Optics · Cross-listed from quant-ph
Parameter-Decoupled Quantum Superresolution without Multiparameter Estimation
X.-F. Qian
Quantum superresolution promises to resolve closely spaced sources beyond the diffraction limit, but existing approaches generally rely on idealized source properties or require simultaneous estimation of multiple coupled parameters of realistic sources. Here we introduce a parameter-decoupled measurement that determines the separation of realistic passive sources without estimating their unknown brightness imbalance, mutual coherence, or relative phase. A complete four-parameter
quantum Fisher information analysis identifies the separation information that remains accessible in the presence of these nuisance parameters. We then construct a directly measurable log-probability invariant from projection channels whose conditional statistics depend only on the separation. Broad classes of channel pairs satisfy the resulting decoupling condition. For a Gaussian point-spread function, the lowest-order implementation asymptotically attains the four-parameter
quantum limit per incident signal in the sub-Rayleigh regime. This approach converts a realistic multiparameter imaging problem into an operationally single-parameter measurement, providing a practical route toward
quantum-enhanced resolution of passive spatial, temporal, and spectral signals.
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Fluid Dynamics · Cross-listed from eess.AS
Towards Physics-Informed Neural Networks for Stiff Guitar String Vibrations
Xinmeng Luan, Kensuke Okada, Ryoya Tabata et al. (+1 more)
Modeling stiff string vibrations is challenging due to their dispersive and high-frequency characteristics. This study investigates the effectiveness of Physics-Informed Neural Networks (PINNs) in simulating the transverse vibration of a one-dimensional linear stiff string with sharp initial conditions induced by plucking. The governing Partial Differential Equation (PDE), along with the associated initial and boundary conditions, is incorporated directly into the loss function of the neural network. For the reference measurements, a wire-breaking experiment was performed to excite the string, and its vibration response was captured using a
laser profiler. The comparison between experimental measurements, finite-difference time-domain (FDTD) simulations, and PINN-based simulations shows good overall agreement, highlighting the potential of PINNs for modeling stiff-string vibrations.
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All authors Xinmeng Luan, Kensuke Okada, Ryoya Tabata, Gary Scavone
Geophysics
Determination of Physical Height Differences from Time Transfer via the ACES Mission – A Simulation Study
Klarissa Emma Lachmann, Jürgen Müller, Peter Vollmair et al. (+1 more)
The determination of physical height differences using highly stable atomic clocks has emerged as a novel approach in relativistic geodesy, exploiting the gravitational
redshift as a direct observable of geopotential differences. In this study, we investigate the feasibility of satellite-based clock comparisons using the Atomic Clock Ensemble in Space (ACES) onboard the International Space Station, which enables time transfer via microwave (MWL) and optical (ELT) links. Since operational optical data are not yet available, a comprehensive full-scale simulation of realistic ACES observation scenarios is performed, including detailed noise models of clocks and links. A slope-based estimation method is applied to time series of clock comparisons in order to extract the relativistic
redshift signal and derive height differences between the ground stations. The performance of the approach is evaluated for quasi-common view, non-common view, and split non-common view configurations, where the latter divides the observation period into shorter intervals. The results show that optical links enable faster convergence and can achieve height accuracies at the decimeter level within a few days and at the centimeter level over longer periods, while microwave links are more strongly affected by noise and bias contributions. Non-common view processing significantly increases observation availability with only minor loss in accuracy, and the split approach provides robust solutions for larger networks. These findings demonstrate the strong potential of satellite-based clock comparisons as a remote-sensing technique for determining physical height differences on a continental scale.
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All authors Klarissa Emma Lachmann, Jürgen Müller, Peter Vollmair, Anja Schlicht
Space Physics · Cross-listed from astro-ph.SR
Stability Analysis of the Proton Hammerhead Distribution Observed by Parker Solar Probe: Linear Theory and Fully Kinetic Simulations under Idealised Conditions
L. Pezzini, J. L. Verniero, F. Bacchini et al. (+3 more)
The non-adiabatic heating of the slow Solar Wind (SW) remains an open problem, with wave–particle interactions as a primary candidate mechanism. Novel in situ Parker Solar Probe (PSP) observations reveal strongly perpendicular anisotropic velocity distribution functions (VDFs), called "hammerhead", correlated with intense wave activity. These VDFs are systematically measured at the Heliospheric Current Sheet (HCS), making the hammerhead an important kinetic signature of the slow SW. In this work, we employ a fully kinetic particle-in-
cell approach, complemented by a linear Vlasov solver to cross-validate the simulation results, to investigate the stability of these VDFs, the timescales over which they evolve, and their interaction with
plasma waves. Our main findings indicate that the hammerhead distribution is primarily susceptible to drift-type instabilities, while energy is nonlinearly transferred back to the
plasma through a combination of Landau and cyclotron resonances, resulting in net heating in the parallel direction, preferentially energizing the beam
proton population. Crucially, these nonlinear interactions do not drastically alter the morphology of the distribution. This suggests the possibility that the hammerhead may be generated locally within the HCS in the inner heliosphere and subsequently advected outward, where it is eventually measured by PSP. This work lays the ground for future investigations into the kinetic physics of the HCS.
