aiming to solve a computational problem by finding the many-body ground state encapsulating the solution. However, its use of an adiabatic evolution depending on the spectral gap of an intricate many-body Hamiltonian makes its analysis daunting. While it is plausible to directly cool the final gapped system of the adiabatic evolution instead, the analysis of such a scheme on a general ground is missing. Here, we propose a specific Hamiltonian model for this purpose. The scheme is inspired by cavity cooling, involving the emulation of a zero-temperature reservoir. Repeated discarding of ancilla reservoir qubits extracts the entropy of the system, driving the system toward its ground state. At the same time, the measurement of the discarded qubits hints at the energy-level structure of the system as a return. We show that quantum computation based on this cooling procedure is equivalent in its computational power to the one based on quantum circuits. We then exemplify the scheme with a few illustrative use cases for combinatorial optimization problems. To circumvent the issue of local energy minima, we implant a mechanism in the Hamiltonian that allows the population trapped in the local minima to tunnel out via high-order transitions, and support the idea with numerical simulations. We also discuss its application to preparing quantum many-body ground states, arguing that the spectral gap is a crucial factor in determining the time scale of the cooling.

When adjuvant radiation therapy (RT) is employed following breast-conserving surgery (BCS), it is imperative to exercise caution regarding the risk of radiation exposure to the heart in patients diagnosed with left-sided breast cancer. Deep-inspiration breath-hold (DIBH) is a technique that regulates the patient’s breathing and expands the chest wall to increase the distance between the treatment area and surrounding organs, thereby providing protection for the heart. The self-monitoring system with a laser distance sensor (LDS) is not attached to the patient’s body and allows for the monitoring of respiration, thereby ensuring the reproducibility of DIBH. The experiment was conducted on 11 clinical left-sided breast cancer patients per group with or without self-monitoring. When self-monitoring was not performed, patients demonstrated a tendency to breathe regardless of the DIBH baseline, and there was no evidence of any tendency to correct errors. The mean distance error between the first and second DIBH was 3.78 mm and 3.95 mm, respectively, with an overall tendency for the average distance error to increase. When self-monitoring was performed, there was a tendency to correct errors according to the DIBH baseline. The average distance error between the first DIBH and the second DIBH was 2.02 mm and 1.98 mm, respectively, which was relatively small. The self-monitoring system with LDS helps to maintain the DIBH throughout the treatment period, thereby ensuring that treatment effects are consistent with the prescribed treatment plan can be expected. Furthermore, LDS, which can measure absolute distance, enhances the accuracy of patient positioning for DIBH.

The spin models in condensed matter physics are important since the strong interaction between spins creates various quantum phases of interest. In this work, we explore the quantum critical region of a spin-one ((S=1)) quantum XXZ model in two dimensions. By adopting a worm algorithm proposed recently, we performed quantum Monte Carlo simulations in the parameter space of temperature (T) and the interaction strength of the z-directional spin component of nearest neighbor spins ((Delta )). The phase diagram is obtained by comparing the Monte Carlo data and analytic consideration of superfluid stiffness and compressibility. We find the critical temperatures between the XY phase and the parameter phase by measuring the superfluid stiffness as a function of temperature and the critical strength of antiferromagnetic interaction ((Delta _c)) by measuring the compressibility as a function of the strength of antiferromagnetic interaction. We compare the results with the case of (S=frac{1}{2}) in our previous stochastic series expansion quantum Monte Carlo study.

Small gantries and long, thin scintillation pixels are used in preclinical positron emission tomography, resulting in parallax errors outside the system’s field of view. To solve this problem, a detector for measuring the depth of interaction (DOI) was developed. In addition, conduct of research on methods for DOI measurement through deep learning is underway. In this study, we designed a detector for measurement of DOI, consisting of two layers of scintillation pixel arrays and developed a method for specifying 3-dimensional (3D) position through deep learning. DETECT2000 simulation was performed to assess the 3D-positioning accuracy of the designed detector. Data acquired through DETECT2000 simulation wereused for learning a deep learning model, and assessment of location specification accuracy was performed using data generated at a new location and the deep learning model. According to the result, the 3D-position measurement accuracy was calculated as 94.48% on average.

We investigate a novel covariant matrix adaption-evolution strategy (CMA-ES)-based method proposed for extracting channel phase information by measuring a two-dimensional (2D) target intensity image (2D-TII) of a coherent beam combining (CBC) system both numerically and experimentally for the first time to the best of our knowledge. The proposed method was first investigated on 1,000 samples of 2D-TIIs numerically generated by a virtual 3-channel CBC system. For all samples, the channel phase information was extracted almost perfectly, with the inter-image correlation coefficient reaching or exceeding 0.99 and the overall root-mean-square phase error of 0.0735 rad within 17 iterations of the algorithm, for example. Next, the investigation was extended onto another 1,000 samples of 2D-TIIs experimentally measured with a real-world 3-channel CBC setup via a charge-coupled device (CCD) camera at a rate of 16 fps with an exposure time of 10 ms. The channel phase information was extracted with the inter-image correlation coefficient reaching or exceeding 0.9 for 972 or 979 samples within 15 or 45 iterations of the algorithm, respectively, with the latter case of which its overall average was estimated at 0.947. The relatively low performance of the proposed method within 21 out of 1,000 samples, where the overall average of the inter-image correlation coefficient remained at 0.880 regardless of further increases in the number of iterations, was attributed to the lowered image contrasts of the measured 2D-TIIs caused by the uncontrolled intrusion of external noise components that could not be rectified by the CCD camera due to its limited exposure time. We expect the proposed method to be useful for research and analysis on a variety of real-world CBC systems as well as other related applications where phase information needs to be extracted.

It is difficult to calculate monitor units in the proton treatment planning system due to the complexity of using this system in the double scattering mode of proton therapy. Moreover, the range and spread-out Bragg peak (SOBP) values using the conversion algorithm (CONVALGO) provided by IBA (({C}_{{text{range}}}), ({C}_{{text{SOBP}}})) are different from the actual measured range (({M}_{{text{range}}})) and SOBP (({M}_{{text{SOBP}}})) values. In this regard, the CONVALGO (FC) value (({FC}_{{text{range}}}), ({FC}_{{text{SOBP}}})) should be measured according to the quality assurance (QA) of patient treatment, which requires physical effort and time. This study, therefore, aimed to reduce the time and effort spent on QA. The predictive model was trained using six parameters. Main option, sub-option, ({M}_{{text{range}}}) and ({M}_{{text{SOBP}}}) were used as input values, and ({FC}_{{text{range}}}) and ({FC}_{{text{SOBP}}}) were used as label. The trained model predicted the CONVALGO (PC) values of ({PC}_{{text{range}}}) and ({PC}_{{text{SOBP}}}). The test dataset has 261 patient data that were not used for training. Difference, mean absolute error (MAE), and root mean square error (RMSE) values were used for comparison. Compared to the FC value, the maximum difference was − 2.2 mm for ({PC}_{{text{range}}}) and − 3.4 mm for ({C}_{{text{range}}}). The acceptable standard of patient QA in our institute is within 1 mm and the number of data points that met the acceptable standard was 196 for ({PC}_{{text{range}}}) and 191 for ({C}_{{text{range}}}). For the MAE of ({PC}_{{text{SOBP}}}), options 1, 2, and 3 showed values within 1 mm. In the MAE of ({C}_{{text{SOBP}}}), the values were > 1 mm for all options.