Optics
Nonlinear Nanophotonic Chip-space Interfaces: On-chip Generation of Structured, Topological and Spatiotemporal Lights Via Nonlinear Čerenkov Radiation
Dunzhao Wei, Bo Chen, Shuai Wan et al. (+15 more)
Miniaturized and reconfigurable interfaces between confined optical modes within integrated photonic chips and structured light propagating in free space would serve as a cornerstone for fundamental optical science and modern photonic technology. In this work, we exploit the anisotropic nonlinear susceptibility tensors associated with thin-film lithium niobate to construct nanophotonic chip-space interfaces capable of flexibly generating and multi-dimensionally engineering structured light via injections of
photons to on-chip waveguides. By harnessing the nonlinear Čerenkov radiation in integrated nonlinear microring resonators, we successfully tailor the spatial profile, polarization state, emission wavelength, topological charge and temporal wave packet of structured optical
vortices, exhibiting reconfigurabilities and tuning ranges far beyond the state-of-the-art. To further showcase the capabilities of our platform, we use a single pump to generate tunable optical skyrmions via the
spin-orbit coupling and multi-state integrated
vortex microcombs in the visible range via synergistic $\chi^{(2)}$ and $\chi^{(3)}$ nonlinear optical processes. Our work bridges the research fields of structured light and integrated nonlinear optics, providing unprecedented opportunities for spatiotemporal light generation and on-chip multidimensional nonlinear optics.
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All authors Dunzhao Wei, Bo Chen, Shuai Wan, Yixuan Wang, Jiantao Ma, Pi-Yu Wang, Chun Chang, Guixin Qiu, Zelin Tan, Xiaoshan Huang, Yan Chen, Tian Jiang, Qiwen Zhan, Fang Bo, Songnian Fu, Xuehua Wang, Chun-hua Dong, Jin Liu
Instrumentation and Detectors
Proto-0: a prototype for validating key technologies of the DarkSide-20k experiment and beyond
Riccardo de Asmundis, Roberta Calabrese, Mauro Caravati et al. (+8 more)
The DarkSide-20k experiment, currently under construction at LNGS, will employ a next-generation dual-phase
liquid-argon Time Projection Chamber (TPC) with SiPM-based
Photon Detector Units and low-background materials to achieve the ambitious goal of operating with an instrumental background close to zero. Proto-0 is a small-scale dual-phase argon TPC operated at INFN Naples, designed to validate the integration of DarkSide-20k key technologies in a realistic detector environment and to study charge extraction and electroluminescence signal formation. In this short paper we report on the early operation of Proto-0 and its single-phase commissioning. We focus on the measurement of the scintillation light yield using external and internal calibration sources.
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All authors Riccardo de Asmundis, Roberta Calabrese, Mauro Caravati, Giuliana Fiorillo, Leandro Flores, Gianfrancesco Grauso, Giuseppe Matteucci, Noemi Pino, Dmitrii Rudik, Maria Adriana Sabia, Yury Suvorov
Computational Physics
Frustrated supermolecules: the high-pressure phases of crystalline methane
Marcin Kirsz, Miguel Martinez-Canales, Ayobami D. Daramola et al. (+3 more)
Methane is the simplest hydrocarbon, yet it exhibits an extraordinarily complicated series of
crystal phases. Notably, the non-plastic phases have large unit
cells with nearly, but not quite cubic
symmetry. Furthermore, although non-polar molecules interact very weakly, their reorganisation across phase transitions is very sluggish. Here, we demonstrate that these complex structures can be understood as simple packing of near-spherical supermolecular clusters of methane molecules: the departure from cubic
symmetry arising from the non-spherical nature of the molecules. We use molecular dynamics based on density functional theory calculations to simulate the finite-temperature
crystal structures of methane, finding that the complex Phase A is based around a 13-molecule regular icosahedron, with 8 additional molecules forming the 21-molecule unit
cell. Similarly, Phase B is based on a body-centred cubic bcc packing of 17-molecule Z16 polyhedra, with the remaining 12 molecules per
cell in tetrahedral interstices. We demonstrate that the favored intermolecular separation depends sensitively on molecular orientation, leading to hindered rotation and suppressed
entropy. The structures are determined by a trade-off between efficient packing and
entropy.
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All authors Marcin Kirsz, Miguel Martinez-Canales, Ayobami D. Daramola, John S. Loveday, Ciprian G. Pruteanu, Graeme J Ackland
Physics Education
How undergraduate physics students use generative AI for computational modeling
Karl Henrik Fredly, Tor Ole B. Odden and Benjamin M. Zwickl
Generative artificial intelligence (genAI) is becoming increasingly prevalent and capable in physics, particularly for programming-related tasks. How, then, does genAI affect students' computational modeling? We interviewed 19 undergraduate students who had recently completed an open-ended computational assignment that encouraged the use of genAI, asking them how they used it. We then conducted a thematic analysis of these interviews using a framework for computational modeling in physics. We found that genAI significantly impacts several aspects of students' computational modeling, such as the planning, implementing, and debugging of computational models. GenAI can also help students find resources and introduce them to new computational tools. Productive use of genAI was associated with students limiting its use to small steps in the modeling process and consistently double-checking the formulas, explanations, and code it provided. We also identified challenges students faced due to an over-reliance on genAI, such as working from false model assumptions and not spending time learning the fundamentals of computational modeling, especially debugging. Finally, we discuss implications for teaching, such as the need to teach students how to use genAI productively and to urge them to plan before they code. We also highlight the continued value of low-stakes assessment and teaching assistants for teaching computational modeling, as the task remains difficult even with the introduction of genAI.
