bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning the in-medium correction factor on nucleon–nucleon elastic cross section
Authors: Wei Guojun , Li Pengcheng , Wang Yongjia , Li Qingfeng , Liu Fuhu 
Published: November 2024

Abstract
The nuclear equation of state cannot be directly measured in the heavy-ion collision experiments; it is usually inferred from the comparison between transport model simulations and experimental measurements. The in-medium correction factor (F, which is defined as the ratio of the cross section in the nuclear medium to that in free space) on the nucleon–nucleon elastic cross section is one of the important inputs of the transport model, and its magnitude is still debated. The advent of machine learning (ML) has profoundly influenced the way scientists study the natural world and has provided a new paradigm that merges traditional investigation with advanced data-driven techniques. The aim of this work is to present a ML-based method to study the in-medium correction factor F. The ultra-relativistic quantum molecular dynamics (UrQMD) transport model is used to simulate

132

Sn

+

124

Sn

collisions at beam energy of 0.27 GeV/nucleon with different impact parameters. The value of F is randomly selected from 0.4 to 0.8 for the simulation of each event. Several observables simulated by the UrQMD model with different F, which are thought to be probably sensitive to the in-medium nucleon–nucleon cross sections, are fed into the LightGBM (Light Gradient Boosting Machine, which is a modern decision tree-based ML algorithm) to establish the mapping between the observables and F. The mean absolute error (MAE), which is the absolute difference between the true and the predicted F, is about 0.080 and 0.021 by using event-by-event and 40-event summed observables, respectively. It indicates that ML can recognize information about the F factor. Furthermore, according to the results of Shapley Additive exPlanations, an interpretability analysis method in ML, features that have the greatest effect on the F are identified. ML combined with the transport model may open a new venue to study the F factor. In addition, the interpretability analysis of the ML algorithm may also offer valuable insights for subsequent research.
α-decays of even–even actinides and superheavy nuclei to the first rotational 2+ states of daughter nuclei
Authors: Seif W M , Adamian G G , Antonenko N V , Abdulghany A R , Nasr A 
Published: November 2024

Abstract
The alpha-decays of even–even isotopes of actinides and superheavy nuclei to the ground 0+ and first 2+ states of their daughter nuclei are studied. The conditions for the maximum intensity of alpha-decay from the ground state to the lowest 2+ state are analyzed in detail based on existing experimental data. The decays to the first 2+ states reach their maximum intensity relative to those to corresponding ground states of daughter nuclei at N

D
= 136, due to the corresponding increasing Q

α
(2+). This correlates with relatively strong negative octupole deformation of daughter nucleus and is also accompanied by decreasing E(2+). For the alpha-decays of heavy nuclei up to Og, the half-lives and population probabilities of the 0+ and 2+ states of the daughter nucleus are described and predicted employing the preformed cluster model.
Radiation in the coffee cup
Authors: Ferreira João Paulo M 
Published: November 2024

Abstract
It is commonly assumed that radiative heat transfer only plays a relevant role in situations involving temperatures of several hundred degrees Celsius and above. Other common misconceptions relate to the cooling of metallic vs non-metallic objects, and the effect of their colour. A series of alternative demonstrations that counteract these beliefs and show the role played by radiation in the cooling of common tableware containing hot liquids are described here. The experiments require basic equipment, easily available even at home. The cooling curves obtained can be modelled with Newton´s law of cooling and the corresponding heat transfer coefficients estimated. The results elucidate the influence of surface emissivity on radiative heat transfer, and that this mechanism has a non-minor share on cooling processes even at temperatures below the normal boiling point of water. A final demonstration concerns heating of the same systems and corroborates the previous conclusions.
Many-body localization in the age of classical computing*
Authors: Sierant Piotr , Lewenstein Maciej , Scardicchio Antonello , Vidmar Lev , Zakrzewski Jakub 
Published: November 2024

