bluuebunny/crossref_metadata_2025_split huggingface dataset:
N-photon bundles emission in high-spin Jaynes–Cummings model
Authors: Wei Huanhuan , Tang Jing , Deng Yuangang 
Published: December 2024

Abstract
High-spin quantum systems, endowed with rich internal degrees of freedom, constitute a promising platform for manipulating high-quality n-photon states. In this study, we explore n-photon bundles emission by constructing a high-spin Jaynes–Cummings model within a single-mode cavity interacting with a single spin-

3

/

2

atom. Our analysis reveals that the n-photon dressed state splittings can be significantly enhanced by adjusting the linear Zeeman shift inherent to the internal degrees of freedom in high-spin systems, thereby yielding well-resolved n-photon resonance. The markedly enhanced energy-spectrum anharmonicity, stemming from strong nonlinearities, enables the realization of high-quality n-photon bundles emission with large steady-state photon numbers, in contrast to conventional spin-1/2 JCM setups. Of particular interest is the realization of an optical multimode transducer capable of transitioning among single-photon blockade, two- to four-photon bundles emission, and photon-induced tunneling by tuning the light-cavity detuning in the presence of both cavity and atomic pump fields. This work unveils significant opportunities for diverse applications in nonclassical all-optical switching and high-quality multiphoton sources, deepening our understanding of creating specialized nonclassical states and fundamental physics in high-spin atom-cavity systems.
Dynamics of non-Hermitian Floquet Wannier–Stark system
Authors: Zhang H P , Zhang K L , Song Z 
Published: December 2024

Abstract
We study the dynamics of the non-Hermitian Floquet Wannier–Stark system in the framework of the tight-binding approximation, where the hopping strength is a periodic function of time with Floquet frequency

ω

. It is shown that the energy level of the instantaneous Hamiltonian is still equally spaced and independent of time t and the Hermiticity of the hopping term. In the case of off resonance, the dynamics are still periodic, while the occupied energy levels spread out at the resonance, exhibiting t

z
behavior. Analytical analysis and numerical simulation show that the level-spreading dynamics for real and complex hopping strengths exhibit distinct behaviors and are well described by the dynamical exponents z = 1 and

z
=
1

/

2

, respectively.
Radiative Transfer Modeling of Haumea’s Dust Ring
Authors: Kalup Csilla , Molnár László , Kiss Csaba 
Published: December 2024

Abstract
Among the growing number of small body rings in the solar system, the ring of Haumea has a special status as it is likely suitable for direct imaging in the visible and submillimeter wavelengths. In this paper, we highlight its sole detectability among Centaur/Trans-Neptunian Object rings using both the Atacama Large Millimeter/submillimeter Array and the James Webb Space Telescope to provide direct constraints on the ring composition for the first time. To overcome the limitations of the currently used simple ring models, we introduce radiative transfer modeling for small body ring systems. Here we perform a thorough analysis of the Haumea ring considering different materials and grain sizes, assuming that the ring consists of small particles with sizes below 1 mm. We present spectral energy distributions of each model for future comparison with multiwavelength measurements, providing a diagnostic tool to determine the dominant grain size and characteristic material of the ring, which are essential inputs for ring formation and evolution theories. Our results also show that for some sub-micron carbon-like or silicate grains, their mid-infrared excess can be detected even if the ring is not resolved, providing a tracer for small grains around the object.
Quantifying the memory and dynamical stability of magnetar bursts*
Authors: Sang 桑 Yu 语 , Lin 林 Hai-Nan 海南 
Published: December 2024