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Medical Physics · Cross-listed from eess.IV
AI End-to-End Radiation Treatment Planning Under One Second
Simon Arberet, Riqiang Gao, Martin Kraus et al. (+9 more)
Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning time and inter-planner variability, improving efficiency and consistency in clinical workflows. Most existing automated approaches rely on multiple dose evaluations and corrections, resulting in plan generation times of several minutes. We introduce AIRT (Artificial Intelligence-based Radiotherapy), an end-to-end deep-learning framework that directly infers deliverable treatment plans from CT images and structure contours. AIRT generates single-arc VMAT prostate plans, from imaging and anatomical inputs to leaf sequencing, in under one second on a single Nvidia A100 GPU. The framework includes a differentiable dose feedback, an
adversarial fluence map shaping, and a plan generation augmentation to improve plan quality and robustness. The model was trained on more than 10,000 intact prostate cases. Non-inferiority to RapidPlan Eclipse was demonstrated across target coverage and OAR sparing metrics. Target homogeneity (HI = 0.10 $\pm$ 0.01) and OAR sparing were similar to reference plans when evaluated using AcurosXB. These results represent a significant step toward ultra-fast standardized RT planning and a streamlined clinical workflow.
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All authors Simon Arberet, Riqiang Gao, Martin Kraus, Florin C. Ghesu, Wilko Verbakel, Mamadou Diallo, Anthony Magliari, Venkatesan Karuppusamy, Sushil Beriwal, REQUITE Consortium, Ali Kamen, Dorin Comaniciu
Instrumentation and Detectors
A High Efficiency Superconducting On-chip Filterbank with Directional Filters for Integral Field Units in the Sub-millimeter Regime
Louis H. Marting, Kenichi Karatsu, Leon G.G. Olde Scholtenhuis et al. (+7 more)
Integrated superconducting spectrometers are developing to the point that they are enabling integral field units, providing large area spectral mapping capabilities for astronomy in the sub-millimeter band. However, these integral field units are only worthwhile if they have a high efficiency, but to date the efficiency of on-chip filterbanks has been quite poor. Here we demonstrate a filterbank with high efficiency by using directional filters. Using a cryogenic thermal load and a noise measurement in combination with a continuous-wave terahertz source to obtain the spectral response of the filters, we are able to accurately measure the filterbank efficiency, accounting for all quasi-optical elements within our setup. We experimentally obtain an average peak coupling efficiency to the detectors of 75% in a filterbank that sparsely samples between 125 GHz to 220 GHz using filters with a mean loaded quality factor of 19.6. Our results demonstrate that a filterbank with a high efficiency is achievable using directional filters, giving a clear route towards efficient integral field units.
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All authors Louis H. Marting, Kenichi Karatsu, Leon G.G. Olde Scholtenhuis, Shahab O. Dabironezare, Alejandro Pascual Laguna, Arend Moerman, David J. Thoen, A. J. van der Linden, Akira Endo, Jochem J.A. Baselmans
Medical Physics
Sparse probabilistic evaluation for treatment planning: a feasibility study in IMPT head & neck patients
Jenneke I. de Jong, Steven J.M. Habraken, Albin Fredriksson et al. (+4 more)
Probabilistic evaluation improves the trade-off between target coverage and OAR sparing in IMPT but remains computationally demanding. This study proposes sparse probabilistic evaluation (SPE), a computationally efficient approach integrated into a clinical TPS. Clinical plans of 20 IMPT HNC patients treated in 2024 were included. SPE used a predefined setup and range error grid with Monte Carlo computed dose distributions. Two grid settings were evaluated: the maximum error Emax (3$\sigma$ or 4$\sigma$) and the number of setup error points nsetup (7, 33, 123). Accuracy and duration of SPE with each grid were evaluated in the calibration group (5 patients). 1000 treatments with normally distributed random ($\sigma$ = 1 mm) and systematic ($\sigma$ = 0.92 mm) setup and range ($\sigma$ = 1.5%) errors were simulated. The dose distribution of the nearest error point in the grid was assigned to each fraction. Probability distributions derived from SPE were compared with those from a reference based on 35,000 Monte Carlo calculations. The found optimal grid (Emax = 3$\sigma$, nsetup = 33) was applied to the validation group (15 patients). Accuracy of SPE in the calibration group increased significantly as the number of error points increased from 7 (tavg = 2 minutes) to 33 (tavg = 9 minutes), with no further improvement between 33 and 123 (tavg = 27 minutes) error points. Increasing Emax only improved accuracy for values above the 98th percentile. Applying SPE to the validation group resulted in median errors of 0.02 Gy RBE (range:-0.11 to 0.07) for the 10th percentile of the D99.8%, CTV distribution and 0.0 Gy RBE (range:-0.14 to 0.23) for the 95th percentile of the D0.03cc,SpinalCord Core distribution. Sparse probabilistic evaluation achieves sufficient accuracy while requiring clinically acceptable computation times, paving the way for probabilistic evaluation in clinical practice.