Abstract
Statistical mechanics provides a framework for describing the physics of large, complex many-body systems using only a few macroscopic parameters to determine the state of the system. For isolated quantum many-body systems, such a description is achieved via the eigenstate thermalization hypothesis (ETH), which links thermalization, ergodicity and quantum chaotic behavior. However, tendency towards thermalization is not observed at finite system sizes and evolution times in a robust many-body localization (MBL) regime found numerically and experimentally in the dynamics of interacting many-body systems at strong disorder. Although the phenomenology of the MBL regime is well-established, the central question remains unanswered: under what conditions does the MBL regime give rise to an MBL phase, in which the thermalization does not occur even in the asymptotic limit of infinite system size and evolution time? This review focuses on recent numerical investigations aiming to clarify the status of the MBL phase, and it establishes the critical open questions about the dynamics of disordered many-body systems. The last decades of research have brought an unprecedented new variety of tools and indicators to study the breakdown of ergodicity, ranging from spectral and wave function measures, matrix elements of observables, through quantities probing unitary quantum dynamics, to transport and quantum information measures. We give a comprehensive overview of these approaches and attempt to provide a unified understanding of their main features. We emphasize general trends towards ergodicity with increasing length and time scales, which exclude naive single-parameter scaling hypothesis, necessitate the use of more refined scaling procedures, and prevent unambiguous extrapolations of numerical results to the asymptotic limit. Providing a concise description of numerical methods for studying ETH and MBL, we explore various approaches to tackle the question of the MBL phase. Persistent finite size drifts towards ergodicity consistently emerge in quantities derived from eigenvalues and eigenvectors of disordered many-body systems. The drifts are related to continuous inching towards ergodicity and non-vanishing transport observed in the dynamics of many-body systems, even at strong disorder. These phenomena impede the understanding of microscopic processes at the ETH-MBL crossover. Nevertheless, the abrupt slowdown of dynamics with increasing disorder strength provides premises suggesting the proximity of the MBL phase. This review concludes that the questions about thermalization and its failure in disordered many-body systems remain a captivating area open for further explorations.
Method for identifying damage to stay cables based on local beam deflection
Authors: Yang Yanxiao , Su Mubiao , Li Wenping 
Published: November 2024

Abstract
In this study, for the problem of difficulty in identifying the damage of diagonal cable using the overall beam deflection, a method of identifying the cable based on the flexibility matrix of local beam segments is proposed. The range of influence of cable damage on the deflection of beams under self-weight is investigated and analysed using the finite element method , and the results show that the damage of cables mainly affects the deflection in their vicinity, while the change of deflection at other locations is minimal; with the change of the location of damaged cables, the influence of the range also changes accordingly. Building on this, the relationship between the difference in deflection of local beams and the change in cable force before and after the cable damage is deduced by combining with the principle of structural mechanics, and the damage index

∆
F

is proposed, and the validity of the method is confirmed by experiments. The experimental results indicate that the deflection of the local beam can be utilized to assess the change in cable force, allowing for the identification of the damaged cable’s location, specifically where the change in cable force is negative. The method is highly resistant to interference. The method can quickly and accurately locate the damaged cable.
Reassessment of 3D synchro-resonant detector for high-frequency gravitational waves
Authors: Woods R C 
Published: November 2024

Abstract
Previously reported results for a gravity wave detector regarding photon generation arising from the interaction between an incident high-frequency gravitational wave, a locally-generated Gaussian electromagnetic beam, and a local steady magnetic field, are reassessed using symmetry and a rigorous interpretation of Poynting’s theorem. The conclusions are that transverse photon generation in this geometry is impossible, and that wave impedance cannot be used as the basis for distinguishing weak photon generation from other spuriae.
Interpolating supersymmetric pair of Fokker-Planck equations
Authors: Ho Choon-Lin 
Published: November 2024

Abstract
We consider Fokker-Planck equations that interpolate a pair of supersymmetrically related Fokker-Planck equations with constant diffusion coefficients. Based on the interesting property of shape-invariance, various one-parameter interpolations of the solutions of the supersymmetric pair of Fokker-Planck systems can be directly constructed.
Tailoring masses to artificial molecules based on the shape of their wavefunctions
Authors: Shushi Tomer 
Published: November 2024

Abstract
In this short paper, we examine artificial molecules composed of coupled artificial atoms such as quantum dots. Similar to artificial atoms, which have position-dependent effective masses for electrons, artificial molecules exhibit this characteristic while comprising more than one artificial atom. While in the literature, such artificial molecules are focused on the kinetic term of the electrons in such a setup, we consider the full description that includes the kinetic and potential terms that involve the nuclei. The proposed artificial molecules consist of nuclei and electrons coupled through Coulomb potentials and kinetic energy influenced by electronic position-dependent effective masses that also depend on the positions of the nuclei and the other electrons in the system. We demonstrate how the Schrödinger equation for such systems can be solved by assuming the entire shape of the molecular wavefunction, guided by a tailored non-parabolic energy-momentum relation for at least one electron within the molecular structure. Additionally, we show that instead of pre-specifying the entire form of the molecular wavefunction, we can consider the coupling between the electrons and nuclei to obtain the wavefunction of the system.
Development and investigation of DMDG-MOSFET biosensor for charged biomolecule detection
Authors: Das Satish Kumar , Biswal Sudhansu M , Giri LalatIndu , Pahi Ipsita , Nanda Umakanta 
Published: November 2024

