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Physics Physics

physics Watch Physics

Thursday 8 October

Chemical Physics

MAST: Motif-Augmented Diffusion with Search Tree for Spectroscopic Molecular Structure Elucidation

Chenghao Jia, Mengdi Liu, Hong Chang et al. (+2 more)

Elucidating molecular structures from spectra is a foundational problem in chemical and materials characterization, yet remains challenging due to spectral ambiguity and the vast molecular space. Although recent diffusion-based generators show strong promise for spectra-conditioned elucidation, existing methods struggle to learn robust spectra-structure relationships from limited paired data when relying solely on global spectral representation. Moreover, the repeated full sampling inference strategy incurs substantial computation overhead. To address these limitations, we propose MAST, a Motif-Augmented diffusion framework with Search Tree, for joint 2D-3D spectroscopic molecular structure elucidation. MAST introduces explicit, interpretable motif priors as intermediate evidences throughout denoising, reducing conditional ambiguity and facilitating spectra-conditioned optimization. We further cast diffusion sampling as reward-guided tree search to prioritize high-reward denoising trajectories, yielding a compact set of spectra-consistent candidates under limited budgets. On the QM9S multi-spectra benchmark, MAST achieves 94.89% exact recovery and improves 3D fidelity, while preserving high chemical validity and stability. Code is available at https://github.com/Jia040223/MAST.
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All authors Chenghao Jia, Mengdi Liu, Hong Chang, Shiguang Shan, Xilin Chen

Optics

Minimizing round-trip loss for near-unity quantum efficiency in organic light-emitting diodes

Junho Kim, Seonjeong Lee, Seunghyup Yoo et al. (+1 more)

Modern organic light-emitting diodes (OLEDs) reach internal quantum efficiencies close to 100%, yet in a planar device only 20-30% of photons escape. External outcoupling structures on high-index substrates recover some of the trapped light, but external quantum efficiencies (EQEs) have stalled at 55-60% across different optical designs, and the origin of this ceiling is not fully understood. Here we identify light extraction in such OLEDs as a multi-pass process: light that the outcoupling structure fails to extract returns to the OLED, is reflected back and may escape over multiple passes, with the efficiency governed by the absorption per round trip. Absorption loss is minor in conventional planar OLEDs, but it becomes dominant and accounts for the observed efficiency ceiling when an outcoupling structure is attached. Consistent with this picture, adding a low-loss auxiliary reflector raised the EQE of an OLED on a high-index microlens substrate from 51% to 77% without any change to the OLED stack or the outcoupling structure, the highest value reported for a single-junction OLED without a macroscopic extraction lens; for an OLED on a conventional glass substrate an estimated 92% of the light delivered to the substrate was extracted. We derive four design rules that keep round-trip losses to a few percent and predict that EQEs around 90% are feasible with established materials. Under these rules, microcavity tuning and emitter orientation largely cease to matter, and high efficiency is retained across a wide range of microlens designs and scattering layers.
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All authors Junho Kim, Seonjeong Lee, Seunghyup Yoo, Malte C. Gather

Optics

Observation of robust corner states in photonic crystals without global symmetries

Zitao Ji, Jianfeng Chen, Yidong Zheng et al. (+2 more)

Robust corner states have attracted considerable attention in recent years, particularly in photonic systems. They are typically realized in second-order topological insulators, including shrunken-expanded lattices and breathing Kagome lattices, where global symmetries are essential in their formation. This reliance on symmetry, however, can make these states highly sensitive to structural disorder. Here, we propose and experimentally demonstrate a class of robust corner states in photonic crystals that require neither global symmetry nor nontrivial topology. By locally tailoring the corner geometry of an otherwise topologically trivial structure, we create strongly localized modes that remain stable under both position and radius disorder. These states are not accidental; rather they originate from a pair of Dirac points in the bulk band structure. Geometric tuning shifts the flatband edge states connecting the Dirac points into an otherwise trivial bandgap, thereby inducing strongly localized corner states. Our findings uncover a previously overlooked class of symmetry-independent, disorder-resilient corner states, extend robust localization beyond conventional topological protection, and provide a route toward light localization in all-dielectric photonic systems.
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All authors Zitao Ji, Jianfeng Chen, Yidong Zheng, Zhaogang Dong, Zhi-Yuan Li

Plasma Physics

FHiVI$^{2}$: A Fast High-Voltage approach for Ionisation Improvement in the context of plasma-assisted magnetron sputtering

R. Jean-Marie-Desiree, L. De Poucques and S. Cuynet

Ionisation control remains a key challenge in plasma-assisted processes and more particularly in magnetron sputtering. In this context, the former directly governs species transport and thin-film properties. Although HiPIMS substantially enhances the ionisation rate of sputtered species, its performance remains constrained by the coupling between sputtering and ionisation, which limits discharge tunability. Here, we introduce Fast High Voltage for Ionisation Improvement (FHiVI$^{2}$), a new transient electrical regime designed to improve the ionisation rate without requiring additional elements. By applying an ad hoc very short, high-voltage pulse during plasma sputtering processes, FHiVI$^{2}$ regime is expected to induce a strongly anisotropic electric-field burst intended to enhance sputtered metallic species ionisation while limiting back-attraction losses and sputtering. To assess the ionising potential of this regime, optical emission spectroscopy together with mass spectrometry were carried out. More particularly, mass spectrometry measurements show an improvement of the ionisation rate by a factor of 2.7 compared with the HiPIMS regime, for an applied voltage of 2 kV which correspond to an additional mean power of only 1.2 W, using a 2-inch tungsten target. These findings suggest that FHiVI$^{2}$ provides a flexible route towards improved ionisation control in magnetron sputtering and opens new perspectives for plasma-assisted processes.
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Computational Physics

