Optics
Quantitative spin-orbit engineering enables subwavelength-scale programmable polarization states for versatile photonic functionalities
Shuaijie Yuan, Xuefeng Zhang, Jin Yang et al. (+7 more)
Precise and programmable control of optical polarization provides a versatile vectorial degree of freedom for light-matter interaction and optical information encoding. Existing polarization state generators (PSGs), however, suffer from poor switchability and modest fidelity at the micrometer scale, which severely constrains their practical applicability. To overcome these limitations, here we present a quantitative
spin-orbit engineering that enables the dynamic synthesis of arbitrary polarization states at subwavelength dimensions. The core concept is to tailor conjugate optical
vortices that independently address the orthogonal
spin components of a vectorially polarized light. This spatial modulation scheme annihilates intrinsic topological charges and reshapes the
spin-orbit interaction, thereby coherently constructing polarization ellipses on demand. Leveraging this mechanism, we experimentally synthesize diffraction-limited arbitrarily polarized beams spanning the entire Poincare sphere with fidelity over 99%. As proof-of-principle demonstrations, we apply the miniaturized PSG platform to Mueller-
matrix polarization microscopy, pixel-level polarization encryption, and parallel polarization-information encoding, illustrating its broad utility of programmable polarization control for subwavelength polarimetric imaging and reconfigurable multiplexed polarization encoding. Compared with state-of-the-art PSGs, our approach uniquely integrates rapid programmability, high fidelity, and subwavelength localization in a single architecture. These multifunctional capabilities of this work position the platform as a promising route for advancing Mueller
matrix polarization microscopy, multidimensional optical storage, and secure optical information processing, and beyond.
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All authors Shuaijie Yuan, Xuefeng Zhang, Jin Yang, Min Cheng, Xinyu Ma, Jinhai Zou, Jinyong Leng, Zhongquan Nie, Bing Lei, Pu Zhou
Optics · Cross-listed from quant-ph
Mode-tunable inter-core coupling of photon-number-resolved quantum light in a telecom multicore fiber
Chiran Wijesundara, Yasmin Sarhan, Henry Strong et al. (+3 more)
Multicore optical fibers (MCFs), developed to scale classical telecommunications, are gaining traction as a
quantum platform for high-dimensional key distribution,
entanglement, and photonic
quantum walks. So far,
quantum light has occupied these fibers only as single-mode path channels; the spatial-mode structure within each core has remained untouched. Here we operate a telecom-grade 39-core fiber far from its design wavelength, where each core supports exactly two LP mode groups (LP01, LP11), and measure heralded
photon-number states |1> and |2>, resolving the
photon number simultaneously with the intra-core spatial mode or with the core index. Displacing the launch prepares a coherent LP01-LP11 superposition whose single-sided intensity pattern shows that the intermodal phase is preserved over the fiber: a drift-resolved joint fit gives a pixel asymmetry (0.4% vs 47%) incompatible with an incoherent mode mixture. Because the two modes couple to neighboring cores at different rates (kappa_LP11/kappa_LP01 = 2.4), the launched mode content acts as a state-selectable coupling knob: the effective inter-core coupling of the passive fiber is set by the launch alone (3.9-13.1%), a tunability that otherwise requires electro-optic, thermo-optic, or mechanical reconfiguration. The propagation is
photon-number independent: the per-
photon crosstalk of heralded |2> states equals that of |1>, bounding any Fock-state dependence to |dx/x| < 6.1% (95% CL), and the imaged mode distributions of |1> and |2> agree to better than 1%. This measured linear-optics null, validated against exact Fock-space simulation, is the baseline against which genuine multiphoton interference in fiber
quantum walks must be certified; we also show how coincidence-based event selection produces spurious
photon-number-dependent crosstalk if accidentals are not subtracted.
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All authors Chiran Wijesundara, Yasmin Sarhan, Henry Strong, Jeffrey Cai, Dan T. Nguyen, Tim Thomay
Optics · Cross-listed from astro-ph.IM
Design, Fabrication, and Free-Space Characterization of a Two-Photon-Polymerized Nano-printed Photonic Lantern
Kyra Watts, Natasha Popenoe, Benjamin Gerard et al. (+6 more)
Photonic lanterns provide an interface between multimode optical fields and arrays of single-mode waveguides, making them promising components for modal filtering, wavefront sensing, and high-contrast astronomical instrumentation. We present the design, simulation, two-
photon-polymerization fabrication, and free-space characterization of a compact photonic lantern optimized for operation at $ 1050~\mathrm{nm} $. The device was designed to transform a multimode input into five nominally single-mode output waveguides. Eigenmode-expansion simulations in Ansys Lumerical MODE were used to optimize the lantern geometry while minimizing insertion loss and output-channel power nonuniformity. The optimized structure was fabricated using a Nanoscribe Photonic Professional GT2 two-
photon-polymerization system and developed as a standalone
polymer-waveguide component. The fabricated lantern was characterized using a free-space optical setup consisting of a $ 635~\mathrm{nm} $
laser for preliminary characterization, collimation and focusing optics, and camera-based imaging of the transmitted fields. Measurements were used to assess optical throughput, output intensity distribution, and light-guiding performance. Differences between simulated and measured results may arise from the wavelength mismatch, fabrication tolerances, material and surface-scattering losses,
alignment errors, and deviations from the idealized material and
geometric parameters used in simulation. These results demonstrate a compact, additively manufactured photonic-lantern platform and establish a pathway toward free-space-coupled astrophotonic systems for future high-contrast
exoplanet-imaging instrumentation.
