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Physics Physics

physics Watch Physics

Thursday 26 February

Medical Physics

Continuous Blood Monitoring with Particle-based Integrated Sensing and Communication (ISAC)

Fatih E. Bilgen and Ozgur B. Akan

Although the circulatory system functions as a continuous source of physiological data, contemporary diagnostics remain bound to intermittent, time-delayed assessments. To resolve this, we present a framework for ubiquitous hematological profiling driven by Integrated Sensing and Communication (ISAC). We demonstrate how electromagnetic signals can be exploited to monitor blood in real-time, effectively converting them into diagnostic tools. We analyze the biological foundations of blood, review existing Complete Blood Count (CBC) and sensing technologies, and detail a novel pipeline for continuous blood monitoring. Furthermore, we discuss the potential applications of deploying these devices to enable real-time CBC and biomarker detection, ultimately revolutionizing how we predict, detect, and manage individual and public health.
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Atmospheric and Oceanic Physics

A fusion of concepts

Jin-Song von Storch

This essay fuses concepts and approaches used to describe fluctuating phenomena in climate systems and statistical mechanics, and explores new ideas essential for understanding such phenomena. Its starting points are the Langevin equation (LE) and the fluctuation-dissipation theorem (FDT). The former was introduced to climate research by Klaus Hasselmann through his stochastic climate models. While a version of the latter, formulated within the framework of linear response theory, has found wide application, the deeper origin of the relation between fluctuations and dissipation has remained inconclusive. This essay goes one step further by seeking the cause of the apparent randomness, rather than merely describing it as in the LE, and by directly linking a fluctuation-dissipation relation to the governing microscopic equations. It postulates that such a relation, also referred to as the integral fluctuation-dissipation relation (IFDR), resides in integrals of the forcings that determine microscopic evolutions (individual trajectories) of the considered system. The IFDR ensures the emergence of well-defined macroscopic quantities, such as variance and spectra, quantities that characterize the system's fluctuations, provided the system is in dynamical equilibrium with constant external forcing. It is the dissipation embodied in IFDR that renders future states uncorrelated with initial conditions, thereby generating apparent randomness. Randomness is therefore not an unphysical artifact; on the contrary, it is a fundamental property of forced-dissipative systems in dynamical equilibrium. Fluctuation phenomena in such systems must be described by two principles: the governing microscopic equations and the IFDR. The two principles are complementary but not reducible to one another.
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Physics and Society

Supervised tax compliance and evasion from a spatial evolutionary game perspective

Qin Li, Ting Ling, Minyu Feng et al. (+1 more)

Taxation constitutes a fundamental component of modern national economic systems, exerting profound impacts on both societal functioning and governmental operations. In this paper, we employ an interdependent network approach to model the coevolution between citizens and regulators within a taxation system that fundamentally constitutes a public goods game framework with complex interactive dynamics. In a game layer, citizens engage in public goods games, facing the social dilemma of tax compliance (cooperation) versus evasion (defection). Tax compliance supports the sustainability of public finances while tax evasion presents markedly stronger short-term incentives. In a regulatory layer, fair regulators punish tax evaders, while corrupt regulators keep silent due to bribes. Governmental regulatory interventions introduce critical institutional constraints that alter the traditional equilibrium of the game. Importantly, there exists a strategy update not only among citizens but also among regulators. Our results indicate that strengthening penalties can effectively curb tax evasion, and the influence of bribery on both tax compliance rates and the proportion of fair regulators is nonlinear. Additionally, increasing regulators' salaries and intensifying the crackdown on corrupt regulators can foster the emergence of fair regulators, thereby reducing tax evasion among citizens. The results offer practical policy implications, suggesting that balanced deterrence and institutional fairness are essential to sustaining compliance, and point to the need for future empirical validation and model extensions.
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All authors Qin Li, Ting Ling, Minyu Feng, Attila Szolnoki

Atomic Physics · Cross-listed from astro-ph.HE

The MARTINI Platform (I): Se I-X atomic calculation and expansion opacity for early-stage kilonova spectral analysis

Matteo Bezmalinovich, Mattia Bulla, Gediminas Gaigalas et al. (+3 more)

Kilonovae represent key sites of r-process nucleosynthesis, making opacity estimation and spectral analysis crucial for constraining their composition. Since light r-process elements shape the early ($\sim$0.5-1.5$\mathrm{d}$) ejecta opacity, a detailed study of the selenium element with a focus on atomic data calculation, expansion opacity estimation and spectral analysis is presented. Se atomic data are calculated from Se I to Se X using the GRASP2018 code. A systematic analysis and evaluation of their precision is performed through detailed comparison with the NIST ASD, and other works available in the literature. These atomic data are then used to estimate expansion opacity at different temperatures (e.g., T=5000 K, 10000 K, 20000 K, 100000 K) and densities (e.g., $\rho = 10^{-13}\,\mathrm{g\,cm^{-3}},\,3\times10^{-12}\,\mathrm{g\,cm^{-3}}$). Spectral analysis has been performed with radiative transfer code POSSIS with a pre-computed opacity grid calculated with new densities and temperatures, ranging from -19.5 to -4.5 $\mathrm{g\,cm^{-3}}$ in log-scale and from 1 000 to 51 000 K, respectively. Two scenarios are considered: one in which the opacity contribution comes from 100% Se ejecta, and another in which Se contributes only partially to the total opacity ($\sim$ 10% of the total mass). Se atomic calculations show a good agreement with NIST ASD, with accurate energy levels and transitions determined alongside atomic data for higher ionisation stages not fully covered by NIST. The expansion opacities calculated with these new Se data exhibit differences in comparison to existing literature works. Se spectral features can only be observed in the KN scenario consisting of 100% Se. When Se accounts for about 10% of the total KN mass, these features become undetectable. All Se results are now available in the new open-source MARTINI platform dedicated to element nucleosynthesis.
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All authors Matteo Bezmalinovich, Mattia Bulla, Gediminas Gaigalas, Diego Vescovi, Matteo Canzari, Sergio Cristallo