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All authors Jenneke I. de Jong, Steven J.M. Habraken, Albin Fredriksson, Johan Sundström, Erik Engwall, Sebastiaan Breedveld, Mischa S. Hoogeman
Chemical Physics
Spin-Orbit Induced Non-Adiabatic Dynamics: An Exact $\Omega$-Representation
Ryan P. Brady and Sergei N. Yurchenko
Transforming rovibronic
Hamiltonians of molecular systems from the $\Lambda S$ (Hund's case a) basis to the adiabatic $\Omega$ representation is widely used to "remove"
spin-orbit coupling (SOC) and enable single-state treatments of spectra and dynamics. We show that this simplification is only apparent: the SOC elimination necessarily generates sizeable non-adiabatic couplings (NACs) from the
nuclear kinetic energy operator. Neglecting these
spin-orbit-induced NACs causes severe errors in rovibronic energies and transition properties. Using an analytically tractable two electronic state model and high-accuracy variational
benchmarks, we derive the exact conditions for numerical equivalence between $\Omega$ and $\Lambda S$ formulations and quantify how missing NAC terms and bond-length-dependent
spin factors degrade predictions. We implement a complete $\Omega$-representation workflow in Duo for diatomics, fully transforming all
Hamiltonian terms and enabling side-by-side $\Omega$ vs $\Lambda S$ calculations. For common single-state pipelines (e.g., LEVEL), we provide diagnostics that flag unsafe regimes and practical remedies to restore accuracy. The results deliver actionable guidance for spectroscopy, photophysics, and kinetics: $\Omega$-based single-state approximations are reliable only when interacting states are well separated in the Franck-Condon region; otherwise, explicit non-adiabatic terms are required - even for "forbidden" transitions.
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Geophysics · Cross-listed from astro-ph.EP
Motional induction in Ganymede's ocean
Simon Cabanes, Thomas Gastine and Alexandre Fournier
We investigate the
magnetic signature of oceanic circulation in Ganymede's subsurface ocean using kinematic induction modeling. Our approach couples zonal jet flows from rotating thermal convection simulations with
magnetic field models incorporating Ganymede's internal dynamo and external contributions from Jupiter. We solve the induction equation in spherical geometry for deep-ocean (493 km) and shallow-ocean (287 km) scenarios with varying
magnetic Reynolds numbers. Ocean flows generate a predominantly toroidal
magnetic field through the omega-effect, with a weaker poloidal component pervading beyond the conductive ocean layer. For some, but not all, induction configurations, analysis of the time-averaged Lowes-Mauersberger spectra reveals that ocean-induced signals dominate at spherical harmonic degrees $\ell \geq 4$. Deep ocean scenarios with
magnetic Reynolds numbers above unity produce surface
magnetic signals up to 9 nT. Our results demonstrate that Ganymede's intrinsic
magnetic field creates favorable conditions for detecting subsurface ocean dynamics, thus emphasizing the need for low-altitude orbits for the Juice probe.
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Chemical Physics
Parity violation effects in helical osmocene: theoretical analysis and experimental prospects
Eduardus, Agathe Bonifacio, Mathieu Manceau et al. (+11 more)
We present a computational investigation of the parity-violating (PV) contributions to the vibrational transitions and
nuclear magnetic resonance shieldings of helical osmocene. A number of promising transitions within the spectral window of currently available sub-Hz metrology-grade
lasers are identified, exhibiting high intensities and parity violation shifts of up to 7 Hz. We discuss the prospects for the synthesis of this compound and for subsequent ultra-precise mid-IR spectroscopy towards the first detection of parity violation in a
chiral molecule.
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All authors Eduardus, Agathe Bonifacio, Mathieu Manceau, Naoya Kuroda, Masato Senami, Juan J. Aucar, I. Agustín Aucar, Marit R. Fiechter, Trond Saue, Jeanne Crassous, Benoît Darquié, Shirin Faraji, Lukáš F. Pašteka, Anastasia Borschevsky
Plasma Physics
Plugging of multi-mirror machines by a traveling rotating magnetic field
Tal Miller, Eli Gudinetsky, Ilan Be'ery et al. (+1 more)
Axial plugging is a critical challenge for fusion in open-ended
magnetic confinement systems. Unlike simple
magnetic mirrors, which suffer from direct axial flow, multi-mirror systems utilize a series of aligned
magnetic cells to suppress
plasma loss; however, the resulting confinement still requires additional plugging to reach Lawson criterion levels. In [T. Miller et al., Phys.
Plasmas 30, 072510 (2023)], it was found that applying a traveling and rotating electric field in multi-mirror machines can significantly suppress axial loss due to a selectivity effect induced by the Doppler shift of the ion cyclotron resonance. However, this method is energetically expensive and vulnerable to
plasma screening effects. Here, we show that using a traveling, rotating
magnetic field can achieve comparable plugging effectiveness while offering better penetration and lower energy costs. Two limiting scenarios, with and without an induced electric field, were considered. The confinement enhancement is calculated using a semi-kinetic rate equation model, in which the rate coefficients are determined from single-particle simulations. While both scenarios exhibit significant confinement enhancement, the scenario without an induced electric field is much more energetically efficient, as it relies on phase-space mixing rather than on energy deposition in the escaping particles. The decoupling of confinement from
plasma collisionality enables fusion conditions in the central
cell while allowing affordable and efficient confinement enhancement in the multi-mirror sections.