Abstract
The time series of energy and waiting time in magnetar bursts carry important information about the source activity. In this study, we investigate the memory and dynamical stability of magnetar bursts from four soft gamma repeater (SGR) sources: SGR 1806−20, SGR 1900+14, SGR J1935+2154, and SGR J1550−5418. Based on the rescaled range analysis, we quantify the memory in magnetar bursts for the first time and find that there exists long-term memory in the time series of both waiting time and energy. We investigate the dynamical stability in the context of randomness and chaos. For all four SGR samples, we find that the waiting time is not completely random; however, the energy of two SGRs is consistent with a total random organization. Furthermore, both waiting time and energy exhibit weak chaos. We also find no significant difference between SGRs and repeating fast radio bursts (FRBs) in the randomness-chaos phase space. The statistical similarity between SGRs and repeating FRBs hints that there may be potential physical connection between these two phenomena.
New Orbital Parameters of 850 Wide Visual Binary Stars and Their Statistical Properties
Authors: Izmailov Igor , Khovritchev Maxim 
Published: December 2024

Abstract
Based on positional observations and measurements of radial velocities, the orbits of 850 wide visual binary stars have been determined. The parameters of the log-normal distributions for the histograms of orbital periods, stellar masses, and semimajor axes in astronomical units have been obtained. The eccentricity histogram for binary stars with orbital periods less than 400 yr follows a normal distribution centered at e = 0.545 +/− 0.029. For stars with longer periods, this distribution obeys the law f = 2e, with accuracy to errors. The mass-to-luminosity relation for stars with well-determined masses is given by:

log

L

⊙

=

4.33
log

M

⊙

−
0.11

, where L
⊙ and

M

⊙

are the luminosity and mass of the star in units of the solar luminosity and mass, respectively.
Electrical Detection of Groundwater Leakage Channels by Spread Spectrum Induced Polarization (SSIP) Geophysical Method, Guizhou, China
Authors: Ahmed Ijaz , Rujun Chen , Shuang Cheng , Ali Shah Shahid 
Published: December 2024

Abstract
An essential resource, groundwater is necessary for the maintenance of human activity, agriculture, and ecosystems. Finding the sources of groundwater leaks is crucial for effective water management and the avoidance of any environmental risks. In the karst region of Fuquan, Guizhou, China, the use of Spread Spectrum Induced Polarization (SSIP) as an innovative technique for locating groundwater leakage channels is the main topic of this research. Four lines of survey were carried out in the study’s targeted region. The results of SSIP were very positive since they showed notable abnormalities in the ground that may be signs of groundwater leaks. The drilling results obtained from Well ZK02 have served to enhance the credibility and reliability of our research. The study’s results demonstrate how well SSIP works as a cutting-edge technique for locating groundwater leakage pathways in karst regions. To maintain the integrity of the ecosystem and optimize the management of water resources, it is essential to identify and mitigate these channels. This study adds to the expanding corpus of information on methods for detecting groundwater and offers insightful information for further investigation in comparable geological settings.
Shallow Subsurface Detection with the Resonance Characteristics of Ambient Noise Recording
Authors: Wang Guanchao , Zhao Guangmao , Niu Yongxiao , Chen Chengshen , Li Guohe , Li Peng 
Published: December 2024

Abstract
Imaging near-surface structures, such as voids, tunnels, or high-contrast anomalies, is an essential and critical task in urban area underground engineering projects; the required accuracy is within a few meters vertically and horizontally, which poses considerable challenges to geophysical surveys in shallow subsurface detection. Geophysical methods like seismic are great tools for subsurface exploration with high resolution. Currently, since explosive sources are prohibited in urban areas, passive seismic methods that record the constant vibration signals generated by natural and human activities have become more desirable. Thus, this abstract presents a novel non-destructive geophysical approach using ambient noise recording, namely seismo-acoustic resonance imaging. This approach is mainly based on the analysis of the resonance frequencies content information within the data, related to the mechanical properties of structures under investigation. These resonance frequencies will then be translated into depth-domain images using a kind of layer-stripping strategy; Further, the images are combined with results of other geophysical methods (GRP, surface wave analysis, autocorrelation, etc.) for necessary interpretation. In practice, as a low-cost single-station geophysical technique, resonance imaging is readily applicable to a broad range of scales, which meets the need for spatial suitability, and efficiency in engineering investigations. Two examples are presented in the paper, as the first is elaborated on a known metro tunnel, and the second is demonstrated in an unknown investigation site. The results of two experiments have shown resonance imaging to be very well adapted for shallow subsurface detection.
Automated Traffic Signal Recognition in Distributed Acoustic Sensing Data via Deep Learning
Authors: Zhang Zhiyu , Li Jing , Xiong Hongqiang , Sun Jiaxin 
Published: December 2024