Atomic Physics · Cross-listed from quant-ph

Spin-Cat Qubit with Biased Noise in an Optical Tweezer Array

Toshi Kusano, Kosuke Shibata, Chih-Han Yeh et al. (+8 more)

Bias-tailored quantum error correcting codes (QECCs) offer a higher error threshold than standard QECCs and have the potential to achieve lower logical errors with less space overhead. The spin-cat qubit, encoded in a large nuclear spin-$F$ system, is a promising candidate for bias-tailored QECCs. Yet its feasibility is hindered by the difficulty of performing fast covariant SU(2) rotation with arbitrary rotation angles for nuclear spins and by a lack of noise characterization for gate operations in neutral atom platforms. Here we demonstrate single-qubit controls of ${}^{173}\mathrm{Yb}$ spin-cat qubits with nuclear spin $I=5/2$ in an optical tweezer array. We implement a covariant SU(2) rotation and non-linear rotations by optical beams and achieve an averaged single-Clifford gate fidelity of $0.961_{-5}^{+5}$. The measurement of the coherence time and spin relaxation time shows that the idling error becomes increasingly biased toward dephasing errors as the magnitude of the encoded sublevel $|m_F|$ increases. Furthermore, we benchmark the noise bias of rank-preserving gates on spin-cat qubits, demonstrating a finite bias of $18_{-11}^{+132}$, in contrast to the case of the two-level system in ${}^{171}\mathrm{Yb}$, which shows no bias within the experimental uncertainty. Our work demonstrates the feasibility of spin-cat qubits for realizing bias-tailored QECCs, paving the way for achieving hardware-efficient quantum error correction.
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All authors Toshi Kusano, Kosuke Shibata, Chih-Han Yeh, Keito Saito, Yuma Nakamura, Rei Yokoyama, Takumi Kashimoto, Tetsushi Takano, Yosuke Takasu, Ryuji Takagi, Yoshiro Takahashi

Instrumentation and Detectors · Cross-listed from hep-ph

Testing beyond the Standard Model scenarios in next-generation long-baseline neutrino oscillation experiments

Pragyanprasu Swain

In this thesis, we assess the sensitivity of next-generation long-baseline neutrino oscillation experiments, DUNE, T2HK, and T2HKK, to three popular beyond the Standard Model (BSM) scenarios. Within the three BSM studies, we examine: (i) long-range neutrino-matter interactions induced by flavor-dependent, anomaly-free gauged baryon-lepton symmetries mediated by ultra-light vector boson, showing that DUNE and T2HK can constrain, discover, and in some favorable cases distinguish among different symmetries; (ii) Lorentz invariance violation (LIV), where we derive analytical dependencies of CPT-conserving and CPT-violating LIV parameters on baseline and energy, highlighting the superior reach of DUNE in probing all the LIV parameters, in contrast to T2HK, which is essentially blind to the CPT-conserving LIV parameters; and (iii) active-sterile oscillations over a broad range of $\Delta m^2_{41}$, where we derive sensitivity to CP phases for benchmark choices of $\Delta m^2_{41}$ and establish exclusion limits, emphasizing the role of near detectors. Together, these studies show that future long-baseline facilities not only resolve the neutrino mass ordering, value of $\delta_{\rm CP}$, and $\theta_{23}$ octant, but also provide powerful probes of BSM physics.
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Optics

Kerr-induced In-line Interferometry for Ultra-sensitive Phase-Contrast Imaging

Glitta R. Cheeran, Mehmet Müftüoğlu, Sobhi Saeed et al. (+2 more)

Measuring the phase of light is fundamental to optical imaging, sensing, and signal processing applications. Conventional optical phase measurements rely on multipath configurations, bulky interferometric setups, and computationally intensive data pipelines, limiting scalability, robustness, and practicality. We introduce a technique that allows for reference-free in-line phase retrieval of abrupt phase transitions in optical pulses directly from spectral measurements. Theory, simulations, and experiments concurrently explain the effect as a result of a Kerr-mediated interference between a projected linear wave component and the high-intensity residual of the phase-altered pulse. Utilizing this phenomenon, we demonstrate algorithm-free phase measurements of up to {\pi}/385 sensitivity and shot-to-shot signal prominence at 13 dB above noise at 80 MHz rates and 50 pJ pulse energies. This approach offers new paths toward the use of femtosecond pulses as broadband data carriers for optical communications, information processing, and direct high-throughput phase imaging.
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All authors Glitta R. Cheeran, Mehmet Müftüoğlu, Sobhi Saeed, Bennet Fischer, Mario Chemnitz

Plasma Physics

Experimental Demonstration of Beam-Driven Wakefield Acceleration in Laser-Plasma Filament