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All authors Kyra Watts, Natasha Popenoe, Benjamin Gerard, Paul Pax, Dominic Sanchez, David Feng, C. Cole Dunn, Cari Johnston, Xiaoxing Xia
Data Analysis and Statistics · Cross-listed from stat.ML
When Is Accuracy Evidence? A Unified Theory of Generalisation, Validation, and Information Fusion
JM Gorriz
K-fold cross-validation (CV) is widely used as evidence of out-of-sample performance, although folds are neither independent experiments nor equally informative under heterogeneous data. Cross Upper-Bound Validation (CUBV) replaces point-wise CV accuracy by conservative upper bounds on true risk. Here we generalise CUBV through a single exponential framework in which the moment-generating function of the generalisation gap is controlled by a cumulant envelope gamma(lambda). This yields a family of risk bounds covering Hoeffding-, Bernstein-, dependency-aware, PAC-
Bayesian, and heterogeneous source-fusion settings. For K-fold CV, dependence between fold-wise gaps is modelled through a joint sub-Gaussian proxy
matrix. Under equicorrelation, this gives an effective number of folds, Keff = K/[1+(K-1)rho], showing that increasing K does not necessarily increase statistical evidence when folds are strongly dependent. The framework is also extended to posterior distributions over predictors and weighted multi-source fusion, where weights are selected by minimising an upper bound on future risk rather than empirical error alone. Experiments with trained linear classifiers on heterogeneous
multimodal Gaussian mixtures compare K-fold CV with full-sample resubstitution plus risk correction. Bounds are evaluated by coverage and tightness. In low-dimensional small-sample settings, K-fold partitioning can increase uncertainty because individual folds under-represent minority modes, while corrected resubstitution can remain valid and tighter; this effect disappears as sample size increases. Overall, gamma-CUBV separates observed performance, uncertainty, dependence, model complexity, and confidence into explicit terms, providing a unified route from CV scores to risk statements and a principled validation criterion for heterogeneous small-sample applications such as neuroimaging.
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Chemical Physics
Uniform instanton theory for bridge-mediated nonadiabatic tunneling
Imaad M. Ansari, George Trenins and Jeremy O. Richardson
Instanton theory provides a semiclassical approximation to nonadiabatic rate constants within a path-integral framework and captures nuclear
quantum effects such as tunneling and zero-point energy. Although the simplest reactions proceed directly from reactants to products, a number of important nonadiabatic processes involve three electronic states and react via a concerted mechanism through a virtual bridge state, also referred to as bridge-mediated tunneling or superexchange. In previous work, we have derived an instanton theory to describe such reactions using a dominant tunneling trajectory that propagates on each of the three potential energy surfaces. However, this approach is only valid when the bridge state is sufficiently low in energy. In contrast, in the high-bridge regime, the trajectories on the bridge surface become infinitesimally short, which causes the previous theory to break down. In this work, we derive the appropriate asymptotic approximation for the high-bridge regime and find that the resulting theory reduces to a two-state golden-rule instanton with an effective coupling that describes a nonresonant hop to the virtual bridge state. We further develop a uniform asymptotic instanton theory that eliminates divergences and smoothly connects the high- and low-bridge regimes. In a companion paper, we apply the method to study the quintet-to-singlet transition (via a triplet bridge) of an iron(II) complex.
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Chemical Physics
Electronic Density versus Geometry for Machine-Learned Molecular Absorption Spectra
Siddharth Dhanpal, Peter Elliott, Paolo Emilio Trevisanutto et al. (+2 more)
Molecular optical absorption spectroscopy provides a direct probe of electronic structure and is widely used for molecular identification, interpretation of photophysical behaviour, and planning of spectroscopy experiments. Calculating the absorption spectra using first-principle excited-state methods, however, is computationally demanding, at least compared to ground-state calculations, which limits their routine application across large molecular sets. Machine-learning (ML) surrogates can reduce this cost and allow rapid spectral prediction. However, their performance depends strongly on how molecular information is represented. Here, we compare using the ground-state electron density versus the molecular geometry as inputs to a ML model for predicting absorption spectra, for a training set of 6874 molecules selected from the QM7
dataset. For each of these molecules, the density was calculated using density functional theory (DFT) and the absorption spectrum was calculated using linear-response (LR) time-dependent DFT (TDDFT). Utilizing the ground-state density as the input to the ML model is motivated by the Hohenberg-Kohn and Runge-Gross
theorems, and the fact that the ground-state density encodes information about bonding, charge localisation, and electronic delocalisation. Hence, it may be a more judicious starting point for the ML model compared to the geometry, as it effectively decouples the chemistry of the ground-state. The question we test is whether the benefits of using the density outweigh the (notprohibitive) penalty of requiring an additional single-point DFT calculation for the density. We find that the density-based convolutional neural network achieves a validation correlation of 0.9926, compared with 0.9795 for the best geometry-based graph model, reducing the residual decorrelation, by approximately 64%.