Ghost tasking for parametrized Gaussian Processes solving linear differential equations

Johanna Moser, Christopher Albert and Sascha Ranftl

Physics-informed machine learning has gained significant attention in recent years. In regimes of limited data, parametrized Gaussian processes have become popular. Existing approaches, however, often face limitations, such as requiring parametrizable (also called controllable) systems or a large number of output tasks. In this work, we introduce a systematic procedure we call "ghost tasking", using auxiliary tasks to circumvent these limitations. We prove that such ghost tasks can render any non-parametrizable system effectively parametrizable, enabling algorithmic construction of parametrized Gaussian Processes while keeping the number of required tasks (i.e. output dimensions) and latent functions low. We find that ghost tasking performs especially well in an inverse problem setting, even with very few available data. We show the usage and power of ghost tasking in three experiments, providing systematic comparisons to the only other currently available method applicable to all experiments. We provide necessary syntax and explications for two computer algebra programs that compute parametrizations for systems with polynomial or rational coefficients. Our theoretical results extend to systems with meromorphic functions.
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Chemical Physics

Gas-phase chemistry of $\mathrm{C}_3\mathrm{H}_3^+$: a key building block for carbon mass growth in space

Corentin Rossi, Jean-Christophe Loison, Anne P. Rasmussen et al. (+4 more)

The gas-phase chemistry of $\mathrm{C}_3\mathrm{H}_3^+$ plays a central role in the growth of carbonaceous species across a wide range of environments, from combustion systems to interstellar media. However, the presence of multiple isomers, primarily the linear propargyl cation and the cyclic cyclopropenyl cation, has so far prevented the determination of reliable isomer-specific reaction kinetics. In this work, we combine tunable vacuum-ultraviolet (VUV) photoionization with controlled ion–molecule reaction measurements to selectively produce and probe the reactivity of $\mathrm{C}_3\mathrm{H}_3^+$ isomers. By employing a titration approach, we extract isomer-specific reaction rate coefficients and branching ratios for reactions of $\mathrm{C}_3\mathrm{H}_3^+$ with $\mathrm{C}_2\mathrm{H}_4$, $\mathrm{C}_3\mathrm{H}_4$, and $\mathrm{C}_3\mathrm{H}_6$. Our results demonstrate a strong contrast in reactivity: the most stable cyclic isomer is found to be essentially unreactive under the investigated conditions, whereas the linear isomer exhibits efficient and diverse chemistry leading to the formation of larger hydrocarbon ions. In particular, the formation of $\mathrm{C}_6\mathrm{H}_5^+$ is observed, providing an important intermediate in pathways toward aromatic species. These findings help resolve long-standing ambiguities in previously reported rate coefficients and provide new quantitative constraints for kinetic and astrochemical models. More broadly, this work highlights the importance of isomer-specific chemistry in carbon growth processes and demonstrates the effectiveness of VUV-based photoionization methods for disentangling complex reaction networks in the gas phase.
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All authors Corentin Rossi, Jean-Christophe Loison, Anne P. Rasmussen, Roland Thissen, Nandana Pattathadathil, Christian Alcaraz, Ugo Jacovella

Fluid Dynamics

On the relationships between pressure geometrization and vortex identification

Han Tu, Hang Zhao and Qi Gao

The profound mathematical and conceptual analogy between pressure in fluid mechanics and gravity in general relativity motivates a novel geometric reinterpretation of flows. This article proposes a theoretical framework for geometrizing pressure by establishing a Newton-Cartan geometry and applying a conformal transformation to the spatial metric. The pressure field is reinterpreted as a geometric potential that induces an effective spatial curvature, encoded in the Ricci tensor Rij and the associated Einstein-like tensor Gij. Within this curved effective space, fluid particles under the exclusive influence of pressure follow geodesics, and the classical Euler equation is recovered in the weak-field limit. The pressure Poisson equation emerges naturally as a consequence of the geodesic equation and the Bianchi identity, revealing pressure as an instantaneous geometric constraint rather than an external force. This framework provides a unified geometric interpretation of widely used vortex identification criteria, demonstrating that the prevailing Eulerian and Lagrangian schemes correspond to different geometric invariants or projections of the effective curvature. In the degenerate two-dimensional (2D) limit, the effective spatial tensor vanishes identically, and the global integral of the total curvature vanishes as well. This topological constraint offers a novel interpretation of the dual-cascade scenario in 2D turbulence: the inverse energy cascade arises from geometric condensation of positive-curvature structures toward larger scales, while the forward enstrophy cascade results from geometric dispersion of negative-curvature structures toward smaller scales.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci

Homogeneous Charge Relaxation in Organic Mixed Ionic-Electronic Conductors

Silan Zhang, Scott T. Keene, Junfu Tian et al. (+11 more)

Organic mixed ionic-electronic conductors (OMIECs) couple ionic and electronic signals, enabling energy storage, neuromorphic computing, and bioelectronics. However, how charge relaxes in water once the bias is removed, which determines how long stored states persist, remains unclear. Using operando charge photometry, we tracked charge in OMIEC films during biasing and open-circuit relaxation. Under bias, charges moved as redox fronts. After bias removal, charge instead relaxed uniformly across the channel. Modeling and cryo-electron microscopy indicate that swelling creates connected water-rich pathways through the bulk. These pathways speed ion motion but also let stored charge leak away. Tuning the terminal side chain of a polythiophene controls water uptake and ion trapping. Bulky hydrophobic side chains enable stable programmable states, whereas hydrophilic side chains support fast electrophysiology sensing.
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All authors Silan Zhang, Scott T. Keene, Junfu Tian, Georgina E. Lindop, Simon M. Fairclough, Zhengkang Qu, Xian Wei Chua, Christopher Slaughter, Christina J. Kousseff, Caterina Ducati, Iain McCulloch, Henning Sirringhaus, Akshay Rao, George G. Malliaras

