Chemical Physics
Accelerating CCSD(T) on Graphical Processing Units (GPUs)
O. Jonathan Fajen, Joseph E. Kelly, Edward G. Hohenstein et al. (+1 more)
Coupled cluster with singles, doubles and perturbative triples (CCSD(T)) often provides ground state correlation energies within "chemical accuracy," but suffers from high computational cost and steep scaling with system size. We present a GPU-accelerated implementation of CCSD(T) in the TeraChem software package. The new implementation achieves state-of-the-art performance, enabling the calculation of the (T) correction for a system with 63 atoms and more than 1000 basis functions in a little under 8 hours on a single node. Additionally, we demonstrate the utility of our optimized implementation for the rapid calculation of full CCSD(T)/CBS stacking energies for all ten unique DNA base pair stacked tetramers. We expect that the TeraChem CCSD(T) implementation will enable the rapid calculation of high-level data that was not previously accessible in a reasonable timeframe.
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All authors O. Jonathan Fajen, Joseph E. Kelly, Edward G. Hohenstein, Todd J. Martínez
Fluid Dynamics
Capillary flow simulation with the phase-field-based lattice Boltzmann solver
R. Thirumalaisamy, S. Kim, H. Otomo et al. (+2 more)
The phase-field-based
lattice Boltzmann (LB) model has been developed to perform high fidelity multiphase flow simulations. Its ability to accurately handle high density ratio and surface tension effects is expected to be beneficial for capillary flow simulation, leading to accurate reproduction of flow patterns such as slug flow, droplet flow, and film flow. This is critical in many engineering cases because the flow patterns significantly affect the velocity and pressure fields. In this study, on top of the LB models based on the conservative Allen-Cahn equation and the volumetric boundary conditions for the complex geometries, an optimized wettability and friction model are implemented. With these models, we conducted a set of
benchmark test cases, including static and dynamic multiphase flow scenarios such as the droplet on the curved surfaces, water-filling channel for the Lucas-Washburn law, and the critical pressure in the three-dimensional channel, an air-driven multiphase flow in the experiments. In all of these cases, the solver produces results that are consistent with both theory and experiment, even with respect to the pressure field accuracy, which has often been overlooked in many previous studies.
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All authors R. Thirumalaisamy, S. Kim, H. Otomo, J. Jilesen, R. Zhang
Fluid Dynamics
Lattice Boltzmann models for the hydrodynamic equations in multiphase flow with high density ratio
H. Otomo, C. Sun, T. Inamuro et al. (+5 more)
Multiphase flows with high density ratios, such as water and air flows, have recently been simulated using the
lattice Boltzmann (LB) method. This approach corresponds to solving the phase field equations, such as the Cahn-Hilliard and Allen-Cahn equations, and the hydrodynamic equations, typically the Navier-Stokes and pressure equations for pseudo-incompressible fluids. Due to the high density ratio, the higher-order numerical truncation errors associated with spatial density gradients can become significant. These errors can lead to problems such as inaccuracies in shear stress, violations of Galilean invariance, and undesirable dependencies on absolute pressure for the pseudo-incompressible solutions. To overcome such problems, the moments of the distribution function and the
equilibrium state must be carefully designed while ensuring robustness. In this work, we propose a new scheme based on the
lattice kinetic scheme (LKS), which directly solves the velocity and pressure fields in the similar discrete space as the LB method. When mapping the LKS-based models to the LB models, the original LKS models are simplified for computational efficiency and the filter collision operator is implemented.
Benchmark test cases confirm that the proposed scheme effectively addresses these issues, achieving high accuracy and robustness while eliminating the iterative steps typically required in the LKS. One of the most significant improvements is the accuracy of the airflow field induced by water motion, likely due to improved momentum transfer across the interface.
