Applied Physics · Cross-listed from cond-mat.mtrl-sci
Anomalous Transverse Response and Multi-Field Ferrialtermagnetic-Ferroelectric Valve with CrSb Flakes
Long Zhang, Xinfeng Chen, Hongfei Liang et al. (+5 more)
Altermagnets combine the zero-stray-field of antiferromagnets with the
spin polarization of ferromagnets, showing great potential for spintronic applications. Here, we propose ferrialtermagnetism as a distinct subclass of altermagnetic family, where
symmetry-inequivalent altermagnetic sublattices possess nonidentical Neel vectors, preventing mutual cancellation of alternating
spin splitting and conferring intrinsic robustness against perturbations. This concept is realized in the three-atomic-layer CrSb (110) flakes, which exhibits
spin splitting of 344 meV, moderate uniaxial
magnetic anisotropy, and high Neel temperature of 657 K. The magneto-optical Kerr and the anomalous
Hall effects are observed. Integrating this ferrialtermagnetic CrSb with ferroelectric Sc2CO2 and Cu spacer, we design an ferrialtermagnetic-ferroelectric valve. This device displays
equilibrium tunneling magnetoresistance and electroresistance of ~10^3%, and non-
equilibrium magnitudes under bias, thermal, or light field reaches ~10^4% with high
spin filtering of 90%. The negative differential resistance and photogalvanic effects, and photocurrent extinction ratio of 283.8 are achieved. These findings establish ferrialtermagnetism as a fertile platform for multi-field-controlled, ultracompact, and self-powered spintronics and electronics.
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All authors Long Zhang, Xinfeng Chen, Hongfei Liang, Jianting Dong, Fei Zou, Yi Yan, Guangqian Ding, Guoying Gao
Atmospheric and Oceanic Physics
Typhoon intensity ReAnalysis (TyRA)
Kosuke Ito, Masataka Aizawa, Udai Shimada et al. (+2 more)
Best-track data have been typically used to explore long-term changes in typhoon intensity over the western North Pacific (WNP). However, the methods used to construct best-track intensities have changed over the past several decades. Several attempts have been made to achieve homogeneous intensity analyses based on the Dvorak method, but their consistency with direct observations can still be improved. This study tries to accurately explain minimum sea-level pressure (MSLP) from aircraft observations during 1981-1986 using CI numbers and other parameters as in Aizawa et al. (2024). Using the optimized coefficients, we reanalyzed MSLP for 1987-2024. The reanalyzed MSLPs were converted into maximum wind speeds using Knaff and Zehr (2007). This Typhoon intensity ReAnalysis (TyRA) exhibited a slightly decreasing trend in the number of intense typhoons, which was not statistically significant. Compared with TyRA, the Joint Typhoon Warning Center (JTWC) best-track contained a larger number of intense typhoons from the late 1980s to the mid-2000s, whereas the Regional Specialized Meteorological Center (RSMC) Tokyo best-track contained a smaller number. In TyRA, typhoons recently weakened over the eastern part of the WNP with some statistical significance. It can be explained by the decrease of mean age of typhoons after typhoon genesis. Large differences among the RSMC Tokyo and JTWC best-track data and TyRA were found for rapid intensification. Furthermore, although previous studies reported that errors in intensity forecasts by the RSMC Tokyo increased in the mid-2000s, the changes in the quality of the RSMC Tokyo best-track data partly explain this.