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All authors Siddharth Dhanpal, Peter Elliott, Paolo Emilio Trevisanutto, Alin M. Elena, Gilberto Teobaldi
Plasma Physics
Hong Qin
The susceptibility tensor of a homogeneous collisionless magnetized
plasma possesses parity-time (PT)
symmetry. For a stationary gyrotropic
equilibrium, with the wave vector $\mathbf{k}$ and the
equilibrium magnetic field $\mathbf{B}_0$ in the $x$–$z$ plane, the kinetic response satisfies $\chi(\omega^*,\mathbf{k})=R\chi(\omega,\mathbf{k})^*R$, where $R=\operatorname{diag}(1,-1,1)$. We show that the susceptibility PT-
symmetry is a reduced-response-space manifestation of PT
symmetry of the underpinning kinetic system. We identify parity $P$ and time reversal $T$ on the electromagnetic kinetic eigenmode space and show that the
Hamiltonian operator $\mathcal{H}_{\mathrm{VM}}$ of the linearized Vlasov–Maxwell system is PT-symmetric, satisfying $PT\mathcal{H}_{\mathrm{VM}}(PT)^{-1}=\mathcal{H}_{\mathrm{VM}}$. The PT
symmetry of the homogeneous magnetized Vlasov–Poisson eigenproblem is also established. Many kinetic instabilities associated with nonmonotonic distributions, rings, loss cones, and resonant energetic-particle populations are fundamentally spontaneous PT-
symmetry breaking, which is achieved through and only through Krein collisions. Three examples demonstrate distinct utilities of this analysis. Definite-sign cyclotron residues protect thermal Bernstein modes from spontaneous PT-
symmetry breaking. The nonmonotonic Dory–Guest–Harris distribution permits sign-indefinite residues and Krein collisions, for which we derive an analytical instability threshold and growth rate. The recently discovered mode-pole resonance instability provides a distinct realization of spontaneous PT-
symmetry breaking and illustrates how PT
symmetry can guide the discovery of kinetic instabilities with applications to fusion energy. These results establish PT
symmetry as a structural principle of
plasma waves and instabilities and open new directions for studying spectral
topology in kinetic
plasmas.
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Plasma Physics · Cross-listed from astro-ph.HE
Guide field effects on particle acceleration in three-dimensional relativistic magnetic reconnection
Despina Karavola, Lorenzo Sironi and Maria Petropoulou
Relativistic
magnetic reconnection is a key mechanism for particle acceleration in astrophysical
plasmas. Recent 3D particle-in-
cell simulations have shown that, for weak guide fields, particles can be accelerated at nearly the maximal rate by escaping the reconnected
plasma and gaining energy from the large-scale upstream electric field. Here, we investigate whether this fast acceleration channel persists as the guide field becomes comparable to the reconnecting field. We perform 3D simulations of relativistic pair-
plasma reconnection, complemented by corresponding 2D runs, using open boundaries along the reconnection outflows to establish a quasi-steady state. We find that increasing the guide field strength reduces the reconnection rate and causes energetic particles to become more closely aligned with the local
magnetic field. In 3D, the fast acceleration channel—absent in 2D—persists across the full range of guide fields investigated, but involves a progressively smaller fraction of particles as the guide field increases. Consequently, stronger guide fields produce steeper particle energy spectra and lower maximum Lorentz factors.
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Atomic Physics · Cross-listed from cond-mat.mtrl-sci
Floquet density response in laser-assisted fast-electron scattering from solids
Ferdinand Evers, Sascha Schäfer and Richard Korytár
We extend the Bethe–Floquet formalism of Joachain and coworkers, originally developed for
laser-assisted electron–atom collisions, to inelastic scattering of fast electrons from a many-body condensed-matter target in a time-periodic light field. At first order in the projectile–target interaction, the general Floquet–
Fourier cross section separates into exact
laser-dressed projectile kernels and a
matrix-valued Floquet density response of the target. For spatially structured or translationally non-invariant systems, the latter is the bi-momentum Floquet structure factor; its momentum diagonal defines the Floquet generalization of the dynamic structure factor, constrained by Hermiticity, positivity, and sum rules. As a controlled realization of the general projectile kernel, an eikonal–Volkov approximation for slowly varying inhomogeneous fields yields a finite-momentum-resolution convolution of the target response. In the homogeneous-field dipole limit, the projectile kernel reduces to Bessel-function sidebands and the cross section takes the familiar Bethe–Floquet form. The Floquet density correlator separates exactly into the outer product of the pump-induced coherent mean density and connected fluctuations. In the straight-trajectory nonrecoil limit, the coherent, target-elastic sector defines the weak-coupling PINEM amplitude; repeated coherent insertions generate the PINEM Bessel ladder, with an explicit no-double-counting prescription for combining this channel with connected losses. As worked examples, we evaluate the connected, target-changing cross section analytically for a metal in the Drude and diffusive limits, recovering Bessel-weighted plasmon-loss and diffusive combs, and for a driven two-level model that exhibits off-diagonal Floquet coherences through Bessel-channel interference.
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Instrumentation and Detectors
Controlled-illumination smartphone imaging for quantitative turbidity measurement and cross-device transfer
Sebastian Olivares, Addles Castillo, Patricia Velasquez et al. (+2 more)
Smartphone imaging could provide a low-cost turbidity measurement method if illumination and acquisition geometry are controlled. We evaluated a 3D-printed enclosure with fixed illumination and a submerged optical target using 162 milk-based suspensions spanning 0.16–50.2 nephelometric turbidity units (NTU), with a portable turbidimeter as the reference. An EfficientNetB0 regression model evaluated using repeated five-fold grouped cross-validation achieved a mean absolute error (MAE) of 1.208 NTU and $R^2=0.9816$, indicating that predictions followed the reference measurements closely. The MAE was 0.335 NTU below 1 NTU and 0.449 NTU from 1 to below 5 NTU; classification accuracy at the operational 5-NTU threshold was 0.9753. When applied without retraining to 103 paired images from a second smartphone, prediction error remained comparable to that on the development smartphone below 10 NTU, but turbidity was increasingly underestimated at higher values. The results demonstrate the measurement performance attainable with a controlled smartphone acquisition system, quantify an important device-dependent transfer limitation, and motivate standardized multi-device acquisition and prospective natural-water validation.