Abstract
The paper explores the analog and sensitivity parameter of a n-channel gate stack Dual Material Double Gate (DMDG) MOSFET biosensor, specifically focusing on its response to a wide range of charged biomolecule introduced into its cavity region. This novel structure offers improved sensitivity and selectivity due to its ability to modulate the threshold voltage and control the electrostatic environment more precisely compared to conventional MOSFET-based biosensors. The analysis includes a thorough examination of the surface potential, electric field, transconductance, and threshold voltage variations influenced by the presence of charged biomolecules. By applying a parabolic-potential technique to solve the 2D Poisson’s equation, the expression for surface potential can be found. The minimal surface potential model is used to calculate the threshold voltage. Using SILVACO ATLAS, the simulation findings suggest that the proposed gate stack DMDG-MOSFET structure demonstrates sensitivity of 0.123 V and 0.607 V for neutral and charged biomolecules respectively emphasizing the impact of gate material engineering on the biosensor’s performance.
Chaos suppression of a Seven-dimensional power system based on the predefined-time sliding mode control method
Authors: Fang Jie , Zhang Shaohui , Wu Yang , Zhao Kaihui 
Published: November 2024

Abstract
To suppress chaotic oscillation in the seven-dimensional power system model, the predefined-time sliding mode control of disturbed seven-dimensional chaotic power system is studied in this paper. Firstly, the dynamic characteristics of the seven-dimensional power system are analyzed, and the existence of chaotic attractors is demonstrated. Then, the seven-dimensional power system is divided into three subsystems according to control outputs, and the chaotic control of the seven-dimensional power system is decomposed into the control problem of three subsystems. For each subsystem, a predefined-time sliding mode controller is designed to regulate the system states converge to the desired values. Compared with other existing control methods, the proposed predefined-time sliding mode controller can control the chaotic power system to the expected states at any predefined time. The minimum upper bound of the convergence time is determined by the adjustable parameters of this controller, which make it meet the control requirements conveniently. Finally, the effective and excellent control performance of the predefined-time control scheme is proved by numerical simulation.
Multi-stability and dynamical analysis of Zhanbota-IIA equation with couple of integrating architectures
Authors: Rashid Butt Asma , Farooq Fozia Bashir , Abbas Hafsa , Alqahtani Nouf Abdulrahman , Imran Muhammad , Bekir Ahmet 
Published: November 2024

Abstract
This research delves into exploring the Zhanbota-IIA equation, which has applications in medical imaging and diagnostics, power systems, and fuzzy logic processing. This study employs two analytical techniques, namely the variational method that emerges from the variational principle and the improved Cham method, to find various types of exact traveling wave solutions. These algorithms yield periodic, dark, singular, and bright soliton solutions as well as combinations of these forms Appropriate parametric values are chosen to make 2D and 3D plots to illustrate how the retrieved solutions behave. Chaotic phenomena are analyzed using different initial conditions and constant parameters through multi-stability analysis. The extracted results illustrate the efficiency of the outlined techniques in resolving exact solutions in nonlinear areas.
Implication of nano-Hertz stochastic gravitational wave background on ultralight axion particles
Authors: Yang Jing , Xie Ning , Huang Fa Peng 
Published: November 2024

Abstract
Recently, the Hellings Downs correlation has been observed by different pulsar timing array (PTA) collaborations, such as NANOGrav, European PTA, Parkes PTA, and Chinese PTA.
These PTA measurements of the most precise pulsars within the Milky Way show the first evidence for the stochastic gravitational wave background of our Universe.
We study the ultralight axion interpretation of the new discovery by investigating the gravitational wave from axion transitions
between different energy levels of the gravitational atoms, which are composed of cosmic populated Kerr black holes and their surrounding axion clouds formed through the superradiant process.
By Bayesian analysis,
we demonstrate that
this new observation naturally admits an ultralight axion interpretation around 10-21 eV, which
is consistent in magnitude with the typical mass of fuzzy dark matter.
Dark matter (h)eats young planets
Authors: Croon Djuna , Smirnov Juri 
Published: November 2024