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All authors H. Otomo, C. Sun, T. Inamuro, W. Li, M. Dressler, H. Chen, Y. Li, R. Zhang
Fluid Dynamics
A data-driven framework to identify restenosis-prone regions in femoral arteries from geometric and inflow waveform parameters
Chotirawee Chatpattanasiri, Federica Ninno, Vanessa D{\i}az-Zuccarini et al. (+1 more)
Haemodynamic indices derived from Computational Fluid Dynamics (CFD), such as Time-averaged Wall Shear Stress (TAWSS) and Oscillatory Shear Index (OSI), are closely associated with restenosis risk in Peripheral Arterial Disease (PAD). However, translating these insights into clinical practice may require computationally efficient approaches such as Reduced Order Model (ROM) or Machine Learning (ML). In this work, we developed an ML-ROM framework to predict critical, restenosis-prone, haemodynamic regions accounting for both vessel geometries and inlet flow waveforms. We generated 500 synthetic femoral-artery geometries parameterised by six
geometric parameters, and created physiologically realistic inflow waveforms via Principal Component Analysis (PCA) of patient data. CFD was used to obtain the Wall Shear Stress (WSS) distribution, from which TAWSS and OSI were computed. Critical regions were then defined by applying threshold-based criteria to the TAWSS and OSI. Four critical-region definitions were considered: two with vessel-specific relative thresholds (TAWSS< 33rd percentile and OSI> 66nd percentile) and two with absolute thresholds (TAWSS< 0.5 Pa and OSI> 0.2). Proper orthogonal decomposition (POD) was then applied to these high-dimensional critical-region data to obtain ROMs; These were then used to train ML models from which the critical region regions could be reconstructed. Three ML architectures were explored: a
Fourier-based architecture, a Long Short-term
Memory (LSTM) architecture, and a Convolutional Neural Network (CNN) architecture. The
Fourier models achieved the highest performance, with the median values of Balanced Accuracy (BA) exceeding 0.92 across all critical-region definitions. The ML-ROM framework also offered a substantial speed-up ratio, about nine orders of magnitude faster than traditional CFD.
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All authors Chotirawee Chatpattanasiri, Federica Ninno, Vanessa D{\i}az-Zuccarini, Stavroula Balabani
Fluid Dynamics
A simulation approach including under-resolved scales for multi-component fluid flows in multi-scale porous structures
Hiroshi Otomo, Rafael Salazar-Tio, Jingjing Yang et al. (+5 more)
In this study, we develop computational models and methodology for accurate multi-component-flow simulation in under-resolved multi-scale porous structures. It is generally impractical to fully resolve the flow in porous structures with large length-scale difference due to tremendously high computational expense. The flow contributions from under-resolved scales need to be accounted for with proper physics modeling as well as simulation processes. Using pre-computed physical properties such as the absolute permeability, K0, the capillary-pressure-saturation curve, and the relative permeability, Kr, in typically resolved porous structures, local fluid force is conjectured and applied to simulation in the under-resolved regions that are represented by porous media. By doing so, accurate simulation of flow in multi-scale porous structures becomes feasible. In order to check the accuracy and robustness of this method, a set of
benchmark test cases are performed for both single-component and multi-component flows in artificially constructed multi-scale porous structures, and simulation results are compared with analytic solutions and/or results with much finer resolution resolving the porous structures. Quantitatively consistent results are obtained with proper input of K0, capillary pressure, and Kr in all tested cases. Specifically, imbibition patterns, entry pressure, residual component patterns, and the absolute and relative permeability are accurately captured with this approach.
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All authors Hiroshi Otomo, Rafael Salazar-Tio, Jingjing Yang, Hongli Fan, Andrew Fager, Bernd Crouse, Raoyang Zhang, Hudong Chen
Computational Physics · Cross-listed from cs.MA
Chain of Unit-Physics: A Primitive-Centric Approach to Scientific Code Synthesis
Vansh Sharma and Venkat Raman
Agentic large
language models are proposed as autonomous code generators for scientific computing, yet their reliability in high-stakes problems remains unclear. Developing computational scientific software from natural-
language queries remains challenging broadly due to (a) sparse representation of domain codes during training and (b) the limited feasibility of RLHF with a small expert community. To address these limitations, this work conceptualizes an inverse approach to code design,
embodied in the Chain of Unit-Physics framework: a first-principles (or primitives)-centric, multi-
agent system in which human expert knowledge is encoded as unit-physics tests that explicitly constrain code generation. The framework is evaluated on a nontrivial combustion task, used here as a representative
benchmark for scientific problem with realistic physical constraints. Closed-weight systems and code-focused agentic variants fail to produce correct end-to-end solvers, despite tool and web access, exhibiting four recurrent error classes: interface (syntax/API)
hallucinations, overconfident assumptions, numerical/physical incoherence, and configuration fragility. Open-weight models with chain-of-thought (CoT) decoding reduce interface errors but still yield incorrect solutions. On the
benchmark task, the proposed framework converges within 5-6 iterations, matches the human-expert implementation (mean error of $3.1\times10^{-3}$ %), with a $\sim$33.4 % faster runtime and a $\sim$30 % efficient
memory usage at a cost comparable to mid-sized commercial APIs, yielding a practical template for physics-grounded scientific code generation. As
datasets and models evolve, zero-shot code accuracy will improve; however, the Chain of Unit-Physics framework goes further by
embedding first-principles analysis that is foundational to scientific codes.