Abstract
Distributed Acoustic Sensing (DAS), an advanced vibration-sensing technology, shows immense promise for data-centric urban surveillance, notably in tracking vehicle speeds. The extraction of vehicle information from DAS data demands real-time processing. Nonetheless, current techniques face challenges in the precise and automated interpretation of vehicle signals. This study presents an integrated two-phase deep learning framework meticulously designed to facilitate the real-time and automated detection of vehicle speeds and directions using Distributed Acoustic Sensing (DAS) data. Initially, the approach employs a contrastive learning-based model to process DAS signals, eliminating disturbances within the profile. The YOLOv8 detection model subsequently accurately detects the processed DAS signals. The vehicle’s speed and direction are ultimately ascertained by harnessing the positional data derived from the bounding box’s coordinates. Within real-world test scenarios, the method introduced can precisely identify vehicles originating from various directions and sources. The strategy demonstrates robust generalizability even in complex scenarios characterized by intense interference and the presence of multiple vehicles. From a quantitative assessment perspective, the system processes DAS data for 60-second intervals in an average of 4.89 seconds, achieving an accuracy rate of 90.07%, which satisfies the demands for real-time vehicle signal detection. The approach presented in this article offers crucial guidance for the real-time, automatic detection of vehicle signals in DAS systems.
Research on Airborne Gamma-ray Spectrometry Survey with Combined Detectors of NaI (Tl) and CeBr3
Authors: Mi Y H , Xu J C , Jiang Z X , Lin T , Li X S , Xiao G Y 
Published: December 2024

Abstract
Airborne gamma-ray spectrometry plays an important role in various fields. The airborne gamma-ray spectrometry system with combined detectors of NaI(Tl) scintillator and CeBr3 scintillator shows dual advantages of large volume with high detection efficiency and better energy resolution. The fusion of spectra data from the two types of detectors achieves high signal-to-noise ratio detection of characteristic peaks, improving the accuracy of nuclide content measurement. The effect has been verified through preliminary testing.
Application of spectral energy algorithm based on the GPR reflected wave for detecting underground area
Authors: Yaohua Li , Huanlin He , Jun Dai , Zhen Gao , Xinyue Tian , Qiang Dai 
Published: December 2024

Abstract
The surface subsidence and collapse which caused by abandoned and remnant underground area affects engineering construction seriously. In order to avoid disaster caused by ground collapse, it is obviously important to find out the depth and distribution range about underground area. Ground Penetrating Radar (GPR) is as a fast and non-destructive detecting technology, and the unshielded antenna with low frequency had been used to detect the shallow underground area which can be distinguished from the underground area with larger-scale and significant differences, but conventional data processing method is difficult to identify the weak useful signal, and also will cause uncertainty for abnormal interpretation. Based on the unique feature of spectral response for the single medium, spectral energy algorithm has been used for processing data about GPR reflected wave in this article. The spectral response feature of air medium has been extract from the signal of radar reflected wave, the spectral energy strength about air medium has been calculated, and the feature of space distribution about underground area has been inversed by three-dimensional reconstruction. The results are basically consistent with this method through validating by high-density resistivity method, and prove that this data processing technology is effective and precise. It provides scientific basis for the construction engineering to implement successfully.
Application of Electrical Resistivity Tomography for underground box culvert detection
Authors: Zhang Zhengtao , Huang Zhaohui , Yang Yunfei , Tian Ying 
Published: December 2024

