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Physics Physics

physics Watch Physics

Monday 3 November

Computational Physics

A fast and rigorous numerical tool to measure length-scale artifacts in molecular simulations

Benedikt M. Reible, Nils Liebreich, Carsten Hartmann et al. (+1 more)

The two-sided Bogoliubov inequality for classical and quantum many-body systems is a theorem that provides rigorous bounds on the free-energy cost of partitioning a given system into two or more independent subsystems. This theorem motivates the definition of a quality factor which directly quantifies the degree of statistical-mechanical consistency achieved by a given simulation box size. A major technical merit of the theorem is that, for systems with two-body interactions and a known radial distribution function, the quality factor can be computed by evaluating just two six-dimensional integrals. In this work, we present a numerical algorithm for computing the quality factor and demonstrate its consistency with respect to results in the literature obtained from simulations performed at different box sizes.
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All authors Benedikt M. Reible, Nils Liebreich, Carsten Hartmann, Luigi Delle Site

Optics

Broadly tunable quantum-enhanced Raman microscopy for advancing bioimaging

Dmitrii Akatev, Yijian Meng, Jonathan Brewer et al. (+3 more)

Stimulated Raman scattering (SRS) microscopy has emerged as a powerful technique for probing the spatiotemporal dynamics of molecular bonds with exceptional sensitivity, resolution, and speed. However, classically, its performance remains fundamentally constrained by optical shot noise, which imposes a strict limit on detection sensitivity and speed. Here, we demonstrate a quantum-enhanced SRS microscopy platform that circumvents this barrier by harnessing amplitude-squeezed light. Specifically, we generate a Stokes beam with $5.2~\mathrm{dB}$ of amplitude squeezing using traveling-wave optical parametric amplification in second-order nonlinear waveguides, and combine it with a tunable coherent pump to access vibrational modes spanning from $1000$ to $3100~\mathrm{cm}^{-1}$. Applied to quantum imaging of metabolites in biological tissue (pork muscle), our quantum-enhanced Raman microscope achieves an average noise suppression of $3.6~\mathrm{dB}$ and a $51\%$ enhancement in signal-to-noise ratio (SNR) – to the best of our knowledge, the largest improvement reported to date in quantum-enhanced SRS microscopy of biological samples.
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All authors Dmitrii Akatev, Yijian Meng, Jonathan Brewer, Maria Chekhova, Ulrik L. Andersen, Mikael Lassen

Computational Physics · Cross-listed from cond-mat.mtrl-sci

Intertwined Hyperferroelectricity, Tunable Multiple Topological Phases and Giant Rashba Effect in Wurtzite LiZnAs

Saurav Patel, Paras Patel, Shaohui Qiu et al. (+1 more)

Composite quantum compounds offer a fertile ground for uncovering the complex interrelations between seemingly distinct phenomena in condensed matter physics for advanced nonvolatile and spintronics applications. Beyond topological superconductors and axion insulators, the idea of intertwined Hyperferroelectricity (HyFE), multiple topological phases and Rashba spin-splitting with reversible spin textures represents the local, global and symmetry-driven characteristics of quantum materials, respectively, offering unique pathways for enhanced functionalities. We unveiled a unified framework to achieve this synergy through the presence of crystalline symmetries and spin-orbit coupling in LiZnAs compound using first-principles calculations. HyFE exhibits ability to maintain spontaneous polarization under open-circuit boundary conditions, even with existence of depolarization field while Rashba effect exhibits paradigmatic spin texture in momentum space with tangential vector field. The presence of unstable $A_{2u}(LO)$ mode leads to free energy minimum with significant well depth and polarization of -66 meV and $P_{HyFE} = 0.282~C/m^2$, respectively indicating stable HyFE. The robust HyFE stem from mode-specific effective charges and larger high-frequency dielectric constants. This study also addresses the subtle question of whether critical point of topological phase transition shifts in response to drastically different Rashba spin-splitting values obtained from VASP and WIEN2k. Moreover, biaxial strain (BAS) induced Weyl semimetal (at 3.4% BAS) and topological insulating phase (after 3.4% BAS) is observed with giant Rashba coefficient of 5.91 eV Å and 2.42 eV Å, respectively. Furthermore, switching of bulk polarization leads to spin texture reversal, providing a robust mechanism to leverage spin degrees of freedom in these Hyperferroelectric Rashba topological materials.
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All authors Saurav Patel, Paras Patel, Shaohui Qiu, Prafulla K. Jha

Data Analysis and Statistics · Cross-listed from cs.LG

MiniFool – Physics-Constraint-Aware Minimizer-Based Adversarial Attacks in Deep Neural Networks

Lucie Flek, Oliver Janik, Philipp Alexander Jung et al. (+8 more)