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All authors L. Pezzini, J. L. Verniero, F. Bacchini, A. N. Zhukov, G. Arrò, R. A. Lòpez
Optics
When Integrated Photonics Should Be Wavy
Oliver R. Müller, J. J. Erik Maris, Yannik M. Glauser et al. (+2 more)
Increasing demand for high-performance optical devices drives the search for improved fabrication and design paradigms. While photonic
circuits have traditionally used structures with two discrete 'binary' height levels, grayscale 'wavy' interfaces, or optical
Fourier surfaces, have recently become possible. They provide precise control over the
Fourier components that govern the optical response. This capability raises the question: When does a wavy device improve performance and why? Here, we show that wavy integrated processors exhibit superior accuracy and efficiency to binary analogs. Inverse-designed wavy interferometers have the design freedom to minimize outscattering to free space and backreflections. They reach a five-fold lower transmission error than binary counterparts and enable bandwidths up to 300 nm. We formalize these findings for other distinct integrated devices, such as photonic
crystals, nanocavities, and beam emitters. A
Fourier-optics analysis identifies a trade-off: wavy profiles manipulate light more accurately, whereas binary profiles excel in interaction strength. As such, tailored wavy profiles emit high-quality beams. However, binary profiles remain preferable in photonic
crystals and nanocavities, where maximal index contrast is required and binarization-induced higher harmonics are benign. Thus, for
quantum information, optical computing, and sensing, optical
Fourier surfaces offer a route to miniaturized integrated
circuits with improved performance.
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All authors Oliver R. Müller, J. J. Erik Maris, Yannik M. Glauser, Sander J. W. Vonk, David J. Norris
Computational Physics
Dirac Cones in d-wave Altermagnets Enable High-Conductivity and High-Efficiency Spin Sources
Tianye Yu, Junwen Lai, Peitao Liu et al. (+2 more)
Low critical charge-current density and low energy dissipation are highly desired in
magnetic random-access
memories, requiring
spin sources to exhibit both high charge-to-
spin conversion efficiency (CSE) and high charge conductivity. Altermagnets with vanishing net
magnetic moment and
spin-splitting bands provide promising
spin-source candidates for
spin-splitting-torque
magnetic random-access
memories. However, achieving both high CSE and charge conductivity remains challenging in altermagnets. In this work, we introduce Dirac cones into two-dimensional d-wave altermagnets, where their intrinsically high carrier mobility enables tunable charge and
spin conductivities with high CSE. Dirac-cone anisotropy provides an effective means of enhancing both CSE and charge conductivity, with cone tilting serving as an additional degree of tunability. Guided by this design principle, we identify a maximum CSE of 92% in Cr2SeTeS. When the Fermi level moves slightly away from the Dirac point, high CSE, high charge conductivity, and the resulting high
spin conductivity can be simultaneously achieved. Our study advances the understanding of time-reversal-odd
spin transport via Dirac-cone engineering and provides a practical route toward developing
spin-source materials that combine high charge conductivity with highly efficient charge-to-
spin conversion.
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All authors Tianye Yu, Junwen Lai, Peitao Liu, Xing-Qiu Chen, Yan Sun
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Complete Neural Electronic Initialization Accelerates Materials DFT
Felix Ærtebjerg, Jonas Elsborg and Arghya Bhowmik
We present the first complete machine learning method for accelerating plane-wave density functional theory (DFT) in materials under the projector augmented wave (PAW) formalism. We formalize seven criteria that a Complete Neural Electronic Initializer must satisfy for practical end-to-end PAW DFT acceleration. Applying these to prior work reveals two structure-dependent components, augmentation occupancies and
spin initialization, whose absence prevents existing acceleration methods from providing complete reference-free initialization. We show that omitting these components can eliminate or reverse the acceleration obtained via models that only predict the smooth valence density. We satisfy the missing requirements by introducing AugNet, a general equivariant model for PAW augmentation occupancies, and the first general
spin density model for materials, which predicts the smooth
spin-difference density and
spin-difference PAW augmentation occupancies using predicted
magnetic moments to constrain the global
magnetic state. Combined with existing valence density models, our full method satisfies all seven criteria and forms a fully reference-free electronic initializer for materials DFT, requiring no electronic quantities from a converged target calculation. We show that perfect initialization could cut PAW DFT wall time by 40-52%, and our method recovers up to 62% of this saving, reducing end-to-end DFT wall time by up to ~25% on unseen structures while preserving converged energies.
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Fluid Dynamics
A multi-scale approach for wall-bounded WCSPH–RANS simulations
Feng Wang, Nikolaus Adams and Xiangyu Hu
Achieving sufficient near-wall resolution remains challenging for wall-bounded
turbulence simulations using weakly compressible smoothed particle hydrodynamics (WCSPH), as local particle refinement imposes restrictive time-step requirements. This work proposes a multi-scale near-wall approach within the Reynolds-averaged Navier–Stokes (RANS) framework to improve near-wall predictions without refining the SPH particle distribution. A local one-dimensional sublayer solver based on the simplified steady $k$–$\omega$ equations is coupled with each wall-adjacent fluid particle. A local flow-rate constraint and a friction-velocity-based iteration scheme are developed to close and solve the sublayer system, while a two-way shear-stress coupling with local feedback improves consistency between the two scales. The proposed approach is evaluated using turbulent straight-channel flows over a wide range of Reynolds numbers and a wavy-channel flow involving separation and recirculation. The results demonstrate improved near-wall velocity, turbulent kinetic energy and friction-coefficient predictions, satisfactory convergence, and good agreement with reference solutions. In particular, the approach improves the convergence of near-wall predictions where conventional wall treatments struggle to provide consistent results, and agrees closely with reference solutions at Reynolds numbers as high as $8.0 \times 10^{7}$ without near-wall particle refinement. For separated flow, convergence comparable to that of locally refined finite-volume simulations is obtained using an approximately uniform particle distribution. These improvements are achieved with limited computational overhead, supporting the application of particle-based methods to engineering flows involving wall-bounded
turbulence.