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All authors Kosuke Ito, Masataka Aizawa, Udai Shimada, Yasuhiro Kawabata, Munehiko Yamaguchi
Chemical Physics · Cross-listed from quant-ph
Quantum Multiscale Modeling: A Hierarchy of Algorithms for Complex Chemical Systems
Seenivasan Hariharan, Kareljan Schoutens, Sachin Kinge et al. (+1 more)
Multiscale modeling of complex chemical systems requires
algorithms that operate coherently across electronic, atomistic, mesoscopic, and continuum scales. While
quantum algorithms have been proposed for each regime, no systematic framework exists to compose them across scale boundaries. Here, we identify the conditions under which fault-tolerant
quantum algorithms might preserve scale-specific
quantum advantages. We map
quantum phase estimation,
Hamiltonian simulation with Gibbs state preparation,
quantum random walks, and
quantum partial differential equation solvers onto electronic structure, molecular dynamics, mesoscopic kinetics, and continuum reactor physics, respectively. Crucially, these correspondences do not imply unconditional end-to-end
quantum advantage; speedups depend heavily on state preparation,
memory architectures,
matrix conditioning, and classical readout costs. Six unresolved questions define this composition problem, illustrated via a
quantum hierarchy for \ce{CO} oxidation over \ce{Pt(111)}. We propose viewing inter-scale transfer as a
quantum channel composition problem at the interface of
algorithm design and non-
equilibrium statistical mechanics, and ask whether information loss at scale boundaries is intrinsic to multiscale modeling or merely a consequence of lossy classical transduction between algorithmic layers. The resulting roadmap suggests that multiscale
quantum advantage is governed primarily by the structure of information transfer between algorithmic layers, rather than by performance at individual scales alone.
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All authors Seenivasan Hariharan, Kareljan Schoutens, Sachin Kinge, Lucas Visscher
Computational Physics
Uncertainty-Aware Structure-Property Mapping of Spinodoid Metamaterials via Heteroscedastic Gaussian Process Regression
Minwoo Park, Junseo Park, Mingyu Lee et al. (+4 more)
Spinodoid metamaterials offer a broad, tunable design space for anisotropic mechanical properties, yet their structure-property relationships are commonly treated as representative mappings from cone-angle descriptors to single effective stiffness values. This deterministic view overlooks the
stochastic nature of Gaussian random field (GRF)-based
topology generation, where identical cone-angle descriptors can produce different morphology realizations and property scatter. Here, we present an uncertainty-aware structure-property mapping framework that reinterprets cone-angle descriptors as
stochastic descriptors associated with input-dependent property distributions. Using heteroscedastic Gaussian process regression (GPR), the framework infers input-dependent predictive uncertainty from sparse one-realization-per-point data without requiring empirical variance labels at every design point. The results show that stiffness scatter differs across tensor components according to each component's mechanically active directions, and that parameter sets yielding identical mean stiffness can carry different aleatoric uncertainty. Applying this uncertainty to reliability-based design optimization (RBDO), we show that a deterministic optimum is highly susceptible to constraint violation once morphology-induced variability is considered, and that a homoscedastic RBDO formulation fails to meet the prescribed reliability target - only the heteroscedastic formulation satisfies the reliability target under the heteroscedastic uncertainty evaluation. This establishes uncertainty-aware surrogate modeling as essential for reliability-aware inverse design of spinodoid metamaterials; extending the framework to nonlinear responses remains for future work.
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All authors Minwoo Park, Junseo Park, Mingyu Lee, Hugon Lee, Hanbin Cho, Ikjin Lee, Seunghwa Ryu
Plasma Physics
VSC: A Zero-Dimensional Fusion Design Platform for Multiple Magnetic Configurations
Zekun Wang, Huasheng Xie, Feng Zhang et al. (+2 more)
The VeloAlpha System Code (VSC) is a computational framework for zero-dimensional fusion power-balance studies across five
magnetic-confinement configurations: tokamaks,
magnetic mirrors, field-reversed configurations (FRCs), dipoles, and stellarators. A common power-balance formulation connects fusion production, charged-particle deposition, radiation, transport loss, external heating, and fusion gain, while each configuration retains its own geometry, profile weights, confinement model, and operating constraints. The same solver interface supports both single-point calculations and two-dimensional
plasma operating contour (POPCON) scans, producing fusion and heating powers, gain, radiation and transport losses, geometry quantities, and configuration-specific validity indicators. VSC therefore makes it possible to study how assumptions about density, temperature,
magnetic field, confinement, and geometry shape the accessible operating space of different fusion concepts within one traceable framework. By combining reduced-order physics models with a unified computational platform, VSC enables rapid assessment and comparative analysis of candidate fusion reactor concepts during the early design stage.
