Table of contents

22 December 2025, Volume 35 Issue 1 Previous issue   

SPECIAL TOPIC — Biophysical circuits: Modeling & applications in neuroscience

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Energy adaptive regulation of a multifunctional neuron circuit Xi-kui Hu(胡锡奎), Juan Yang(杨娟), and Ping Zhou(周平) Chin. Phys. B, 2026, 35 (1):  010503.  DOI: 10.1088/1674-1056/ae1451 Abstract ( 11 )   PDF (3716KB) ( 3 )   This study constructs a dual-capacitor neuron circuit (connected via a memristor) integrated with a phototube and a thermistor to simulate the ability of biological neurons to simultaneously perceive light and thermal stimuli. The circuit model converts photothermal signals into electrical signals, and its dynamic behavior is described using dimensionless equations derived from Kirchhoff's laws. Based on Helmholtz's theorem, a pseudo-Hamiltonian energy function is introduced to characterize the system's energy metabolism. Furthermore, an adaptive control function is proposed to elucidate temperature-dependent firing mechanisms, in which temperature dynamics are regulated by pseudo-Hamiltonian energy. Numerical simulations using the fourth-order Runge—Kutta method, combined with bifurcation diagrams, Lyapunov exponent spectra, and phase portraits, reveal that parameters such as capacitance ratio, phototube voltage amplitude/frequency, temperature, and thermistor reference resistance significantly modulate neuronal firing patterns, inducing transitions between periodic and chaotic states. Periodic states typically exhibit higher average pseudo-Hamiltonian energy than chaotic states. Two-parameter analysis demonstrates that phototube voltage amplitude and temperature jointly govern firing modes, with chaotic behavior emerging within specific parameter ranges. Adaptive control studies show that gain/attenuation factors, energy thresholds, ceiling temperatures, and initial temperatures regulate the timing and magnitude of system temperature saturation. During both heating and cooling phases, temperature dynamics are tightly coupled with pseudo-Hamiltonian energy and neuronal firing activity. These findings validate the circuit's ability to simulate photothermal perception and adaptive temperature regulation, contributing to a deeper understanding of neuronal encoding mechanisms and multimodal sensory processing.

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Synchronization of neuromorphic memristive Josephson junction network and its application Dejun Yan(严德军), Fuqiang Wu(吴富强), and Wenshuai Wang(汪文帅) Chin. Phys. B, 2026, 35 (1):  010505.  DOI: 10.1088/1674-1056/ae1456 Abstract ( 7 )   PDF (29816KB) ( 5 )   Neuromorphic circuits based on superconducting tunnel junctions have attracted much attention due to their high-speed computing capabilities and low energy consumption. Josephson junction circuits can effectively mimic biological neural dynamics. Leveraging these advantages, we construct a Josephson junction neuron-like model with a phase-dependent dissipative current, referred to as a memristive current. The proposed memristive Josephson junction model exhibits complex dynamical behaviors. Furthermore, considering the effect of a fast-modulated synapse, we explore synchronization phenomena in coupled networks under varying coupling conductances and excitatory/inhibitory interactions. Finally, we extend the neuromorphic Josephson junction model—exhibiting complex dynamics—to the field of image encryption. These results not only enrich the understanding of the dynamical characteristics of memristive Josephson junctions but also provide a theoretical basis and technical support for the development of new neural networks and their applications in information security technology.

GENERAL

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Multiscale structural complexity analysis of the Chinese classics A Dream of Red Mansions and All Men Are Brothers Jing Feng(冯靖), Ping Wang(王萍), and Changgui Gu(顾长贵) Chin. Phys. B, 2026, 35 (1):  010506.  DOI: 10.1088/1674-1056/ae1fe9 Abstract ( 12 )   PDF (408KB) ( 2 )   Text, as a fundamental carrier of human language and culture, exhibits high structural and semantic complexity. Its systematic analysis is essential for understanding linguistic patterns and cultural transmission. A Dream of Red Mansions and All Men Are Brothers, two masterpieces of Chinese classical literature, have long been central to debates regarding the authorship of their later chapters. Previous studies, often based on word-frequency statistics, function word distributions, entropy measures, and complex network analyses, have provided valuable insights into stylistic differences; however, they remain limited in capturing cross-scale structural features. To address this gap, we apply a multi-scale structural complexity approach based on character-frequency time series to analyze the structural evolution of both novels under various segmentation strategies. Our results reveal significant differences in peak complexity positions, overall complexity levels, and intra-textual variations between the two works, which are closely linked to changes in authorship and stylistic patterns. This study not only provides new quantitative evidence for resolving authorship disputes in classical literature but also demonstrates, from the perspective of structural complexity, the profound depth and unique charm of Chinese literary expression, highlighting the richness of Chinese language and culture. Moreover, it emphasizes the potential of structural complexity analysis as a versatile tool for textual analysis and style attribution.