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Computational Physics · Cross-listed from cond-mat.supr-con
Universal Dzyaloshinski-Moriya interaction dictates pairing in unconventional superconductor families
Baishun Yang, Yida Chu, Xuelei Sui et al. (+3 more)
The collinear-antiferromagnetic
spin-fluctuation paradigm has long guided unconventional superconductivity research, yet fails to reconcile the noncollinear
spin phenomena observed across cuprates, iron-based
superconductors, and nickelates. Using extensive first-principles calculations and unbiased large-scale DMRG simulations, we show that Dzyaloshinski-Moriya interaction (DMI)-arising from local inversion-
symmetry breaking-is a common ingredient across these families. This DMI unifies hallmark observations in parent compounds-incommensurate orders,
spin-wave gaps, and noncollinear textures. Under hole doping, strong DMI drives
spin vortices to merge with pi-shifted hole stripes, forming hybrid
vortex-hole stripe phases. These phases stabilize charge order while supporting, not suppressing, superconductivity. By contrast, under electron doping, these
vortices pin holes and suppress long-range superconductivity. Our results establish DMI as a unifying link between noncollinear magnetism and superconductivity, identifying hole-strip-
vortex coupling as a microscopic pairing engine. Given that DMI is common across major
superconductor families, these findings challenge the prevailing pairing mechanism and offer an experimentally testable roadmap for materials optimization.
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All authors Baishun Yang, Yida Chu, Xuelei Sui, Haiqing Lin, Shijie Hu, Bing Huang
Optics
Symmetry Properties of Bound States in the Continuum in Hexagonal Lattice Photonic Crystal Slabs
Rhys Jones and Sang Soon Oh
Bound states in the continuum (BICs) within photonic
crystal (PhC) cavities realise the full confinement of light despite lying within the continuum of radiation modes. While their diverse practical applications has attracted considerable research interest, developing the fundamental understanding of BICs is important for the design of future devices. This paper uses a group theoretical approach to determine the basis functions of the irreducible representations (irreps) of a PhC with the
symmetry of the $C_{6v}$ space group, from which the spatial distribution of the electromagnetic fields within the cavity can be determined. Furthermore, the reflection parity of the electric field and a $k \cdot p$ perturbation theory approach are used to determine the far-field polarisation of each irrep. The $k \cdot p$ perturbation explains why the $E_2$ irrep has a topological charge of $-2$, as well as showing that a topological charge does not necessarily indicate the presence of a BIC. Additionally, it is found that the quality factor of the modes do not necessarily scale as $Q \propto 1/|k|^{2|q|}$, but are instead dependent on the coupling to the radiative mode in the $k \cdot p$ perturbation, which is determined from the
symmetry of each irrep.
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Biological Physics
Signature of mechanically induced cell extrusions in cell size distribution
Ali Tahaei and Marko Popović
How a growing tissue organizes its own homeostatic state is a central question in the physics of living matter. We show that when a growing epithelial sheet counteracts increasing
cell density by mechanically squeezing
cells out of its plane, a homeostatic in-plane pressure emerges as a generalization of a yield stress. We find that in the quasistatic growth limit the homeostatic state is marginally stable, with a pseudogap in the distribution of local distances to the extrusion threshold pressure. Because such mechanically induced extrusions arise from an instability of individual
cells, the pseudogap is imprinted in the distribution of
cell areas. This provides an image-based way to test for presence of mechanically induced extrusions and we identify this signature in the developing wing epithelium of D.~melanogaster. We expect the same principles to apply to confined three-dimensional tissues.
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Data Analysis and Statistics · Cross-listed from astro-ph.IM
Bayesian classification of astronomical spectra with class uncertainties
Simon Barton, Martin Sahlén, Andreas Korn et al. (+1 more)
Context: We developed a probabilistic machine learning method with the aim of performing the O(10)-way classification of low- and high-resolution spectra of stellar and extragalactic targets for the upcoming 4MOST survey. In fulfilment of the survey requirements, this method should be able to express uncertainty in the input data as well as uncertainty introduced in its prediction. Aims: Four different methods are explored: (1) convolutional neural networks (CNNs), (2) the Dirichlet distribution, (3) Monte Carlo dropout (MCD), (4)
Bayesian neural Networks (BNNs) + variational inference (VI). Training and validation was performed using labelled spectra from the SDSS database and a custom 4MOST mock
dataset. All the methods were compared in terms of the same metrics: accuracy, area under the curve (AUC), expected calibration error (ECE), Shannon
entropy, negative log-likelihood (NLL), Brier score, training time, and inference time. Methods: A CNN with simple architecture and about 20,000 parameters was trained to achieve classification accuracies of 91.5% on SDSS data and 92.8% on 4MOST mock data. The direct Dirichlet prediction and VI models tested provide uncertainties on class membership probabilities, but they confuse classes more often. The MCD on a CNN is found to be the most suitable; it boosts the point-estimate accuracies to 92.6% and 93.9%, while still providing fast training and sufficiently fast inference. Compared to a standard CNN, the method additionally provides well-calibrated uncertainties at marginal extra cost.