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All authors Zekun Wang, Huasheng Xie, Feng Zhang, Jian Bao, Ming Yang
Computational Physics
Compact and Stable Representation of Real-Frequency Spectral Functions for Machine Learning
Xinyang Dong, Ido Zemach, Lei Zhang et al. (+2 more)
We introduce a compact and stable moment representation for real-frequency Green's functions, hybridization functions, and self-energies for machine-learning applications, avoiding the inefficiency of dense frequency grids as well as the ill-posed analytic continuation of Matsubara approaches. The representation is constructed from Cayley-mapped trigonometric moments with the Jacobian included, which preserve spectral-weight normalization, tie the moment sequence to a positive
matrix-valued spectral measure, and admit a systematic route to a pole representation via ESPRIT. This provides a fixed-dimensional learning target in which physical constraints such as normalization and positivity can be imposed directly. Using a graph-
attention neural network with FiLM conditioning, we
benchmark the representation on single-orbital DMFT,
antiferromagnetic DMFT, and a two-orbital
impurity model. The results demonstrate accuracy matching or exceeding that of direct frequency-domain learning, reliable reproduction of the density and staggered magnetization, stable self-energy reconstruction through Dyson equation inversion, and accurate recovery of
matrix-valued spectra with orbital mixing.
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All authors Xinyang Dong, Ido Zemach, Lei Zhang, Guy Cohen, Emanuel Gull
Optics
Leveraging Raman response in X-cut thin-film lithium tantalate for ultrabroadband combs and polychromatic visible light
Xin Wang, Mingkun Xiao, Min Sun et al. (+9 more)
X-cut thin-film lithium tantalate (TFLT) offers a unique combination of third nonlinearity, electro-optic effects, and a high optical damage threshold. However, its strong Raman response has historically hindered broadband Kerr comb generation. Here, we leverage this inherent Raman response by engineering coupling-defined dissipation. This allows us to reconfigure the relative thresholds of Raman and Kerr processes without modifying the intrinsic microresonator dispersion. Through this coupling-engineered threshold control, we can deliberately access distinct comb states, ranging from pure Kerr combs to Raman-Kerr synergistic broadband combs. We demonstrate a Kerr comb spanning 450 nm and a Raman-Kerr comb spanning 650 nm, representing the broadest combs reported to date on X-cut TFLT platforms. Moreover, in strongly coupled devices, we show that a single near-infrared pump can generate visible emission across multiple bands (from violet to red) via cascaded second sum-frequency processes. Our work demonstrates that a strong Raman response can be transformed from a parasitic competitor into an enabling mechanism for achieving broader comb spectra and generating polychromatic visible light. This work establishes X-cut TFLT as a powerful monolithic platform for nonlinear light sources, electro-optic functions, and complex photonic systems.
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All authors Xin Wang, Mingkun Xiao, Min Sun, Ronghong Gao, Yuqi Chen, Zhengshun Lei, Xun Zhang, Wenfeng Zhou, Jintian Lin, Yikai Su, Xingchen Ji, Yong Zhang
Optics
Abnormal motions of optical vortex-antivortex-coupled wavepackets in the parabolic potential
Haolin Lin, Junhui Jia, Chunhao Liang et al. (+4 more)
The (quasi)particles or structured wavepackets in
parabolic potential exhibit well-known harmonic oscillations, typically described by the Lissajous equations. However, such conventional harmonic laws rely on a fundamental assumption that the different constituent components of the (quasi)particles or wavepackets do not interact. Here we challenge this paradigm, by taking advantage of intrinsic couplings among distinct constituents-specifically by leveraging nontrivial couplings between
vortices and antivortices embedded in a spatially structured wavepacket. We demonstrate theoretically and experimentally abnormal motions by considering two different optical waveforms. For a
vortex-antivortexcoupled dipole mode, we reveal counterintuitive propagation regimes, including periodic annihilation and regeneration of the dipole, its non-orbital motion and realization of a critical
equilibrium state without nonlinearity. For a circular chain of
vortices with an antivortex set at the center, we successfully tune the oscillation frequency of the overall configuration in the potential, thus disobeying the classical Lissajous trajectories, by precisely engineering the nonlocal
vortex-antivortex couplings. Since the harmonic oscillations have been proven to be fundamental physical phenomena in distinct disciplines and led to numerous important applications, our demonstrations provide different opportunities to trigger considerable investigations and potential applications, by leveraging the underlying anomalous motions of the
vortex-antivortex-coupled wavepackets in the
parabolic potential.
