Papers

Beam Intercepting Devices (BIDs) include targets, scrapers, collimators, protection absorbers and beam dumps. They enable secondary particle production, shape or clean beams, and protect sensitive components by concentrating beam losses into shielded locations. In high-power proton machines, BIDs operate close to thermo-mechanical limits under intense radiation fields, and their reliability directly impacts accelerator availability. This review summarizes the dominant design drivers (energy deposition, temperature gradients, thermal stress, fatigue, radiation damage and activation), outlines a pragmatic design workflow combining energy-deposition assessment with coupled thermal/structural and fluid dynamic analyses, and reviews representative BIDs at PSI's High Intensity Proton Accelerator (HIPA), including current hardware and developments for the IMPACT project (Isotope and Muon Production using Advanced Cyclotron and Target technology).

Deep learning has become a prevailing paradigm across a wide range of geophysical applications. Yet most existing studies concentrate on methodological refinements – novel network architectures, physics-informed constraints, or taskspecific loss functions – while paying comparatively little attention to a more fundamental challenge of any data-driven approach: the availability and representativeness of high-quality training data. This limitation is especially pronounced in geophysics. Unlike computer vision, which benefits from large-scale, well-curated benchmarks such as ImageNet, comparably abundant and reliably labelled geophysical data are prohibitively expensive to acquire and, in most field settings, lack accessible ground-truth supervision. To alleviate this data deficiency, we propose GeoVolDiff, a generative framework for three-dimensional geological volumes. It comprises three coupled stages: (i) constructing a foundational training corpus through physics-based forward simulation; (ii) training a Latent Diffusion Model (LDM) to capture the statistical distribution of 3D geological structures; and (iii) synthesizing diverse, structurally plausible volumes at scale for downstream geophysical tasks. We examine the utility of the synthesized data on a representative downstream task, seismic impedance inversion. Without incorporating any additional physical or geological prior, inversion networks pre-trained exclusively on synthesized data attain competitive performance on both synthetic and field datasets, indicating that data synthesised by the generative model can serve as an effective surrogate for costly field-acquired labels.

Objective. Motion management is a critical challenge in proton therapy for mobile tumours. This study aims to develop and evaluate a novel four-dimensional (4D) pencil beam delivery strategy that incorporates respiratory motion into a dynamic treatment plan to improve dose conformity and treatment efficiency. Approach. To assess this 4D pencil beam delivery strategy, a mobile phantom was used. The generated 4D treatment plans were assessed with various scanner configurations, including gantry-free and magnet-free scanner heads. For each setup, the treatment time, dose conformity, and robustness against irregular breathing patterns were quantified. The influence of scanner head design and patient-specific motion irregularities on overall plan quality was evaluated. Main Results. The 4D planning tool generated treatment plans that achieved clinically acceptable dose distributions across all configurations. In magnet-free configurations, static beam operation substantially increased treatment time and reduced dose conformity. In contrast, configurations using a single scanner magnet, without a gantry, maintained acceptable conformity within practical treatment times. Significance. The proposed 4D delivery strategy demonstrates feasibility for treating mobile targets with simplified, gantry-free and magnet-free scanner designs. Further improvements could be achieved by synchronising the patient's breathing with 4D delivery, which may enhance dose accuracy during irregular or interrupted breathing. By reducing system complexity while preserving dosimetric performance, this approach offers a pathway toward more accessible and cost-effective proton beam therapy for motion-affected tumours.