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All authors Tal Miller, Eli Gudinetsky, Ilan Be'ery, Ido Barth
Optics
From Displacement to Angle: Diamond-Based 3D Rotation Sensing for High-Precision Cellular Force Measurement
Linjie Ma, Bicong Wang, Tai Nam Yip et al. (+3 more)
Cellular traction forces are conventionally measured by tracking the displacement of beads or micropillars, an approach fundamentally limited by optical diffraction and the classical Euler-Bernoulli beam assumption, which is accurate only when the traction-induced deformation is relatively small while the aspect ratio of micropillars is large. Here we introduce an alternative approach: quantifying force through direct measurement of rotational angle, in addition of displacement of the micropillar, using fluorescent nanodiamonds as embedded 3D orientation markers. Specifically, by integrating optically detected
magnetic resonance (ODMR) with
laser polarization modulation (LPM), we determine the complete three-dimensional orientation of nanodiamonds attached to PDMS micropillars with sub-degree precision ($\sim$0.5$^\circ$). This angle-based measurement framework bypasses the resolution constraints of displacement tracking and remains valid for stocky beams or when large deformations occur. Finite-element simulations demonstrate that our method reduces force estimation errors by at least 10% compared to conventional displacement-based approaches. Moreover, we successfully capture multidimensional pillar deformations – including bending and twisting – that are inaccessible to conventional displacement-only method. Taken together, our work establishes diamond-based angular force microscopy as a high-precision platform for mechanobiology.
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All authors Linjie Ma, Bicong Wang, Tai Nam Yip, Yong Hou, Yuan Lin, Zhiqin Chu
Fluid Dynamics
Confined drying of a binary liquid mixture droplet: A quantitative interferometric study under humidity control
Ole Milark, Jean-Baptiste Salmon and Benjamin Sobac
We present a methodology that combines Mach-Zehnder interferometry, a custom relative humidity (RH) controlled chamber, and a confined two-dimensional droplet geometry to enable precise investigations of drying of complex fluids and the associated transport mechanisms. This approach is applied to a model binary mixture, water-glycerol, the concentration-dependent thermodynamic and transport properties of which are relatively well documented. High-resolution interferometric imaging (6 $\mu$m pixel$^{-1}$, 1 frame s$^{-1}$) allows simultaneous measurement of drying kinetics and internal concentration fields with $\pm 0.5\%$ accuracy, characterized here over a wide range of RH (25-95%), and thus Péclet numbers. The experimental results closely match a quasisteady, isothermal model of vapor-
diffusion-controlled evaporation coupled to
diffusion within the droplet. These data enable extraction of both the concentration-dependent mutual
diffusion coefficient $D(\varphi)$ and the water chemical activity $a_w(\varphi)$ over almost the entire range of glycerol volume fraction $\varphi$, even from a single low-RH experiment. While $a_w(\varphi)$ agrees well with literature values, our measurements yield a consistent fit for $D(\varphi)$. Complementary experiments with fluorescence microscopy confirm that buoyancy-driven convection, although present, remains negligible, so that mass
diffusion dominates solute transport in this confined geometry. The overall agreement validates the methodology, demonstrating its robustness as a quantitative framework for probing drying dynamics and transport in complex fluids, with broad applicability to controlled evaporation studies.
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Chemical Physics
Quantum-corrected NMR crystallography at scale
Matthias Kellner, Ruben Rodriguez-Madrid, Jacob B. Holmes et al. (+4 more)
Structure determination by chemical-shift-driven NMR crystallography relies on comparing chemical shieldings measured in solid-state NMR experiments with simulations. However, computational cost limits the accuracy of shielding predictions, that usually rely on low-level electronic-structure approximations and neglect thermal and
quantum mechanical
nuclear motion, leading to large errors, especially for highly informative hydrogen-bonded
protons. To address these limitations, we introduce a
quantum-
nuclei-corrected (QNC-NMR) approach. We generate inexpensively
quantum ensembles using PET-MOLS, a novel machine-learning learning model of the interatomic potential transferable across molecular
crystals. Using them as inputs to a chemical-shift model results in a 33 % improvement of the agreement with experiments for hydrogen-bonded
protons, without the need for empirical corrections. The ability to sample structures consistent with the experimental conditions enables further refinement of the shielding model by finetuning it against measured shieldings. The favorable scaling with system size allows similar improvements for amorphous materials that are otherwise inaccessible to explicit DFT simulations.