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Optics
Scintillation index analysis for multi-wavelength Gaussian beams in turbulent underwater channels
Shideh Tayebnaimi and Kamran Kiasaleh
We investigate the scintillation index of multi-wavelength Gaussian optical beams propagating through a turbulent optical channel. We consider a turbulent environment ranging from weak to strong, with a specific focus on the weak turbulent regime. Furthermore, the impacts of absorption and scattering effects are taken into account. It is shown here that the use of a multi-wavelength beam results in a reduction in the scintillation index, thereby enhancing the performance of the
underwater optical link.
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Computational Physics · Cross-listed from math-ph
Exact quantum dynamics of Fermi–Hubbard systems using the Gaussian phase-space representation with diffusion gauges
F Rousse, M Fasi, A Dmytryshyn et al. (+3 more)
We use the Gaussian Phase-Space Representation to solve the real-time dynamic of interacting
fermions in 1D, 2D, and 3D systems. The method is exact up to a spiking point, which represents a limit on the practical simulation time. The spiking can be delayed, and the practical simulation time extended, by adjusting the gauges of the representation, resulting in different equivalent
stochastic differential equations. Here, we work on the so-called
diffusion gauge and propose an
algorithm to find efficiently new implementations of the noise terms. Compared with our initial results [F. Rousse et al. 2024, J. Phys. A: Math. Theor. 57, 015303], the new method achieves a significantly longer practical simulation time and can be applied to significantly larger systems.
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All authors F Rousse, M Fasi, A Dmytryshyn, M Gulliksson, J F Corney, M Ogren
Space Physics
A robust empirical relationship between speed and turbulence energy in the near-Earth solar wind
Rohit Chhiber, Yanwen Wang, Manuel E. Cuesta et al. (+2 more)
The connection between
turbulence and
solar-wind acceleration, long known in space physics, is further developed in this Letter by establishing a robust empirical law that relates the bulk-flow speed to the magnetohydrodynamic-scale fluctuation energy in the
plasma. The model is based on analysis of twenty-five years of near-Earth observations by NASA's Advanced Composition Explorer. It provides a simple way to estimate
turbulence energy from low-resolution speed data – a practical approach that may be of utility when high-resolution measurements or advanced
turbulence models are unavailable. Potential heliospheric applications include space-weather
forecasting operations, remote imaging
datasets, and energetic-particle transport models that require
turbulence amplitudes to specify
diffusion parameters.
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All authors Rohit Chhiber, Yanwen Wang, Manuel E. Cuesta, Jiaming Wang, Sohom Roy
Optics
Decomposition of the total wave aberration in generalized optical systems
Mateusz Oleszko, Ralf Hambach and Herbert Gross
The increasing use of freeform optical surfaces raises the demand for optical design tools developed for generalized systems. In the design process surface-by-surface aberration contributions are of special interest. The expansion of the wave aberration function into field and pupil dependent coefficients is an analytical method used for that purpose. An alternative numerical approach utilizing data from the trace of multiple ray sets is proposed. The optical system is divided into segments of the optical path measured along the chief ray. Each segment covers one surface and the distance to the subsequent surface. Surface contributions represent the change of the wavefront that occurs due to propagation through individual segments. Further, the surface contributions are divided with respect to their phenomenological origin into intrinsic, induced and transfer components. Each component is determined from a separate set of rays. The proposed method does not place any constraints on the system geometry or the aperture shape. However, here we concentrate on near-circular apertures and specify the resulting wavefront error maps using an expansion into Zernike
polynomials. Hence, for the first time additive surface Zernike contributions are obtained.
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Applied Physics
A Novel Class-F 2.45/5.8 GHz Dual-Band Rectifier for Wireless Power Transmission
Siyi Xiao, Changjun Liu, Haoming He et al. (+2 more)
This letter proposes a high-efficiency dual-band class-F rectifier for wireless power transmission (WPT). The rectifier comprises a dual-band harmonic termination network, a dual-band matching network, a single Schottky diode, and a dc pass filter. A theoretical analysis of the harmonic termination network is performed to improve the rectifying efficiency. The network exhibits good class-F operation by controlling the second and third harmonics in dual bands. A rectifier operating at 2.45 and 5.8 GHz was designed, fabricated, and measured for validation. The measurements show maximum RF-dc conversion efficiencies of 74.9% and 61.9% with 200 and 500{\Omega} loads at 2.45 and 5.8 GHz, respectively. The proposed rectifier achieves dual-band harmonic control with high efficiency.