A surface geometry consisting of parallel, meandering streamwise grooves has been experimentally studied as an alternative means of passive transverse forcing of turbulent boundary-layer flow. Contrary to the original expectation, the flow does not exhibit a spanwise-uniform undulation aligned with the grooves; instead, a converging-diverging flow pattern results. This flow pattern can be attributed to the spanwise periodicity of the lateral pressure gradient. The forcing effect is found to initially increase with the groove amplitude, but it saturates when the groove slope becomes too steep. The observed induced flow, referred to as a Passive Stokes Layer (PSL), can be considered as being composed of an inertial (pressure-driven) outer solution generated by the displacement effect of the non-smooth surface geometry, and a viscous inner solution to accommodate the no-slip condition at the wall. The mechanism of transverse flow generation is elucidated by an inviscid flow model that relates the forcing to the surface geometric properties, with predictions in good agreement with the experimental results. Although a reduction in the near-wall turbulence levels over the groove surfaces is observed, no direct evidence for (mean) drag reduction is evident from the data. Instead, an estimate of the frictional drag potential is based on establishing a tentative relation to an equivalent spatial Stokes layer (SSL) induced by active wall forcing. This theoretical comparison indicates that the induced passive forcing is sufficient to act on the (active) spanwise forcing mechanism, but produces at most a few per cent of frictional drag reduction. Any potential savings are likely offset by pressure drag and other losses, so that, similar to active forcing, its potential for net drag reduction in practical applications is limited.

Physical systems do not merely add noise to search processes; they impose constraints that generate structured correlations. We propose a principle of constraint-enhanced physical search in which temporal correlations in exploration are matched to constraint-induced spatial correlations in the update dynamics. Using a minimal tug-of-war bandit model (TOW), we show that a conservation law converts local observations into differential evidence across alternatives, while a temporally correlated drive controls the order of exploration. Search efficiency is improved not by stronger randomness or by maximal anti-correlation, but by matching the temporal correlation to the physical update scale that converts feedback into evidence. A scaling estimate identifies the update-noise-to-contrast ratio as the leading parameter that limits how strongly temporal anti-correlation can be used. The results suggest a general organizing principle for physical search: constraints and fluctuations can generate structured spatiotemporal correlations, and efficient exploration emerges when these correlations are matched to the update dynamics.

We study a class of Sturm–Liouville problems of the form \[ -(p\,y')' + q\,y = \lambda\, w\, y, \] on a finite interval with complex-valued coefficients, where $p$ and $w$ are piecewise smooth, the ratio $w/p$ is real and positive, and $q$ is bounded. We prove that all eigenvalues in the open left half-plane are contained in a bounded set, which implies that only finitely many eigenvalues lie in this region. This stands in contrast to the known unboundedness, for real-valued coefficients, when $p$ or $w$ changes sign independently. A canonical instance of this class, with $w=p$, arises in transverse-magnetic (TM) diffraction by metallic lamellar gratings, a benchmark problem in computational photonics, central to the development of modal methods. In Fourier modal methods, in particular, the emergence of spurious modes with unbounded propagation constants (eigenvalues), rooted in discretization of sign-changing coefficients, leads to notorious convergence difficulties. These modes cannot be excluded a priori, since genuine eigenvalues are not constrained by conventional bounds in this regime. Nevertheless, our result shows that the physical eigenvalues remain bounded, providing a rigorous criterion for identifying spurious modes in low-loss metallic gratings.

Field-programmable gate arrays provide a high-performance solution for real-time signal processing in emerging quantum and photonic technologies. We present an FPGA-based fast feedforward system, that incorporates a high quantum efficiency fully fibre based homodyne detector, to enable low-latency signal processing critical for continuous variables (CV) measurement-based quantum information processing (MB-QIP) protocols. CV MB-QIP typically relies on adaptive measurements and/or displacements via feedforward to achieve scalability and universality, but existing implementations typically handle these operations in post-processing, limiting real-time applicability. Our system performs signal acquisition, conditioning, and logic operations in real-time, meeting the tight latency requirements of photonic quantum computing protocols. The detector exhibits a large clearance of 15 dB at 1 GHz with 4 mW linear oscillator and quantum efficiencies of >95% with a total system latency of 196 ns. This work highlights the role of FPGAs in bridging the gap between theoretical models and physical implementations in photonics-based technologies

Optical vortices carry quantized phase information (topological charge) and are considered candidates for information processing in all-optical circuits. Accurately identifying the quantized vortex charge in a way that is most efficient is essential for data processing. Here, we demonstrate that using only intensity information machine learning algorithms are able to classify vortices into distinct phase categories using a properly trained model. Preprocessing of the original intensity data leads to an improved prediction accuracy of the trained classifier and a much shorter training time (~3 orders of magnitude faster). The learning mechanism of the algorithms is revealed by the statistical analyses based on calculation of Cohen's d. We also find that the training efficiency is associated with nonlinearity, non-Hermiticity, and the vortex shape. In some cases, the trained classifier performs well across distinct physical models. Our findings will benefit and accelerate vorticity-based binary information processing and can also be extended to other physical systems.