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All authors Haolin Lin, Junhui Jia, Chunhao Liang, Yanwen Hu, Boris A. Malomed, Yangjian Cai, Shenhe Fu
Geophysics
A Multiscaling Fingerprint of Earthquake Diffusion in Seismic Swarms
Cataldo Godano and Giuseppe Petrillo
Seismic swarms are commonly associated with fluid migration and other transient processes, yet their spatial migration remains difficult to quantify using conventional
diffusion models. Here we analyze ten persistent earthquake swarms identified within the relocated Southern California earthquake catalogue using a consensus clustering approach. We characterize their migration through the multiscaling spectrum $\varepsilon(q)$ obtained from the temporal
evolution of the moments of interevent distances. All analyzed swarms exhibit a common scaling signature: the spectrum is approximately linear for negative moments but departs systematically from a single linear behavior for positive moments, indicating that small and large interevent distances evolve with different effective scaling laws. In contrast, the Landers tectonic sequence displays a high-order saturation of $\varepsilon(q)$, consistent with spatially bounded
diffusion. These results reveal that earthquake swarms are characterized by strong anomalous
diffusion and suggest that the multiscaling spectrum provides a quantitative fingerprint capable of distinguishing swarm migration from conventional tectonic earthquake sequences.
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Biological Physics · Cross-listed from cond-mat.soft
Molecular Dynamics-Derived Coloured Noise Mediates Anderson Localisation and Environment-Assisted Transport of Tryptophan Excitons in Tubulin
Chen Xin
The tryptophan residues in tubulin $\alpha\beta$-dimers form an ordered aromatic network that has been proposed to support
quantum exciton transport even under physiological environmental noise. Existing studies of this system mostly assume white-noise dephasing, but the statistical properties of the
protein-solvent bath coupled to tryptophan sites remain uncharacterised under physiological conditions. Here we characterise this fluctuation bath via all-atom molecular dynamics simulations of a solvated tubulin dimer at 310 K, combining high-frequency and long-time trajectories with 10 fs and 10 ps sampling intervals. The resulting autocorrelation of the site-energy fluctuations is tri-exponential, with three well-separated decay modes: sub-100-fs and picosecond fluctuations driven by water dynamics, and a nanosecond mode originating from
protein conformational rearrangements. All three modes fall deep within the non-Markovian regime. We further demonstrate that the slow
protein mode introduces strong quasi-static disorder, which results in Anderson localisation, while the two fast water modes frequently tune chromophore pairs through resonance, enabling environment-assisted
quantum transport (ENAQT). On the full eight-site network, the coloured-noise bath confines
excitons predominantly to strongly coupled proximal tryptophan pairs, in marked contrast to the more uniform delocalisation predicted by the standard white-noise Haken-Strobl model. Our workflow generalises to other pigment-
protein systems with solvent-exposed chromophores.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Tiling decomposition multiplicity predicts stability of GaN(0001) surface reconstructions
Tetsuji Kuboyama, Akira Kusaba, Karol Kawka et al. (+1 more)
The stable adatom configurations of a
semiconductor surface have traditionally been sought by sampling: density functional theory (DFT) energies steer a heuristic or
Bayesian search through a configuration space far too large to cover. Here we show that, for the GaN(0001)-$(6\times6)$ surface under the electron counting (EC) rule, the search can instead be posed as a discrete tiling problem and solved exhaustively. Enumerating all rhombus tilings of the surface
lattice, together with all EC-compatible adatom arrangements built on them, yields the complete catalog of 416,683 configurations at fixed stoichiometry (3 Ga adatoms and 18 H atoms), organized by
symmetry into 14 Ga placement classes. The number of tilings compatible with a given configuration, its tiling decomposition multiplicity $n_\mathrm{til}$, predicts stability. Within each class, the configuration maximizing $n_\mathrm{til}$ is the most stable. The rule holds strictly in 13 of the 14 classes; in the remaining class the minimum is itself among the highest-multiplicity configurations, with the $n_\mathrm{til}$-max configuration only 8.5 meV above it; this ordering is reproduced by independent DFT calculations, and the difference is negligible at growth temperature. Stability screening uses a machine-learning interatomic potential validated against 710 DFT-computed structures. The rule reduces the candidate set for first-principles evaluation from 416,683 to 24 configurations, all of which have been evaluated with DFT. Analysis of the rule identifies the local mechanism, the avoidance of adjacent bare surface sites, while the existence of a compatible tiling remains a separate requirement with an energy cost of its own. Enumeration thus provides what sampling cannot: a coverage guarantee, and a route to stable-structure prediction in which first-principles input enters only at the final ranking step.