In this paper, we present a new algorithm, MiniFool, that implements physics-inspired adversarial attacks for testing neural network-based classification tasks in particle and astroparticle physics. While we initially developed the algorithm for the search for astrophysical tau neutrinos with the IceCube Neutrino Observatory, we apply it to further data from other science domains, thus demonstrating its general applicability. Here, we apply the algorithm to the well-known MNIST data set and furthermore, to Open Data data from the CMS experiment at the Large Hadron Collider. The algorithm is based on minimizing a cost function that combines a $\chi^2$ based test-statistic with the deviation from the desired target score. The test statistic quantifies the probability of the perturbations applied to the data based on the experimental uncertainties. For our studied use cases, we find that the likelihood of a flipped classification differs for both the initially correctly and incorrectly classified events. When testing changes of the classifications as a function of an attack parameter that scales the experimental uncertainties, the robustness of the network decision can be quantified. Furthermore, this allows testing the robustness of the classification of unlabeled experimental data.
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All authors Lucie Flek, Oliver Janik, Philipp Alexander Jung, Akbar Karimi, Timo Saala, Alexander Schmidt, Matthias Schott, Philipp Soldin, Matthias Thiesmeyer, Christopher Wiebusch, Ulrich Willemsen

Biological Physics · Cross-listed from cs.RO

Thermo-responsive closing and reopening artificial Venus Flytrap utilizing shape memory elastomers

Shun Yoshida, Qingchuan Song, Bastian E. Rapp et al. (+2 more)

Despite their often perceived static and slow nature, some plants can move faster than the blink of an eye. The rapid snap closure motion of the Venus flytrap (Dionaea muscipula) has long captivated the interest of researchers and engineers alike, serving as a model for plant-inspired soft machines and robots. The translation of the fast snapping closure has inspired the development of various artificial Venus flytrap (AVF) systems. However, translating both the closing and reopening motion of D. muscipula into an autonomous plant inspired soft machine has yet to be achieved. In this study, we present an AVF that autonomously closes and reopens, utilizing novel thermo-responsive UV-curable shape memory materials for soft robotic systems. The life-sized thermo-responsive AVF exhibits closing and reopening motions triggered in a naturally occurring temperature range. The doubly curved trap lobes, built from shape memory polymers, close at 38{\deg}C, while reopening initiates around 45{\deg}C, employing shape memory elastomer strips as antagonistic actuators to facilitate lobe reopening. This work represents the first demonstration of thermo-responsive closing and reopening in an AVF with programmed sequential motion in response to increasing temperature. This approach marks the next step toward autonomously bidirectional moving soft machines/robots.
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All authors Shun Yoshida, Qingchuan Song, Bastian E. Rapp, Thomas Speck, Falk J. Tauber

Optics

Direct Mapping of Intrinsic Topology of Bound States in the Continuum via Nonlinear Emission

Shuzheng Chen, Hongwei Wang, Zijian He et al. (+7 more)

The direct mapping of the intrinsic topology in a leaky photonic band is crucial and challenging in topological photonics. For instance, observables in bound states in the continuum (BICs) feature complex topological textures such as a polarization vortex in momentum space, which nonetheless is difficult to be characterized in far-field scattering, especially considering the dominant direct channel. Here, we propose and experimentally demonstrate a hybrid nonlinear metasurface that enables a direct visualization of the intrinsic topology in BICs via second-harmonic generation (SHG). The enhanced local-source of SHG from the ultrathin indium tin oxide can effectively excite the emissions from the eigenmodes of a TiO2 photonics crystal slab, achieving three-order enhancement of SHG magnitudes. Importantly, these enhanced SH emissions carry topological polarization textures of BICs to the far field. With this, we can directly construct polarization vector maps of symmetry-protected BICs and chiral symmetry-broken quasi-BICs, clearly visualizing the winding structure around V points, the generation and evolution of chiral C points. This work provides a universal approach for characterizing topological photonic systems via coherent nonlinearity processes, opening new avenues for studying topological phenomena in non-Hermitian photonic systems.
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All authors Shuzheng Chen, Hongwei Wang, Zijian He, Liyu Zhang, Kai Wang, Xu Jiang, Jiaxing Yang, Yuda Wan, Guangwei Hu, Peixiang Lu

Atomic Physics · Cross-listed from quant-ph

Light-induced Frequency Shift and Relaxation of Ground-State 3He via Metastability-Exchange Collisions

L. Y. Wu and H. Yan

Metastability-exchange collisions (MECs) lie at the heart of metastability-exchange optical pumping (MEOP) in 3He, enabling the transfer of polarization from the metastable state to the ground state, as well as the optical detection of nuclear magnetic resonance. Leveraging MECs, optically pumped 3He nuclear magnetometers have been developed since the earliest demonstrations of MEOP. However, it also induces an additional frequency shift and relaxation of the nuclear spin precession, thereby limiting the sensitivity of the magnetometer. In this work, we identify a new source of frequency shift and relaxation in the 3He nuclear spin, arising from the light shift. This effect arises from an MEC-mediated interaction between light and the nucleon spin. We develop a theoretical model to describe this light-induced effect and highlight its significance in low magnetic fields. This effect is experimentally demonstrated, and its dependence on various parameters – including magnetic field strength, light intensity, and wavelength – is investigated. Our result provides a better understanding of the frequency shift and relaxation of 3He spin precession under MEOP conditions. Moreover, our experiment reveals an MEC-mediated coupling between the 3He nuclear spin and light, which may indicate the feasibility of MEC-assisted optical manipulation of 3He nuclear spins at the quantum level, as proposed in several theoretical schemes.
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Optics

Temporal Transfer Matrix Method for Exceptional-Point Media via Canonical Basis Expansion