Integrated tunable lasers are central to coherent communications, wavelength-routed optical interconnects, spectroscopy and frequency-modulated continuous-wave LiDAR, yet chip-scale sources rarely combine broad wavelength coverage, nanosecond switching, high spectral purity and stable high-power operation. Here we demonstrate a frequency-agile hybrid external-cavity laser enabled by the Pockels effect in thin-film lead zirconate titanate (PZT). The strong linear electro-optic response of PZT provides direct, non-thermal tuning of compact microring resonators with a wavelength-tuning efficiency of 17 pm/V. In contrast to conventional anisotropic Pockels materials, the near-isotropic in-plane electro-optic behaviour of thin-film PZT relaxes crystal-axis layout constraints, allowing efficient Vernier wavelength selection in compact ring cavities. The PZT resonators also show no measurable photorefractive resonance distortion and no resolvable DC-bias drift during operation, preserving stable wavelength-selective feedback. The demonstrated laser achieves an 82 nm tuning range, a 5 mW fiber-coupled output power, a side-mode suppression ratio (SMSR) exceeding 56.7 dB, and a wavelength-switching time of 5.5 ns. These results establish thin-film PZT photonics as a powerful electro-optic platform for compact, high-power, and frequency-agile integrated laser sources.

Neutrino oscillation experiments provide a unique probe to search for the physics beyond the Standard Model. In this work, we search for a broad class of anomaly-free flavor-dependent $U(1)^\prime$ symmetries using atmospheric neutrino data for the first time. Gauging these $U(1)^\prime$ symmetries give rise to ultra-light vector gauge bosons mediating long-range interactions (LRI) of neutrinos. These new interactions are sourced by the matter present in local and distant Universe, which can affect oscillations of neutrinos passing through the Earth. We use 8 years of high-purity $\nu_\mu$ charged-current neutrino events from IceCube DeepCore to search for these new interactions. We find no evidence for such new interactions in the data sample and place stringent constraints on the corresponding LRI potentials. These results are also translated as the bounds on the coupling strength and mass of mediator over their wide ranges for a plethora of $U(1)^\prime$ symmetries.

Modeling high-dimensional data is challenging, yet essential to understanding many complex systems. Maximum entropy models such as Ising and Potts models have been used extensively to capture pairwise interactions from correlation patterns in data, allowing to infer graphical representations of complex systems from observations (e.g., from protein sequences or neural population activity). Recently, there has been growing interest in modeling higher-order correlation patterns involving simultaneously three or more variables. While progress has been made in binary data with high-order Ising models, we extend this framework to the more general case of discrete data. We introduce q-state spin models, a complete family of maximum entropy models that generalize the vector Potts model to include long-range and arbitrary high-order interactions. In the pairwise case, our models allow for more diverse interaction types compared to the standard vector Potts model. We discuss their statistical interpretation with examples and relate them to discrete Fourier analysis. Using a loop expansion of the partition function, we show that the statistical properties of spin models are fully captured by the algebraic structure of their interactions. We define gauge transformations under which this structure, and thus the partition function, remains invariant. Models equivalent under gauge transformations can be seen as different representations of the same abstract statistical model, despite generally having interactions of different orders, extending results from the binary case. For practical application to data analysis, we focus on a subset of models known in the binary case as Minimally Complex Models, generalizing them to discrete data. We obtain a closed-form expression for the marginal likelihood of these models, enabling fast model selection. We illustrate their use with simple real-world examples.