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All authors Tetsuji Kuboyama, Akira Kusaba, Karol Kawka, Pawel Kempisty
Plasma Physics
Development and validation of a local neoclassical transport module in NLT with applications to EAST-relevant impurity transport and trapped-electron-mode stability
Dandan Liao, Lei Ye, Guoxu Wang et al. (+5 more)
A local neoclassical transport module has been developed and validated in the semi-Lagrangian gyrokinetic code NLT for multi-species collisional
plasmas. The module incorporates a linearized multi-species Sugama collision operator and provides two complementary solution strategies. In the initial-value formulation, a composite substep source-integration scheme is introduced to accurately evaluate the neoclassical drive along unperturbed particle trajectories while retaining large macroscopic time steps. A direct steady-state solver is also implemented to obtain the stationary neoclassical response without long-time relaxation. The two approaches are benchmarked against the Eulerian neoclassical code NEO for electron-ion
plasmas and three-species
plasmas with carbon
impurities. The NLT results reproduce the NEO particle and heat fluxes, parallel flows, and bootstrap current over a broad collisionality range. As representative applications, the validated framework is applied to EAST-relevant tungsten
impurity transport and core trapped-electron-mode stability. The results show that tungsten neoclassical transport is sensitive to local profile gradients, while the increased effective collisionality associated with larger \(Z_{\rm eff}\) can reduce the linear TEM growth rate under the considered EAST-relevant conditions. These developments extend NLT toward realistic multi-species collisional transport simulations.
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All authors Dandan Liao, Lei Ye, Guoxu Wang, Xiaotao Xiao, Chengkang Pan, Qilong Ren, Wei Zhang, Nong Xiang
Medical Physics
Quantum Generalized Equivalent Uniform Dose (QgEUD): A Simulation Method for Phase-Dependent Radiobiological Dose Effects
Yusuke Anetai
The generalized equivalent uniform dose (gEUD) provides a biologically interpretable measure of heterogeneous dose distributions and is widely used in radiobiological modeling. However, because gEUD depends solely on dose magnitude, it does not explicitly account for collective cellular interactions or phase-dependent biological responses. Here, we propose a
quantum generalized equivalent uniform dose (QgEUD), which extends the conventional gEUD kernel into the complex domain by introducing a phase variable while preserving the original dose-weighting formalism. This formulation yields a two-dimensional response surface that recovers conventional gEUD on the real axis and incorporates interaction-dependent radiobiological effects through phase modulation. The local response of the surface is characterized by a Kähler metric, providing an intrinsic measure of sensitivity to dose weighting and phase perturbations. To demonstrate the framework, local dose elements are modeled by an Ising
Hamiltonian with dose- and phase-dependent interactions, and
equilibrium response maps are obtained using Metropolis Monte Carlo simulations. Simulations in a virtual radiotherapy phantom preserve the overall dose distribution while producing spatially modulated biological-effect maps governed by collective interactions. The corresponding Kähler response identifies regions exhibiting enhanced sensitivity beyond dose magnitude alone, and parameter sensitivity analysis confirms stable convergence under practical simulation conditions. These results establish QgEUD as a
quantum-inspired extension of gEUD that integrates heterogeneous dose aggregation, phase-dependent interactions, and
geometric response within a unified mathematical framework, providing a basis for interaction-aware radiobiological modeling and future
quantum-compatible optimization.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
AeroMELD: A Linear Embedding of Aerosol Populations for Diagnostics and Latent Dynamics
Ehsan Saleh, Saba Ghaffari, Wenhan Tang et al. (+5 more)
Accurately representing atmospheric aerosol populations is essential for simulating aerosol-cloud interactions, radiative forcing, and ice nucleation, yet existing reduced schemes impose structural assumptions that limit their ability to capture composition diversity and mixing state. Machine-learning approaches offer more flexible representations, but standard autoencoders do not preserve the mathematical structure of aerosol populations and therefore cannot support physically meaningful process operators. We introduce AeroMELD (Aerosol Measure