M. Galletti, L. Verra, A. Biagioni et al. (+10 more)

Self-guided femtosecond laser pulses propagating in low-pressure gas can generate plasma filaments, establishing a new framework for plasma wakefield acceleration. Unlike conventional schemes relying on mechanically confined or preformed plasma channels, this method exploits the intrinsic non-linear light-matter interaction, greatly reducing the energy required to generate plasma. This, in turn, allows to realise tunable stages, potentially operating above kHz repetition rate and with meter-scale interaction lengths and transverse sizes down to a few tens of micrometres. Moreover, the laser-plasma filament reproducibility is intrinsically higher than state-of-the-art discharge-plasmas, where the breakdown process is initiated in a stochastic and uncontrolled manner. As a result, laser-based plasma formation offers improved reliability and control over plasma parameters. Here we report a proof-of-principle experimental demonstration of beam-driven wakefield acceleration of electron bunches with an accelerating field exceeding 250 MV/m in a laser-generated plasma filament. The results are cross-checked with numerical simulation, showing an excellent agreement and providing a complete picture of the physical process. Beyond particle acceleration, the concept bridges laser filamentation physics, advanced plasma photonics and compact accelerator technologies, offering a promising route towards sustainable, high-repetition-rate plasma-based facilities.
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All authors M. Galletti, L. Verra, A. Biagioni, M. Carillo, L. Crincoli, R. Demitra, G. Parise, G. Di Pirro, R. Pompili, F. Stocchi, F. Villa, A. Zigler, M. Ferrario

Optics

Experimental investigation of the effect of dispersion on squeezing generation in a synchronously pumped optical parametric oscillator

Edoardo Suerra, Samuele Altilia, Stefano Olivares et al. (+4 more)

An experimental investigation of intracavity dispersion effects in a synchronously pumped optical parametric oscillator (SPOPO) is presented. A flexible setup combining spectral and phase shaping of both pump and local oscillator fields with frequency-resolved balanced homodyne detection is employed to examine how intracavity dispersion influences squeezing. Different cavity configurations with varying finesse and dispersion conditions are studied, and the squeezing is measured as a function of pump power and local oscillator bandwidth. Contrary to expectations based on existing theoretical models, the measured squeezing levels remain essentially unchanged as dispersion varies. To account for these observations, a modeling approach is introduced in which intracavity dispersion is described as an effective spectral filtering occurring at the stage of SPOPO supermode generation. Within this framework, the filtering is incorporated directly into the interaction Hamiltonian of the nonlinear process. This perspective establishes a consistent experimental benchmark for the study of dispersion in SPOPOs and underscores the importance of spectral filtering in the interpretation of multimode squeezing experiments.
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All authors Edoardo Suerra, Samuele Altilia, Stefano Olivares, Alessandro Ferraro, Sebastiano Corli, Enrico Prati, Simone Cialdi

Atomic Physics

Full Single-Quantum Control of Particles in Penning Traps for Symmetry Tests at the Quantum Limit

J.M. Cornejo, J.-A. Coenders, A. Lissel et al. (+9 more)

The BASE collaboration aims to measure antimatter systems with the highest precision in order to perform a rigorous test of CPT symmetry and search for physics beyond the Standard Model. As part of the BASE collaboration, we pursue the development of quantum logic inspired cooling and detection techniques for g-factor measurements of (anti-)protons. Implementing these methods requires full quantum-level control of individual antimatter particles confined in cryogenic Penning traps. By mapping the (anti-)proton's internal state onto a co-trapped 9Be+ "logic" ion via free Coulomb coupling in a double-well potential, we can accelerate measurement cycles and push g-factor precision measurements on (anti-)protons toward the quantum limit. Here, we present an overview of the proposed method and the current status of the project, with special emphasis on the new cryogenic multi-Penning-trap stack and the proton detection system.
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All authors J.M. Cornejo, J.-A. Coenders, A. Lissel, N. Poljakov, M. Prasse, Y. Priewich, J. Schaper, M. Schubert, B. Hampel, M. Schilling, S. Ulmer, C. Ospelkaus

History and Philosophy of Physics · Cross-listed from quant-ph

No Absolute Hierarchy of Quantum Complementarity

Kunika Agarwal, Sahil Gopalkrishna Naik, Ananya Chakraborty et al. (+4 more)

Bohr's principle of complementarity, prohibiting simultaneous access to certain physical properties within a single experimental arrangement, is considered to be a defining feature of quantum mechanics. It is commonly viewed as inducing an intrinsic hierarchy among incompatible observables: some sets of quantum properties are fundamentally more incompatible than others, as quantified by the maximal sharpness permitting their joint measurement. We show that this hierarchy ceases to be absolute in the multi-copy regime. Analyzing qubit spin observables, we prove a No-Comparison Theorem establishing that no global ordering of incompatible observable sets is preserved across all finite-copy configurations. In particular, two sets of observables can exhibit reversed complementarity ordering depending solely on whether the available resources are arranged as identical copies or as parallel-antiparallel pairs. Thus, the degree of quantum incompatibility is not an intrinsic property of observables alone but depends on the global configuration of the prepared quantum probes. Our results uncover a configuration-dependent structure of complementarity, reveal a subtle role of entanglement in shaping the structure of measurement limitations, and call for a reassessment of quantum information protocols under finite resources.
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All authors Kunika Agarwal, Sahil Gopalkrishna Naik, Ananya Chakraborty, Guruprasad Kar, Ram Krishna Patra, Snehasish Roy Chowdhury, Manik Banik