Silicon pixel detectors are widely used in high-energy physics experiments as tracking detectors close to the primary interaction vertex. They provide excellent space-point resolution together with fast electronic readout. Many of them employ only digital (binary) readout which makes the applicability of centre-of-gravity algorithms less obvious. Charge sharing between neighboring pixels improves the resolution beyond the single-pixel limit, but in practice there is a lack of quantitative understanding of the achievable gains. This work provides a simplified analytical and numerical model with which the maximum improvement achievable through charge sharing is quantified for both one and two-dimensional pixel geometries. A phenomenological parameterisation of the resolution as a function of the average cluster size is derived and compared to experimental data from several detector technologies.

Muography is a non-invasive imaging technique that uses cosmic-ray muons, commonly divided into transmission (absorption) and scattering muography. For transmission muography, the inversion algorithm critically determines reconstruction quality. However, widely used schemes may produce smearing artifacts when measurement locations are limited and data are sparse. We develop an optimized Metropolis–Hastings (M–H) algorithm that mitigates smearing and retrieves sharper, more accurate density distributions without auxiliary data. Additionally, we implement an inverse distance weighting (IDW) approach to reconstruct the air–rock interface from muon measurements. The optimized M–H algorithm is applied in Monte Carlo simulations and applied to field data from the TianQin Tunnel experiment using the MuGrid-v2 detector. The IDW-reconstructed air–rock interface is validated against Light Detection and Ranging (LiDAR) measurements. In simulations, the optimized M–H algorithm improves high-density anomaly detection precision from $42\%$ to $100\%$ at threshold $5.1\,\mathrm{g/cm^3}$, with gains of $6\%$ to $42\%$ across other threshold and low-density scenarios, together with the TianQin Tunnel reconstructions, these results demonstrate the effectiveness of the proposed approach.

The fascia lata plays a central role in force transmission and body mechanics, yet its in vivo mechanical behavior remains poorly characterized. Existing approaches – shear wave elastography and direct force measurements alike – share a fundamental limitation: none simultaneously captures both the elastic and viscous components of fascial mechanics within a single experiment. The primary aim of this study is therefore to develop an experimental and modeling framework that enables the reproducible measurement of the effective viscoelastic properties of the fascia lata in vivo. To this end, we combine controlled ramp-relaxation experiments on the human fascia lata with a constitutive model that integrates fiber recruitment and dual-timescale viscoelastic relaxation. We emphasize that this is an effective model: rather than describing intrinsic local material properties, it characterizes the mechanical response of the fascia lata complex including its coupling to the hip-thigh musculoskeletal system under controlled loading conditions. The model captures both the nonlinear stiffening during elongation and the dual decay of force during relaxation, using a minimal set of physically interpretable parameters. Repeated trials demonstrate good reproducibility, with parameter variability within 10%. Our results support the view that fascia lata behaves as a hierarchical, hydrated composite whose macroscopic mechanical response emerges from the coupled effects of collagen alignment, matrix viscoelasticity, and fluid flow. This work provides a quantitative foundation for future in vivo investigations into how training, rehabilitation, or aging influence the evolution of fascial mechanical properties.

We review the definitions of 22 parameters of a multiport antenna array operating in a specified direction: 4 excitation-dependent parameters for emission, 10 excitation-independent parameters for emission, and 8 parameters for reception. We concisely set forth their main properties. As examples, we compute and discuss these parameters in the cases of two simple 6-port antenna arrays made of parallel dipole antennas. We investigate the effect of a change of variable describing the excitation during emission. This allows us to find an “invariance under a change of excitation variable”, and to compare some of the parameters with the ones used by other authors. We study passive linear embeddings of the MAA ports, to reveal an “invariance under an invertible lossless linear embedding”.

This manuscript describes the establishment of a local production line for 10 cm x 10 cm Gas Electron Multiplier (GEM) foils at the Forschungs- und Technologiezentrum Detektorphysik (FTD) at the university of Bonn. GEM foils are widely used in modern gaseous detectors, providing high-gain signal amplification and high-rate capability. Our fabrication process utilizes a double-mask photolithographic technique on 50 $\mu$m polyimide cladded on both sides with 5 $\mu$m copper. The chemical etching procedure that is required to achieve uniform hole geometries with outer hole diameters of 70 $\mu$m and inner hole diameters of 50 $\mu$m will be described. Quality control protocols, including semi-automated optical inspection and high-voltage leakage current tests, demonstrate that foils produced at our facility achieve uniform hole size distributions and leakage currents of less than 1 nA at 600 V in air with no discharge hotspots. These results confirm that the production chain is capable of delivering high-performance foils suitable for research and development purposes.