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All authors Simon Barton, Martin Sahlén, Andreas Korn, Christian Glaser
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Adsorption of Phosgene Gas on Pristine and Noble Metal-Doped B12N12 Nanocages: Insights from Density Functional Theory
Shahariar Chowdhury, Mohammad Abdul Matin, Samiran Bhattacharjee et al. (+1 more)
This study examines phosgene (COCl2) adsorption on pristine and noble metal-doped (Ag, Au, Pd, Pt) B12N12 nanocages using dispersion-corrected density functional theory [B3LYP-D3(BJ)]. Boron-site substitution narrows the HOMO-LUMO gap far more than nitrogen-site substitution (69-82% vs 41-67%) and was adopted throughout. All systems were fully optimized; multiple starting geometries converged to two stable minima per dopant, X-O and X-Cl. Pristine B12N12 binds phosgene weakly (Eads = -12.8 to -24.9 kJ mol^-1). Doping strengthens binding, spanning -14.0 to -60.7 kJ mol^-1 after counterpoise correction, with platinum exhibiting the highest affinity and structural stability. Natural population analysis indicates phosgene donates at most 0.33 e, and QTAIM classifies all cage-adsorbate bond critical points as closed-shell or intermediate, confirming physisorption. Vibrational frequency analysis confirms all structures as true minima and reveals that the adsorption
entropy penalty (59-161 J mol^-1 K^-1) is decisive. Under Grimme's quasi-harmonic approximation, pristine cages fail to bind phosgene (Delta G = +23.8 to +27.9 kJ mol^-1), whereas only Pt-O (Delta G = -8.8 kJ mol^-1) and Pd-O (-7.2 kJ mol^-1) adsorb phosgene spontaneously at 298 K. Transition-state theory indicates rapid room-temperature recovery (tau = 43 ms for Pt-O), while thermodynamic desorption occurs at 69.6 deg C, ensuring a practical regeneration window. Silver-doped cages provide narrow post-adsorption gaps and high electrophilicity but cannot retain phosgene at ambient conditions. Platinum doping is therefore the most effective strategy for reversible phosgene detection using B12N12 nanocages.
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All authors Shahariar Chowdhury, Mohammad Abdul Matin, Samiran Bhattacharjee, Ishtiaque M. Syed
Computational Physics
Perspective on Magnetic Nanoparticle Modeling: Interactions, Timescales and Regimes
Deniz Mostarac, Andrey A. Kuznetsov, Manuel Wolfschwenger et al. (+7 more)
The response of
magnetic nanoparticles (MNPs) to applied
magnetic fields underpins a broad range of biomedical and technological applications. In this Perspective, we review the principal modeling approaches for describing MNP dynamics across different physical regimes, ranging from coarse-grained macrospin descriptions to spatially resolved micromagnetic simulations. Selecting an appropriate model depends on the relevant energy scales and timescales, including those associated with
magnetic anisotropy. We compare the assumptions, computational requirements, and regimes of applicability of the fixed-point-dipole, effective-field, thermal Stoner-Wohlfarth,
diffusion-jump, coupled Landau-Lifshitz-Gilbert, egg, and micromagnetic models. Particular
attention is given to coupling magnetization dynamics with translational and rotational particle motion, hydrodynamic interactions, and long-range dipolar interactions. By relating the relevant physical regimes to the resolution and computational cost of each approach, we provide practical guidance for model selection and outline challenges for predictive multiscale simulations of interacting MNP systems.
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All authors Deniz Mostarac, Andrey A. Kuznetsov, Manuel Wolfschwenger, Santiago Helbig, Claas Abert, Rudolf Weeber, Daniel Baumgarten, Patrick Ilg, Dieter Suess, Sofia Kantorovich
Applied Physics
Liquid-Nitrogen Micropillar-Wick Cooling for Cryogenic Electronics: A Numerical Study of Thermal Performance and Capillary Dry-Out Limits
Felix Mende, Marcus Wislicenus, Dianping Jiang et al. (+2 more)
Cryogenic computing technologies are maturing rapidly, but heat removal remains a key challenge when increasing the device density and operating power. Two-phase evaporative cooling is a promising approach to solve this issue, because it can dissipate high heat fluxes while maintaining small temperature rises. Here, we numerically investigate
liquid-$\mathrm{N_2}$-filled silicon micropillar wicks as a capillary-fed thin-film evaporation concept for cryogenic electronics. The model combines Young-Laplace meniscus calculations, Hertz-Knudsen-Schrage evaporation, unit-
cell heat-transfer and
liquid-flow simulations, and an array-level thermal and capillary-flow model. For a representative geometry with a pillar diameter of $10\,\mu\mathrm{m}$, pitch of $24\,\mu\mathrm{m}$, and pillar height of $75\,\mu\mathrm{m}$ at an applied heat flux of $20\,\mathrm{W\,cm^{-2}}$, the predicted chip-temperature rise is approximately $2.7\,\mathrm{K}$. This is substantially below the estimated temperature rises for representative conduction cooling through an indium-interlayered copper heat sink and direct
liquid-$\mathrm{N_2}$ immersion. The corresponding predicted single-fed dry-out length is approximately $2.7\,\mathrm{mm}$, equivalent to an ideal double-fed coolable width of approximately $5.3\,\mathrm{mm}$. The results indicate that local thermal performance is favorable, whereas lateral scalability is primarily constrained by capillary dry-out. An approximate capillary-viscous scaling relation provides a compact framework for comparing dry-out limits across working fluids and related wick geometries and for identifying strategies to extend capillary-fed transport.