Embedding for Latent Dynamics), a mathematically grounded framework for constructing low-dimensional latent variables that retain this structure. We show that any permutation-invariant linear encoder must take a scale-shape decomposition, with total number concentration represented explicitly and latent shape given by a barycentric combination of per-particle
embeddings. This aggregated latent state retains the diagnostic expressiveness of a Deep Sets model by moving the nonlinear post-aggregation stage into the learned diagnostic map while preserving latent linearity. Using particle-resolved data as ground truth, we encode weighted particle populations directly rather than binned aerosol states; size-resolved mass and number distributions serve only as diagnostic targets and visual summaries. The latent space accurately reconstructs these distributions, CCN spectra, optical coefficients, and immersion-freezing behavior while preserving the linear population structure needed for hybrid ML-physics models. Although the experiments focus on diagnostic reconstruction, the
embedding is designed so that emissions and mixing can be represented exactly and nonlinear microphysical processes learned in a controlled latent space. This work establishes a foundation for learning aerosol-process
evolution directly in latent space.
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All authors Ehsan Saleh, Saba Ghaffari, Wenhan Tang, Jeffrey H. Curtis, Lekha Patel, Peter A. Bosler, Nicole Riemer, Matthew West
Plasma Physics
Efficient hot electron generation via low-coherence lasers
Huiya Liu, Yao Zhao, Ning Kang et al. (+13 more)
Hot electrons generated in
laser-produced
plasmas are a central focus in inertial confinement fusion, laboratory astrophysics, and high-energy-density physics. These electrons originate from instabilities in nonlinear
laser-
plasma interactions, which are critically modulated by
laser bandwidth. Here, we experimentally demonstrate enhanced generation of hot electrons by utilizing instantaneous low-coherence
lasers with two bandwidths (0.2% and 0.6%) at intensities of 2-8x10^{14} W/cm^2 and energies up to 620 J. A significant enhancement of hot electron temperature and hard X-ray yield is observed with the broadband
lasers compared to a conventional narrowband
laser. The results show that the hot electron energy conversion efficiency of the 0.6% broadband
laser is approximately 4 times higher than that of the narrowband
laser, reaching a maximum value of 2.8%. These findings validate a moderate-bandwidth
laser as an efficient hot electron source and support the generation of bright X-ray sources for advanced imaging in high-energy-density physics.
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All authors Huiya Liu, Yao Zhao, Ning Kang, Fujian Li, Guoxiao Xu, Honghai An, Jun Xiong, Zhiyong Xie, Xichen Zhou, Zhiheng Fang, Wei Wang, Lailin Ji, Xiaohui Zhao, Liang Hao, Lifeng Wang, Anle Lei
Atomic Physics · Cross-listed from quant-ph
Many-Body Physics with Rydberg Atoms: Quantum Simulation and Non-equilibrium Dynamics
Zhengyang Bai, Cheng Chen, Fan Yang et al. (+1 more)
Rydberg atoms, characterized by their strong and long-range dipole-dipole interactions, provide a versatile platform for exploring intriguing collective and many-body effects. Recently, the experimental realization of these effects in dense ensembles and reconfigurable atomic arrays has attracted significant interest, particularly for applications in
quantum simulations and non-
equilibrium physics. This review focuses on such recent development, discussing the theoretical foundations of the interactions between Rydberg atoms and the ensuing many-body physics, while providing a critical survey of experimental techniques for their precise manipulation and observation. We further discuss recent breakthroughs in leveraging Rydberg collective effects to probe novel many-body phases and non-
equilibrium dynamics of these systems. By synthesizing theoretical insights with experimental milestones, we provide a comprehensive perspective on this rapidly evolving field and its transformative potential for future
quantum technologies.