Chemical Physics · Cross-listed from cond-mat.stat-mech

Mutual Linearity of Complexes in Chemical Reaction Networks

Pedro E. Harunari, Guilherme Fiusa and Matteo Polettini

Exact statements about how a system far from equilibrium responds to changes in its rate constants are scarce beyond linear response, yet they are central to the control of biochemical networks. A notable exception is mutual linearity: in a jump process, controlling the rates of a single transition makes any two stationary probabilities obey an exact affine relation, arbitrarily far from equilibrium. With nonlinear mass-action kinetics, and conservation laws in place of a normalization, chemical reaction networks seem to defy mutual linearity since species concentrations obey no such relation. We show that it was there all along, in the complexes' activities (mass-action monomials) rather than in the concentrations of species. For zero-deficiency networks with a single linkage class, controlling one reaction makes any three stationary activities obey a linear relation whose coefficients are independent of the controlled rate constants, the conserved quantities (hence the initial state), and even of the stoichiometry of complexes. This predicts hidden activities and bounds the activity ratios the control can reach, while a violation signals nonzero deficiency or multiple linkage classes.
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Geophysics

Escaping Geological Generative Prior Distributions in Bayesian Travel Time Tomography

Pratyay Roy, Xuebin Zhao and Andrew Curtis

Solutions to geophysical inverse problems are generally non-unique, and greatly benefit from additional geological prior information. Generative Neural Networks (GNNs) are commonly used to parametrise such information, typically restricting solutions to a lower-dimensional latent space. The final inversion result is obtained by mapping the latent space parameters to the original higher-dimensional model space using the GNNs. However, solutions then remain confined to a low-dimensional geological generative manifold; if the true Earth model lies outside of this manifold, standard latent space inversion fails. We propose a Bayesian model space inversion method that uses the generative manifold as a guide to find the solutions that lie outside this manifold. We validate our approach in non-linear travel-time tomography experiments on both simple and more geological structures. By comparing our method with model space inversion using uniform prior probabilities and standard latent-space inversion, we demonstrate that the less informative uniform prior fails to constrain the solution, while the latent space approach fails when the true Earth model lies outside of the generative manifold. Conversely, our new model-space inversion method successfully recovers complex off-manifold geological features while maintaining low solution uncertainty.
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Optics

Temporal chirality in Floquet photonic media

Rui-Chuan Zhang, Yixin Sha and Yi Yang

We reveal temporal chirality in time-modulated photonic media: reversing the orientation of a closed loop traced by the complex permittivity can leave the Floquet spectrum unchanged while strongly modifying the directional scattering response under the same excitation. This behavior is linked to two symmetry constraints on the evolution operator, namely pseudo-Hermiticity and pseudo-unitarity. We prove the general occurrence of temporal chirality based on a complex Bogoliubov parametrization of the scattering amplitudes. We illustrate these findings in a single-harmonic temporal-$\mathcal{PT}$-symmetric system: both modulation-loop orientations support the same vacuum-like Floquet photonic bands at the phase transition, but one suppresses backward photon generation whereas the other induces strong growth, as confirmed by full-wave simulations. Our results establish temporal chirality as a distinct notion in time-varying photonics and identify modulation-loop orientation as a control knob for Floquet wave dynamics.
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Physics and Society

A Gauge-Invariant Clustering Coefficient for Complex-Weighted Bipartite Networks

Anjali Waghmare, Yu Tian and Renaud Lambiotte

Structural measures such as the clustering coefficient and the average shortest-path length characterise how a network is organised. These measures are typically formulated for real, non-negative edge weights. A class of quantum and photonic architectures has complex edge weights instead, whose phases determine whether alternative routes interfere constructively or destructively. These architectures are also bipartite, so triangles are absent and the smallest closed cycle is a four-node square. Existing measures address complex weights and bipartite structure separately: bipartite clustering coefficients quantify clustering through four-node squares but do not contain phase information, while interferometric coefficients retain phase but are defined on triangles. In this work, we define a clustering coefficient for complex-weighted bipartite networks which reduces to the classical bipartite coefficient when the phases vanish, becomes negative when alternative routes cancel, and can be obtained for all nodes from a single sparse matrix product. We show that the phase accumulated around a square is the smallest gauge-invariant carrier of structural phase information in a bipartite network. The clustering coefficient factorises into a topological contribution and a phase contribution, making a bipartite Watts–Strogatz ensemble analytically tractable. For phases uniformly distributed on $[-\Delta,\Delta]$, the mean phase contribution is $(\sin\Delta/\Delta)^4$, independent of node, degree, and topology. We also derive closed-form expressions for the clustering coefficient, open-path visibility, and phase variance. We numerically verify these predictions and further show that phase disorder increases coherent distance.
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Physics and Society · Cross-listed from cond-mat.stat-mech

The Fiedler dimension of networks of networks: from fractal to small-world architectures