SPECIAL TOPIC — AI + Physical Science

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Structures and dynamics of helium in liquid lithium: A study by deep potential molecular dynamics Xinyu Zhu(朱新宇), Jianchuan Liu(刘建川), Tao Chen(陈涛), Xinyue Xie(谢炘玥), Jin Wang(王进), Yi Xie(谢懿), Chenxu Wang(王晨旭), and Mohan Chen(陈默涵) Chin. Phys. B, 2026, 35 (1):  013101.  DOI: 10.1088/1674-1056/ae15f1 Abstract ( 9 )   PDF (775KB) ( 0 )   Current experimental techniques still face challenges in clarifying the structural and dynamic properties of helium (He) in liquid lithium (Li). A critical example of this technical hurdle is the formation of He bubbles, which significantly affects the transport of He within liquid Li — a vital aspect when considering liquid Li as a plasma-facing material in nuclear fusion reactors. We develop a machine-learning-based deep potential (DP) with ab initio accuracy for the Li—He system and perform molecular dynamics simulations at temperatures ranging from 470 K to 1270 K with a wide range of He concentrations. We observe that He atoms exhibit a tendency to aggregate and form clusters and bubbles in liquid Li. Notably, He clusters exhibit a significant increase in size at elevated temperatures and high concentrations of He, accompanied by the phase separation of Li and He atoms. We also observe an anomalous non-linear relationship between the diffusion coefficient of He and temperature, which is attributed to the larger cluster size at higher temperatures. Our study provides a deeper understanding of the behavior of He in liquid Li and further supports the potential application of liquid Li under extreme conditions.

ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS

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Phase sensitivity of a lossy truncated SU(1,1) interferometer with double-port homodyne detection Yu-Wei Xiao(肖煜伟), Yue Ji(吉悦), Jia-Yi Wei(魏嘉怡), Jian-Dong Zhang(张建东), and Li-Li Hou(侯丽丽) Chin. Phys. B, 2026, 35 (1):  014205.  DOI: 10.1088/1674-1056/adfd46 Abstract ( 11 )   PDF (509KB) ( 2 )   We theoretically investigate the phase sensitivity of a truncated SU(1,1) interferometer fed with a two-mode coherent state and employing double-port homodyne detection. On the one hand, we analytically demonstrate that the two-mode coherent state provides better phase sensitivity than the single-mode coherent state. In addition, we show that the double-port homodyne detection is a quasi-optimal measurement. For a bright coherent-state input, the sensitivity of this scheme saturates the phase-sensitivity bound determined by the quantum Fisher information. On the other hand, we quantitatively illustrate the advantage of double-port homodyne detection over the single-port scheme under ideal conditions and in the presence of photon loss, respectively. Furthermore, our analysis indicates that the scheme we propose is robust against photon loss.

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Steady-state fretting response governed by periodic stress variations induced by oblique excitation Shenghao Lu(卢晟昊), Huan Wang(王欢), and Shaoze Yan(阎绍泽) Chin. Phys. B, 2026, 35 (1):  014601.  DOI: 10.1088/1674-1056/ae181b Abstract ( 9 )   PDF (1224KB) ( 2 )   This study investigates the mechanisms of friction-induced vibration under periodic variations in stress distribution using an improved fretting friction model. A fretting friction test system integrated with a total reflection method was developed to analyze interfacial contact behavior under dynamic loading conditions. An improved fretting friction model was established, incorporating three critical nonlinear parameters: the hysteretic friction coefficient, tangential stiffness fluctuations, and stress distribution. Through systematic validation, the model demonstrates high-fidelity replication of experimental steady-state amplitude—frequency responses. Key findings reveal that non-uniform stress distribution governs irregularities in the vibration response, and increased uniformity intensifies stick—slip instabilities. Near the stick—slip transition threshold, distinct vibration anomalies emerge due to the coupled effects of stress heterogeneity, friction hysteresis, and stiffness variations during state transitions. Furthermore, the magnitude of the normal contact force systematically alters the dominant interfacial contact mechanism. The different interfacial contact states at various frequencies lead to distinct steady-state responses. This shift elevates resonance frequencies and amplifies higher-order resonant peaks. The fretting friction model provides a predictive framework for vibration control under dynamic interfacial loading.

CONDENSED MATTER: STRUCTURAL, MECHANICAL, AND THERMAL PROPERTIES

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Machine learning-assisted optimization of MTO basis sets Zhiqiang Li(李志强), and Lei Wang(王蕾) Chin. Phys. B, 2026, 35 (1):  016301.  DOI: 10.1088/1674-1056/ae0a39 Abstract ( 11 )   PDF (14788KB) ( 4 )   First-principles calculations based on density functional theory (DFT) have had a significant impact on chemistry, physics, and materials science, enabling in-depth exploration of the structural and electronic properties of a wide variety of materials. Among different implementations of DFT, the plane-wave method is widely used for periodic systems because of its high accuracy. However, this method typically requires a large number of basis functions for large systems, leading to high computational costs. Localized basis sets, such as the muffin-tin orbital (MTO) method, have been introduced to provide a more efficient description of electronic structure with a reduced basis set, albeit at the cost of reduced computational accuracy. In this work, we propose an optimization strategy using machine-learning techniques to automate MTO basis-set parameters, thereby improving the accuracy and efficiency of MTO-based calculations. Default MTO parameter settings primarily focus on lattice structure and give less consideration to element-specific differences. In contrast, our optimized parameters incorporate both structural and elemental information. Based on these converged parameters, we successfully recovered missing bands for CrTe2. For the other three materials — Si, GaAs, and CrI3 — we achieved band improvements of up to 2 eV. Furthermore, the generalization of the machine-learned method is validated by perturbation, strain, and elemental substitution, resulting in improved band structures. Additionally, lattice-constant optimization for GaAs using the converged parameters yields closer agreement with experiment.