Computational Physics · Cross-listed from cond-mat.mes-hall

First-principles and tight-binding analysis of thermoelectricity in irradiated WSe$_2$

Cynthia Ihuoma Osuala, Tanu Choudhary, Raju K. Biswas et al. (+2 more)

Electronic and thermoelectric transport in zigzag monolayer WSe$_2$ nanoribbons are studied under monochromatic irradiation. The electronic structure is described within a six-orbital tight-binding framework constructed from the relevant tungsten and selenium orbitals, with atomic spin-orbit coupling included explicitly. Periodic driving is incorporated via the Peierls substitution, and in the high-frequency limit the system is mapped onto an effective static Floquet Hamiltonian with polarization-dependent renormalized hoppings. Coherent transport is evaluated using wave-function matching within the Landauer-Büttiker formalism. The lattice thermal conductivity is obtained independently from density functional perturbation theory combined with an iterative solution of the phonon Boltzmann transport equation. Light-induced hopping renormalization reshapes the band dispersion and transmission spectrum near the Fermi level, modifying the Landauer transport integrals that determine electrical and thermal conductances and the Seebeck coefficient. Together with spin-orbit-driven band splitting and reduced lattice thermal conductivity from enhanced anharmonic scattering, this leads to a thermoelectric figure of merit $ZT$ exceeding unity over a broad temperature range.
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All authors Cynthia Ihuoma Osuala, Tanu Choudhary, Raju K. Biswas, Sudin Ganguly, Santanu K. Maiti

Data Analysis and Statistics · Cross-listed from quant-ph

Optimization-based Unfolding in High-Energy Physics

Simone Gasperini, Gianluca Bianco, Marco Lorusso et al. (+2 more)

In experimental High-Energy Physics, unfolding refers to the problem of estimating the underlying distribution of a physical observable from detector-level data, in the presence of statistical fluctuations and systematic uncertainties. Starting from its reformulation as a regularized quadratic optimization problem, we develop a framework to address unfolding using both classical and quantum-compatible methods. In particular, we derive a Quadratic Unconstrained Binary Optimization (QUBO) representation of the unfolding objective, allowing direct implementation on quantum annealing and hybrid quantum-classical solvers. The proposed approach is implemented in QUnfold, an open-source Python package integrating classical mixed-integer solvers and D-Wave's hybrid quantum solver. We benchmark the method against widely used unfolding techniques in RooUnfold, including response Matrix Inversion, Iterative Bayesian Unfolding, and Singular Value Decomposition unfolding, using synthetic datasets with controlled distortion effects. Our results demonstrate that the optimization-based approach achieves competitive reconstruction accuracy across multiple distributions while naturally accommodating regularization within the objective function. This work establishes a unified optimization perspective on unfolding and provides a practical pathway for exploring quantum-enhanced methods in experimental HEP data analysis.
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All authors Simone Gasperini, Gianluca Bianco, Marco Lorusso, Carla Rieger, Michele Grossi

Fluid Dynamics

Acoustic Signatures of Pinch-Off Cavities During Water-Entry

Zirui Liu, Tongtong Ding, Mingyue Kuang et al. (+4 more)

This study experimentally, numerically, and theoretically investigates the cavity/bubble dynamics and radiated acoustics during the water entry of a centimeter-scale cylindrical projectile with a conical nose. Experiments were conducted in a laboratory tank, employing synchronized high-speed imaging and hydrophone measurements to characterize the cavity closure modes and their resultant acoustic signatures across a range of Froude numbers. The acoustic signal features a weak radiated signal upon impact, followed by significant pressure oscillations spanning more than 20 cycles in the flow field after cavity elongation and pinch-off. A numerical model based on the Finite Volume Method (FVM) successfully captures these physical processes. Subsequently, a semi-theoretical model that incorporates the projectile's boundary effect is developed from potential flow theory. The model not only yields a dominant cavity oscillation frequency that agrees well with experimental data, but also reveals that the boundary effect leads to a cavity oscillation frequency markedly higher than the Minnaert frequency of an equivalent-volume ellipsoidal bubble containing an internal rigid core. The dominant cavity frequency falls nearly linearly with Fr, governed by nose geometry and projectile inertia. This study clarifies the underlying physics connecting cavity dynamics during water entry to underwater acoustic radiation.
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All authors Zirui Liu, Tongtong Ding, Mingyue Kuang, Zimeng Li, Junyi Zhao, A-Man Zhang, Shuai Li

Optics

Quantum squeezing in an all-resonant periodically poled lithium niobate microresonator

Xinyi Ren, Reshma Kopparapu, Tushar Sanjay Karnik et al. (+12 more)