Neng Wang and Guo Ping Wang

We present a generalized temporal transfer matrix method (TTMM) for time-varying media that accurately captures wave dynamics in media operating at exceptional points (EPs). The method expands wave fields in the canonical basis of each temporal layer and derives the complete time evolution of all basis vectors. Temporal matching and phase-delay matrices are constructed from the generalized modal matrices and their corresponding eigenvalues. Additionally, an amplitude-boosting matrix is introduced to account for the power-law amplification of field amplitudes associated with EP dynamics. This matrix depends only on the order of the EP and naturally reduces to the identity matrix in its absence. The proposed TTMM is validated through two representative EP media, demonstrating its accuracy and broad applicability.
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Optics · Cross-listed from quant-ph

Super-resolved reconstruction of single-photon emitter locations from $g^{(2)}(0)$ maps

Sonali Gupta, Amit Kumar, Vikas S Bhat et al. (+1 more)

Single-photon sources are vital for emerging quantum technologies. In particular, Nitrogen-vacancy (NV) centers in diamond are promising due to their room-temperature stability, long spin coherence, and compatibility with nanophotonic structures. A key challenge, however, is the reliable identification of isolated NV centers, since conventional confocal microscopy is diffraction-limited and cannot resolve emitter distributions within a focal spot. Besides, the associated intensity scanning is a time-expensive procedure. Here, we introduce a raster-scanned $g^{(2)}(0)$ mapping technique combined with an inversion-based reconstruction algorithm. By directly measuring local photon antibunching across the field of view, we extract the effective emitter number within each focal spot and reconstruct occupancy maps on a sub-focal-spot grid. This enables recovery of the number and spatial distribution of emitters within regions smaller than the confocal focal spot, thereby offering possibilities of going beyond the diffraction limit. Our simulations confirm robust reconstruction of NV-center distributions. The method provides a practical diagnostic tool for locating single-photon sources in an efficient and accurate manner, at much lesser time and effort compared to conventional intensity scanning. It offers valuable feedback for nanophotonic device fabrication, supporting more precise and scalable integration of NV-based quantum photonic technologies.
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All authors Sonali Gupta, Amit Kumar, Vikas S Bhat, Sushil Mujumdar

Optics

NIR-II Fluorescence Project Technology for Augmented Reality Surgical Navigation

Yuhuang Zhang, Xiaolong Liu, Zihang Liu et al. (+8 more)

NIR-II fluorescence imaging provides superior tissue penetration and clarity, yet its clinical use in surgical navigation is hindered by a critical workflow issue. Surgeons must divert their attention between the operative field and external monitors, increasing cognitive load and disrupting procedures. Current strategies have failed to resolve this fundamental problem. Here, we developed a co-axial NIR-II fluorescence projection navigation system to enable real-time, in situ visualization. This system creates an intraoperative augmented reality by directly projecting high-precision, pseudocolored fluorescence images onto the surgical field, spatially integrating functional signals with patient anatomy. Validated through in vitro, in vivo, and clinical patient studies, our system eliminates visual field switching, reduces intraoperative distraction, and preserves natural stereoscopic vision. This approach represents a paradigm shift toward a more coherent, efficient, and ergonomically optimized optical imaging modality for surgical navigation.
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All authors Yuhuang Zhang, Xiaolong Liu, Zihang Liu, Chao Liu, Jie Yang, Jian Feng, Siying Sun, Zhe Feng, Xiaoxiao Fan, Hui Lin, Jun Qian

Fluid Dynamics

Convective flux analysis on the propagation mechanism of oblique detonation waves

Yunfeng Liu

The aim of this study is to investigate the propagation mechanism of oblique detonation waves using the vector flux analysis method through numerical simulations. A two-dimensional numerical study is conducted on stoichiometric hydrogen-air oblique detonation waves based on the conservative Euler equations and a one-step global chemical reaction model. The wedge angle is 25{\deg}, with a freestream static temperature of 851.5 K, velocity of 2473.4 m/s, and pressure of 42.5 kPa. The motion mechanism of transverse waves is analyzed using the vector flux method. The results show that the oblique detonation front consists of three regions: an induction zone, an overdriven detonation zone, and a transverse-wave region. Under different activation energies, only either upward-propagating or downward-propagating transverse waves exist on the oblique detonation front; the two do not occur simultaneously. At low activation energy, downward-propagating transverse waves dominate, whereas at high activation energy, upward-propagating transverse waves appear.
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Fluid Dynamics · Cross-listed from cs.GR

An Adjoint Method for Differentiable Fluid Simulation on Flow Maps

Zhiqi Li, Jinjin He, Barnabás Börcsök et al. (+6 more)