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All authors Zhengyang Bai, Cheng Chen, Fan Yang, Weibin Li
Applied Physics · Cross-listed from cond-mat.mtrl-sci
Telecom-band Chiral Light Detection through Hidden Giant Third-Order Nonlinear Circular Dichroism in Two-dimensional Halide Perovskite
Yuki Takahashi, Daichi Okada, Koshi Oi et al. (+5 more)
Chiral nonlinear optical (NLO) responses enable efficient discrimination of circularly polarized light (CPL) and are attracting increasing interest for optical and optoelectronic technologies. However, studies on NLO properties in
chiral materials have largely focused on second-order NLO processes, while the role of chirality in third-order NLO processes remains poorly explored. Here, we demonstrate telecom-band CPL detection by third harmonic generation circular dichroism (THG-CD) in the
chiral two-dimensional perovskite (R/S-MBACl)2PbI4 and uncover a
giant hidden THG-CD anisotropy that is accessible via polarization-resolved detection. Polarization-resolved THG measurements reveal that opposite
chiral NLO responses emerge in orthogonal THG polarization channels. Therefore, these
chiral anisotropic contributions largely cancel each other in the total-THG signal detection, leading to underestimation of the THG-CD dissymmetry in conventional evaluations based on total-THG intensity. By separating these hidden
chiral contributions, we observe exceptionally large dissymmetry factors exceeding 1.9 and achieve selective extraction of
chiral NLO responses with opposite handedness, without any structural
chiral inversion. These findings highlight the importance of polarization-resolved analysis for evaluating more accurate
chiral NLO responses inherent to the material and provide a promising platform for optical information processing, encryption, and anti-counterfeiting technologies at technologically relevant telecommunication wavelengths.
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All authors Yuki Takahashi, Daichi Okada, Koshi Oi, Kazuki Mitamura, Takahiko Endo, Yasumitsu Miyata, Taishi Takenobu, Kenichi Yamashita
Fluid Dynamics
Wall-scaled eddies and embedded shear layers in high-Reynolds-number moderate adverse-pressure-gradient boundary layers
Ahmad Zarei, Mitchell Lozier, Ivan Marusic et al. (+1 more)
This study compares high-Reynolds-number turbulent boundary layers under zero and low-to-moderate adverse pressure gradients, showing similar scaling and energy contributions from the wall-scaled attached-eddy hierarchy and superstructures in both flows. The main differences occur in the outer/wake region, where APG-induced energisation is linked to an outer-scaled, embedded-shear-layer-type organisation that progressively penetrates the logarithmic region as the pressure-gradient strength increases. The analysis uses two complementary
datasets for ZPG and APG boundary layers at matched friction Reynolds numbers of approximately 10,000, with minimal upstream pressure-gradient history: a new two-point hot-wire
dataset and a previously published two-dimensional particle image velocimetry
dataset. In the hot-wire experiment, one probe is fixed near the wall while the second traverses the full boundary layer, allowing estimation of the linear coherence spectrum. The results confirm the
geometric self-similarity of the wall-scaled eddy hierarchy that remains coherent with the wall. Using the linear coherence spectrum as a spectral filter shows that most of the additional APG-induced energy is incoherent with the wall and is linearly superimposed on the wall-coherent component of the streamwise variance. This wall-incoherent contribution explains the departure of the variance profile from the inverse logarithmic law observed in canonical high-Reynolds-number boundary layers. Conditional averaging of the particle image velocimetry data identifies the structures responsible for this energy amplification. The results link enhanced outer-region Reynolds stresses, an outer inflection point in the mean velocity profile, and an ejection-sweep organisation of Reynolds shear stress, all characteristic of shear-layer dynamics.