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All authors Sebastian Olivares, Addles Castillo, Patricia Velasquez, Roxana Arce, Nicolas Richardson
Optics
Active Phase and Amplitude Modulation in Perovskite Polaritonic Waveguides
Andrea Zacheo, Marco Marangi, Tim Colin Meiler et al. (+6 more)
Integrated photonic technologies require active materials capable of providing large optical modulation within compact footprints and low losses. The large optical nonlinearities of
exciton-polaritons offer a promising route to meet these requirements, yet their integration into photonic
circuits remains challenging because strong light-matter interactions must be combined with low-loss transport and spatially localized control. Here, we demonstrate active phase and amplitude modulation in halide perovskite polaritonic waveguides integrated with electrical microheaters. Local electrothermal actuation drives a structural phase transition in the perovskite, modifying the complex refractive index dispersion near the excitonic resonance. By tuning the excitonic fraction of the propagating mode, the waveguides can therefore operate either as a phase shifter with a tuning efficiency of 0.2 mW mm, approximately one order of magnitude lower than silicon modulators with similar geometries, or as an intensity switch , providing 1 dB/um modulation depth at 20 mW. Our work establishes phase-change excitonic reconfiguration as a route towards compact polariton
circuits for nonlinear photonic applications.
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All authors Andrea Zacheo, Marco Marangi, Tim Colin Meiler, Filippo Martinelli, Antonio Fieramosca, Vincenzo Ardizzone, Giorgio Adamo, Daniele Sanvitto, Cesare Soci
Optics
Two-Laser Heterodyne Detection System for ALPS II
Henry Frädrich, Aaron D. Spector, Axel Lindner et al. (+1 more)
The Any Light Particle Search II employs a highly sensitive heterodyne detection system to measure an ultra-weak electromagnetic field that is reconverted from
axions inside a regeneration cavity (RC). The initial design of the heterodyne system utilized a local oscillator
laser (LO) that was resonant with the RC to form an interference beatnote with the weak signal field exiting the cavity. A weakness of this design is that it is possible for the out-of-mode field component of the LO to be larger than the in-mode component, allowing its noise to dominate the optical component of the noise budget and reducing the SNR of the experiment. This problem can be addressed by introducing a second, non-resonant
laser as the LO. Since the in-mode light of this
laser does not couple to the cavity, significantly more of its power is reflected than when the LO is resonant. We present a model for the measurement noise that predicts these design changes increase the SNR by a factor of roughly 35. This model was then confirmed experimentally by injecting a weak signal to the RC and examining the difference in the sensitivity of the detection system in each of these configurations.
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All authors Henry Frädrich, Aaron D. Spector, Axel Lindner, Guido Müller
Chemical Physics
Bogoliubov self-consistent $GW$ and second-order Green's function methods for attractive fermionic interactions
Mauricio Rodríguez-Mayorga, Johannes Tölle and Pierre-François Loos
Describing fermionic systems with attractive interactions, such as
superconductors and atomic
nuclei, beyond the mean-field level remains a central challenge. In this work, we investigate the performance of Bogoliubov fully self-consistent $GW$ (Bog.~sc$GW$) and second-order Green's function (Bog.~scGF2) methods, implemented within a unified imaginary-time and imaginary-frequency framework. Using the attractive Hubbard model as a
benchmark against full configuration interaction (FCI), we find that Bog. scGF2 provides a more accurate description than Bog.~sc$GW$. In particular, Bog.~sc$GW$ systematically overestimates the correlation energy, with errors increasing rapidly as the attractive interaction strength grows. These results highlight the importance of exchange contributions in strongly correlated fermionic systems, even when exchange effects are included only at low order in perturbation theory.
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Atmospheric and Oceanic Physics
Stochastic thermodynamics and predictability of Ornstein-Uhlenbeck processes: an application to the Madden-Julian Oscillation
Roberta Benincasa, Danni Du, Gregory S. Duane et al. (+1 more)
Climate oscillations are intrinsically out-of-
equilibrium phenomena, yet the connection between their predictability and nonequilibrium thermodynamic properties remains unexplored. We develop a coarse-grained
stochastic thermodynamic framework for Ornstein-Uhlenbeck (OU) processes and apply this framework to
climate data via linear inverse models (LIMs), linking predictability,
entropy production, dynamical activity, and path action.
Climate oscillations are often studied in a 2d phase space of
climate indices, which are even under time-reversal, motivating our focus on 2d OU dynamics with even variables. We find that coordinate-invariant properties of 2d OU processes can be reduced to a minimal three-parameter description: two diffusivities and a phase-space rotation. We show that these quantities fundamentally characterize distinct aspects of the dynamics. We find that higher irreversibility and dynamical activity do not necessarily imply reduced predictability. Rather, it is the path action which is most closely connected to a commonly used measure of predictability, the anomaly correlation coefficient (ACC). As an illustrative example, we apply this framework to the Madden-Julian Oscillation (MJO) over the twentieth century. We find that the MJO has become simultaneously more predictable, as seen previously, while at the same time becoming more irreversible and more active. Predictability is driven predominantly by the reduced mean
diffusion.
Entropy production reflects the combined
evolution of all three parameters. These results suggest that
stochastic thermodynamics provides a powerful lens for studying nonequilibrium
climate phenomena.