This paper presents a novel adjoint solver for differentiable fluid simulation based on bidirectional flow maps. Our key observation is that the forward fluid solver and its corresponding backward, adjoint solver share the same flow map as the forward simulation. In the forward pass, this map transports fluid impulse variables from the initial frame to the current frame to simulate vortical dynamics. In the backward pass, the same map propagates adjoint variables from the current frame back to the initial frame to compute gradients. This shared long-range map allows the accuracy of gradient computation to benefit directly from improvements in flow map construction. Building on this insight, we introduce a novel adjoint solver that solves the adjoint equations directly on the flow map, enabling long-range and accurate differentiation of incompressible flows without differentiating intermediate numerical steps or storing intermediate variables, as required in conventional adjoint methods. To further improve efficiency, we propose a long-short time-sparse flow map representation for evolving adjoint variables. Our approach has low memory usage, requiring only 6.53GB of data at a resolution of $192^3$ while preserving high accuracy in tracking vorticity, enabling new differentiable simulation tasks that require precise identification, prediction, and control of vortex dynamics.
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All authors Zhiqi Li, Jinjin He, Barnabás Börcsök, Taiyuan Zhang, Duowen Chen, Tao Du, Ming C. Lin, Greg Turk, Bo Zhu

Geophysics

Diffusion Models Bridge Deep Learning and Physics in ENSO Forecasting

Weifeng Xu, Xiang Zhu, Xiaoyong Li et al. (+19 more)

Accurate long-range forecasting of the El \Nino-Southern Oscillation (ENSO) is vital for global climate prediction and disaster risk management. Yet, limited understanding of ENSO's physical mechanisms constrains both numerical and deep learning approaches, which often struggle to balance predictive accuracy with physical interpretability. Here, we introduce a data driven model for ENSO prediction based on conditional diffusion model. By constructing a probabilistic mapping from historical to future states using higher-order Markov chain, our model explicitly quantifies intrinsic uncertainty. The approach achieves extending lead times of state-of-the-art methods, resolving early development signals of the spring predictability barrier, and faithfully reproducing the spatiotemporal evolution of historical extreme events. The most striking implication is that our analysis reveals that the reverse diffusion process inherently encodes the classical recharge-discharge mechanism, with its operational dynamics exhibiting remarkable consistency with the governing principles of the van der Pol oscillator equation. These findings establish diffusion models as a new paradigm for ENSO forecasting, offering not only superior probabilistic skill but also a physically grounded theoretical framework that bridges data-driven prediction with deterministic dynamical systems, thereby advancing the study of complex geophysical processes.
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All authors Weifeng Xu, Xiang Zhu, Xiaoyong Li, Qiang Yao, Xiaoli Ren, Kefeng Deng, Song Wu, Chengcheng Shao, Xiaolong Xu, Juan Zhao, Chengwu Zhao, Jianping Cao, Jingnan Wang, Wuxin Wang, Qixiu Li, Xiaori Gao, Xinrong Wu, Huizan Wang, Xiaoqun Cao, Weiming Zhang, Junqiang Song, Kaijun Ren

Applied Physics · Cross-listed from cond-mat.mtrl-sci

Strong coupling between coherent ferrons and cavity acoustic phonons

Yujie Zhu, Jiaxuan Wu, Anna N. Morozovska et al. (+7 more)

Coherent ferrons, the quanta of polarization waves, can potentially be hybridized with many other quasiparticles for achieving novel control modalities in quantum communication, computing, and sensing. Here, we theoretically demonstrate a new hybridized state resulting from the strong coupling between fundamental-mode (wavenumber is zero) coherent ferrons and cavity bulk acoustic phonons. Using a van der Waals ferroelectric CuInP2S6 membrane as an example, we predict an ultra-strong ferron-phonon coupling at room temperature, where the coupling strength g_c reaches over 10% of the resonant frequency {\omega}_0. We also predict an in-situ bistable electric-field control of mode-specific ferron-phonon hybridization via ferroelectric switching. We further show that CuInP2S6 allows for reaching the fundamentally intriguing but challenging deep strong coupling regime (i.e., g_c/{\omega}_0>1) near the ferroelectric-to-paraelectric phase transition. Our findings establish the theoretical basis for exploiting coherent ferron as a new contender for hybrid quantum system with strong and highly tunable coherent coupling
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All authors Yujie Zhu, Jiaxuan Wu, Anna N. Morozovska, Eugene A. Eliseev, Yulian M. Vysochanskii, Venkatraman Gopalan, Long-Qing Chen, Xufeng Zhang, Wei Zhang, Jia-Mian Hu

Computational Physics

BzScope: an absolute cross section calculator for neutron-phonon scattering

Ming Tang, Zi-Yi Pan, Ni Yang et al. (+2 more)

BzScope is a Python package designed for efficiently calculating absolute cross sections of neutron-phonon inelastic scattering for crystalline powders in large phase spaces, addressing the limitations of traditional histogramming techniques in reproducing sharp structures and ensuring convergence. The package employs an adapted integral method and supports calculations of single- and two-phonon scattering functions in ideal crystalline powders, with numerical robustness up to a momentum transfer of 100 Ang^-1. Higher order scatterings up to several hundred orders are calculated by incoherent approximation in a well-established thermal neutron scattering physics package, NCrystal. In addition, a NCrystal plugin is made available for NCrystal-enabled Monte Carlo packages, facilitating direct comparison between the new physics and experimental data. Validation against NCrystal demonstrates good agreement in incoherent scattering for cubic systems Ni. In addition, it shows improved accuracy for low-symmetry materials $NiP_2$ by avoiding the isotropic atomic displacement approximations in NCrystal. Benchmarks the experimental differential cross section of LiH and total cross section of Be confirm its reliability. BzScope integrates with NCrystal via a plugin and therefore can be directly used in any NCrystal-enabled Monte Carlo package. This tool enhances the efficiency and accuracy of neutron scattering simulations, advancing the study of condensed matter dynamics.
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All authors Ming Tang, Zi-Yi Pan, Ni Yang, Thomas Kittelmann, Xiao-Xiao Cai