Three-dimensional (3D) assemblies of gold nanoparticles (AuNPs) offer a rich platform for plasmonic coupling and near-field engineering, yet their optical behavior is often complex due to structural disorder and fabrication-induced variability. Here, we present a systematic optical investigation of large-scale 3D AuNP assemblies fabricated via meniscus-guided assembly, focusing on the reproducibility and spatial uniformity. Spatially-resolved dark-field scattering measurements reveal that high-aspect-ratio AuNP pillars exhibit uniform scattering spectra along their height and across different pillars, despite variations in geometry and structure. Electromagnetic simulations suggest that this robustness arises from an ensemble-averaged plasmonic response governed by many local coupling regions within a finite plasmon delocalization length. Simulated near-field and surface charge distributions suggest that the broad ensemble response remains spatially distributed under representative structural perturbations, consistent with volumetric averaging. Building on this robust platform, we introduce compositional modulation through a core-satellite architecture by incorporating smaller AuNPs. This yields a composition-dependent spectral redistribution, including an additional long-wavelength spectral feature in the core-satellite assemblies. Wavelength-dependent surface-enhanced Raman scattering measurements reveal contrasting responses under 633 and 785 nm excitation, reflecting redistribution of local plasmonic coupling pathways. These results establish design principles for robust 3D plasmonic nanoparticle assemblies with ensemble-averaged and composition-tunable optical responses.

A low-order Galerkin model is developed for a rotating fluid annulus driven by localized heating at the outer bottom periphery, with uniform cooling at the inner cylindrical wall. The model retains the full cylindrical geometry and employs Bessel-function radial eigenfunctions satisfying physically correct Dirichlet-Neumann boundary conditions. A dual-series least-squares procedure determines the conductive base state under the mixed thermal boundary condition. Galerkin projection onto the leading radial and vertical basis functions yields a 10-variable dynamical system governing the mean meridional overturning, thermal wind, baroclinic wave amplitudes, and their nonlinear interactions. Linear stability analysis yields explicit critical Rayleigh numbers for both mean and wave instabilities, showing that rotation raises Ra_c in proportion to T^2. The model reproduces the Nu ~ Ra^(1/4) scaling, rotational suppression at low Ra, and the boundary-layer-dominated flow structure observed in companion axisymmetric simulations.

The ionization mechanisms of small H$_2$O/D$_2$O clusters embedded in helium nanodroplets (HNDs) irradiated with extreme ultraviolet photons of energy $h\nu$ = 21.6 eV are investigated using Penning ionization electron-ion coincidence spectroscopy. Both protonated (H$_2$O)$_{n-1}$H$^{+}$/(D$_2$O)$_{n-1}$D$^{+}$ ($n$ = 3-6) and unprotonated (H$_2$O)$_{n}$$^{+}$/(D$_2$O)$_{n}$$^{+}$ ($n$ = 2-5) cluster ions were observed. Penning ionization electron spectra measured in coincidence with water cluster ions emitted from water clusters doped into both large and small HNDs are analyzed and compared with photoelectron-photoion coincidence spectra measured for free water clusters at $h\nu$ =20.6 eV. The results reveal suppression of fragmentation inside HNDs and stabilization of intact cluster ions. Quantum chemical calculations support the coexistence of proton-transferred and hemibonded conformers under the cryogenic conditions of helium nanodroplets.