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All authors Roberta Benincasa, Danni Du, Gregory S. Duane, Jeffrey B. Weiss
Atmospheric and Oceanic Physics · Cross-listed from stat.ML
DAWIS: Data Assimilation with Windowed Inverse Sampling via Multitask Interpolants
Erik Wikingsson, Martin Andrae, Tomas Landelius et al. (+1 more)
Flow- and
diffusion-based generative models have recently emerged as flexible and highly efficient forecasting models for dynamical systems. When combined with inference-time guidance, they offer a promising route to high-dimensional non-Gaussian data assimilation (DA), the problem of combining forecasts with observations to estimate latent system states. Existing filters, however, condition on a fixed history and assimilate only the most recent observation, leaving them unable to revise past states when new observations arrive. Estimates then stay tethered to a history that later observations may contradict, and errors accumulate over the assimilation run. To this end, we introduce **DAWIS**, a unified DA method covering filtering, fixed-lag smoothing, and block smoothing within a single framework. DAWIS replaces the single flow time of a state-level prior with a multitask
stochastic interpolant over a window of consecutive states, assigning a separate flow time to each. An assimilation cycle inverts the window to a vector of per-state turning points and regenerates it under observation guidance, with the turning points controlling how strongly each state is held fixed, revised, or generated from scratch. The same construction can also absorb the forecast into the assimilation cycle, removing the need for a separate forecasting model. Experiments on challenging nonlinear systems show that DAWIS improves on both filtering and smoothing baselines under sparse, noisy, and nonlinear observations. The code for DAWIS is available at https://github.com/Erik-Wikingsson/DAWIS
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All authors Erik Wikingsson, Martin Andrae, Tomas Landelius, Fredrik Lindsten
Atmospheric and Oceanic Physics · Cross-listed from stat.ML
SDECast: Probabilistic Weather Forecasting in Continuous Time with Neural SDEs
Maria Marchenko, Martin Andrae, Fredrik Lindsten et al. (+1 more)
Existing machine learning weather forecasting models typically generate forecasts through autoregressive rollouts at a fixed temporal resolution. While highly efficient for long-range prediction, this formulation can suffer from severe error accumulation when used with shorter time steps and does not explicitly encode the locality and temporal continuity of atmospheric dynamics. To address these limitations, we introduce **SDECast**, a Neural
Stochastic Differential Equation (SDE) framework for continuous-time probabilistic weather forecasting. SDECast extends SDE Matching to learn
stochastic dynamics directly in physical space, without requiring repeated SDE simulation during training. On a simulated geophysical flow, we show that SDECast recovers meaningful drift dynamics and faithfully reproduces the underlying continuous-time behavior. We then demonstrate its scalability to global weather forecasting at hourly resolution, where SDECast produces skillful probabilistic forecasts for lead times of up to five days.
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All authors Maria Marchenko, Martin Andrae, Fredrik Lindsten, Christian A. Naesseth
Computational Physics
Experimental Bench Validation of a Computational Fluid-Structure Interaction Model of Transcatheter Aortic Valve Dynamics
Jae H. Lee, Paul Ahern, Anh D. Nguyen et al. (+4 more)
Purpose: This study extends our fluid-structure interaction (FSI) framework for surgical bioprosthetic heart valves in an experimental pulse duplicator to a transcatheter aortic valve replacement (TAVR) device. We assess hemodynamic and leaflet kinematic agreement across pulse rates and the transferability of calibrated boundary-model parameters. Methods: We compared simulated and experimental pressure, volumetric flow rate, projected dynamic valve area (PDVA), and leaflet kinematics at 60, 70, and 80 beats per minute (bpm). Reduced-order boundary-model parameters were calibrated using only data acquired at 70 bpm and were subsequently held fixed. At each pulse rate, a condition-specific pump-pressure waveform was constructed from the measured upstream pressure and flow rate. The 60 and 80 bpm cases therefore evaluate parameter transfer under measurement-informed upstream forcing. Results: Across the three conditions, normalized root-mean-square errors are 2.88-3.08% for aortic flow rate, 7.64-8.07% for upstream ventricular pressure, 3.50-6.21% for downstream aortic pressure, and 3.07-4.70% for PDVA. The simulations reproduce the principal pressure, flow, valve-opening, and valve-closure features. The downstream aortic pressure and PDVA measurements at 60 and 80 bpm were not used to construct the upstream forcing or recalibrate the model parameters and therefore provide the principal out-of-calibration validation evidence. Conclusion: The results provide conditional experimental bench validation evidence for downstream hemodynamics and valve dynamics under measurement-informed upstream forcing and support boundary-parameter transfer across pulse rates without recalibration. This work advances an experimentally supported, high-fidelity FSI framework for evaluating TAVR device performance.
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All authors Jae H. Lee, Paul Ahern, Anh D. Nguyen, Masod Sadipour, Robert Hunt, Wyatt Kmetz, Boyce E. Griffith
Physics and Society · Cross-listed from eess.SY
How suboptimal is my stochastic network controller allowed to be? Completion certificates with application to power grids hosting AI data centers
Michael Chertkov
Power grids are beginning to host AI data centers whose demand can change abruptly and in a correlated way, and operators and planners must decide whether existing controllers can absorb the resulting transients and where new flexibility is worth installing. We cast this as a question in
stochastic control: how far from optimal is an implementable controller? For controlled
diffusions with affine, state-independent actuation, additive and possibly degenerate noise and quadratic control cost, any Hamilton-Jacobi-Bellman (HJB) subsolution bounds the optimal cost from below and simulation bounds the deployed cost from above, so their gap certifies the permissible suboptimality. We construct subsolutions from path-integral control by completing the control geometry: enlarging the control Gramian until it matches the physical noise makes the problem linearly solvable, and its Feynman-Kac value is an automatic lower bound whose HJB residual is exactly the energy of the fictitious control. A dual noise-deflation construction can be tighter but requires a
curvature condition. The geometry yields planning rules: price control authority in proportion to local noise variance, and use shadow values to guide sparse reinforcement. For nonlinear
stochastic swing dynamics of the IEEE 118-bus system after a severe load loss, a simple generator controller is certified within 2.8% of optimal under homogeneous forcing; under heterogeneous forcing the gap is 39% with uniform prices and 1.2% once the same total authority is repriced, before any hardware is added.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci
Second-order Raman and anharmonic lattice dynamics in lead-halide perovskites
Chao Shen, Florian Kluibenschedl, Ayan A. Zhumekenov et al. (+4 more)
We explore the microscopic origin of THz-driven
lattice dynamics in methylammonium lead bromide CH$_3$NH$_3$PbBr$_3$ using two-dimensional THz Kerr-effect spectroscopy. The analysis of the experiment enables discrimination between competing nonlinear excitation mechanisms and reveals that the dominant pathway is
phonon-mediated rather than purely photonic. In particular, we argue that the commonly observed 1.15~THz Raman-active $A_g$ mode is not excited directly by the THz electric field. Instead, it emerges through cubic anharmonic coupling to an infrared-active
phonon at 0.68~THz. Furthermore, a satellite feature at 1.36~THz is identified as a two-
phonon Raman response of the same infrared-active mode. The observation of strong quadratic coupling involving the infrared-active
phonon suggests an unconventional form of electron-
phonon dressing present in lead-halide perovskites.