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All authors Felix Mende, Marcus Wislicenus, Dianping Jiang, Munehiro Tada, Lukas M. Eng
Physics and Society
Detectability limits of scaling laws
Alec Kirkley
Power law scaling relations between size and output are central to quantitative theories of cities, organisms, and other complex systems. Competing theories predict scaling exponents that differ by small fractions, but there is no existing theory for verifying whether a given
dataset can even distinguish exponents at the required resolution to address such discrepancies. Here we derive a resolution limit for scaling exponents, giving the smallest exponent difference that any method of analysis can detect. We find that the Hurst exponents governing the
evolution of systems' sizes and deviations from the scaling law determine how long a record of growing systems must be before it can separate competing scaling theories. Empirical results suggest that many available data panels are insufficient for reliable scaling model selection.
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Accelerator Physics
Approximate solution of an adapted Bethe transport equation for electron scattering in foils
J.M. Corstens
A new semi-analytical model for electron scattering in foils is presented valid for thin foils and electron-beam kinetic energies up to roughly $100$ keV and from 20 keV at a dimensionless foil thickness of $20$, and higher energies for thinner foils. To perform calculations, an approximate solution is constructed by Hankel transforms of an adapted Bethe transport equation for electron scattering. The Wentzel differential cross section is used in the Bethe transport Eq. and resulting integrals are solved analytically or approximated. These approximate solutions of the transport Eq.'s were compared to the Goudsmit-Saunderson solutions in gold, for thin samples with dimensionless thicknesses $\lambda=5,10,20$. We also compare to the Kawrakow \cite{Kawr} model, which uses the small angle approximation. We show that in the regime of $20$ to $100$ keV beam energies, our model performs better than Kawrakow's model and this is opposite above about 100 keV. Exactly, some angularly distributed beams and the influence of energy loss of the beam can be simulated with our model.
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Instrumentation and Detectors
A compact fibre-coupled active beamstop for fast time-resolved monitoring of synchrotron X-ray beams
Friedjof Tellkamp, David von Stetten and Martin Kollewe
We have developed a compact fibre-coupled active beamstop for simultaneous interception and time-resolved monitoring of the direct X-ray beam in synchrotron diffraction experiments. The complete beamstop tip has a maximum transverse dimension of 1 mm and incorporates a 700 $\mu$m-wide Ce:YAG scintillator. The scintillator converts the intercepted X-rays into visible light, which is transported through a multimode optical fibre to a silicon photodiode at the bottom of the blade that is connected to a dedicated fast amplifier electronics. Tests with a pulsed
laser yielded a system decay time of 69.4 ns, consistent with reported luminescence decay times for Ce:YAG. Measurements at the P14.EH2 end station of PETRA III demonstrated the detection of individual bunch signals separated by 192 ns in the 40-bunch operating mode. The active beamstop also provided an in-situ timing signal for synchronising an experimental sequence with the approximately 190 $\mu$s transmission window of a mechanical X-ray chopper. The device therefore combines a compact obstruction of the direct beam with fast monitoring of X-ray timing and flux during diffraction data acquisition.
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Physics and Society
Multilayer Analysis of the Global Trade Network
Chenyang Li, Leonardo Brogi, Andrea Civilini et al. (+3 more)
Global trade is more than a single network of aggregate flows. Beneath the observable exchange of products among economies lies a complex multilayer structure, formed by thousands of product-specific trade relationships that differ in their similarity, interdependence, and temporal
evolution. Using the CEPII's BACI database, which records bilateral product-level trade flows between economies, we represent the global trade network from 1995 to 2024 as a temporal multilayer network, with economies as nodes and directed weighted trade flows as edges. To investigate product-level organisation and cross-layer similarity, temporal structural change, and the structural role of individual economies, we introduce a random-walk-based similarity measure that provides a unified framework for comparing weighted and directed trade layers. Our results show that the global trade network remains relatively stable over short periods but undergoes gradual structural change over longer timescales. We also find that similarity-based product communities only partially align with the official product taxonomy, indicating that products assigned to the same official category do not necessarily exhibit similar trade-network structures. Finally, we show that an economy's structural influence is not always determined by its trade volume. These results highlight the value of multilayer network analysis for revealing patterns in global trade that remain hidden at the aggregate level.