Atmospheric and Oceanic Physics

Tipping Points and Cascading Transitions: Methods, Principles, and Evidences

Sheng Fang, Ziyan Wang, Jürgen Kurths et al. (+1 more)

This review synthesizes recent advancements in understanding tipping points and cascading transitions within the Earth system, framing them through the lens of nonlinear dynamics and complexity science. It outlines the fundamental concepts of tipping elements, large-scale subsystems like the Atlantic Meridional Overturning Circulation and the Amazon rainforest, and classifies tipping mechanisms into bifurcation-, noise-, and rate-induced types. The article critically evaluates methods for detecting early-warning signals, particularly those based on critical slowing down, while also acknowledging their limitations and the promise of non-conventional indicators. Furthermore, we explore the significant risk of cascading failures between interacting tipping elements, often modeled using conceptual network models. This shows that such interactions can substantially increase systemic risk under global warming. The review concludes by outlining key challenges related to data limitations and methodological robustness, and emphasizes the promising role of artificial intelligence and complex network science in advancing prediction and risk assessment of Earth system tipping dynamics.
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All authors Sheng Fang, Ziyan Wang, Jürgen Kurths, Jingfang Fan

Optics

Higher-order spatiotemporal wave packets with Gouy phase dynamics

Wangke Yu and Yijie Shen

Spatiotemporal (ST) wave packets refer to a broad class of optical pulses whose spatial and temporal dependence cannot be treated separately. Such space time non-separability can induce exotic physical effects such as non-diffraction, non-transverse waves, and sub or superluminal propagation. Here, a family of ST non-separable pulses is presented, where a modal order is proposed to extend their spatiotemporal structural complexity, analogous to the spatial higher-order Gaussian modes. The modal order is strongly coupled to the Gouy phase, which can unveil anomalous spatiotemporal dynamics, including ultrafast cycle-switching evolution, ST self-healing, and sub- or super-luminal propagation. We further introduce a stretch parameter that stretches the temporal envelope while keeping the Gouy-phase coefficient unchanged. This stretch invariance decouples pulse duration from modal order, allowing us to tune the few-cycle width without shifting temporal-revival positions or altering the phase or group-velocity laws. Moreover, an approach to analyzing the phase velocity and group velocity of the higher-order ST modes is proposed to quantitatively characterize the sub- or supe-luminal effects. The method is universal for a larger group of complex structured ultrafast pulses, laying the basis for both fundamental physics and advanced applications in ultrafast optics and structured light.
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Optics

Intensity and Phase correction Enhanced interferometric scattering microscopy (iSCAT)

Xiang Zhang, Wenfu Lin, Yatao Yang et al. (+1 more)

Interferometric scattering microscopy was widely applied in nanoscopic detection and tracking due to its high sensitivity and label-free manner. The sensitivity is limited by contrast. Oblique illumination provided high contrast with lower power density. However, no model has been established to illustrate the schematic and complex rotation setup was needed. Here, we established a model of contrast and the unexpected reflections both in intensity and phase modulation. Then, the contrast enhancement was verified in oblique illumination. To provide a uniform contrast measurement, the phase map of oblique illumination was calibrated through scanning without the need for rotation. Our work gives new insights in oblique illumination and may inspire new idea to enhance contrast with phase and intensity modulation.
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All authors Xiang Zhang, Wenfu Lin, Yatao Yang, Yifan Wang

Applied Physics

Ar$\chi$i-Textile Composites: Drapable Hybrid Woven Composites for Lightning Strike Protection

Hridyesh Tewani, Vincent Scheerer, Madison Owens et al. (+8 more)

Carbon fiber-reinforced polymers (CFRPs) have been extensively used in the aerospace and wind energy industries due to their superior specific mechanical properties and corrosion resistance. However, their higher electrical resistivity makes them susceptible to lightning strike damage, which necessitates the addition of a surface lightning strike protection (LSP) layer. Traditional LSP systems, such as copper mesh or expanded foil, reduce lightning strike damage, but are not easily drapable around complex geometries and may introduce delamination-prone regions within the composite. Here, we propose a novel manufacturing strategy for architected hybrid composites as drapable LSP by weaving stainless steel yarns within the woven carbon fiber composites. We varied the metal-to-carbon yarn ratio and stacking configuration to assess damage evolution under quasi-static arc exposures and simulated lightning strikes. Our results elucidate that incorporating hybrid layers into composites significantly reduced surface temperatures, through-thickness damage, and mass loss under both electric arc impacts. The composites with the proposed LSP layers also exhibited higher retention of flexural modulus and strength compared to the reference CFRP. Advanced air mobility (AAM) vehicles, which operate at lower altitudes, face significant safety challenges due to their high susceptibility to lightning strikes. Therefore, the proposed hybridized composites can be used as an efficient and drapable LSP around complex shapes in AAM vehicles, offering enhanced safety and protection.
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All authors Hridyesh Tewani, Vincent Scheerer, Madison Owens, Emilio Cumbajin, Camila De Leon, MD Rashid Hussain, Pruthul Kokkada Ravindranath, Rachel Van Lear, David Jack, David Wallace, Pavana Prabhakar