Lorenzo Grimaldi, Andrea Gabrielli and Pablo Villegas

Is the relaxation of a modular network dictated by its modules or by the network that connects them? The answer fixes the time scales of diffusion, consensus, and synchronization, all set by the Fiedler eigenvalue. We show that, for bundled networks, the two levels act one after the other: a random walker must first escape from its module and then spread over the network that connects them. The equilibration time is the sum of these two times, the time needed to reach the base from inside a fiber and the relaxation time of the base, slowed down by the mass of the fibers. The consequences are unexpected. However large the modules are, a small-world core always imposes its own Fiedler dimension; the modules survive only as a logarithmic correction, which slows down equilibration and hides the true exponent up to sizes far beyond any real network. Effective dimensions measured on finite modular systems can therefore be systematically biased. We analytically work out all combinations of finite-dimensional and small-world bases and fibers, and compare them with numerically exact spectra of representatives of each category.
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Biological Physics

Femtosecond Three-Dimensional Imaging of Single-Protein with Hard X-ray Laser

Paul Lourdu Xavier, Andrew J. Morgan, Johan Bielecki et al. (+66 more)

The extremely intense pulses of X-ray free-electron lasers (XFELs) have enabled imaging of radiation-sensitive samples, such as macromolecular microcrystals, beyond radiation damage limits. These sources have the potential to deliver biomolecular single-particle imaging, similar to cryo-electron microscopy but without the need for cryo-fixation and with temporal resolution from femtoseconds to milliseconds. While this possibility was recognized before XFELs were built, the biological single-particle imaging work-flow has previously only been demonstrated on large virus particles. Based on decades of improvements in X-ray beam focusing, particle delivery, diffraction detection, and advanced analysis, here we demonstrate imaging of a single molecular complex, the giant-hemoglobin erythrocruorin (Ery) with X-ray laser pulses. Two-dimensional classes of diffraction patterns could be reconstructed to 15 Angstrom resolution, and 3D images to approximately 20 Angstrom, while the 3D merged intensity in reciprocal space extended beyond 20 Angstrom. The resolution discrepancy is likely due to heterogeneity caused by gas-phase compaction of the complexes. With increased throughput, this approach could be used to reveal in-situ structural details during mass spectrometry studies of biomolecules, while improvements in sample delivery may provide ultrafast snapshot imaging of biological single-particles in their native-state beyond the limitations of radiation damage.
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All authors Paul Lourdu Xavier, Andrew J. Morgan, Johan Bielecki, Amit K. Samanta, Simon Dold, Chufeng Li, Xinyue Gao, Spencer K. Passmore, Ruslan P. Kurta, Tim B. Berberich, Emiliano De Santis, Wenhui Zhang, Juncheng E, Faisal H. M. Koua, Romain Letrun, Luca Gelisio, Oleksii Turkot, Egor Sobolev, Lukas V. Haas, Jannik Lübke, Jingxuan He, Madeline B. F. Memovich, Kevin Janson, Stefanie Lenzen, Safi Rafie-Zinedine, Mansi Butola, Oleksandr Yefanov, Fabian Trost, Chan Kim, Tomas Popelar, Tokushi Sato, Yevheniy Ovcharenko, Rebecca Boll, Sergey Usenko, Thomas M. Baumann, Alberto De Fanis, Björn Senftleben, Matteo Porro, Andrea Castoldi, Ibrahym Dourki, Cyril Danilevski, Ekaterina Round, Christina Schmidt, Huijong Han, Roberto Alvarez, Ervin Chia, Cornelia Cazey, Carolin Seuring, Ruojie Sha, Maia Azubel, David A. Bushnell, Sébastien Boutet, Sergey Ovchinnikov, Adrian P. Mancuso, Michael Meyer, Richard Bean, Anton Barty, Filipe R. N. C. Maia, Richard A. Kirian, Thomas D. Grant, N. Duane Loh, Carl Caleman, Erik G. Marklund, Nadia Zatsepin, Andrew V. Martin, Saša Bajt, Roger D. Kornberg, Jochen Küpper, Henry N. Chapman

Physics and Society

Tracking High-Impact Researchers Through Highly Cited Tails

Hirushan Sajindra and Eoin Ó Colgáin

It is well recognised that field weighted citations are approximately lognormally distributed. This skewness reflects competition for attention, whereby most publications are gradually forgotten and only a minority continue to be recalled years later. Exploiting this observation, we construct a researcher-level indicator based on authorship of top 10% cited papers in All Science Journal Code (ASJC) bins and apply it to publications affiliated with Irish institutions over a typical funding cycle. Restricting attention largely to original research papers, we find that researchers authoring strictly more than one ASJC top-decile paper in a given year exhibit persistent participation in the highly cited tail of the literature in subsequent years, thus the simple track record indicator possesses predictive value. In contrast, the median researcher in cohorts of Research Ireland and European Research Council awardees selected through qualitative peer review either authors no top-decile paper or less than the median researcher in our ranking. These results demonstrate that research excellence as judged by qualitative peer review and influence on the research literature identify substantially different cohorts of researchers. In the absence of evidence, funding bodies and universities may conflate these two. While research reputation may be enhanced through many channels, highly cited papers constitute the most widely observable manifestation of international scholarly influence. Our analysis indicates that literature influence may be improved through greater use of data in track record pre-screening prior to qualitative peer review.
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Plasma Physics