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All authors Chenyang Li, Leonardo Brogi, Andrea Civilini, Piero Mazzarisi, Nicola Perra, Vito Latora
Atmospheric and Oceanic Physics
Surface Stokes drift from compact drifting wave buoys
Alexey S. Mironov, Fabrice Collard, Gwenaele Jan et al. (+1 more)
Surface Stokes drift depends strongly on the energy and directions of short waves, which are incompletely resolved by routine wave observations. We derive surface Stokes drift vectors from wave measurements collected by compact drifting buoys during three deployments in the North-East Atlantic and the Alboran Sea. The calculation uses vertical-acceleration spectra and first directional
Fourier moments, which describe the mean wave direction and directional concentration at each frequency; it accounts for the Doppler shift caused by buoy motion relative to the water and adds a calibrated high-frequency tail above an intrinsic frequency of 0.7 Hz. Across 13,139 records, the median estimated speed is 0.081 m/s at a median wind speed of 6.8 m/s. Over the measured band of 0.04-1 Hz, accounting for wave directions reduces the magnitude by a median 39% relative to the unidirectional assumption. The median ratio of the parameterised tail magnitude above 0.7 Hz to the total estimated magnitude is 0.37. Comparisons with WAVEWATCH III and Copernicus Marine MFWAM show strong covariation and similar wind-dependent differences from the buoy-derived estimates. On the station-matched sample from the two Atlantic deployments, WAVEWATCH III directional spectra indicate that these differences within the compared band arise mainly from spectral levels rather than from net directional reduction. The observations provide constraints for model evaluation; the contribution of the unresolved short waves remains sensitive to the assumed spectral tail and its directional spreading.
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All authors Alexey S. Mironov, Fabrice Collard, Gwenaele Jan, Bertrand Chapron
Fluid Dynamics
Periodic Neural Mapping for Unsteady Rotor-Blade Pressure and Aeroelastic Load Prediction
Lionel Salesses, Joachim Dominique, Tariq Benamara et al. (+2 more)
Accurate prediction of unsteady aerodynamic loads remains a major challenge in turbomachinery design. High-fidelity Computational Fluid Dynamics (CFD) simulations are expensive, while aeroelastic Quantities of Interest (QoI) depend sensitively on the temporal
evolution of the pressure field. This work introduces periodic
Fourier Neural Mapping (p-FNM), a neural-operator framework for predicting unsteady pressure distributions on turbine rotor blades simulated using the chorochronic numerical hypothesis. The architecture embeds temporal periodicity into the model and learns a continuous mapping from operating conditions and time to pressure fields. Unlike sequential latent-space approaches, p-FNM predicts pressure fields independently at any time, avoiding error accumulation while preserving temporal continuity. The model is evaluated on a database of unsteady rotor-blade simulations and compared with a reduced-order baseline based on a variational autoencoder and recurrent neural network, refered as the Temporal Prediction Model (TPM). Performance is assessed for pressure fields and Generalized Aerodynamic Forces (GAFs), the primary aeroelastic QoI. Across all training
datasets, p-FNM consistently outperforms TPM. On the largest
dataset, p-FNM achieves a pressure-field mean absolute percentage error of 0.46% and a GAF-magnitude prediction error of 4.42%, corresponding to improvements of 60.7% and 77.6%, respectively. The minimum weighted phase error reaches 0.060 rad, demonstrating accurate preservation of the temporal characteristics of the aerodynamic response. The results show that GAF prediction is more challenging than pressure-field prediction and that temporal coherence is critical for accurately predicting spectral aerodynamic quantities. These findings demonstrate the potential of periodic neural operators for reduced-order modeling and aeroelastic analysis in turbomachinery.
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All authors Lionel Salesses, Joachim Dominique, Tariq Benamara, Théo Flament, Franck Mastrippolito
Optics
Programmable Intrinsic Circularly Polarized Emission
Yujie Jiao, Zhenqin Li, Yide Chang et al. (+11 more)
Circularly polarized luminescence (CPL) is central to chiral photonics, yet programming circularly polarized emission at the nanoscale remains challenging. Here, we program intrinsic CPL at its microscopic origin in
laser-written all-inorganic perovskite nanocrystals embedded in glass. High-resolution transmission electron microscopy reveals a core-shell-like variation in interplanar spacing associated with intrinsic CPL, consistent with torsional
lattice distortion. The torsional
lattice distortion breaks inversion
symmetry, while density functional theory calculations show that it lifts the
spin degeneracy of the band-edge electronic states. Power-dependent measurements further reveal a transition from birefringence-mediated circular polarization to intrinsic CPL, accompanied by the emergence of a distinct core-shell-like
lattice distortion in the nanocrystals. By tuning the incident linear polarization angle and focal depth, we deterministically control both the handedness and magnitude of the intrinsic CPL, with |glum| of approximately 4 ^ 10^-3. These results show that programmable intrinsic CPL originates from the structural and electronic properties of the emitting nanocrystals, enabling circularly polarized emission to be controlled at its microscopic origin and spatially encoded within a monolithic material.