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All authors Siyi Xiao, Changjun Liu, Haoming He, Yuhao Feng, Wenquan Che
Instrumentation and Detectors · Cross-listed from eess.SY
A Bidirectional Diode-Clamp Circuit Paradigm for Time-Resolved Measurement of Electrical Short-Circuits
Alex Mwololo Kimuya and Dickson Mwenda Kinyua
Conventional electrical fault models, which rely on static thresholds and instantaneous trip mechanisms, fail to capture the time-evolving dynamics of real faults, creating vulnerabilities in modern power systems. This paper introduces a diode-clamp
circuit architecture that reconceives short-
circuits as governed, sustained processes and establishes a physics-consistent, measurement system. An Arduino-based data acquisition system recorded continuous fault
evolution across multiple input voltages and durations. Multi-resolution sampling at 10ms, 50ms, and 100ms enabled high-fidelity capture of both transients and sustained-state dynamics. The clamped mechanism constrained the
circuit to a bounded regime, enabling repeatable observation. Experiments yielded definitive, measurable minima and maxima for voltage, current, and resistance, empirically refuting the classical assumption of instantaneous, unbounded current. Newly introduced metrics quantify this performance: the Sustained-to-Capacitive Energy Ratio (SCER ~1.53x10^12) proves fault energy originates from sustained dynamics, not transient discharge. The Sustained Fault Efficiency (SFE>1) demonstrates that governed fault power can exceed nominal operating power. This work provides the first fully validated short-
circuit quantification system, yielding empirical data for next-generation battery management, adaptive grid protection, and fault-tolerant electronics.
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Applied Physics
A C-band microwave rectenna using aperture-coupled antenna array and novel Class-F rectifier with cavity
C Yu, F Tan and C Liu
A rectenna (rectifying
antenna) is usually applied to a microwave power transmission (MPT) system as a terminal, which receives microwave (MW) power and converts them into DC power. A 5.8 GHz aperture-coupled patch
antenna array is developed with a gain of 19.5 dBi, which is a part of the rectenna. A novel Class-F rectifier with a series diode is proposed to achieve a high rectifying efficiency based on harmonic termination techniques. The input
circuit of the proposed rectifier is taken into consideration to reach the Class-F condition, while mostly only the output
circuit is involved in conventional Class-F designs. A low-pass filter based on defected ground structure is implemented, which not only blocks the harmonics produced in rectifying but also presents desired impedance at harmonics. The current and voltage waveforms on the diode are well enforced. The radiation feature of the rectifier is presented as well. It shows that an optimized cavity, which shields the parasite radiation, may achieve a 5% enhancement on the MW-to-DC conversion efficiency. A C-band rectifier based on HSMS-286 Schottky diode is fabricated and measured. A MPT simple demo system is constructed with the proposed rectifier and
antenna. A measured maximum MW-to-DC conversion efficiency of 72% is achieved on the rectifier. The design method is extremely valuable in a high conversion efficiency rectenna design based on harmonic termination techniques.
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Chemical Physics
Machine Learning Photodynamics Unveils a Controlled H$_2$ Loss Channel in Methaniminium Cation
Daniil N. Chistikov, Pavel M. Radzikovitsky, Dmitry S. Popov et al. (+4 more)
The methaniminium cation, CH$_2$NH$_2^+$, plays an important role in Titan's N$_2$–CH$_4$ atmospheric chemistry. As the simplest protonated Schiff base (PSB), it also serves as a model for studying the nonadiabatic dynamics of retinal PSB, the chromophore central to vertebrate
vision. While previous studies have established CN bond cleavage and photoisomerization as the primary pathways in the photochemistry of CH$_2$NH$_2^+$, we now report a new UV-induced photochemical pathway to HCNH$^+$, the dominant ion in Titan's upper atmosphere. Through high-level XMCQDPT2 and CASSCF(12,12) calculations, we identify a novel S$_1$/S$_0$ conical intersection that mediates the concerted double H-atom elimination from the carbon center of CH$_2$NH$_2^+$, yielding carbene CNH$_2^+$ as a direct precursor to HCNH$^+$. On-the-fly trajectory surface hopping dynamics confirm the presence of direct H$_2$ loss following excitation to either the S$_2$ or S$_1$ state. Furthermore, our large-scale, machine learning-accelerated simulations reveal that mode-specific pre-excitation can selectively funnel the dynamics into this new channel via the vibronically allowed S$_1$ state, enabling targeted control of the photochemical outcome.