Compressional heating above 1 keV on the LM26 magnetized target fusion machine

S. J. Howard, D. Krotez, P. Carle et al. (+43 more)

The LM26 device has achieved a peak electron temperature of $T_e = 1180 \pm 65$ eV as measured by filtered X-ray diodes, supported by adjacent Thomson scattering measurements of $T_e = 1090 \pm 40$ eV, with a deuterium ion temperature of $T_i = 459 \pm 33$ eV as inferred from neutron yield. LM26 compresses a spherical tokamak plasma inside an initially 1.76 m diameter solid lithium liner imploded by theta-pinch coils. Radial compression by a factor of 2.75 increases $T_e$ over fivefold, while $T_i$ increases as much as twofold. The integrated observation of magnetic flux compression, electron heating, ion heating, and neutron production in a magnetized plasma compressed by a large lithium liner is an important milestone for magnetized target fusion
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All authors S. J. Howard, D. Krotez, P. Carle, J. Sanchez Rojo, R. Underwood, A. Froese, M. Reynolds, N. Sirmas, K. Conquergood, K. Epp, P. Forysinski, D. Plant, R. Zindler, E. Love, D. P. Brennan, N. Kumar, C. MacDonald, A. Wong, W. Zawalski, B. Rablah, W. Kozicki, C. Preston, A. Lee, X. Feng, M. Schellenberg-Beaver, R. Tingley, J. Gorenstein, V. Suponitsky, Z. Seifollahi Moghadam, D. Froese, E. Cessford, J. Pratt, J. Crofts, J. Sardari, G. Faust, D. Ross, J. Wilkie, S. Bernard, C. Connor, S. Bolanos, C. Gutjahr, E. Chan, C. Eyrich, A. Mahoney, M. Davidson, M. Laberge

Atmospheric and Oceanic Physics

legoESM: a modular, differentiable, multiscale, AI-ready Earth system model built with AI agents

Pierre Gentine, Dhruv Balwada, Aytaç Paçal et al. (+12 more)

Earth system models (ESMs) have grown tremendously in realism, yet key uncertainties persist in the climate response to greenhouse-gas forcing, particularly due to cloud radiative feedbacks. In addition, their software architecture was not designed for accelerator hardware or modern artificial intelligence (AI). Here we present legoESM, a composable, differentiable, multiscale ESM written in JAX. It builds on decades of community-developed parameterizations and numerical methods, recast in a unified framework by AI coding agents under a human-specified scientific contract and verified through benchmarking. Dynamical cores, physics schemes, grids, complexity levels and components are swappable like building blocks, and can use conventional physics or machine-learned emulators. A single code base spans metre-scale large-eddy simulation to global simulations and weather to climate. End-to-end differentiability enables gradient-based calibration, variational data assimilation and online training. legoESM modular architecture enables systematic evaluation of diverse model variants to explore structural uncertainty and test hypotheses. legoESM produces realistic simulations across scales, reduces land-surface temperature bias through gradient-based calibration, and scales efficiently on GPUs to kilometer-scale simulations. It offers an open, community infrastructure for hypothesis testing, research and teaching in Earth sciences and a template for multiscale physical systems.
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All authors Pierre Gentine, Dhruv Balwada, Aytaç Paçal, Linnia Hawkins, Alistair Adcroft, Hang Fan, Jianing Fang, Aya Lahlou, Kara D. Lamb, David M. Lawrence, Julien Le Sommer, Joseph Mouallem, Juan Nathaniel, Duncan Watson-Parris, Veronika Eyring

Plasma Physics

WEST advanced wall protection achievements toward long pulse operation

R. Mitteau, M.H. Aumeunier, L. Dubus et al. (+8 more)

Long pulse operation in magnetic fusion devices requires well controlled plasma power exhaust to the divertor & wall, and avoidance of wall hot spots that could evolve in wall damage. At WEST, 10 major plasma facing components are monitored using 10 series of temperature/power indicators, based on multiple diagnostic systems, among which the infrared viewing system is especially relevant. These indicators span from the most basic ones (temperatures, power and energy from deterministic models) to advanced processes using artificial intelligence acquired through machine learning. Some advanced processes do operate in real time, and feedback on power actuators through the plasma control system, providing active control toward remaining within the safe operational domain. Other advanced processes intervene as forensic tools post discharge to identify possible dangerous situations regarding the power loading to the wall, so that the discharge run plan is adjusted to avoid running into aggravating wall events. No critical wall power event happened during the campaigns C9 to C11 (2024-2025), totalling about 13h of plasma, that would have affected the campaign plan. While it cannot be demonstrated that the active & intelligent wall protection enabled the new plasma duration record of 1337 seconds, the wall protection system as a whole plausibly contributed to obtaining these record durations by preventing wall hot spots to become critical during the campaigns.
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All authors R. Mitteau, M.H. Aumeunier, L. Dubus, J. Gerardin, V. Gorse, E. Grelier, V. Moncada, S. Vives, X. Litaudon, M. Jakubowski, J. Fellinger

Optics

RF-Resolved RIN Engineering of High-Power CW Yb Fiber Laser Architectures Using Seed Topology, Seed Power, Pumping Geometry and Cavity FSR

Anitta Augustine, V. Meher, Shantanu Dambare et al. (+1 more)