Quantum noise limits the sensitivity of optical measurements, but squeezed states of light enable quantum-enhanced metrology, sensing, and information processing. Most on-chip squeezed-light sources rely on Kerr ($\chi^{(3)}$) nonlinearities, remain limited by pump power and excess loss constraints. Quadratic ($\chi^{(2)}$) platforms instead provide stronger parametric interactions, lower pump power requirements, and greater spectral engineering flexibility. Here, we demonstrate strong, broadband squeezed-light generation on a thin-film lithium niobate (TFLN) photonic chip using a dual-resonant optical parametric amplifier implemented in a single periodically poled LN (PPLN) microresonator. Near-full-depth domain inversion is achieved simultaneously with highly over-coupled resonances, exhibiting escape efficiencies exceeding 90% and intrinsic quality factors above 2.5 million in a 0.6 mm$^2$ X-cut TF-PPLN resonator, enabling efficient squeezing at 1587 nm when pumped at 793.5 nm. Operating in the continuous-wave regime, we directly measure -0.81 dB of squeezing below the shot-noise limit with a pump power of 27 mW, together with +4.29 dB of anti-squeezing. From these measurements, we infer an on-chip squeezing level of -7.52 dB $\pm$ 0.22 dB (95% confidence interval: [-7.96,-7.10] dB), and an on-chip anti-squeezing level of +9.62 dB $\pm$ 0.25 dB. We demonstrate single-mode squeezing at degeneracy with a squeezed-light spectrum exceeding 10.3 THz. This work reports the highest squeezing ratio among integrated $\chi^{(2)}$ cavity platforms and the first quasi-phase matched, fully resonant $\chi^{(2)}$ cavity squeezer on chip, establishing a scalable route to fully integrated power-efficient squeezed-light sources for quantum-enhanced sensing and metrology.
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All authors Xinyi Ren, Reshma Kopparapu, Tushar Sanjay Karnik, Chun-Ho Lee, Kiwon Kwon, Clayton Cheung, Yue Yu, Shi-Yuan Ma, Bo-Han Wu, Ran Yin, Lian Zhou, Quntao Zhuang, Dirk Englund, Zaijun Chen, Mengjie Yu

Optics · Cross-listed from quant-ph

Quantum-Optically Resolving the Number of Colloidal Quantum Dots in a Subwavelength Volume

Zhi-Bo Ni, Jia-Wang Yu, Jiong-Zhao Li et al. (+9 more)

The number resolution of solid-state artificial atoms is of fundamental interest for the study of quantum few-body systems, yet remains experimentally challenging. Quantum optical experiments offer a non-invasive approach which links up macroscopic measurements with the quantity of quantum emitters. In this work, we propose a time-domain quantum optical methodology for the strict numbering of colloidal CdSe/CdS/ZnS quantum dots (QDs) confined in subwavelength-size polystyrene capsules. The non-polarized, homogeneously broadened emission of colloidal QDs in the subwavelength volume satisfies the description of Dicke's superradiance of identical quantum emitters. An analytic relation describes the numerical dependence of the second-order photon correlation on the number and the collective lifetime of emitters, yielding an experimental counting range of colloidal QDs from one to ten. This work provides a robust pathway for the non-invasive numbering of artificial atoms and the investigation of collective light-matter interactions at the nanoscale.
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All authors Zhi-Bo Ni, Jia-Wang Yu, Jiong-Zhao Li, Xiao-Tian Cheng, Mei-Na Jiang, Zi-Xuan Song, Xiao-Qing Zhou, Wei Fang, Chen-Hui Li, Feng Liu, Xing Lin, Chao-Yuan Jin

Plasma Physics

Gyrokinetic turbulent transport simulations on steady burning condition in D-T-He plasmas

Motoki Nakata and Mitsuru Honda

Ion temperature gradient(ITG) and trapped electron modes(TEM) driven turbulent transport in an ITER-like plasma is investigated by means of multi-species gyrokinetic Vlasov simulations with D, T, He, and real-mass kinetic electrons including their inter-species collisions. Beyond the conventional zero-dimensional power balance analysis presuming the global energy and particle confinement times, gyrokinetic-simulation-based evaluation of a steady burning condition with He-ash exhaust and D-T fuel inward pinch is demonstrated. It is clarified that a significant imbalance appears in the turbulent particle flux for the fuel ions of D and T, depending on the D-T density ratio and the He-ash accumulation. Then several profile regimes to satisfy Reiter's steady burning condition are, for the first time, identified by the gyrokinetic simulation. Also, the impacts of zonal flows and nonthermal He-ash on the optimal profile regimes are examined.
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Plasma Physics

Isotope Effects on TEM-driven Turbulence and Zonal Flows in Helical and Tokamak Plasmas

Motoki Nakata, Masanori Nunami, Hideo Sugama et al. (+1 more)

Impacts of isotope ion mass on trapped electron mode (TEM) driven turbulence and zonal flows in magnetically confined fusion plasmas are investigated. Gyrokinetic simulations of TEM-driven turbulence in three-dimensional magnetic configuration of LHD plasmas with hydrogen isotope ions and real-mass kinetic electrons are realized for the first time, and the linear and the nonlinear nature of the isotope and collisional effects on the turbulent transport and zonal-flow generation is clarified. It is newly found that combined effects of the collisional TEM stabilization by the isotope ions and the associated increase in the impacts of the steady zonal flows at the near-marginal linear stability lead to the significant transport reduction with the opposite ion mass dependence in comparison to the conventional gyro-Bohm scaling. The universal nature of the isotope effects on the TEM-driven turbulence and zonal flows is verified for a wide variety of toroidal plasmas, e.g., axisymmetric tokamak and non-axisymmetric helical/stellarator systems.
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All authors Motoki Nakata, Masanori Nunami, Hideo Sugama, Tomo-Hiko Watanabe