Applied Physics

Experimental Investigation of Acoustic Kerker Effect in Labyrinthine Resonators

Iuliia Timankova, Mikhail Smagin, Mikhail Kuzmin et al. (+4 more)

Controlling the directionality of the acoustic scattering with single acoustic metaatoms has a key importance for reaching spatial routing of sound with acoustic metamaterials. In this paper, we present the experimental demonstration of the acoustic analogue of the Kerker effect realized in a two-dimensional coiled-space metaatom. By engineering the interference between monopolar and dipolar resonances within a high-index acoustic metaatom, we achieve directional scattering with suppressed backward or forward response at the first and second Kerker conditions respectively. Experimental measurements of the scattered pressure field, in a parallel-plate waveguide environment, show good agreement with the full-wave simulations. Our results validate the feasibility of Kerker-inspired wave control in acoustic systems and open new opportunities for directional sound manipulation.
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All authors Iuliia Timankova, Mikhail Smagin, Mikhail Kuzmin, Andrey Lutovinov, Andrey Bogdanov, Yong Li, Mihail Petrov

Chemical Physics

Screening in the Heitler-London Model: Revisiting the Bonding and Antibonding States of the Hydrogen Molecule

Washington P. da Silva, Daniel Vieira, Jonas Maziero et al. (+1 more)

The present manuscript revisits one of the earliest approaches to treating molecular systems within the Schrödinger formalism of quantum mechanics: the Heitler-London (HL) model. Originally proposed in 1927 and based on a linear combination of atomic orbitals, the HL model provided a foundational description of covalent bonds and has served as the basis for numerous variational methods. Focusing on the hydrogen molecule, we begin by revisiting the analytical calculations of the original HL model, from which the qualitative physics of bonding and antibonding states can be obtained. Subsequently, we propose including electronic screening effects directly in the original HL wave function. We then compare our proposal with variational quantum Monte Carlo (VQMC) calculations, whose trial wave function allows us to optimize the electronic screening potential as a function of the inter-proton distance. We obtain the bond length, binding energy, and vibrational frequency of the H$_2$ molecule. Beyond revisiting this foundational approach in quantum mechanics, our proposal can serve as improved input for constructing new, but still analytically simple, variational wave functions to describe dissociation or bond formation.
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All authors Washington P. da Silva, Daniel Vieira, Jonas Maziero, Edgard P. M. Amorim

Chemical Physics

Multistate iterative qubit coupled cluster (MS-iQCC): a quantum-inspired, state-averaged approach to ground- and excited-state energies

Robert A. Lang, Shashank G. Mehendale, Ilya G. Ryabinkin et al. (+1 more)

We introduce the multistate iterative qubit coupled cluster (MS-iQCC) method, a quantum-inspired algorithm that runs efficiently on classical hardware and is designed to predict both ground and excited electronic states of molecules. Accurate excited-state energetics are essential for interpreting spectroscopy and chemical reactivity, but standard electronic structure methods are either too computationally expensive for larger systems or lose reliability in the presence of strong electron correlation. MS-iQCC addresses this challenge by simultaneously optimizing multiple electronic states in a single, state-averaged procedure that treats ground and excited states on equal footing. This removes the energetic bias that is introduced when excited states are computed one at a time and constrained to remain orthogonal to previously optimized states. The approach supports multireference electronic structure by allowing multideterminantal initial guesses and by adaptively building a compact exponential ansatz from a pool of qubit excitation generators. We apply MS-iQCC to H$_4$, H$_2$O, N$_2$, and C$_2$, including strongly correlated geometries, and observe robust convergence of all targeted state energies to chemically meaningful accuracy across their potential energy surfaces.
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All authors Robert A. Lang, Shashank G. Mehendale, Ilya G. Ryabinkin, Artur F. Izmaylov

Sunday 2 November

Applied Physics

Data-Driven Design Rules for TADF Emitters from a High-Throughput Screening of 747 Molecules

Jean-Pierre Tchapet Njafa, Elvira Vanelle Kameni Tcheuffa, Aissatou Maghame Foumkpou et al. (+1 more)

TADF emitter performance depends on both thermodynamic and kinetic factors. We analyze 747 experimentally known TADF molecules computationally to extract quantitative design guidelines. Using a validated xTB-based workflow, we examine how architecture, geometry, and electronic structure affect photophysical properties. Among architectures, D-A-D frameworks achieve the smallest \deltaest. A favorable torsional angle of $50{\deg}-90{\deg}$ balances small $\Delta E_{\text{ST}}$ with the spin–orbit coupling needed for reverse intersystem crossing. Clustering separates high-performance candidates and highlights multi-resonance emitters for blue emission. From these results, we identify 127 candidates with predicted $\Delta E_{\text{ST}} < 0.1 eV$ and oscillator strength $f > 0.1$. These HTVS-derived design guidelines and candidates can guide future TADF emitter development.
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All authors Jean-Pierre Tchapet Njafa, Elvira Vanelle Kameni Tcheuffa, Aissatou Maghame Foumkpou, Serge Guy Nana Engo