We report, to the best of our knowledge, the first controlled, like-for-like experimental mapping of how four practical design parameters–seed-cavity topology, seed power, amplifier pumping geometry, and seed-cavity free spectral range (FSR)–jointly shape the radio-frequency (RF)-resolved relative intensity noise (RIN) of high-power continuous-wave (CW) Yb-doped fiber lasers. We compare a standalone bidirectional fiber Bragg grating (FBG) oscillator, an FBG-seeded master-oscillator power amplifier (MOPA), and unidirectional ring-seeded MOPAs with FSRs of approximately 11.5 and 5 MHz, all near 1064 nm at a common 72 W output, with RIN measured from 10 kHz to 1 GHz. Across all settings, the low-frequency RIN is technical-noise limited and nearly architecture-independent, whereas RIN above 160 kHz is governed by the seed-cavity topology and its transfer through the amplifier. Higher seed power suppresses the mid- and high-frequency RIN, but the seed-alone and amplified-output comparison reveals opposite transfer for the two topologies: for FBG seeding the 2 MHz-1 GHz RMS RIN increases through amplification (3.66 percent to 4.14 percent at 15 W seed), whereas for ring seeding it decreases (1.47 percent to 1.35 percent). Forward pumping gives the best power-scaling/noise trade-off, while reducing the ring FSR from approximately 11.5 to 5 MHz preserves the high-frequency RIN advantage, confirming it is not a mode-spacing effect. At matched conditions, ring seeding lowers the integrated RMS RIN by 2-3 times (160 kHz-2 MHz) and approximately 3 times (2 MHz-1 GHz, approximately 9-10 dB to near -127.4 dBc/Hz). These results yield band-resolved design rules linking each band to its dominant lever. The unidirectional ring-seeded MOPA thus offers a simple, scalable route to broadband pump-RIN suppression for nonlinear and frequency-conversion photonics.
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All authors Anitta Augustine, V. Meher, Shantanu Dambare, V. Balaswamy

Chemical Physics

Unitary Coupled Cluster Nuclear Shielding Constants in a Quantum Linear Response Framework

Juliane H. Fuglsbjerg, Sonia Coriani, Jacob Kongsted et al. (+1 more)

We present calculations of nuclear shielding constants, a key ingredient in nuclear magnetic resonance spectroscopy, within a quantum-computing-suitable framework. We employ quantum linear response (qLR) theory in combination with the unitary coupled cluster (UCC) ansatz and its orbital-optimized (oo-UCC), factorized (fUCC), and orbital-optimized factorized (oo-fUCC) variants. The methods are assessed for seven small molecules against CASCI, CASSCF, CCSD, and CCSD(T) reference calculations. The different UCC-based qLR approaches yield shielding constants in good agreement with comparable classical methods. Factorization, which is necessary for quantum-computing implementations, has only a negligible effect on the calculated shielding constants. Orbital optimization, in contrast, leads to substantial improvements, with oo-UCC and oo-fUCC showing markedly better agreement with CCSD and CCSD(T). Our results establish oo-fUCC combined with qLR as a promising approach for computing nuclear shielding constants on quantum computers.
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All authors Juliane H. Fuglsbjerg, Sonia Coriani, Jacob Kongsted, Stephan P. A. Sauer

Fluid Dynamics

Using analogues to investigate error growth and predictability in turbulence

Carlos Granero-Belinchon, Mickaël Bourgoin and Bérengère Dubrulle

In this study, we revisit Lorenz's pioneering concept of analogues to investigate error growth and predictability in fully developed turbulence using experimental data. By applying the method to a 1D turbulent velocity time series, we successfully identify the three error growth regimes intuited by Lorenz and later formalized by turbulence theory: the chaotic exponential regime, the algebraic regime of spontaneous stochasticity, and the saturation regime. Our analysis reveals that the Lyapunov exponent and the exponent of the algebraic regime depend on the initial error. We interpret this dependence as a statistical bias induced by the intermittency of turbulence, where rare events, characterized by lower Lyapunov exponents and more singular velocity increments, are preferentially sampled when considering larger initial errors. These findings not only validate Lorenz's qualitative intuition but also provide new quantitative insights into the predictability of turbulent flows, paving the way for potential applications in the prediction of extreme events.
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Instrumentation and Detectors

Thomson Scattering Measurement of 1 keV Electron Temperature on Lawson Machine 26

P. Carle, S. Edwards, X. Feng et al. (+11 more)

LM26 is a magnetized target fusion experiment built to demonstrate compressional heating of a plasma with a collapsing solid lithium liner. We report the design of a Thomson scattering diagnostic for LM26 and measurements from the LMC-12 compression shot where an electron temperature of $1090 \pm 40 \rm{eV}$ was measured with high confidence. The LM26 Thomson scattering diagnostic can measure temperature during compression at 8 times and 2 spatial points. Access limitations restricted the design to narrow f/30 views, and a forward scattering configuration with scattering angles < 20deg. The small solid angle of the scattered light view is largely compensated for by the 10 times increase in the density during compression to $> 10^{20}\rm{m}^{-3}$. Measuring at a small scattering angle significantly narrows the Thomson spectral broadening of the laser line. The narrow spectrum (1030-1063 nm) is advantageous for the design of optical components and to minimize noise from plasma background light. UKAEA polychromators specialized for small broadening measurements were used to analyze the scattered light. Results are also presented for an uncompressed plasma preceding LMC-12. Stray light was not a significant source of error. This design provides a strong design basis for Thomson scattering systems on future LM26 configurations.
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All authors P. Carle, S. Edwards, X. Feng, A. Froese, M. Greenwood, A. Lee, M. Reynolds, A. Rudy, J. Sanchez Rojo, M. Schellenberg-Beaver, R. Svihra, R. Tingley, R. Zindler, M. Maslov

Chemical Physics

Optical absorption spectra from the $GW$-Bethe-Salpeter framework for thousands of atoms

Maximilian Graml, Ritaj Tyagi, Rémi Pasquier et al. (+2 more)

The frequency-dependent absorption and emission of light determine the colors of matter and underpin today's technologies, from solar cells to light-emitting diodes. Predicting optical properties from first principles remains a computational challenge, especially for large and disordered systems. The $GW$ plus Bethe-Salpeter equation ($GW$-BSE) approach provides predictive accuracy for optical properties, but conventional implementations become costly as system size grows. Here, we present a $GW$-BSE framework combining real-time propagation, atom-centered basis sets, and a locally optimized real-space resolution of the identity. The cost of each propagation step scales quadratically with system size and roughly equals the cost of one self-consistent-field iteration in a density-functional calculation with a semilocal functional. This computational efficiency allows us to calculate the absorption spectrum of a nanographene containing 4616 atoms and opens a path toward routine calculations of optical properties for large disordered systems.
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All authors Maximilian Graml, Ritaj Tyagi, Rémi Pasquier, Štěpán Marek, Jan Wilhelm

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

Can end-to-end learning from raw electronic structure explain magnetic anisotropy?