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All authors Chao Shen, Florian Kluibenschedl, Ayan A. Zhumekenov, Mikhail Lemeshko, Osman M. Bakr, Artem G. Volosniev, Zhanybek Alpichshev
Chemical Physics · Cross-listed from quant-ph
Pathway-resolved analysis of internal conversion enabled by Gaussian boson sampling
Mikhail Roiz, Rashid Valiev, Jan-Lucas Eickmann et al. (+4 more)
Gaussian
Boson Sampling (GBS) has provided strong evidence of
quantum advantage, motivating the search for real-world applications. Such applications rely on mapping physical problems to the native GBS output:
photon-number patterns sampled from a highly non-trivial probability distribution. Here we derive a GBS-compatible mapping for the rate constant $k_\mathrm{IC}$ of internal conversion (IC), incorporating two important physical effects – Duschinsky rotations and Herzberg–Teller contribution. We validate this framework using sampling simulations of dibenzoterrylene, reproducing reported values of $k_\mathrm{IC}$. Beyond $k_\mathrm{IC}$ reconstruction, we show that the
photon-number patterns of GBS encode the vibrational mode combinations responsible for the IC process, which we refer to as non-radiative pathways. This pathway-resolved data can then be grouped in different ways to extract multiple physically motivated observables. In particular, it enables $k_\mathrm{IC}$ analysis at several levels, from individual modes and mode family contributions to recurring vibrational configurations shared by multiple pathways. We find that Duschinsky rotations increase the fraction of $k_\mathrm{IC}$ associated with correlated vibrational pathways from 46% to 86%, and identify the mode combinations with the largest rate contributions. These pathway-resolved insights can guide targeted molecular modifications, including selective deuteration and bond substitution, to control non-radiative decay.
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All authors Mikhail Roiz, Rashid Valiev, Jan-Lucas Eickmann, Theo Kurten, Benjamin Brecht, Michael Stefszky, Christine Silberhorn
Plasma Physics
Quantum approaches for particle-in-cell codes
Ryan J. J. Connor, Andrew J. Daley, Callum W. Duncan et al. (+1 more)
Solving the high-dimensional, nonlinear partial differential equations that govern the rich physics of
plasmas remains a major computational challenge. In fluid dynamics,
quantum-inspired methods based on tensor-network techniques have recently emerged as a promising new paradigm, offering large degrees of data compression on conventional hardware and a natural pathway towards solving exponentially large problems on
quantum computers. Early studies suggest that tensor-network methods may also help overcome key bottlenecks in computational
plasma dynamics, particularly for industry-relevant scenarios where conventional simulations remain costly. In this work, we present recent progress in developing tensor-network methods compared to standard particle-in-
cell codes and discuss their capability to overcome the bottlenecks of conventional approaches. We further extend the tensor-network formulation to support the insertion of electromagnetic fields at arbitrary spatial locations. This capability is demonstrated through the injection of a
laser field to accelerate a
plasma, providing a key step towards tensor-network-based simulation of externally driven
plasma systems.
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All authors Ryan J. J. Connor, Andrew J. Daley, Callum W. Duncan, Preetma Soin
Optics · Cross-listed from quant-ph
Stimulated Parametric Down-Conversion: From Foundational Coherence to Structured Light Applications
M. F. Z. Arruda, M. G. Damaceno, G. H. dos Santos et al. (+4 more)
Stimulated parametric down-conversion (StimPDC) is the seeded version of the process that underlies much of photonic
quantum information. Replacing the
vacuum at one input port with a coherent seed leaves the interaction
Hamiltonian, the phase-matching function and the two-
photon amplitude unchanged, while raising the output to levels accessible with ordinary classical detectors. This review treats the transverse spatial physics of that process. We show that a single relation, in which the idler amplitude is the pointwise product of the pump field with the complex conjugate of the seed, organizes results usually presented separately: the image and coherence transfer experiments of the 1990s; phase conjugation and its use for wavefront correction; the conservation and conjugation of orbital angular momentum, together with the generation of radial modes and
geometric intensity patterns; and the processing of vector
vortex beams carrying spatially varying polarization. We then consider StimPDC as an instrument rather than as an object of study, covering stimulated emission
tomography, the experimental realization of Klyshko's advanced-wave picture, and the transfer of partial coherence, including the conservation of the twist phase of twisted Gaussian Schell-model beams. We close with the
quantum regime, reached when the seed approaches the single-
photon level or the idler is used as a herald, and with an assessment of open problems and prospective applications.