Abstract
We study the effect of dark matter annihilation on the formation of Jovian planets. We
show that dark matter heat injections can slow or halt Kelvin-Helmholtz contraction, preventing
the accretion of hydrogen and helium onto the solid core. The existence of Jupiter in our solar
system can therefore be used to infer constraints on dark matter with relatively strong
interaction cross sections. We derive novel constraints on the cross section for both
spin-dependent and spin-independent dark matter. We highlight the possibility of a positive
detection using future observations by JWST, which could reveal strongly varying planet
morpholoiges close to our Galactic Center.
Cryptanalysis and Improvement to the Quantum Private Query Protocol for Enhancing Database Privacy
Authors: Shen Zhengda , Shao Wenzhu , Li Zhigang , Peng Xiaoyu , Mu Nankun , Miraj Mahabubur Rahman , Liu Bin 
Published: November 2024

Abstract
In order to protect the privacy of query user and database, some QKD-based quantum private query (QPQ) protocols were proposed. One example is the protocol proposed by Zhou et al., in which the user makes initial quantum states and derives the key bit by comparing the initial quantum state and the outcome state returned from the database by ctrl or shift mode instead of announcing&#xD;two non-orthogonal qubits as others which may leak part secret information. In some extent, the security of the database and the privacy of the user are strengthened. Unfortunately, we find that in this protocol, the dishonest user can obtain, utilizing unambiguous state discrimination, much more database information than that is analyzed in Zhou et al.’s original research. To strengthen the database security, we improved the mentioned protocol by modifying the information returned by the database in various ways. The analysis indicates that the security of the improved protocols is greatly enhanced.
Sudden change of interferometric power for X-shape states
Authors: Zhu 朱 Dian 典 , Zhang 张 Fu-Lin 福林 , Chen 陈 Jing-Ling 景灵 
Published: November 2024

Abstract
Quantum interferometric power (IP), a discordlike measure, plays an important role in quantum metrology. We study the dynamics of IP for two-qubit X-shape states under different noisy environments. Our study shows that IP exhibits sudden change, and one side quantum channel is enough for the occurrence of a sudden change of IP. In particular, we show that the initial state having no sudden change of quantum discord exhibits a sudden change of IP under the dynamics of amplitude noise, but the converse is not true. Besides, we also investigate the dynamics of IP under two different kinds of composite noises. Our results also confirm that sudden change of IP occurs under such composite noises.
Critical station identification of metro networks based on the integrated topological-functional algorithm: A case study of Chengdu
Authors: Zeng 曾 Zi-Qiang 自强 , He 何 Sheng-Jie 圣洁 , Tian 田 Wang 旺 
Published: November 2024

Abstract
As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel integrated topological-functional (ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm under different conditions is validated. The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in the overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insight into urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience.
Improving subject transfer in EEG classification with divergence estimation
Authors: Smedemark-Margulies Niklas , Wang Ye , Koike-Akino Toshiaki , Liu Jing , Parsons Kieran , Bicer Yunus , Erdoğmuş Deniz 
Published: November 2024

Abstract

Objective. Classification models for electroencephalogram (EEG) data show a large decrease in performance when evaluated on unseen test subjects. We improve performance using new regularization techniques during model training. Approach. We propose several graphical models to describe an EEG classification task. From each model, we identify statistical relationships that should hold true in an idealized training scenario (with infinite data and a globally-optimal model) but that may not hold in practice. We design regularization penalties to enforce these relationships in two stages. First, we identify suitable proxy quantities (divergences such as Mutual Information and Wasserstein-1) that can be used to measure statistical independence and dependence relationships. Second, we provide algorithms to efficiently estimate these quantities during training using secondary neural network models. Main results. We conduct extensive computational experiments using a large benchmark EEG dataset, comparing our proposed techniques with a baseline method that uses an adversarial classifier. We first show the performance of each method across a wide range of hyperparameters, demonstrating that each method can be easily tuned to yield significant benefits over an unregularized model. We show that, using ideal hyperparameters for all methods, our first technique gives significantly better performance than the baseline regularization technique. We also show that, across hyperparameters, our second technique gives significantly more stable performance than the baseline. The proposed methods require only a small computational cost at training time that is equivalent to the cost of the baseline. Significance. The high variability in signal distribution between subjects means that typical approaches to EEG signal modeling often require time-intensive calibration for each user, and even re-calibration before every use. By improving the performance of population models in the most stringent case of zero-shot subject transfer, we may help reduce or eliminate the need for model calibration.