Rafał Topolnicki, Jan Navrátil and Piotr Błoński

Machine-learning models trained directly on electronic spectra can predict spin–orbit-driven properties, yet models with comparable predictive accuracy may learn different electronic dependencies. We examine this problem using magnetic anisotropy in atomic-scale magnets and a validation strategy designed to assess the physical relevance of learned spectral relationships. We compare a bidirectional gated recurrent unit and a one-dimensional convolutional neural network, both trained to predict magnetic anisotropy energy (MAE) from spin- and orbital-resolved scalar-relativistic densities of states (SR-DOS). Despite comparable in-domain (ID) accuracy, the architectures learn only partly overlapping spectral dependencies. Shapley additive explanations identify spectral features shared between the two architectures that can be associated with plausible spin–orbit-coupling pathways consistent with second-order perturbation theory (PT2). Adding PT2-derived MAE contributions to the model inputs has little effect on ID performance but can improve transfer beyond the training domain, with gains differing between architectures. Controlled spectral perturbations further demonstrate that similar attribution patterns do not imply the same functional dependence of the predicted MAE on spectral weight. The contrasting responses provide a functional context for architecture-dependent out-of-domain transfer. End-to-end learning can identify candidate electronic signatures of magnetic anisotropy. Their credible microscopic interpretation, however, rests on convergent evidence from predictive performance, model comparison, physical theory, controlled spectral interventions, and evaluation under distribution shift.
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Biological Physics

Three-dimensional imaging of isolated membrane-protein complexes in vacuo with an X-ray laser

Kartik Ayyer, Tej Varma Yenupuri, Johan Bielecki et al. (+51 more)

The prospect of imaging single biomolecules, viruses and cells with intense, ultrashort X-ray pulses has driven the development of X-ray free-electron lasers (XFELs). However, the weak scattering from small particles is easily swamped by background from residual gas, which has so far limited applications to strongly scattering targets such as viruses, cell organelles and cells. Here we report a three-dimensional (3D) reconstruction of an isolated 1-MDa membrane-protein complex, photosystem I (PS I), from single-particle diffraction data. PS I trimers were aerosolised by charge-reduction electrospray ionisation and injected into the European XFEL beam, with partial helium gas exchange reducing background scattering by 80%. From 32 788 diffraction patterns of single trimers in random orientations, we reconstructed the 3D electron density to a resolution of 3.8 nm, limited by the detector geometry. The disc-shaped density, about 22 nm across and 10 nm thick, matches the size of a PS I trimer in a detergent micelle and is consistent with the compaction predicted by molecular dynamics simulations of the complex in vacuo and observed in native mass spectrometry. These results show that membrane-protein complexes can be imaged in vacuo with X-ray lasers, an important step towards ultrafast diffractive imaging of single macromolecules.
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All authors Kartik Ayyer, Tej Varma Yenupuri, Johan Bielecki, Lutz A. Eichacker, J. Domingo Meza-Aguilar, Louise J. Persson, Lena Worbs, Patrick Adams, Roberto Alvarez, Adil Ansari, Alfredo Bellisario, Rebecca Boll, Carl Caleman, Sebastian Cardoch, Andrea Castoldi, Joe P. J. Chen, Cyril Danilevski, Merle Dechering, Simon Dold, Armando D. Estillore, Alberto De Fanis, Lukas V. Haas, Patrick Konold, David Lomitze, Abhishek Mall, Dimitra Manatou, Iñaki de Diego Martinez, Parichita Mazumder, Andrew J. Morgan, Anna Munke, Yevheniy Ovcharenko, Matteo Porro, Safi Rafie-Zinedine, Amit K. Samanta, Christina Schmidt, Arezu Sehati, Jonas A. Sellberg, Björn Senfftleben, Carolin Seuring, Zhou Shen, Nicusor Timneanu, Sergey Usenko, Daniel Westphal, August Wollter, Tamme Wollweber, Paul Lourdu Xavier, Henry N. Chapman, Janos Hajdu, Richard A. Kirian, Jochen Küpper, Erik G. Marklund, Petra Fromme, Michael Meyer, Filipe R. N. C. Maia

Chemical Physics

Predictable Accuracy of Martini 3 Absolute Protein-Ligand Binding Free Energies across 15 Targets