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All authors M. F. Z. Arruda, M. G. Damaceno, G. H. dos Santos, R. Medeiros de Araújo, N. Rubiano da Silva, S. P. Walborn, P. H. Souto Ribeiro
Biological Physics · Cross-listed from cond-mat.soft
Discontinuous buckling from cytoplasmic mechanics in vertex models of epithelia
Chandraniva Guha Ray and Pierre A. Haas
The
cell cortex and
cell adhesion contribute to the mechanics of epithelial
cells and hence tissues. Vertex models of epithelia represent the
cell cortex and
cell adhesion, but these models mostly ignore the other subcellular structures that compose the cytoplasm surrounded by the cortex. Here, we reveal the mechanical consequences of these structures in a minimal vertex model of an epithelial monolayer, in which the single-
cell energy includes a cytoplasmic contribution that represents, e.g., the cost of confinement of cytosolic
polymers. Strikingly, our simulations show that the buckling transition of the monolayer under compression becomes discontinuous in an intermediate range of values of the associated cytoplasmic modulus. By asymptotic solution of this buckling problem in the continuum limit of the model, we explain this reentrant behaviour in terms of the tricritical points of a sixth-order Landau theory. Our results thus underline how
cell-scale mechanics beyond the cortex and
cell adhesion can change emergent, tissue-scale behaviour even qualitatively.
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Plasma Physics
Dynamics-aware bandwidth selection for smoothed charge deposition in 2D electrostatic particle-in-cell
Ayushi Agrawal, Shan-Chang Lin, Ezhilmathi Krishnasamy et al. (+1 more)
Charge deposition in the particle-in-
cell (PIC) method can be viewed as kernel density estimation on a spatial mesh. This allows the smoothing bandwidth to be selected through statistical criteria such as mean integrated squared error or cross-validation, but it also changes the electric field acting on the particles. Therefore, a selected bandwidth can alter the growth or damping of physical modes. We develop a dynamics-aware bandwidth-selection procedure that combines a density-error objective with constraints on specified linear modes. These constraints follow from the
plasma equilibrium and the combined transfer of deposition, filtering and field gathering within the model rate-tolerance boundary. We demonstrate the need for
equilibrium information through a controlled two-stream experiment. The controlled two-stream scan varies the beam drift while holding the initial spatial density, thermal samples, wavevector and fixed-filter transfer unchanged. Across four resolved
equilibria approaching marginal stability, this filter reduces the measured growth rate by $0.7\%$ to $9.1\%$.
Equilibrium-dependent interior settings satisfy the prescribed $10\%$ rate tolerance. We then apply the constrained selection rule to 85 Gaussian candidates, that reduces density and grid-field mean-square errors by $7.40\%$ and $3.70\%$ on independently evaluated snapshots. A separate projected-linear calculation at that exact width gives a ratio of mean individual growth rates of $0.9556$, with paired $95\%$ interval $[0.9453,0.9640]$, consistent with the prediction $0.9513$. Analysis of finite-marker loading and ensemble averaging explains how the measured rates relate to the response model. Together, these results demonstrate a filter-design procedure that combines statistical error reduction with subsequent validation of the selected linear dynamics.
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All authors Ayushi Agrawal, Shan-Chang Lin, Ezhilmathi Krishnasamy, Pascal Bouvry
Instrumentation and Detectors
Residual AM and PM Noise of Selected X-Band Amplifiers
Archita Hati, Craig Nelson and Scott Littrell
In microwave systems design, amplitude modulation (AM) noise is often ignored relative to phase modulation (PM) noise. However, in high-performance applications requiring ultra-low PM noise, AM noise becomes a critical limiting factor due to AM-to-PM conversion mechanisms. Because AM noise specifications are rarely, if ever, provided for commercial microwave components, this study characterizes the residual AM and PM noise of several 10 GHz amplifiers. We present performance data for various Heterojunction Bipolar Transistor (HBT) amplifier designs and demonstrate the noise reduction achieved through power-summed configurations. For example, a discrete-die GaAs HBT amplifier achieves residual PM noise below $-160$ dBrad$^2$/Hz and AM noise of approximately $-155$ dB/Hz at a 1 kHz offset in a quad power-summed configuration. A notable finding is that the majority of amplifier designs surveyed in this study exhibit higher AM noise relative to their PM noise, with only a few exceptions. The impact of bias supply quality on residual noise is also quantified, demonstrating that the choice of voltage regulator is a first-order design parameter below 1 kHz offset.
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Optics · Cross-listed from quant-ph
Self-organized Layered Structures of Nitrogen-Vacancy Centers with Preferential Orientation in Heteroepitaxial Diamond Films
Vadim Lebedev, Alejandro Martínez-Méndez, Jesús Moreno-Meseguer et al. (+6 more)
Here, we report the fabrication and characterization of single
crystal diamond films on a two-inch wafer-scale containing three-dimensional layered structures of negatively charged nitrogen-vacancy color centers (NV$^{-}$). The (100)-oriented layered diamond films were grown by chemical vapor deposition (CVD) to create spatially separated regions of enhanced emission associated with NV$^{-}$ centers. Such localized emission enhancement as well as 2D and 3D arrays of
spins could enable close-packed architectures for emerging
quantum devices, such as data processors,
memory cells, and
magnetic sensors. A cyclic sequence of CVD growth and oxygen-
plasma etching is employed, resulting in the in-situ formation of layered inverted pyramidal structures with flat $\{$111$\}$ sidewalls. These pits are subsequently overgrown by nitrogen-doped diamond to achieve NV$^{-}$-rich facets with a uniform N-V bond arrangement and improved nitrogen incorporation efficiency.