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All authors Yujie Jiao, Zhenqin Li, Yide Chang, Yongsen He, Xiaoyu Sun, Wei Lyu, Jiayu Ding, Zhaolin Zhong, Puxin Yang, Chi Chen, Bangjie Song, Min Qiu, Yanming Wang, Siying Peng
Optics
Frequency-swept Brillouin spectroscopy
Lin Kang, Shahrin Jahan Jaima and Jitao Zhang
Spontaneous Brillouin microscopy provides non-contact access to the viscoelastic properties of materials. Standard measurements typically utilize a single-wavelength continuous-wave
laser to illuminate a specimen and excites a spontaneous Brillouin scattering signal, which is then recorded by a spectrometer. Existing Brillouin spectrometers are mostly built around either a scanning Fabry-Pérot etalon or a virtually imaged phased array (VIPA) etalon. While performing well, these setups are bulky and demand significant optical expertise to construct and maintain. Here, we propose a new approach to conducting Brillouin spectroscopy. In this approach, a frequency-swept
laser excites a series of Brillouin spectra with incrementally shifted central frequencies, while a frequency picker, consisting of a narrow bandpass filter and a highly sensitive single-
photon detector, sequentially records each spectral component to reconstruct the full spectrum. We demonstrate that the frequency-swept Brillouin spectroscopy can run under shot-noise limited condition using standard samples. Compared with conventional spectrometers, our system features a much more compact design for portable applications and holds potential for rapid mechanical imaging through multiplexing.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci
Single Best Fits Can Be Misleading: Resolving Common Trapping Signatures across FA–Cs Perovskites
Maxim Simmonds, Katarzyna Pydzińska-Białek, Thomas C. Rossi et al. (+6 more)
Identifying defects responsible for non-radiative recombination in metal-halide perovskites remains challenging, with no common defect signatures established across compositions. Here, we combine fluence-dependent time-resolved photoluminescence, full Shockley–Read–Hall modelling and
Bayesian posterior inference across an FA$_{1-x}$Cs$_x$PbI$_3$ compositional series. We show that trap occupation governs carrier dynamics and defect-parameter identifiability in semiconducting materials: weakly occupied states exhibit electron-capture-coefficient–trap-density degeneracies, whereas trap filling lifts them. In our perovskite systems, a non-degenerate signature $T\beta$, characterized by a strongly asymmetric $\beta_p/\beta_n$ capture-coefficient ratio, occurs across all compositions, suggesting substantial trap filling is a general feature of perovskite carrier dynamics. We further identify $T\alpha$ as a shared, device-performance-limiting non-radiative recombination channel, while a shallow $T\epsilon$ signature unique to FAPbI$_3$ produces the largest steady-state non-radiative recombination rate and is consistent with the previously observed high stacking-fault density of this composition. This framework therefore provides a basis for comparing trapping signatures across different semiconducting materials at room temperature.
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All authors Maxim Simmonds, Katarzyna Pydzińska-Białek, Thomas C. Rossi, Mostafa Othman, Aïcha Hessler-Wyser, Christian Wolff, Christophe Ballif, Vincent M. Le Corre, Eva Unger
Chemical Physics
Enriching molecular Raman spectroscopy with vibrational strong coupling
Matteo Castagnola, Anne Todsen Hansen, Morten Hanefeld Dziegiel et al. (+3 more)
Raman spectroscopy is widely used for molecular identification in biological samples, but spectral congestion often obscures key molecular fingerprints. Strategies to enrich vibrational spectra with additional controllable features are therefore desirable. We theoretically show that vibrational strong coupling (VSC) can reshape Raman spectra by reorganizing vibrational energies and intensities. Near-resonant coupling enables the resolution of quasi-degenerate vibrational modes and redistributes Raman activity among molecular vibrations, brightening otherwise Raman-inactive modes. Off-resonant coupling mediates effective interactions between vibrations, leading to tunable intensity reorganizations and spectral shifts via cavity-controlled vibrational mixing. Using a microscopic theory of Raman scattering, we show that observing Raman signals from collective VSC polaritons requires appropriate geometries for the scattering setup, the sample, and the cavity environment, helping to explain why polaritonic Raman signatures have remained challenging to observe experimentally.
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All authors Matteo Castagnola, Anne Todsen Hansen, Morten Hanefeld Dziegiel, Anders Kristensen, Søren Raza, Simone Latini
Chemical Physics
From sparse quantum-computing data to atomistic simulation with universal machine-learning interatomic potentials
Tuan Minh Do, Yuichiro Yoshida, Kenji Ishihara et al. (+1 more)
We propose a framework for incorporating
quantum-computing-based electronic-structure calculations into universal machine-learning interatomic potentials (uMLIPs). Rather than constructing an interatomic potential from scratch, we refine a pretrained DFT-based uMLIP using a small set of accurate reference energies obtained from
quantum computing. We demonstrate the approach for three chemically distinct applications: the Menshutkin reaction, water adsorption in the metal-organic framework HKUST-1, and CO hopping on a high-
entropy-
alloy nanoparticle. For the Menshutkin reaction, fine-tuning on gas-phase configurations improves the transition-state energy inside a carbon nanotube but not the product energy. For water adsorption in HKUST-1, fine-tuning with only 14 reference configurations brings adsorption thermodynamics obtained from millions of configurations sampled by Widom insertion into closer agreement with reference values. For CO hopping on an IrPdPtRhRu nanoparticle, the preference for on-top over bridge adsorption is recovered in the finite-temperature free-energy profile obtained from enhanced-sampling molecular dynamics, even though the reference data contain only energies. These results demonstrate that the proposed framework provides a practical route for incorporating
quantum-computing calculations into realistic atomistic simulations and that
quantum-computing reference data can improve pretrained uMLIPs.