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All authors Matthias Kellner, Ruben Rodriguez-Madrid, Jacob B. Holmes, Victor Paul Principe, Seio Inoue, Lyndon Emsley, Michele Ceriotti
Physics and Society
Risk mapping novel respiratory pathogens with large-scale dynamic contact networks
Matthijs Romeijnders, Michiel van Boven and Debabrata Panja
Background: Human-to-human transmission of pathogens fundamentally depends on interactions among infectious and susceptible individuals, yet traditional population-scale models often overlook the
stochastic, behaviour-driven, and highly heterogeneous nature of these interactions. Methods: Here, we develop a large-scale actor-based model capturing early epidemic dynamics of a novel respiratory pathogen on dynamic contact networks. We build these networks upon explicitly integrating detailed demographic and residential registry data from the Netherlands. The model simulates the Dutch population characterised by age, residency and mobility patterns, with actors interacting stochastically across households, workplaces and schools. Results: We show how the geographic and demographic profiles of initial cases impact transmission trajectories, with densely populated municipalities in the country's western core acting as key hubs driving epidemic spread. The framework enables rigorous assessment of intervention strategies incorporating behavioural adaptations. As case studies, we quantify the effects of symptomatic self-isolation and travel restrictions to and from major urban centres, highlighting their potential to modulate epidemic outcomes. Conclusions: Our findings underscore the necessity of integrating fine-scale human-to-human contact realism and population scale in epidemic
forecasting and control.
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Plasma Physics
Gyrofluid Magnetic Reconnection Beyond the {\delta} F Approximation
F. F. Locker, M. Rinner, M. Held et al. (+1 more)
Magnetic reconnection in a two-dimensional system is studied employing a novel Full-F gyrofluid model with arbitrary- wavelength polarization. In strongly magnetized
plasmas, the long wavelength dimension parallel to the
magnetic field can be separated from the much smaller perpendicular scales, motivating an isolated two-dimensional description. While previous studies have predominantly employed delta- F gyrofluid models, the present Full-F formulation is applied to simulate Harris-sheet
magnetic reconnection with domain aspect ratios L_y/L_x <= 16, investigating tearing-mode growth, plasmoid formation, and the influence of finite ion Larmor radius (FLR) effects. In addition to a linear tearing-mode analysis, a non-modal stability analysis of the linearized system is performed. The
evolution operator is shown to be strongly non-normal, exhibiting large condition numbers and extended pseudospectra that indicate the possibility of significant transient amplification, even in marginally stable regimes. Such transient amplification may facilitate the transition from linear tearing growth to rapid nonlinear acceleration. We focus on low-
plasma-beta
magnetic reconnection on the scale of the drift scale and incorporate ion FLR effects, placing the simulations in the context of magneti- cally confined fusion
plasmas such as tokamaks. After discussing numerical resolution and convergence, we present a parameter scan varying the normalized electron skin depth and the ion-to-electron temperature ratio. Finally, the influence of aspect ratio, polarization model, and FLR effects on the reconnection dynamics and plasmoid formation is investigated.
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All authors F. F. Locker, M. Rinner, M. Held, A. Kendl
Chemical Physics
On the interpretation of molecular photoexcitation with long and ultrashort laser pulses
Jiří Janoš, Federica Agostini, Petr Slavíček et al. (+1 more)
Photoexcitation is an inherent part of any photochemical or spectroscopic experiment, yet its impact on the excited-state dynamics is often overlooked. However, it is the excited molecular state, built upon photoexcitation and shaped by the characteristics of the light source, that determines the fate of the excited molecule and its subsequent photochemical reactions. In this work, we investigate how excited molecular states are built by different
laser pulses, leveraging two representations of the molecular wave function: the Born-Huang expansion and the exact factorization. We explore the generation of two limiting cases: a stationary molecular state generated with a long
laser pulse and an electronic wave packet created by an ultrashort (attosecond)
laser pulse. The standard concepts of population transfer between electronic states, the resonance condition, or sudden vertical excitation, inherent to the Born-Huang representation and used by chemists to approximate the impact of photoexcitation on molecular systems, are brought to a new light by the exact factorization.
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All authors Jiří Janoš, Federica Agostini, Petr Slavíček, Basile F. E. Curchod
Optics
Generalized Optics-Free Cross-Correlation Ghost Imaging via Holographic Projection with Grayscale and Binary Amplitude-only Computer-Generated Holograms
Yuhan Guo, Xiangyu Yin, Chunguang Meng et al. (+2 more)
In certain applications or wavelength regimes, essential optical components for imaging systems are either unavailable or challenging to fabricate. To address this, we propose an optics-free classical ghost imaging (GI) scheme utilizing visible light. By employing grayscale and 0-1 binary amplitude-only computer-generated holograms (CGHs), generated via a modified Gerchberg-Saxton
algorithm combined with Otsu's thresholding method, we achieve accurate replication of light intensity distributions with central
symmetry in the
holographic projection plane. Experimentally, we first optimized system parameters by analyzing the point spread function (PSF) and subsequently demonstrated cross-correlation GI through the precise replication of dynamic speckle patterns. Furthermore, by incorporating sparse target patterns, we significantly enhanced the imaging quality. Given the high-speed modulation capabilities of digital micromirror devices (DMDs) for 0-1 binary amplitude-only CGHs, the proposed scheme represents a significant advancement toward practical implementation, particularly in the X-ray regime where conventional optics are difficult to employ.