Abstract
The detection of underground box culverts is a crucial aspect in the process of urban planning and development. Based on the specific geological conditions encountered during underground box culvert surveys in particular cities, a geoelectric model is constructed. Utilizing the RES2DINV and RES2DMOD software from Electrical Resistivity Tomography, we carry out forward and inverse calculations for underground box culverts under conditions of either high or low resistivity, employing a dipole-dipole array. This study summarizes the resistivity characteristics of box culverts and, ultimately, Analysis of Dipole-Dipole Array Response Characteristics for Box Culvert Detection Targets in High and Low Resistivity Environments Formed Under Different Moisture Conditions.
Evaluation and monitoring of offshore CO2 storage using marine electromagnetic sounding
Authors: Qiu Ning , Pan Chunwu , Liu Bin , Sun Zhen , Li Pengchun 
Published: December 2024

Abstract
The storage of offshore carbon dioxide (CO2) is seen as an effective way to reduce greenhouse gas emissions. Submarine sediments offer a large volume and adequate permeability for the long-term injection of CO2 at high pressure and low temperature. The selection and monitoring of offshore CO2 storage sites have a significant impact on their stability and safety. Therefore, accurately identifying the distribution of offshore CO2 storage is crucial for monitoring. This study utilizes marine controllable source electromagnetic sounding (CSEM) to investigate the sensitivity of identifying plume transport distributions in offshore CO2 storage monitoring. The results show that CSEM is effective in monitoring the distribution of CO2 plumes during offshore storage processes. The changes in electromagnetic field response can reflect the distribution of CO2 plumes, providing important basis for the stability and safety of offshore CO2 storage site selection and monitoring.
Investigating the Time-Frequency Electromagnetic Method for Detecting Deep Karst Geothermal Reservoirs in Tianjin
Authors: Zhengpu Cheng , Ming Lei , Shu Li , Sheng Lian , Qiang Wei 
Published: December 2024

Abstract
Tianjin, renowned for its geothermal wealth, features the Wumishan Formation of the Jixian System as its principal geothermal reservoir, exemplifying a classic carbonate reservoir. Aiming to delineate the stratigraphic structure and uncover concealed faults beneath Dongli Lake’s 5-kilometer depth in Tianjin, while also pinpointing the spatial distribution and structural attributes of the primary deep thermal reservoirs to forecast potential geothermal zones, the authors have innovatively adapted the time-frequency electromagnetic method—traditionally employed in deep oil and gas exploration—for the deep geothermal investigation of Dongli Lake. This approach involved meticulous data acquisition, sophisticated processing, and resistivity inversion techniques. Utilizing seismic and borehole data, the horizon was calibrated to provide a nuanced portrayal of the subsurface structure. The study postulates the existence of seven concealed faults, characterized as NNE and NWW-oriented tensional normal faults. Notably, the Cangdong Fault (F1), serving as a critical conduit for the area’s principal thermal fluids, is implicated in heat conduction, storage, and the modulation of geothermal anomaly zones’ distribution and configuration. The Wumishan Formation’s thermal reservoir predominantly lies to the west of the Cangdong fault, with the top interface buried at depths ranging from −2200 to −2400 meters, exhibiting a progressive increase in resistivity, indicative of continuous A-type electrical properties. The karst fissures within the third and fourth sections, when well-developed, lead to localized low resistivity anomalies and H-type electrical signatures due to the accumulation of hot water, thereby highlighting the prospective geothermal zones at targeted depths. This paper delineates four such favorable areas, offering vital foundational data and support for the future development and exploitation of these geothermal resources.
Research on the Application of Transient Electromagnetic Exploration in Coal Mine Water Disaster Prevention and Control
Authors: Chengshuai Li , Han Lu , Zhanli Zhang , Qingyang Zhang , Qianqian Duan , Teng Zhang , Mingxia Zhou 
Published: December 2024

Abstract
The geophysical exploration of mines mainly involves advanced detection to delineate areas with abnormal water content for the prevention and drainage of hydrogeological disasters in coal mines. In this study, transient electromagnetic method was used for the detection of coal mine working faces. After the coal mine working face is connected, “geophysical exploration and drilling” work must be carried out before backfilling. After the transient electromagnetic data of geophysical exploration is collected, the basic result map is formed through data processing. Combined with professional mapping processing software Voxler, the software performs 3D visualization processing, which can display detection results more intuitively and stereoscopically, making it easy to analyze and interpret anomalies in space, and achieving good application results.
Seismic monitoring technology of driving and detection integrated of coal mine roadway
Authors: Li Shenglin , Zhang Pingsong , Hu Xiongwu , Wu Rongxin , Guo Liquan 
Published: December 2024