Biological Physics

AI-driven Large-scale Electron Microscopy enables Whole-tissue Subcellular Digitization

Li Xiao, Liqing Liu, Hongjun Wu et al. (+7 more)

The distribution and interactions of cellular organelles play a critical role in mediating cellular physiology and pathology. Large-scale electron microscopy enables visualization of organelle distribution and interactions at the tissue level with nanometer resolution, but robust and efficient computational analysis tools are lacking. Here, we present a deep learning tool for universal large-scale 2D/3D electron microscopy analysis, DeepOrganelle. This new tool enables high-throughput, cell-resolved spatiotemporal mapping and digitization of organelle distribution and interactions. When applied to spermatogenesis across 12 stages and 22 differentiation status of the germ cells, DeepOrganelle uncovered previously unrecognized, stage-dependent dynamics of mitochondria-endoplasmic reticulum contact sites within one subphase of prophase I during meiosis. It also revealed coordinated organelle redistribution in Sertoli cells towards the blood-testis barrier, digitizing the remodeling dynamics of the tissue. This study demonstrates that DeepOrganelle provides a powerful framework that captures subcellular dynamics at the whole-tissue level.
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All authors Li Xiao, Liqing Liu, Hongjun Wu, Jiayi Zhong, Xixia Li, Yan Zhang, Junjie Hu, Sun Fei, Ge Yang, Tao Xu

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

EPR Revisited: Context-Indexed Elements of Reality and Operational Completeness

Mikołaj Sienicki and Krzysztof Sienicki

We reframe the EPR argument through an operational lens, replacing the notion of fixed "elements of reality" with context-indexed conditional states - what's often referred to as a measurement assemblage. This move deliberately sidesteps the assumption of context-independent values for incompatible observables. Our updated version of the Reality Criterion works like this: if Alice measures observable x and obtains outcome a, then Bob's system must adopt a conditional state that ensures the corresponding outcome for that specific context. Crucially, we also assume operational completeness - a condition that quantum mechanics satisfies when we're dealing with quantum-reachable assemblages. Now, in any theory where one party cannot signal to the other (so-called one-sided no-signaling theories), perfect predictions do support drawing context-indexed inferences. But - and this is key - they don't legitimize assigning fixed values across all contexts. We rigorously demonstrate this distinction. To ground the argument, we offer examples: the qubit singlet scenario using Pauli settings and CJWR thresholds, a continuous-variable case based on the Reid criteria, and a counterexample in the spirit of the PR box, which highlights the boundaries of what quantum theory can actually reach.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci

Domain Morphology, Electrocaloric Response, and Negative Capacitance States of Ferroelectric Nanowires Array

Anna N. Morozovska, Oleksii V. Bereznykov, Maksym V. Strikha et al. (+4 more)

We analyzed the domain morphology, electrocaloric response, and negative capacitance states in a one-dimensional array of uniformly oriented, radial symmetric ferroelectric nanowires, whose spontaneous polarization is normal to their symmetry axis. The wires are densely packed between flat electrodes. Using finite element modeling based on the Landau-Ginzburg-Devonshire approach, electrostatics, and elasticity theory, we calculated the distributions of spontaneous polarization, domain structures, electric potential, electric field, dielectric permittivity, and electrocaloric response in the nanowires. Due to size and depolarization effects, the paraelectric and ferroelectric (poly-domain or single-domain) states of the wires can be stable, depending on their radius and the dielectric permittivity of the surrounding medium. It is demonstrated that dipole-dipole interaction between the nanowires determines the stability of the polar (or anti-polar) state in the array when the wire radius is significantly smaller than the critical size of the paraelectric transition in an isolated wire. We reveal that a large region of a mixed state, characterized by poly-domain ferroelectric states with nonzero average polarization inside each wire and zero average polarization of the whole array, can be stable. By selecting the dielectric permittivity of the surrounding medium and the nanowire radius, one can maximize the negative capacitance effect in the capacitor with densely packed wires. It is also possible to achieve maximal enhancement of the electrocaloric response due to size effects in the wires. The underlying physics of the predicted enhancement is the combined action of size effects and the long-range electrostatic interactions between the ferroelectric dipoles in the nanowires and the image charges in the electrodes
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All authors Anna N. Morozovska, Oleksii V. Bereznykov, Maksym V. Strikha, Oleksandr S. Pylypchuk, Zdravko Kutnjak, Eugene A. Eliseev, Dean R. Evans

Accelerator Physics · Cross-listed from hep-ex

Beam-Beam Backgrounds for the Cool Copper Collider

Dimitrios Ntounis, Laith Gordon, Lindsey Gray et al. (+4 more)

In this paper, we present a comprehensive characterization of beam-beam backgrounds for the Cool Copper Collider (C$^3$), a proposed linear $e^{+}e^{-}$ collider designed for precision Higgs studies at center-of-mass energies of 250 and 550 GeV. Using a simulation pipeline based on the Key4hep framework, we evaluate incoherent pair production and hadron photoproduction backgrounds through the SiD detector for baseline, power-efficiency, and high-luminosity C$^3$ operating scenarios. The occupancy induced by the beam-beam background is evaluated for each scenario, validating the compatibility of the existing SiD detector design with operations at C$^3$ without substantial modifications. At the same time, the modular simulation framework and analysis methodology presented in this paper offer a versatile toolkit for background studies in future collider proposals, contributing to a common platform for different machine designs.
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All authors Dimitrios Ntounis, Laith Gordon, Lindsey Gray, Elias Mettner, Tim Barklow, Emilio A. Nanni, Caterina Vernieri