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All authors Yuhan Guo, Xiangyu Yin, Chunguang Meng, Liming Li, Huiqiang Liu
Instrumentation and Detectors
Experimental characterisation of a combined LVDT position sensor and voice-coil actuator for gravitational wave detectors
K. A. Kukkadapu, P. Li, H. Van Haevermaet et al. (+3 more)
A detailed characterisation of a combined Linear Variable Differential
Transformer (LVDT) position sensor and voice-coil (VC) actuator designed for seismic isolation systems in gravitational wave detectors is presented. A dedicated experimental setup and a finite-element simulation framework were developed to measure and model a representative Einstein
Telescope pathfinder Type-A LVDT+VC assembly. The setup employs a precision translation stage and balance to quantify LVDT displacement response and VC force output under controlled conditions. We found a good agreement between experiment and simulation: the measured LVDT response was determined with an uncertainty of 0.5% and differed by only 1.3% from the model prediction, demonstrating high linearity over a $\pm$5~mm range. In addition, the VC force measurements agreed within the total uncertainty: the maximum normalised force was determined with a precision of 2.3% and matched the simulated value with only 0.6% discrepancy. These results validate the combined sensor-actuator design and our measurement methodology. The demonstrated linear response and stable actuation confirm that this LVDT+VC device can be used for low-frequency suspension control. Our framework therefore provides a validated tool to optimise existing sensor and actuator designs, and to study novel prototypes for next-generation gravitational wave detectors.
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All authors K. A. Kukkadapu, P. Li, H. Van Haevermaet, A. N. Koushik, W. Beaumont, N. van Remortel
Atomic Physics · Cross-listed from quant-ph
Vertical ion transport in a surface Paul trap: escalator and elevator approaches
Alexey Russkikh and Nikita Zhadnov
Surface ion traps confining and manipulating tens of ion
qubits have become the leading platform for
quantum processors with high
quantum volume. These devices employ the
Quantum Charge-Coupled Device (QCCD) architecture, wherein multiple trapping zones are linked by an on-chip transport network that shuttles ion chains, enabling full connectivity through physical ion transport in a plane parallel to the chip surface. The ability to move ions perpendicular to this plane can offer additional advantages, including tuning the
laser-ion interaction strength, systematic studies of surface-induced heating mechanisms, and precise
alignment with a mode of an external optical cavity. We introduce an "escalator" - a geometrically optimized transition between trapping zones of different confinement heights - and present a comparative analysis of two "elevator" configurations that reposition the RF null dynamically via additional electrode voltages. Both approaches enable nearly a twofold change in the ion confinement height above the chip surface.
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Physics and Society
Estimating the Containment Effectiveness and Economic Cost of Inner-city Non-Pharmaceutical Interventions
Xihan Zhang, Yuqing Liu, Chen Zhao et al. (+1 more)
Non-pharmaceutical interventions (NPIs) are crucial for controlling pandemics, but existing research often overlooks the heterogeneity of individual behavior, which can lead to inaccurate evaluations of the effectiveness of strategies. In this paper, we use a large
dataset of fine-grained real-world individual trajectory data from a major Chinese city to examine the trade-off between the epidemic containment effectiveness and economic cost of different NPIs. Our findings reveal significant variations in the outcomes of different NPIs across activation mechanisms and initial scales of undetected transmission. Based on these results, we construct a two-dimensional evaluation framework that comprehensively evaluates the impact of both the containment effectiveness and economic cost, which suggests that implementing stringent strategies-such as lockdown or contact tracing-at low activation thresholds can achieve optimal epidemic control with minimal economic cost. Our study provides a data-driven decision-making framework for understanding the implementation effectiveness and applicability of emergency management policies within urban systems.
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All authors Xihan Zhang, Yuqing Liu, Chen Zhao, Guijun Li
Optics
Modeling Coherent Nonlinear Microscopy of Axially Layered Anisotropic Materials Using FDTD
Mohammad Reza Farhadinia and Nicolas Olivier
Providing quantitative interpretation of coherent nonlinear microscopy images, such as third-harmonic generation (THG), is generally hampered by the complex phase-matching conditions, especially in the presence of sample linear heterogeneity. We recently presented a numerical pipeline using the finite-difference time-domain (FDTD) method to take this heterogeneity into account. However, due to software restrictions, we only considered nonlinear materials with diagonal nonlinear susceptibilities. We now expand the recently developed FDTD approach to model nonlinear microscopy for anisotropic materials that obey Kleinman
Symmetry, organized in layers along the optical axis, and validate our simulations on well-described geometries.
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Optics
Long-range mid-infrared energy transfer mediated by hyperbolic phonon polaritons
Gonzalo Álvarez-Pérez, Simone De Liberato and Huatian Hu
We provide a framework to theoretically describe long-range energy transfer in single and twisted two-dimensional
hyperbolic slabs. We demonstrate that
phonon polaritons (PhPs,
quantum superpositions of
photons and
lattice vibrations in polar dielectrics) can mediate and enhance room-temperature energy transfer at ranges far exceeding those of conventional mid-infrared (MIR) platforms, and with extreme directionality. This is because the dipole-dipole interaction potential energy diverges along the asymptotes of the real-space
hyperbolic opening angle. Our findings allow us to extend classical and
quantum interactions between dipoles, typically strictly confined to the near-field, beyond several free-space MIR wavelengths. We use $\alpha$-MoO$_3$ as a representative material, but this mechanism is not limited to the MIR: it is general to anisotropic media across the whole electromagnetic spectrum.