Luis J. Walter and Tristan Bereau

Alchemical free-energy calculations predict protein-ligand binding affinities with close-to-experimental accuracy, but their cost restricts them to small sets of ligands. Coarse-grained (CG) models such as Martini 3 retain a rigorous statistical-mechanical treatment at a fraction of this cost, yet their accuracy for protein-ligand binding has not been assessed systematically. Here, we compute absolute binding free energies for 172 ligands across 15 protein targets with a Martini 3 double-decoupling protocol and compare them against atomistic FEP+ and OpenFE references. Martini underbinds for every target, by 2.7 to 8.7 kcal/mol. This offset is systematic: it comprises a uniform contribution that grows with the number of charged pocket residues. A linear model in this number, which requires only the protein structure, reduces the mean absolute error from 5.7 to 1.2 kcal/mol in leave-one-out cross-validation, close to the 1.0 kcal/mol obtained with exact per-target offsets. The ranking of ligands within a target varies more widely (median Spearman $\rho$ of 0.32, from $-$0.41 to 0.89) and is rationalized by the structure-activity relationship of each series: Martini ranks ligands well when their affinity is driven by hydrophobicity, $\pi$-stacking, or size, and poorly when it is driven by hydrogen bonding or charge. Both trends follow from Martini's calibration against bulk partitioning, which captures neither the dielectric environment of a binding pocket nor the directionality of hydrogen bonds. While MMGBSA retains the atomistic detail needed to rank congeneric ligands, Martini yields physically meaningful free energies, and its coarse-graining maps many atomistically distinct molecules onto one representation, making it a complementary tool for rapidly spanning chemical space.
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Optics · Cross-listed from cond-mat.mtrl-sci

Predicting plasmonic pole representations of complex dielectric spectra using convolutional neural networks

Dario A. Leon

Extracting spectral properties such as energy position, broadening, and spectral weight from dielectric spectra is critical for interpreting collective electronic excitations in many-body physics. Conventional approaches typically rely on nonlinear fitting procedures that can be computationally demanding and highly sensitive to initialization and fitting choices. In this work, we develop a convolutional neural-network framework for the direct inversion of dielectric spectra into their underlying plasmonic pole structures using a multipole-Padé representation. Rather than training on a constrained database of spectra associated with a specific set of materials, the network is trained entirely on synthetic spectra generated from the analytical multipole-Padé expression with randomized parameters. This enables the network to learn the general mapping between the spectra and their features in an unbiased way, without requiring large, material-specific datasets derived from real materials. We demonstrate that the synthetically trained network generalizes to complex first-principles and experimental dielectric spectra, extracting the underlying pole parameters with high accuracy in a single forward pass. This approach provides an efficient and robust alternative to conventional nonlinear fitting, enabling high-throughput, automated analysis of dielectric spectra across diverse materials and applications.
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Chemical Physics

Non-Perturbative Vibrational Excitation by Arbitrary Electric Fields from Classical Phase-Space Dynamics

Sameernandan Upadhyayula and Jiří J. L. Vaníček

We present a non-perturbative framework for the quantum treatment of vibrational excitation in molecular systems driven by electric fields with arbitrary time dependence. For harmonic potentials with linear dipole coupling, the field-induced dynamics is exactly described by a displaced coherent state, whose evolution is completely determined by a complex phase-space coordinate. Closed-form expressions for this coordinate reveal a clear distinction between resonant and non-resonant regimes. The resulting vibrational populations follow a Poisson distribution determined by a dimensionless time-dependent phase-space displacement, for both resonant and non-resonant driving. Resonant driving results in an enhanced phase-space displacement, whereas finite detuning between the driving and vibrational frequencies leads to an exponential suppression of the phase-space displacement and vibrational excitation. While the approach reduces to the standard time-dependent perturbation theory in the weak-field limit, it remains valid in the strong-field regime, where perturbative treatments fail. Our results provide a transparent phase-space picture of vibrational control and enable non-perturbative state preparation in ultrafast spectroscopy.
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Applied Physics · Cross-listed from cond-mat.mtrl-sci

Robust skyrmion nucleation and transport via composition gradient in rare earth-transition metal ferrimagnets

Pietro Diona, Luca Maranzana and Sergey Artyukhin

Magnetic skyrmions are typically nucleated via localized excitation methods, such as laser heating, spin-orbit torques, or engineered defects, and their controlled transport is often limited by the skyrmion Hall effect. Here, we demonstrate that spatial gradients in rare-earth–transition-metal alloys, achievable through patterned laser writing, enable both deterministic nucleation and controlled transport. The strategy leverages engineered compositional gradient to cross the magnetization compensation point, defining regions with opposite magnetization. An out-of-plane magnetic field selectively reverses the magnetization, generating a skyrmion. Crucially, the same compositional design enables a channel tuned to the spin angular momentum compensation point, where skyrmions are driven by spin-orbit torques at high velocity with vanishing skyrmion Hall effect. Local composition variations act as pinning sites, enabling threshold-controlled trapping and release.
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Applied Physics · Cross-listed from cond-mat.soft

Autonomous thermodynamic cycles via robotic mobility and sensing

Sofia Kuperman, Ezra Ben-Abu, Yaron Veksler et al. (+3 more)

Thermodynamic cycles are the foundation of energy conversion across natural and engineered systems, transforming heat into useful work. However, these cycles traditionally operate between fixed thermal reservoirs, restricting them to specific locations and temperature differences. Here, we introduce autonomous thermodynamic cycles enabled by robotic mobility and sensing, allowing robots to perform thermodynamic cycles by accessing spatially varying temperature fields. We experimentally realize this concept using multistable gas-filled capsules that circulate within the system across a thermal gradient. Our model reveals that rapid transitions in the capsules' energy states allow the system to operate as a mobile heat engine that harvests and stores energy. By linking the capsule-scale internal energy dynamics to the robot's large-scale navigation strategy, we optimize locomotion paths that balance motion cost and energy harvesting. These findings demonstrate that thermodynamic cycles can emerge when autonomous systems navigate their environments, offering an artificial analog of organisms that forage for energy across spatial resources.
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All authors Sofia Kuperman, Ezra Ben-Abu, Yaron Veksler, Anna Zigelman, Sefi Givli, Amir D. Gat