Plasma Physics

Nonlinear entropy transfer via zonal flows in gyrokinetic plasma turbulence

Motoki Nakata, Tomo-Hiko Watanabe and Hideo Sugama

Nonlinear entropy transfer processes in toroidal ion temperature gradient (ITG) and electron temperature gradient (ETG) driven turbulence are investigated based on the gyrokinetic entropy balance relations for zonal and non-zonal modes, which are coupled through the entropy transfer function regarded as a kinetic extension of the zonal-flow production due to the Reynolds stress. Spectral analyses of the "triad" entropy transfer function introduced in this study reveal not only the nonlinear interactions among the zonal and non-zonal modes, but also their effects on the turbulent transport level. Different types of the entropy transfer processes between the ITG and ETG turbulence are found: The entropy transfer from non-zonal to zonal modes is substantial in the saturation phase of the ITG instability, while, once the strong zonal flow is generated, the entropy transfer to the zonal modes becomes quite weak in the steady turbulence state. Instead, the zonal flows mediate the entropy transfer from non-zonal modes with low radial-wavenumbers (with contribution to the heat flux) to the other non-zonal modes with higher radial-wavenumbers (but with less contribution to the heat flux) through the triad interaction. The successive entropy transfer processes to the higher radial-wavenumber modes are associated with transport regulation in the steady turbulence state. In contrast, in both the instability-saturation and steady phases of the ETG turbulence, the entropy transfer processes among low-wavenumber non-zonal modes are dominant rather than the transfer via zonal modes.
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Optics

Emerging Multidimensional Real-Space Topological Structures at Chiral Bound States in the Continuum

Xingqi Zhao, Jingguang Chen, Jiajun Wang et al. (+6 more)

As widely studied topological singularities, bound states in the continuum (BICs) have revealed rich physical properties through their momentum-space topology. Here, we reveal and experimentally demonstrate that magnetically induced chiral BICs possess multidimensional topological structures extending into real space. We design and realize a gyromagnetic photonic crystal slab where magnetic field breaks the time-reversal symmetry and lifts the degeneracy of BICs, creating a pair of chiral BICs with opposite circular polarizations. Near-field scanning measurements reveal phase vortices with quantized topological charges, spatially distributed near-field chirality, and skyrmionic Stokes textures arising from magnetic control. Our work unveils a previously unexplored dimension of BIC topology and establishes gyromagnetic photonic crystals as versatile platforms for manipulating complex topological states.
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All authors Xingqi Zhao, Jingguang Chen, Jiajun Wang, Lixi Rao, Wenzhe Liu, Fang Guan, C. T. Chan, Lei Shi, Jian Zi

Accelerator Physics

Advancing accelerator virtual beam diagnostics through latent evolution modeling: an integrated solution to forward, inverse, tuning, and UQ problems

Mahindra Rautela and Alexander Scheinker

Virtual beam diagnostics relies on computationally intensive beam dynamics simulations where high-dimensional charged particle beams evolve through the accelerator. We propose Latent Evolution Model (LEM), a hybrid machine learning framework with an autoencoder that projects high-dimensional phase spaces into lower-dimensional representations, coupled with transformers to learn temporal dynamics in the latent space. This approach provides a common foundational framework addressing multiple interconnected challenges in beam diagnostics. For forward modeling, a Conditional Variational Autoencoder (CVAE) encodes 15 unique projections of the 6D phase space into a latent representation, while a transformer predicts downstream latent states from upstream inputs. For inverse problems, we address two distinct challenges: (a) predicting upstream phase spaces from downstream observations by utilizing the same CVAE architecture with transformers trained on reversed temporal sequences along with aleatoric uncertainty quantification, and (b) estimating RF settings from the latent space of the trained LEM using a dedicated dense neural network that maps latent representations to RF parameters. For tuning problems, we leverage the trained LEM and RF estimator within a Bayesian optimization framework to determine optimal RF settings that minimize beam loss. This paper summarizes our recent efforts and demonstrates how this unified approach effectively addresses these traditionally separate challenges.
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Plasma Physics · Cross-listed from astro-ph.SR

A Multi-Diagnostic Observational Framework for Magnetosonic Solitary Waves During Geomagnetic Storms in Solar Cycles 24 and 25 using Cluster II Mission

Murchana Khusroo and Yimnasangla

Solitary structures, commonly known as solitons, are a class of nonlinear plasma waves that are abundantly found in near-Earth plasmas and planetary magnetospheres. They are nonlinear, localized plasma waves that maintain their shape and velocity over time and distance. While their occurrence in various space plasma environments has been extensively reported, their observation during geomagnetic storms, large-scale disturbances driven by interactions between the solar wind and Earth's magnetosphere, remains limited. In this study, we present a comparative investigation of magnetosonic soliton signatures during geomagnetic storms associated with Solar Cycles 24 and 25. Using high-resolution in-situ magnetic field measurements from the Cluster II mission, we systematically examine the plasma conditions favorable for soliton generation and their evolution during storm-time dynamics. A comprehensive multi-diagnostic observational framework, incorporating several state-of-the-art analytical techniques, is developed to reliably detect and characterize magnetosonic solitons. The results demonstrate that solitary structures in both storms predominantly occur during the early storm intervals, prior to the main phase, suggesting that they may serve as potential precursor signatures of enhanced geomagnetic activity.
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Data Analysis and Statistics · Cross-listed from cs.IT