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Applied Physics · Cross-listed from cond-mat.other
Trap-Enhanced Steep-Slope Negative-Capacitance FETs Using Amorphous Oxide Semiconductors
Yungyeong Park, Hakseon Lee and Yeonghun Lee
Amorphous
oxide semiconductors (AOSs) have recently gained
attention as a promising channel material of back-end-of-line (BEOL)-compatible transistors for monolithic three-dimensional (3D) integrations. However, the degradation in device performance resulting from the high trap densities in AOS, compared to conventional crystalline channel materials, has remained an intractable issue. We introduce the negative-capacitance (NC) operation into the AOS-based transistors. Negative-capacitance field-effect transistors (NCFETs) have been proposed for low-power devices, enabling sub-60 mV/decade subthreshold swing SS induced by a ferroelectric layer. In this work, we develop an AOS NCFET model to investigate the influence of traps within the channel on the steep-slope operation. It is revealed that as the trap density of the channel increases, SS of the MOSFET increases, while the SS of the NCFET decreases. The physical interpretation for steep SS is attributed to the fact that the trapped charges enhance the negative potential drop of the NC layer, enabling the abrupt device switching. This finding will accelerate the development of BEOL transistors and other applications based on the AOS materials in conjunction with the NC effect.
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Optics
Enhancement of Circular Dichroism in Chiral Dielectric Metasurfaces by Ion Beam Irradiation
Anna Fitriana, Katsuya Tanaka, Lukas Raam Jaeger et al. (+4 more)
Resonant
chiral dielectric metasurfaces can support circular dichroism exceeding that of natural materials, but their small dissipative losses simultaneously limit the maximization of circular dichroism, which inherently relies on absorption. Importantly, while the condition for optimal circular dichroism in resonant structures can be rigorously formulated based on the concept of critical coupling, controlling the amount of absorption experimentally, and ideally tuning it to the optimal value post-fabrication, remains elusive. Here, we experimentally tailor the dissipative losses of
chiral bilayer dielectric metasurfaces post-fabrication using energetic ion beam irradiation. Specifically, we study the transmission characteristics of C4-symmetric
chiral metasurface consisting of silicon nanocuboid arrays embedded in silica glass using polarization-resolved spectroscopy. We enhance the circular dichroism from 0.70 in the pristine, unirradiated metasurface to 0.85 after irradiation. Our experimental results are complemented by numerical simulations allowing us to retrieve the refractive index changes induced by the ion beam irradiation in the constituent materials of the metasurface. Our work offers a new approach to globally maximize optical chirality in engineered nanostructures, paving the way towards
chiral emission and advanced polarization control applications
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All authors Anna Fitriana, Katsuya Tanaka, Lukas Raam Jaeger, Martin Hafermann, Thomas Pertsch, Carsten Ronning, Isabelle Staude
Geophysics · Cross-listed from cs.LG
Ensemble Graph Neural Networks for Probabilistic Sea Surface Temperature Forecasting via Input Perturbations
Alejandro J. González-Santana, Giovanny A. Cuervo-Londoño and Javier Sánchez
Accurate regional ocean
forecasting requires models that are both computationally efficient and capable of representing predictive uncertainty. This work investigates ensemble learning strategies for sea surface temperature (SST)
forecasting using Graph Neural Networks (GNNs), with a focus on how input perturbation design affects forecast skill and uncertainty representation. We adapt a GNN architecture to the Canary Islands region in the North Atlantic and implement a homogeneous ensemble approach inspired by bagging, where diversity is introduced during inference by perturbing initial ocean states rather than retraining multiple models. Several noise-based ensemble generation strategies are evaluated, including Gaussian noise, Perlin noise, and fractal Perlin noise, with systematic variation of noise intensity and spatial structure. Ensemble forecasts are assessed over a 15-day horizon using deterministic metrics (RMSE and bias) and probabilistic metrics, including the Continuous Ranked Probability Score (CRPS) and the Spread-skill ratio. Results show that, while deterministic skill remains comparable to the single-model forecast, the type and structure of input perturbations strongly influence uncertainty representation, particularly at longer lead times. Ensembles generated with spatially coherent perturbations, such as low-resolution Perlin noise, achieve better calibration and lower CRPS than purely random Gaussian perturbations. These findings highlight the critical role of noise structure and scale in ensemble GNN design and demonstrate that carefully constructed input perturbations can yield well-calibrated probabilistic forecasts without additional training cost, supporting the feasibility of ensemble GNNs for operational regional ocean prediction.
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Atmospheric and Oceanic Physics
Machine Learning Based Mesh Movement for Non-Hydrostatic Tsunami Simulation
Yezhang Li, Stephan C. Kramer and Matthew D. Piggott
This study investigates the use of machine learning based mesh movement method, specifically the Universal Mesh Movement Network (UM2N), with depth integrated non-hydrostatic shallow water models. Motivation for this comes from the need for models which balance efficiency and accuracy for use in probabilistic coastal hazard assessment. Implementations are built on the discontinuous Galerkin finite-element (DG-FE) based software, Thetis, which leverages the partial differential equation (PDE) framework Firedrake for automated code generation. Verification on
benchmark test cases and validation against laboratory measurements of coastal hazards, focusing on tsunami propagation, run-up, and inundation is performed. In these tests, the UM2N-driven meshes help resolve key non-hydrostatic dynamics including wave refraction over a conical shoal, run-up with wetting-drying on a conical island, and tsunami inundation in the Monai Valley laboratory
benchmark, and yield numerical solutions in close agreement with reference fine-mesh computations and measured data. Notably, in the Monai Valley case, UM2N achieves a ~91% reduction in wave-peak error at the nearshore gauge compared with ~74% for the conventional Monge–Ampère (MA) mesh movement, both relative to the coarse fixed mesh. The UM2N surrogate based approach accelerates the conventional mesh movement step, achieving a ~32% reduction in total runtime and ~2 times speed-up in mesh movement step time over the MA solver on GPU, while offering a significant improvement in robustness over long integration periods and under strongly nonlinear wave conditions.