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All authors Daniil N. Chistikov, Pavel M. Radzikovitsky, Dmitry S. Popov, Ivan V. Dudakov, Vadim V. Korolev, Vladimir E. Bochenkov, Anastasia V. Bochenkova
Data Analysis and Statistics · Cross-listed from q-fin.ST
Early-Warning Signals of Political Risk in Stablecoin Markets: Human and Algorithmic Behavior Around the 2024 U.S. Election
Kundan Mukhia, Buddha Nath Sharma, Salam Rabindrajit Luwang et al. (+4 more)
We study how the 2024 U.S. presidential election, viewed as a major political risk event, affected cryptocurrency
markets by distinguishing human-driven peer-to-peer stablecoin transactions from automated algorithmic activity. Using structural break analysis, we find that human-driven Ethereum Request for Comment 20 (ERC-20) transactions shifted on November 3, two days before the election, while exchange trading volumes reacted only on Election Day. Automated smart-contract activity adjusted much later, with structural breaks appearing in January 2025. We validate these shifts using surrogate-based robustness tests. Complementary energy-spectrum analysis of Bitcoin and Ethereum identifies pronounced post-election
turbulence, and a structural vector autoregression confirms a regime shift in stablecoin dynamics. Overall, human-driven stablecoin flows act as early-warning indicators of political stress, preceding both exchange behavior and algorithmic responses.
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All authors Kundan Mukhia, Buddha Nath Sharma, Salam Rabindrajit Luwang, Md. Nurujjaman, Chittaranjan Hens, Suman Saha, Tanujit Chakraborty
Accelerator Physics
A Core Ontology for Particle Accelerators: Interoperable Data and Workflows Across Facilities
Chris Tennant
We propose a small, shared core ontology for particle accelerators that provides a semantic backbone for interoperable data and workflows across facilities. The ontology names key device types, signals, parameters, and regions, and relates them through explicit properties (e.g., hasSetpoint, hasReadback, partOf). Each site contributes a lightweight facility bundle, a profile that maps local conventions into the shared vocabulary plus data slices that instantiate those mappings, without renaming channel addresses or changing existing systems. Using standard W3C technologies, the approach supports both sparse and rich descriptions. We demonstrate the idea on two beamline segments at different laboratories. A single semantic query is expressed once and evaluated against both knowledge bases, returning the locally correct PVs. The ontology thereby enables not only portable workflows but also interoperable data, since measurements and catalogs are annotated with shared semantics rather than facility-specific names. The framework complements, rather than replaces, existing middle layers and
lattice/data standards, and it creates a stable foundation for reusable tools and agentic workflows.
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Optics
Deep learning-based dynamic error correction and uncertainty estimation for digital twin-assisted fringe projection profilometry of rotating gears
Zhangsheng Li, Jiancheng Qiu and Gao Xu Wu
This paper presents a deep learning-based method for dynamic gear measurement and uncertainty estimation. A twin-system proposed on the Unity platform is utilized to flexibly generate diverse simulated
datasets. This effectively addresses the scarcity of real-world gear measurement data and facilitates verification of network performance.The designed Concrete Dropout-Pixel wise Uncertainty Network integrates the Concrete Dropout mechanism for pixel-level uncertainty estimation. Two lightweight layers are employed in the output layer to enhance the spatial continuity of prediction results.During network training, a transfer learning strategy is adopted: the model is first pretrained with a small amount of three-phase-shifting (3-PS) data, then fine-tuned on the target gear measurement
dataset. Experimental results demonstrate that, compared with the traditional three-step phase-shifting (3-PS) method, the proposed approach achieves significant improvements in phase prediction accuracy, three-dimensional reconstruction accuracy, dynamic error correction capability, and uncertainty estimation reliability.This work provides a practical and efficient technical solution for fringe projection-based dynamic gear measurement.
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Fluid Dynamics
Self-similar multishock implosions for ultrahigh compression of matter
M. Murakami
We present a class of self-similar solutions describing ultrahigh compression of a uniform-density target by spherically converging, stacked shock waves. Extending the classical Guderley model, we derive a scaling law for the final density of the form $\rho_{r}/\rho_{0} \propto \hat{P}^{\beta (N-1)}$, where $N$ is the number of shocks, $\hat{P}$ the stage pressure ratio, and $\beta$ a numerical exponent determined by the adiabatic index $\gamma$. One-dimensional hydrodynamic simulations confirm the validity of this scaling across a broad parameter range. Notably, the relation remains accurate even in the strongly nonlinear regime up to $\hat{P} \sim 70$, well beyond the perturbative limit, highlighting the robustness and practical relevance of the model. Owing to its volumetric geometry, this compression scheme inherently avoids the Rayleigh–Taylor instability, which typically compromises shell-based implosions, and thereby establishes a theoretical
benchmark for instability-free compression in inertial confinement fusion.