A Thermodynamic Structure of Asymptotic Inference

Willy Wong

A thermodynamic framework for asymptotic inference is developed in which sample size and parameter variance define a state space. Within this description, Shannon information plays the role of entropy, and an integrating factor organizes its variation into a first-law-type balance equation. The framework supports a cyclic inequality analogous to a reversed second law, derived for the estimation of the mean. A non-trivial third-law-type result emerges as a lower bound on entropy set by representation noise. Optimal inference paths, global bounds on information gain, and a natural Carnot-like information efficiency follow from this structure, with efficiency fundamentally limited by a noise floor. Finally, de Bruijn's identity and the I-MMSE relation in the Gaussian-limit case appear as coordinate projections of the same underlying thermodynamic structure. This framework suggests that ensemble physics and inferential physics constitute shadow processes evolving in opposite directions within a unified thermodynamic description.
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Optics

Ab-initio study of high harmonic generation from fullerenes: Multi-orbital effects, correlations, and size dependence

Km Akanksha Dubey and Ofer Neufeld

We study with ab-initio theory high harmonic generation (HHG) from a series of gas-phase fullerenes (from C$_{20}$ to C$_{60}$, including isomers) under varying laser conditions (linearly polarized at various angles and different ellipticities). We explore the role of multiple orbitals in the dynamics and show that due to the tight energy level spacing in these systems (forming the equivalent of energy bands), multiple orbitals contribute and cause severe spectral interferences. HHG cutoff and plateau ranges are shown relatively similar across species of different sizes. We further explore the role of correlations, which are known to be prevalent in C$_{60}$ and similar species and responsible for plasmonic resonances. We find that the independent-particle approximation, where electrons are not dynamically interacting, fails to quantitatively describe features in the spectrum besides the cutoff energy. This failure is broad across the HHG plateau and perturbative regime in all species. Broadly, correlations are seen to reduce HHG yields and cause sharper emission peaks. Lastly, we study HHG ellipticity and angular dependence across species and show that: (i) HHG angular sensitivity becomes less prevalent for larger fullerenes. This arises from a more isotropic structure of the higher point-group molecules. (ii) HHG yields decay faster with the driving laser ellipticity for smaller systems, owing to their reduced size creating smaller recombination cross sections with re-colliding electron wave packets (with C$_{60}$ posing an anomalous exception to this rule). Our predictions pin-point fullerenes as an ideal system for exploring multi-electron interactions in HHG and strong-field physics, and should motivate experiments.
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Physics and Society

The Swarm Intelligence Freeway-Urban Trajectories (SWIFTraj) Dataset – Part I: Dataset Description and Applications

Yu Han, Xinkai Ji, Chen Qian et al. (+3 more)

This paper presents a detailed description and characterization of a new open-source vehicle trajectory dataset, namely SWIFTraj, constructed from videos recorded by a swarm of 16 drones equipped with 5.4K-resolution cameras. The dataset is distinguished from existing open-source trajectory datasets in several aspects. First, it provides long-distance continuous trajectories of up to 4.5 km on a freeway, enabling in-depth investigation of traffic phenomena and their spatial and temporal evolution. Second, the data collection site covers an integrated network consisting of a long freeway corridor and parts of its connected urban network, facilitating traffic analysis and modeling from a network perspective. The potential applications of the dataset for transportation research, including traffic flow analysis, modeling, and control at multiple scales, as well as topics related to autonomous driving, are thoroughly discussed. Finally, SWIFTraj is released as a freely accessible open-source dataset to support and accelerate future research in the transportation community. The dataset is publicly available at the SWIFTraj website (https://www.swiftraj.com).
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All authors Yu Han, Xinkai Ji, Chen Qian, Le Zhang, Ying Yang, Pan Liu

Plasma Physics · Cross-listed from quant-ph

Optimizing Doppler laser cooling protocols for quantum sensing with 3D ion crystals in a Penning trap

John Zaris, Wes Johnson, Athreya Shankar et al. (+4 more)

Large, 3D trapped ion crystals offer improved sensitivity in quantum sensing protocols, and are expected to be implemented as platforms in near-future experiments. However, numerical techniques used to study the laser cooling of such crystals are inefficient as the number of ions, $N$, in the crystal increases. Here we develop a powerful numerical framework to simulate laser cooling of up to $10^5$ ions stored in a Penning trap. We apply this framework to characterize and optimize the cooling of ellipsoidal 3D crystals. We document new pathways to enhanced cooling based on the addition of an axial component to the potential energy-dominated $\boldsymbol{E}\times\boldsymbol{B}$ modes. Furthermore, we observe greatly enhanced cooling of the perpendicular kinetic energy to below 1 mK in prolate ion crystals, enabling a simplified cooling beam setup for such crystals. We propose specific values of trap and laser beam parameters which lead to optimal cooling in a variety of examples. This work illustrates the feasibility of preparing large 3D crystals for high-sensitivity quantum science protocols, motivating their use in future experiments.
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All authors John Zaris, Wes Johnson, Athreya Shankar, John J. Bollinger, Allison L. Carter, Daniel H.E. Dubin, Scott E. Parker

Medical Physics

Evaluating the resolution of AI-based accelerated MR reconstruction using a deep learning-based model observer

Zitong Yu, Rongping Zeng, Frank Samuelson et al. (+1 more)