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Atmospheric and Oceanic Physics · Cross-listed from astro-ph.EP
Global Abiotic Sulfur Cycling on Earth-like Terrestrial Planets
Rafael Rianço-Silva, Javed Akhter Mondal, Matthew A. Pasek et al. (+3 more)
Sulfur is a redox active element that may have helped mediate an electron flow that kickstarted life and which presently is an essential element for all life on Earth. Despite current uncertainties in global sulfur fluxes, modeling sulfur's abiotic cycling through Earth's deep history is important for understanding the impact of a
planet wide biosphere on sulfur geochemical cycling and availability and vice versa. We present here an open-source, dynamical box model for estimating global sulfur fluxes and concentrations among surface and deep Earth reservoirs over Earth history, allowing tracking and estimation of the sulfur distribution in planetary reservoirs over deep time in the absence of life. While the main model presented here does not take into account the abrupt
evolution of redox-shunting biosynthetic pathways such as oxygenic photosynthesis, we also modeled the abiotic sulfur cycle before and after a Great Oxidation Event-like transition on Earth-like
planets. Our results suggest a considerably distinct chemical makeup of sulfur content in marine sediments in the absence of life on an Earth-like
planet, leading to a marine sediment sulfate content two orders of magnitude larger than on present-day Earth and a marine sediment sulfide content 4 orders of magnitude lower than on present day Earth, attributable to the lack of microbial sulfur metabolism. This model could be useful for understanding sulfur cycling on potentially habitable
exoplanets.
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All authors Rafael Rianço-Silva, Javed Akhter Mondal, Matthew A. Pasek, Henry Jurney, Marcos Jusino-Maldonado, Henderson James Cleaves
Chemical Physics · Cross-listed from cs.LG
Latent Diffusion-Based 3D Molecular Recovery from Vibrational Spectra
Wenjin Wu, Aleš Leonardis, Linjiang Chen et al. (+1 more)
Infrared (IR) spectroscopy, a type of vibrational spectroscopy, is widely used for molecular structure determination and provides critical structural information for chemists. However, existing approaches for recovering molecular structures from IR spectra typically rely on one-dimensional SMILES strings or two-dimensional molecular graphs, which fail to capture the intricate relationship between spectral features and three-dimensional molecular geometry. Recent advances in
diffusion models have greatly enhanced the ability to generate molecular structures in 3D space. Yet, no existing model has explored the distribution of 3D molecular geometries corresponding to a single IR spectrum. In this work, we introduce IR-GeoDiff, a latent
diffusion model that recovers 3D molecular geometries from IR spectra by integrating spectral information into both node and edge representations of molecular structures. We evaluate IR-GeoDiff from both spectral and structural perspectives, demonstrating its ability to recover the molecular distribution corresponding to a given IR spectrum. Furthermore, an
attention-based analysis reveals that the model is able to focus on characteristic functional group regions in IR spectra, qualitatively consistent with common chemical interpretation practices.
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All authors Wenjin Wu, Aleš Leonardis, Linjiang Chen, Jianbo Jiao
Biological Physics
Network-based drug repurposing for MYH9-related nephritis
Muhammad Ali, Tommaso Gili and Guido Caldarelli
Using tools from network theory, we analyze the organization of a MYH9-oriented drug-like library in chemical space using a multi-descriptor framework. The
dataset is drawn from ZINC, a publicly available database of commercially accessible compounds curated for virtual screening and drug discovery. Starting from 6004 molecules, preprocessing yields 5000 structurally valid and descriptor-complete compounds. Similarity is defined via Tanimoto distance on Morgan fingerprints and single-descriptor distances for xLogP, HBD, HBA, molecular weight, and rotatable bonds. For each representation, we construct k-nearest-neighbor networks and identify communities using the Louvain-Leiden
algorithm. All networks exhibit highly significant modularity (Q=0.91-0.99) relative to degree-preserving null models, demonstrating pronounced nonrandom chemical organization across descriptors. Cross-descriptor robustness is quantified through a co-clustering
matrix over 1.25 X 10^7 molecular pairs, measuring how consistently compound pairs co-occur within the same community across descriptor-specific networks. Although most pairs show limited agreement, a sparse high-consensus core emerges, highlighting the complementarity of the descriptors. Minimum spanning trees derived from structural and consensus similarities reveal distinct backbone
topologies: a scaffold-driven, sparse structure versus a compact, hub-rich consensus network. Betweenness centrality on these backbones identifies compounds that are both structurally central and descriptor-balanced. These results provide a statistically validated network representation of chemical space and a principled strategy to extract consensus-stable compounds for downstream screening.
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