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All authors Ahmad Zarei, Mitchell Lozier, Ivan Marusic, Rahul Deshpande
Optics
Non-Abelian holonomic transformations in digitally coupled acoustic waveguides guided by the global adiabatic criterion
Jin-Kang Guo, Jia Li, Jin-Lei Wu et al. (+1 more)
An acoustic platform is validated for implementing compact non-Abelian holonomic transformations (NHTs) guided by a global adiabatic criterion (GAC). A tripod model is mapped onto a digitally coupled four-waveguide structure, where designed coupling envelopes and an acoustically-induced-transparency phase-control module implement a two-stage phase-stitched holonomic
evolution. Compared with a reference Gaussian envelope, the GAC-guided power-law profile flattens the spatial distribution of the global nonadiabatic burden, thereby providing a quantitative basis for compact acoustic implementation. Full-wave simulations show Pauli-$X$ and Hadamard-type target transformations, with excellent agreement between the extracted normalized intensities and analytical coupled-mode predictions. These target responses are obtained with half the coupling length required by the reference Gaussian implementations. More uniquely, the same phase-stitched structure also supports unidirectional acoustic mode conversion, which is closely related to a reduced two-mode non-Hermitian picture associated with an encircled exceptional point (EP). These results validate acoustic NHTs as a robust
geometric route for compact wave control, establish the GAC as a powerful guideline for fast adiabatic transport in digitally coupled systems, and further demonstrate that the same phase-stitched architecture supports unidirectional mode conversion through EP-assisted branch selection.
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All authors Jin-Kang Guo, Jia Li, Jin-Lei Wu, Chuan-Cun Shu
Fluid Dynamics
Understanding the Theory–Experiment Discrepancy in Pressure Drop of Dilute Polymer Solutions in Channel Flows
Nan Hu, Jonghyun Hwang, Evgeniy Boyko et al. (+1 more)
For decades researchers have experimentally observed that the flow of dilute viscoelastic
polymer solutions through contraction or contraction–expansion channels yields results at odds with theory and simulations. In particular, the experimentally reported pressure drops are larger than those of generalized Newtonian reference fluids with the same shear viscosity, while constitutive models, such as Oldroyd-B and FENE-P, predict smaller pressure drops under conditions of low Reynolds numbers and stable flow at small Weissenberg ($Wi$) or Deborah ($De$) numbers. This apparent contradiction between experiments and theory has been a long-standing puzzle in the field. Here, we characterize the properties of dilute viscoelastic
polymer solutions and employ two distinct types of pressure-sensing systems, conventional recessed pressure taps and flush-mounted diaphragm sensors, to systematically measure pressure drops across channels of different geometrical configurations. These measurements yield qualitative agreement with theoretical predictions across all geometries if the largest relaxation time is adopted for the analysis of the flow. Our results indicate that the apparent discrepancies mentioned above can be attributed to improper interpretation of the measurements and to mismatches between experimental conditions and assumptions made in the theoretical and numerical studies, which include hole pressure effects, the choice of relaxation time of the fluid, and the presence of experimental flow instabilities. For quantitative improvements, our results suggest the use of continuum-level constitutive models containing more realistic microscopic features of
polymer solutions.
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All authors Nan Hu, Jonghyun Hwang, Evgeniy Boyko, Howard A. Stone
Computational Physics
Structure-preserving variational neural fields: Uncertainty-quantified reduced-order modeling of nonlinear conservation laws
Aviral Prakash and Marc L. Klasky
Reduced-order models, such as latent dynamics models, are becoming mainstream for accelerating simulations for parameterized physical systems governed by nonlinear conservation laws. However, most existing latent dynamics frameworks suffer from two important limitations: they do not provide uncertainty estimates for model predictions, and they do not guarantee adherence to the underlying conservation laws. While these challenges have been addressed separately in prior work, a unified framework that simultaneously provides uncertainty quantification and exact conservation-law preservation remains largely unexplored. In this work, we develop a variational latent neural field framework that integrates Gaussian process-inspired surrogates, enabling estimation of predictive confidence for both in-distribution and out-of-distribution parameter regimes. Three variants of the framework are considered: IRS-UQ, PI-IRS-UQ, and ECLEIRS-UQ, corresponding to unconstrained, physics-informed, and conservation-structure-preserving formulations, respectively. Exact conservation-structure preservation is achieved by
embedding the solution dynamics within a conservation-law
manifold through a space-time divergence-free representation of the solution-flux field. We demonstrate the applicability of the framework through three numerical experiments: 1) 1-D advection, 2) 2-D Euler and 3) 2-D shallow water equations in parameterized settings. Numerical experiments demonstrate that the proposed approach provides accurate predictions together with uncertainty estimates, while remaining robust to sparse and noisy training data. Comparisons between the proposed three approaches show that conservation-structure preserving latent representations improve robustness to degraded training data while maintaining competitive predictive accuracy and uncertainty quantification capability.
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