Deep Learning-based Model Observers (DLMOs) were developed to evaluate a multi-coil sensitivity encoding parallel MRI at different acceleration factors on the Rayleigh discrimination task as a surrogate measure of resolution. Gaussian-convolved singlet and doublet signals with varying intensities and lengths were inserted into the white matter of synthetic brain images. K-space data were generated using a simulated MRI at acceleration factors of one (1x, fully sampled), 4.9x, and 16.4x, and reconstructed using a conventional root-sum-of-squares (rSOS) method and an AI-based U-Net method. DLMOs were first trained on fully sampled images and then fine-tuned for each acceleration factor using transfer learning. With a human-label alignment training strategy, the DLMOs achieved discrimination performance similar to that of trained human observers. Resolution was assessed using the area under the receiver operating characteristic curve (AUC), while PSNR and SSIM provided complementary task-agnostic comparisons. Although the U-Net method yielded significantly higher PSNR and SSIM than rSOS across different acceleration factors (p<0.05), task-based evaluation using the proposed DLMO showed inferior performance relative to fully sampled reconstruction. U-Net (4.9x) exhibited modest gains over rSOS (4.9x) for short signals (4-5 mm), but its AUC decreased by approximately 25% and 5% for 4 mm and 5 mm signals, respectively, compared with rSOS (1x). Similar declines were observed for U-Net (16.4x). These results demonstrate that AI-based accelerated MR reconstruction may improve visual appearance, but may not preserve task performance. The proposed DLMO approach may be employed to characterize the discriminative efficacy of AI-based undersampled MRI reconstruction.
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All authors Zitong Yu, Rongping Zeng, Frank Samuelson, Prabhat Kc

Atmospheric and Oceanic Physics

A Synergistic Approach: Dynamics-AI Ensemble in Tropical Cyclone Forecasting

Yonghui Li, Wansuo Duan, Hao Li et al. (+3 more)

This study addresses a critical challenge in AI-based weather forecasting by developing an AI-driven optimized ensemble forecast system using Orthogonal Conditional Nonlinear Optimal Perturbations (O-CNOPs). The system bridges the gap between computational efficiency and dynamic consistency in tropical cyclone (TC) forecasting. Unlike conventional ensembles limited by computational costs or AI ensembles constrained by inadequate perturbation methods, O-CNOPs generate dynamically optimized perturbations that capture fast-growing errors of FuXi model while maintaining plausibility. The key innovation lies in producing orthogonal perturbations that respect FuXi nonlinear dynamics, yielding structures reflecting dominant dynamical controls and physically interpretable probabilistic forecasts. Demonstrating superior deterministic and probabilistic skills over the operational Integrated Forecasting System Ensemble Prediction System, this work establishes a new paradigm combining AI computational advantages with rigorous dynamical constraints. Success in TC track forecasting paves the way for reliable ensemble forecasts of other high-impact weather systems, marking a major step toward operational AI-based ensemble forecasting.
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All authors Yonghui Li, Wansuo Duan, Hao Li, Wei Han, Han Zhang, Yinuo Li

Optics

Photonic Neuromorphic Computing enabled by a BIC Metasurface

Jingsong Fu, Ruiheng Jin, Zhaohui Xie et al. (+8 more)

Photonic neuromorphic computing promises revolutionary advances in parallel and high-speed processing, yet a key challenge persists: co-integrating nonlinearity, dense connectivity, and intrinsic memory monolithically to enable brain-inspired, spatiotemporal information processing. Here, we overcome this challenge by introducing a monolithic photonic recurrent network based on an active metasurface operating at bound state in the continuum (BIC). The BIC mode mediates strong,long-range coupling across the lattice, creating a reconfigurable recurrent network topology in hardware. Concurrently, the gain medium provides both optical nonlinearity for neuronal activation and a finite carrier lifetime that serves as a built in, analog temporal memory. This synergy enables computation to emerge directly from the collective spatiotemporal dynamics of the driven-dissipative photonic system, effectively realizing a physical reservoir computer on a chip. We experimentally validate a minimal yet physically complete system on benchmark tasks: brain MRI image classification and human action recognition, achieving 92.16% and 85.36% accuracies, respectively. This work establishes a scalable pathway toward ultrafast, energy-efficient neuromorphic intelligence where processing is an inherent property of tailored light matter interaction.
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All authors Jingsong Fu, Ruiheng Jin, Zhaohui Xie, Haijun Tang, Xiong Jiang, Yue Cui, Xiangtong Kong, Wentao Hao, Geyang Qu, Can Huang, Qingha Song

Classical Physics

Nonlinear stabilization of chiral modes in space-time modulated parametric oscillators

Scott Lambert, Elise Jaremko and Jayson Paulose

Phase control of parametric modulation in coupled oscillator networks enables these networks to access dynamical states with desired spatiotemporal symmetries. Floquet theory-based approaches successfully predict such states in linear systems, but whether their symmetry properties persist under nonlinearity remains largely unexplored. Here, we establish the existence of nonlinear chiral steady states in a ring of three coupled parametric oscillators with modulation phases chosen to selectively amplify a circulating mode in the linearized system. We find that a cubic nonlinearity limits the exponential growth of the amplified mode, producing a steady finite-amplitude motion that retains the expected chirality. By exploiting the system's spatiotemporal symmetry, we reduce the dynamics to a single averaged equation that quantitatively predicts nonlinear trajectories, steady-state amplitudes, and characteristic time scales of the full three-body system. The chiral steady states possess finite basins of attraction and are accessible from wide ranges of initial conditions and system parameters. Finite-element simulations of elastic plate resonators quantitatively reproduce these features, establishing the relevance of the reduced model to realistic continuum systems. Our results demonstrate that desirable properties of linear time-modulated systems, such as chirality and directional amplification, persist into strongly nonlinear regimes, opening pathways to robust nonreciprocal signal routing and amplification in parametrically driven platforms.
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