Medical Physics · Cross-listed from cs.AI

Knowledge Elicitation with Large Language Models for Interpretable Cancer Stage Identification from Pathology Reports

Yeawon Lee, Christopher C. Yang, Chia-Hsuan Chang et al. (+1 more)

Cancer staging is critical for patient prognosis and treatment planning, yet extracting pathologic TNM staging from unstructured pathology reports poses a persistent challenge. Existing natural language processing (NLP) and machine learning (ML) strategies often depend on large annotated datasets, limiting their scalability and adaptability. In this study, we introduce two Knowledge Elicitation methods designed to overcome these limitations by enabling large language models (LLMs) to induce and apply domain-specific rules for cancer staging. The first, Knowledge Elicitation with Long-Term Memory (KEwLTM), uses an iterative prompting strategy to derive staging rules directly from unannotated pathology reports, without requiring ground-truth labels. The second, Knowledge Elicitation with Retrieval-Augmented Generation (KEwRAG), employs a variation of RAG where rules are pre-extracted from relevant guidelines in a single step and then applied, enhancing interpretability and avoiding repeated retrieval overhead. We leverage the ability of LLMs to apply broad knowledge learned during pre-training to new tasks. Using breast cancer pathology reports from the TCGA dataset, we evaluate their performance in identifying T and N stages, comparing them against various baseline approaches on two open-source LLMs. Our results indicate that KEwLTM outperforms KEwRAG when Zero-Shot Chain-of-Thought (ZSCOT) inference is effective, whereas KEwRAG achieves better performance when ZSCOT inference is less effective. Both methods offer transparent, interpretable interfaces by making the induced rules explicit. These findings highlight the promise of our Knowledge Elicitation methods as scalable, high-performing solutions for automated cancer staging with enhanced interpretability, particularly in clinical settings with limited annotated data.
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All authors Yeawon Lee, Christopher C. Yang, Chia-Hsuan Chang, Grace Lu-Yao

Atmospheric and Oceanic Physics · Cross-listed from cs.CL

OceanAI: A Conversational Platform for Accurate, Transparent, Near-Real-Time Oceanographic Insights

Bowen Chen, Jayesh Gajbhar, Gregory Dusek et al. (+6 more)

Artificial intelligence is transforming the sciences, yet general conversational AI systems often generate unverified "hallucinations" undermining scientific rigor. We present OceanAI, a conversational platform that integrates the natural-language fluency of open-source large language models (LLMs) with real-time, parameterized access to authoritative oceanographic data streams hosted by the National Oceanic and Atmospheric Administration (NOAA). Each query such as "What was Boston Harbor's highest water level in 2024?" triggers real-time API calls that identify, parse, and synthesize relevant datasets into reproducible natural-language responses and data visualizations. In a blind comparison with three widely used AI chat-interface products, only OceanAI produced NOAA-sourced values with original data references; others either declined to answer or provided unsupported results. Designed for extensibility, OceanAI connects to multiple NOAA data products and variables, supporting applications in marine hazard forecasting, ecosystem assessment, and water-quality monitoring. By grounding outputs and verifiable observations, OceanAI advances transparency, reproducibility, and trust, offering a scalable framework for AI-enabled decision support within the oceans. A public demonstration is available at https://oceanai.ai4ocean.xyz.
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All authors Bowen Chen, Jayesh Gajbhar, Gregory Dusek, Rob Redmon, Patrick Hogan, Paul Liu, DelWayne Bohnenstiehl, Dongkuan Xu, Ruoying He

Optics

Graphene-Enabled Terahertz Metamaterial Absorber for Ultra-Wide Refractive Index Sensing

Osama Haramine Sinan, Roktim Barua, Nipa Dhar et al. (+1 more)

This study introduces a graphene-assisted terahertz metamaterial absorber operating at a resonance frequency of 8.436 THz. The unit cell incorporates a graphene-based split-ring resonator (SRR) configuration with additional auxiliary splits on the top layer. The structure achieves near-perfect absorption of 99.99% under TM polarization, maintaining absorption above 90% for incident angles up to 75$^{\circ}$. In addition, the proposed design remains polarization-insensitive up to 50$^{\circ}$. The sensor demonstrates a figure of merit (FOM) of $4.22 RIU^{-1}$ and achieves a maximum Q-factor of 20.98, corresponding to a full width at half maximum (FWHM) of 402 GHz. An equivalent circuit model is also developed to verify the resonance behavior. Due to the strong dependence of the resonant frequency on the surrounding refractive index (RI), the absorber is applied as an RI-based sensor. It exhibits a high sensitivity of 1698 GHz/RIU across a wide refractive index range from 1.0 to 2.0. The proposed design holds promise for sensing applications involving gases, oils, solvents, polymers, and high-index dielectric materials, including the biomedical refractive index window (1.30-1.39) for label-free biosensing.
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All authors Osama Haramine Sinan, Roktim Barua, Nipa Dhar, Muhammad Asad Rahman