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Physics and Society
Entropy-Driven Sensor Deployment and Source Detection in Hypergraphs
Qiao Ke, Chengjun Zhang, Chuang Liu et al. (+3 more)
Identifying the
diffusion source in complex networks is critical for understanding and controlling epidemic spread. In realistic settings, full observation of node states is rarely available, making sensor-based source detection a practical alternative. However, existing sensor-based methods are often confined to simple networks, failing to capture the higher-order group dynamics of real-world spreading process. By deploying a limited number of sensors to monitor the
diffusion process, one can infer the origin from partial observations. Yet, determining optimal sensor placement is challenging, i.e., poor deployment leads to redundant or noisy data, while optimal placement must balance coverage diversity and information value under limited resources. To address these challenges, we propose a dedicated framework termed Sensor-based Source Detection in Hypergraphs (SSDH). Specifically, we introduce a novel
entropy-driven sensor deployment strategy that effectively captures critical early-stage
diffusion signals by maximizing information gain under limited resources. Furthermore, we develop a source localization
algorithm that quantifies propagation uncertainty through a newly defined path uncertainty-based score. By integrating this score with topological distance, SSDH enables accurate and robust source identification. Extensive experiments on both synthetic and empirical hypergraphs demonstrate that SSDH consistently outperforms competing
algorithms by 5%–30% across different sensor ratios, final spreading ratios, and infection probabilities. These results validate the effectiveness of SSDH and highlight its superior capability to tackle source localization in complex systems characterized by higher-order interactions.
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All authors Qiao Ke, Chengjun Zhang, Chuang Liu, Mingxia Jing, Suoyi Tan, Xiu-Xiu Zhan
Plasma Physics
Generation of giga-electron-volt proton beams by micronozzle acceleration
M. Murakami, D. Balusu, S. Maruyama et al. (+2 more)
Our proposed ion acceleration scheme, micronozzle acceleration (MNA), generates
proton beams with extremely high kinetic energies on the giga-electron-volt (GeV) order. The underlying physics and performance of MNA are studied with two-dimensional particle-in-
cell simulations. In MNA targets, a micron-sized hydrogen rod is embedded inside a hollow micronozzle. Subsequent illumination of the target along the symmetric axis by an ultraintense ultrashort
laser pulse forms a strong electrostatic field with a long lifetime and an extensive space around the downstream tail of the nozzle. The electric field significantly amplifies the kinetic energies of the accelerated
protons, and > GeV
protons are generated at an applied
laser intensity of 10^22 W/cm^2 .
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All authors M. Murakami, D. Balusu, S. Maruyama, Y. Murakami, B. Ramakrishna
Physics Education · Cross-listed from hep-ph
The Gauge Principle and Foundations of The Standard Model: A Pedagogical Introduction Through QED
Taha Anwar
The Standard Model of particle physics is built on the principle of local gauge
symmetry. This work provides a pedagogical introduction for advanced undergraduates by using
quantum electrodynamics (QED) as the simplest example of a gauge theory. Beginning with the Lagrangian formulation of classical mechanics, special relativity, and basic
quantum mechanics, we develop classical field theory, reformulate electromagnetism in covariant form, introduce the Dirac equation for
spin 1/2 particles, and finally arrive at the gauge principle. By showing how the requirement of local U(1) invariance leads naturally to the electromagnetic interaction, we illustrate the essential logic behind gauge theories and highlight the conceptual structure that underlies the Standard Model Lagrangian.
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Plasma Physics
Gigagauss magnetic field generation by bladed microtube implosion
D. Pan and M. Murakami
We demonstrate the generation of ultrahigh
magnetic fields in the order of gigagauss using a bladed microtube target whose inner surface is periodically slanted in a sawtooth-like pattern. When irradiated by ultra-intense, ultrashort
laser pulses, hot electrons with MeV energies are produced at the outer surface and swiftly transported to the inner surface, initiating a rapid implosion of
plasma toward the central axis. The unique blade-induced asymmetry gives rise to
vortex-shaped flows of ions and electrons near the center, forming strong azimuthal loop currents that generate ultrahigh
magnetic fields at the center. Two-dimensional particle-in-
cell simulations, supported by a simple analytical model, elucidate the underlying physics and reveal key scaling laws governing the field strength and spatial confinement.