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All authors Vadim Lebedev, Alejandro Martínez-Méndez, Jesús Moreno-Meseguer, Jan Engels, Jürgen Weippert, Jan Kustermann, Felix Hoffmann, Javier Prior, Jan Jeske
Atmospheric and Oceanic Physics
S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales
Chenyu Dong and Gianmarco Mengaldo
The subseasonal-to-seasonal (S2S) timescale, roughly from two weeks to two months ahead, is a critical forecast window for sectors such as agriculture, energy, and water management. Yet, it is widely known as the `predictability desert'. Recent AI weather models excel up to two weeks ahead but deteriorate beyond, largely because they are trained to predict fine-scale details that are neither predictable nor essential at S2S timescales. We argue that a more physically grounded objective is to forecast only the slowly varying components that remain predictable. Computer
vision reached the same conclusion with the Joint-
Embedding Predictive Architecture (JEPA), which predicts in latent space, discarding unpredictable details. In this work, we introduce S2S-JEPA, which brings the JEPA paradigm to S2S forecasting. It is tailored to this task through design elements from state-of-the-art AI weather models. S2S-JEPA achieves comparable skill to the gold-standard ECMWF physics-based ensemble and surpasses it on multiple metrics at weeks 5 to 6.
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Classical Physics · Cross-listed from quant-ph
Orbital-Rotation Shadow Tomography Reduces the Classical Cost of Quantum-Classical Auxiliary-Field Quantum Monte Carlo
Luning Zhao, Joshua Goings, Evgeny Epifanovsky et al. (+1 more)
Quantum-classical auxiliary-field
quantum Monte Carlo (QC-AFQMC) is a promising route to using
quantum computers for strongly correlated electronic structure problems, but its scalability is limited by a classical post-processing bottleneck: the measured
quantum trial state must be used to evaluate overlaps, force biases, and local energies for many walkers throughout the AFQMC propagation. Existing matchgate-shadow approaches avoid the exponential cost of generic classical shadows, but their post-processing remains expensive for large systems. In this work, we show that particle-number-preserving fermionic shadows, implemented as orbital-rotation shadows, are able to drastically reduce QC-AFQMC post-processing costs. We derive efficient
estimators for overlaps and their derivatives, giving $O(N^3)$ scaling for overlaps and force biases and $O(N^4)$ scaling for local energies per shadow and walker and with $O(N)$ Cholesky vector. For fixed normalized target determinants, we also prove that the overlap
estimator is unbiased with variance upper bounded by $O(\eta)$, where $\eta$ is the particle number, yielding a sufficient budget of $O(\eta/\epsilon^2)$ ideal independent measurements for additive overlap error $\epsilon$. We combine these
estimators with a novel virtual-correlation-energy treatment and a GPU implementation and demonstrate QC-AFQMC using orbital-rotation shadows. Performance projections for $\pi$-conjugated molecules up to pentacene with a (22e, 22o) active space and 356 total orbitals show that the full classical post-processing workflow can be completed in slightly more than two days on 8$\times$A100 graphics processing units (GPUs). These results significantly reduce classical post-processing costs for QC-AFQMC and motivate further improvements in preparation and measurement of the trial state on
quantum hardware.
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All authors Luning Zhao, Joshua Goings, Evgeny Epifanovsky, Martin Roetteler
Physics and Society · Cross-listed from cs.AI
Peer Influence across Heterogeneous AI Models
Frida Nøhr Laustsen, Marie Haahr Petersen, Victoria Popa et al. (+4 more)
When two AI
agents disagree, who persuades whom? As multi-
agent systems increasingly combine
language models of different families and sizes, the answer can determine which judgments survive interaction. Measuring persuasion as the probabilistic shift in an
agent's decision after a single exchange with a dissenting peer, we test seven open-weight models across three
language understanding tasks. We find that persuasion is strong: when models disagree, receivers often abandon their initial judgment after seeing a peer's answer and explanation. Surprisingly, however, neither standalone certainty nor model scale reliably predicts persuasion dynamics. Models producing almost perfectly consistent decisions in isolation can be among the most susceptible to persuasion, and small models can match larger ones as persuaders and resist their influence just as effectively. Furthermore, we show that the size of the shift depends more on the susceptibility of the listener than on the persuasiveness of the speaker. Persuasion patterns are therefore specific to each model pairing, with heterogeneity amplifying persuasion in some combinations and suppressing it in others, allowing a dissenting
agent running a small model to overturn the judgments of a much larger one. These findings show that the behavior of interacting models cannot be inferred from their individual properties but must be evaluated in the combinations in which they will operate.
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All authors Frida Nøhr Laustsen, Marie Haahr Petersen, Victoria Popa, Ariel Flint, Romualdo Pastor-Satorras, Andrea Baronchelli, Luca Maria Aiello
Fluid Dynamics
Development of a class of dynamic RANS closures for coarse-grained approaches to turbulence
Yves Tessier Urrecha, Giorgio Manzi, Filippo Cancellotti et al. (+1 more)
This work represents a crucial advancement in the development of a new class of
turbulence closures conceived by Cimarelli et al. [1]. This new class of closures is based on the theoretical framework provided by the temporally filtered Navier-Stokes equations. This framework represents a unifying formalism for coarse-grained approaches to
turbulence ranging from the statistical to the scale-resolving ones and provides exact equations relating turbulent stresses at different levels of coarsening. The latter have been used in Cimarelli et al. [1] as the theoretical foundation to derive a new class of closures based on the dynamic computation of the model coefficient appearing in the definition of eddy viscosity. Here, we extend this class of dynamic RANS models by deriving a new formulation based on the k-{\omega} model including an alternative version where the non-physical decay of free-stream
turbulence reproduced by the transport equations of k and {\omega} is solved in an elegant way. A scale-resolving simulation campaign is performed and the analysis of the results reveals interesting features. Among others, the new dynamic k-{\omega} model demonstrates strong robustness to a coarsening of the temporal resolution and successfully captures complex flow phenomena, including laminar-to-turbulent transition and the sensitivity of boundary-layer separation and reattachment to free-stream
turbulence levels prescribed at the boundaries.
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All authors Yves Tessier Urrecha, Giorgio Manzi, Filippo Cancellotti, Andrea Cimarelli