Abstract
Hidden geological features, such as water and gas, cause frequent accidents during coal mine roadway driving. Seismic monitoring technology of driving and detection integrated presents distinct advantages and is a geological guarantee technology urgently needed for intelligent driving of roadways. The success of this technology hinges on the high-resolution signals impulse processing and high-precision imaging. This article employs a seismic while driving field test during coal roadway driving to validate the efficacy of the proposed impulse algorithm and its full waveform inversion method. The inversion results demonstrate that these methods effectively process seismic signals while driving. With a limited detection signals, the distribution characteristics of rock properties in front of the driving can be reliably inverted, enabling the precise identification of abnormal structures. This capability furnishes valuable geological information for roadway driving, thereby enhancing construction safety.
Identification of abnormal operation of electric energy metering equipment based on multi-dimensional and multi-layer association rule mining algorithm
Authors: Sun Jianfeng , Gao Yang , Long Cunyu , Hua Shubei 
Published: December 2024

Abstract
In order to comprehensively and deeply explore the potential correlations and patterns in operational data, this paper proposes a method for identifying abnormal operation of electric energy metering equipment based on multi-dimensional and multi-layer association rule mining algorithms. A multi-level association rule mining model has been constructed to automatically discover potential correlations and abnormal patterns between different indicators, thereby accurately identifying abnormal operation of energy metering equipment. The raw running data is converted into a form suitable for association rule mining, and evaluation metrics such as support and confidence are calculated for each rule. Abnormal operation of energy metering equipment is identified based on these evaluation indicators. The experimental results show that it can effectively identify the abnormal operation of energy metering equipment, providing strong technical support for equipment maintenance and troubleshooting of power companies.
Quantity bidding strategy of inter-provincial and intra-provincial two-level peak regulation market of coal-fired units considering prediction error
Authors: Gao Weiheng , Luan Xichen , Li Jinchang , Wang Zhengfeng 
Published: December 2024

Abstract
Under the background of the ‘carbon peaking and carbon neutrality’ target, the proportion of new energy installed capacity has been greatly increased. The problem of wind and photovoltaic power abandonment has become more and more serious. In the construction of inter-provincial and intra-provincial multi-level electricity markets, it is urgent to establish a source-network coordination mechanism and tap new consumption capacity to adapt to the rapid development of new energy. This paper first sorts out the joint operation process of the inter-provincial and intra-provincial two-level electric energy market and the peak regulation market. Then, with the goal of minimizing the total cost of the inter-provincial peak regulation market and provincial joint market, a collaborative optimization model of inter-provincial and intra-provincial peak regulation quantity bidding strategy is established. The expected scenario generation method considering prediction error is proposed. The collaborative optimization solution process is explained. Finally, the proposed model is simulated to verify the effectiveness of the collaborative optimization of inter-provincial and intra-provincial peak load regulation.
Design and kinematics simulation of tower climbing robot
Authors: Jiang Dongqing , Li Sanyan , Liu Ying 
Published: December 2024

Abstract
To solve the task of auxiliary maintenance of the electric power overhead tower, this team designed a 6-DOF inchworm bionic robot and completed the overall structural design of the robot. Then ADAMS was used to carry out the kinematic analysis of the inchworm robot in the two working conditions of linear climbing and crossing the tower node. The results showed that the motion design of the robot was reasonable, and the feasibility of the structural design was further verified, which provided a reference for the motion control of the robot. Finally, the team made a test prototype and completed the posture and working conditions of the robot such as shrinking, stretching, incline climbing, and upside-down climbing. The experimental results show that the bionic robot has stable performance, which further verifies the correctness of the structural design and the feasibility of the motion mode of the Inchworm robot.