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Optics
Photonic chip-based Reconfigurable Radar Compound Jamming Signal Generator
Senyu Zhang, Wei Luo, Shuang Zheng et al. (+7 more)
Microwave photonics (MWP) serves as a powerful bridge between the
radio-frequency and optical worlds, unlocking unprecedented bandwidth and speed for critical information systems. Recently, MWP-based radar jamming has demonstrated significant potential in overcoming electronic bottlenecks; however, existing solutions rely heavily on bulky discrete components and generate deterministic symmetric waveforms that are vulnerable to advanced counter-countermeasures. Here, we break this status quo by demonstrating the first monolithic photonic chip-based reconfigurable radar compound jamming signal generator. Implemented on a compact 25 mm2 silicon photonic footprint, our system features high integration and electrical reconfigurability, supporting agile switching among four distinct jamming modes. Crucially, we introduce a composite jamming mechanism that exploits time-frequency coupling to break the inherent
symmetry of traditional deceptive jamming, generating controllable asymmetric false-target clusters. The on-chip system exhibits an operating bandwidth exceeding 20 GHz and is capable of generating over 20 high-fidelity false targets simultaneously. This work establishes a fully functional platform combining broad bandwidth, multi-mode flexibility, and asymmetric deception, paving the way for miniaturized, intelligent photonic solutions in next-generation electronic warfare.
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All authors Senyu Zhang, Wei Luo, Shuang Zheng, Yunlong Li, Yiqiang Ou, Qi Tian, Yifei Chong, Zihang Yang, Li Shen, Minming Zhang
Accelerator Physics
NeutrSHINE: a high repetition rate ultrafast neutron source driven by SHINE electron beam
Tianyu Ma, Yuchen Liu, Zhangfeng Gao et al. (+11 more)
Neutrons serve as unique probes for exploring the microscopic structure of matter, with the performance of a
neutron source fundamentally governing the depth of scientific exploration and the breadth of industrial applicability. To address application demands including
nuclear data measurement in the ultra-high-energy region, fundamental particle physics research, highly efficient non-destructive
neutron testing, and extreme environment simulation, an ultrafast
neutron source driven by the 8 GeV electron beam from the Shanghai high-repetition-rate extreme light facility (SHINE) was conceptually proposed, named NeutrSHINE. Using multidisciplinary simulation tools, key neutronic parameters, thermal behavior of high-power
neutron targets, and the factors affecting the time resolution of the source were analyzed. The results affirm the technical feasibility and promising application prospects of the NeutrSHINE concept.
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All authors Tianyu Ma, Yuchen Liu, Zhangfeng Gao, Zuokang Lin, Hao Li, Zijian Zhang, Zhiyuan Lin, Guanchao Wu, Yu Zhang, Yinan Zhu, Zhiwen Xu, Xinying Jin, Weishi Wan, Haixiao Deng
Computational Physics
Control of localized states of itinerant electrons and their magnetic interactions
Yaxin Sun, I. S. Lobanov, Jiahao Su et al. (+2 more)
Controlling the
magnetic properties of nanosystems by an electric field offers a number of advantages for spintronics applications. Using the noncollinear Alexander-Anderson model, we have shown that the interaction of localized
magnetic moments formed by itinerant electrons strongly depends on the position of the d-level relative to the
Fermi level, which determines the number of localized electrons. Depending on this parameter, the ground state of the
magnetic dimer can be
ferromagnetic,
antiferromagnetic, or noncollinear without the effects of
spin-orbit interaction. The
magnetic state can be controlled by shifting the d-level with an electric field, even without current flow. For a sufficiently large value of the hopping parameter between localized states there can be several self-consistent solutions with different values of
magnetic moments. This opens new possibilities for manipulation of the
magnetic structure of nanosystems. The results obtained lead to a new interpretation of the mechanisms of magnetization reversal, recording, and deleting of
magnetic structures in tunneling spectroscopy experiments.