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All authors Tuan Minh Do, Yuichiro Yoshida, Kenji Ishihara, Wataru Mizukami
Medical Physics
Voxel-Matching NORDIC: Non-local patch formation by time-series similarity increases tSNR in high-resolution BOLD fMRI
Alessandro Nigi, Natalia Petridou and Jeroen C.W. Siero
Submillimeter functional
magnetic resonance imaging (fMRI) based on blood-oxygenation-level-dependent (BOLD) signal enables the study of
brain function at the submillimeter level, uncovering insights into fine-scale organisations like cortical layers and columns. However, its inherently low contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) often limit its reliability and applicability. Noise Reduction with Distribution Corrected Principal Components Analysis (NORDIC PCA) is a locally low-rank denoising
algorithm that reduces thermal noise levels in BOLD fMRI in a local patch manner. However, local patches often contain a mixture of signals from multiple tissues that negatively affects the low-rank structure of the patches, which limits the denoising capabilities of the
algorithm. We propose an alternative approach for patch formation by gathering similar non-local voxels, dubbed voxel-matching (VM) NORDIC. The results on submillimeter-resolution BOLD fMRI data indicate that VM-NORDIC effectively promotes the low rank of the patches by boosting signal redundancy, allowing for more efficient noise attenuation. Moreover, the method barely affects spatial smoothness due to the non-local voxel selection based on time-series similarity. In particular, VM-NORDIC outperforms standard NORDIC with default local patching (Standard-NORDIC) in terms of temporal SNR (tSNR) (~9-90% larger than Standard-NORDIC; ~23-250% larger than the original) and spatial smoothness estimates (~20% of the smoothness induced by Standard-NORDIC). These improvements are fundamental to improving the validity and precision of fMRI studies at submillimeter resolutions.
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Optics
Mechanical Activation of Terahertz Tunneling in Metallic Nanogaps
Dasom Kim, Dukhyung Lee, Young-Mi Bahk et al. (+1 more)
Metallic nanogaps concentrate terahertz (THz) fields into deep subwavelength volumes and support field-driven electron tunneling when the insulating barrier becomes sufficiently narrow. Here, we demonstrate mechanical control of tunneling-mediated nonlinear THz transmission in a flexible nanogap metasurface. The metasurface consists of Au/PMMA/Au nanogaps fabricated on a polyethylene terephthalate substrate, enabling continuous tuning of the gap geometry through macroscopic bending. In the flat state, the resonant transmission exhibits only a weak dependence on the incident THz field strength. Upon bending, increasing the incident field strength induces pronounced resonance suppression accompanied by saturation of the voltage developed across the nanogaps. This nonlinear response is consistent with the opening of a field-dependent tunneling conduction channel through the mechanically narrowed PMMA barriers. Simmons-model calculations illustrate the strong increase in tunneling current density and the associated dissipative gap response as the local gap width approaches the few-nanometer regime. These results establish mechanical deformation as a macroscopic means of controlling tunneling-mediated THz nonlinearities in flexible metasurfaces.
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All authors Dasom Kim, Dukhyung Lee, Young-Mi Bahk, Dai-Sik Kim
Optics · Cross-listed from cond-mat.mes-hall
Rydberg excitons in core-shell nanostructures I. Optical properties
Sylwia Zielińska-Raczyńska, Gerard Czajkowski and David Ziemkiewicz
Optical properties of Cu$_2$O-metal core-shell nanostructures containing Rydberg
excitons are examined. Calculations of electron and hole eigenfunctions and eigenenergies are used to calculate
exciton energy and its dependence on system geometry and dimensionality. The limits of very small and very large structures are discussed, making the results applicable to low principal
quantum number
excitons as well as to Rydberg states. The Real Density
Matrix Approach method is used to calculate the optical properties of the studied systems.
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Instrumentation and Detectors · Cross-listed from astro-ph.IM
Development of a Temperature-Variable Cold Blackbody Calibrator for Millimeter and Submillimeter Wave Detectors
Kazuki Watanabe, Taiki Sato, Shuhei Inoue et al. (+3 more)
We report the design, fabrication, and characterization of a cryogenic blackbody calibrator intended for laboratory-based detector characterization, providing multi-temperature calibration of millimeter- and submillimeter-wave detectors over a temperature range of 4 K to ~10 K. The device employs a Stycast/SiC absorber shaped for uniform array illumination and mounted on a phosphor-bronze substrate with optimized thermal links. Measured thermal conductance and heat capacity show the expected temperature dependence, although the conductance was lower than estimated, yielding a thermal time constant of 8.5 s at 10 K versus the 3.7 s design estimate. The response remains practical, demonstrating the calibrator's effectiveness as a stable reference source for precise calibration of detector arrays.
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All authors Kazuki Watanabe, Taiki Sato, Shuhei Inoue, Shinsuke Uno, Tatsuya Takekoshi, Tai Oshima