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All authors Yaxin Sun, I. S. Lobanov, Jiahao Su, Ho-Kin Tang, V. M. Uzdin
Physics and Society
Relations Between the Inequality Indices Gini, Pietra and Kolkata: Theory and Data Analysis
Asim Ghosh and Bikas K. Chakrabarti
We study relations between three inequality indices, namely the Gini ($g$), Pietra ($p$) and Kolkata ($k$) introduced in 1912, 1915 and 2014 respectively and all are derived from the Lorenz function $L(x)$ introduced in 1905. The Kolkata index (which corresponds to a fixed point of the complementary Lorenz function $L_c(x) \equiv 1-L(x)$) gives the fraction $k$ of wealth possessed by the richest $1-k$ fraction of people ($k$ = 0.8 corresponds to Pareto's 80-20 law from 1896). We show rigorously that while the Pietra index value $p$ should be greater than or equal to $2k-1$, the Robin Hood index should strictly be equal to the excess wealth fraction $2k-1$ possessed by the richest $1-k$ fraction of people. Our numerical data analysis for US IRS Income data (1983-2022), Bollywood (India) movie income data (1999-2024) and the citation inequalities across the publications by forty Nobel Laureates (2020-2025) in Economics, Physics, Chemistry and Medicine clearly show that $p/(2k-1)$ is always greater than unity but the deviation is never more than five percent. Assuming some simple analytic form for the Lorenz function, we also derived the relations $k = (1/2) + (3/8)g$ for small $g$ values and $p/g = 3/4$. However, by considering the Lorenz function appropriate for the generalized Pareto power law distribution, we obtain an extended range ($1_+ < p/g \leq e/2$) that captures most of the empirical data.
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Optics
Observation of linear and nonlinear light trapping on topological dislocations
S. K. Ivanov, A. V. Kireev, K. Sabour et al. (+11 more)
Topological dislocations in otherwise periodic
lattices represent global structural defects that, nevertheless, typically leave the
lattice periodicity intact far from the dislocation. Such dislocations arise in diverse physical systems ranging from crystalline solids, acoustic and photonic
lattices and
crystals to matter waves in optical
lattices. Dislocations drastically affect the
evolution of wave excitations in their vicinity, enabling novel mechanisms for trapping on topological defects and controlling the energy flow. Moreover, when combined with nonlinearity, such systems give rise to new types of self-sustained states of topological origin that have never been observed to date. Here we demonstrate experimentally, for the first time at optical frequencies, the waveguiding at various types of topological edge dislocations, resulting in the formation of localized photonic eigenstates with distinct and tunable shapes. Using femtosecond
laser-writing techniques, we fabricated waveguide arrays with precisely tailored dislocation parameters, enabling full control over the degree of localization and internal structure of the associated modes. We further demonstrate both theoretically and experimentally that in the high-power regime, the families of thresholdless dislocation
solitons bifurcate from such modes, which inherit shape diversity of their linear counterparts. Our results reveal a nontrivial interplay between nonlinearity and global
lattice deformations and establish dislocation
solitons as a new class of nonlinear topological states. They may stimulate the observation of new types of nonlinear states and interaction scenarios for excitations in nonlinear physical systems, where
lattices with controllable global deformations can be created.
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All authors S. K. Ivanov, A. V. Kireev, K. Sabour, N. S. Kostyuchenko, S. A. Zhuravitskii, N. N. Skryabin, I. V. Dyakonov, A. A. Kalinkin, V. O. Kompanets, S. P. Kulik, S. V. Chekalin, A. Ferrando, V. N. Zadkov, Y. V. Kartashov
Applied Physics
New record in optical gain and room-temperature nanolasers in multiple wavelengths in 2D ErOCl single crystals
Shipeng Yao, Hao Sun, Zhang Liang et al. (+5 more)
Erbium-based materials have long been recognized for their important telecom-band applications, yet their widespread adoption in integrated optoelectronics has been hindered by two fundamental limitations: the difficulty in achieving high erbium density without concentration quenching which leads to small optical gain in doped materials, and the difficulty in fabricating a practical device with single
crystal nanowires that demonstrated high optical gain previously1,2. Here, we overcome these limitations by synthesizing 2D single
crystal ErOCl that has an Er density of 1.75*1022 cm-3. The high-quality single
crystal material significantly reduces the density-related quenching effect that dominates in randomly doped materials with high Er concentration. This results in a record optical gain coefficient over 1500 dB/cm at 1536 nm band, at least larger by an order of magnitude than the previous gain record in Er materials. Leveraging this exceptional gain medium, we demonstrate room-temperature continuous-wave lasing operation by integrating with a photonic
crystal microcavity, achieving a record-low threshold of 7 {\mu}W with the most compact size of any Er-based
lasers. Furthermore, the unique Stark splitting characteristics of ErOCl provide optical gain in three wavelength bands and lead to lasing in these wavelengths by engineering the cavity. This is the first time that optical gain has been shown in three different wavelength bands in Er materials, together with the smallest size of
laser cavity, could have many important applications in on-chip sensing and optical communication.
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All authors Shipeng Yao, Hao Sun, Zhang Liang, Zhen Wang, Lin Gan, Jinhua Wu, Zhangyu Hou, Cun-Zheng Ning