We investigate the linear stability of a rotating fluid annulus subjected to localized heating at the outer periphery of the bottom surface and uniform cooling at the inner cylindrical wall through a rigorous stability analysis. The localized forcing generates a non-axisymmetric base state, invalidating the classical normal-mode decomposition. We employ Floquet-Bloch theory in the azimuthal coordinate combined with a BiGlobal eigenvalue formulation in the meridional plane. The non-axisymmetric base state is expanded in azimuthal Fourier harmonics; perturbations are expressed as quasi-periodic Bloch modes that couple all azimuthal wavenumbers through base-state harmonics. Full linearised perturbation equations, the BiGlobal block-operator structure, pressure elimination, solenoidal projection, and the modal energy budget are derived. Instability is driven by cross-modal baroclinic energy release and shear production - mechanisms absent in classical axisymmetric theory.

A nonlinear equation for dust drift waves is derived assuming two-dimensional propagation and ignoring the role of dust acoustic waves. Both the nonlinear dust density term and the dust vorticity term are taken into account. If vorticity term is ignored, the equation gives two dimensional solitary waves and if density nonlinearity effect is discarded, then it reduces to Hasegawa-Mima equation for dust drift waves which admits dipole vortex solutions.

We propose a reduced asymptotic model for the mutual interaction between a weakly nonlinear surface gravity wave field and a slowly evolving incompressible current in a homogeneous rotating fluid. The formulation builds on the Craik-Leibovich theory for the wave-averaged momentum equation, but the Stokes drift is not prescribed externally. Instead, it is determined by a companion amplitude equation for a narrow-band wave field concentrated near the wavenumber circle associated with a prescribed carrier frequency. The derivation combines a multiple-time-scale expansion in wave steepness with a phenomenological closure that neglects quartic wave-wave interactions while retaining the third-order Stokes correction. Importantly, no spatial-scale separation is imposed on the wave-current interaction, allowing the wave equation to represent current-induced advection, refraction, and multidirectional scattering. The resulting equations conserve wave action and admit closed energy and momentum budgets for the coupled wave-current system. The model thus provides a tractable bidirectional extension of the classical Craik-Leibovich framework for regimes in which current-induced wave evolution feeds back significantly on the mean flow.

We have demonstrated highly-sensitive photon counting in the infrared based on the two-photon absorption (2PA) in a silicon avalanche photodiode, where the required photon energy for inducing effective conductivity was provided by an intense mid-infrared (MIR) field at 3 $\mu$m. The used MIR pumping scheme could not only benefit from the enhanced 2PA coefficient in the non-degenerate regime, but also eliminate the detrimental background noises due to the pump harmonic excitation of the pump. Consequently, the enhancement factor for the signal counting rate unprecedented reached to about $10^{5}$ with input infrared pulses at the femtojoule level. Additionally, the noise equivalent power was substantially improved by two orders of magnitude comparing to conventional schemes with near-infrared pumping. Therefore, the presented configuration might provide an alternative to realize sensitive infrared detection and imaging with desirable features of room-temperature operation, no phase-matching requirement, and broadband responding window, which would find a variety of applications including remote ranging, sensitive sensing, biochemical imaging, and trace spectroscopy.

We report a passive stabilization of the repetition rate for a mode-locked fiber laser by using an electro-optic modulator in a phase-biased nonlinear amplifying loop mirror. The underlying mechanism, in contrast to active feedback operations, lies in the cross-phase modulation between electrical and optical pulses within an electro-optic crystal. The resulting spectral shift can automatically compensate the cavity-length drift via the group velocity dispersion. Consequently, the artificial actuator enables to obtain a capture range up to 2.3 mm, much longer than that achieved by index changes of the modulator. A robust and tight locking for the repetition rate is then realized with a standard deviation as low as 9 $\mu$Hz with a 1-s sample time over 11 hours, corresponding to a fractional instability of 4.3$\times$10$^{-13}$. Furthermore, a dynamic optical sampling by repetition-rate tuning has been manifested with a fast refresh rate at 100 kHz and a broad scanning range over 305 ps. The demonstrated passive servo action may provide a simple yet effective way to stabilize the repetition rate with high precision, large bandwidth and wide tunability.

Frequency upconversion technique, where the infrared signal is nonlinearly translated into the visible band to leverage the silicon sensors, offers a promising alternation for the mid-infrared (MIR) imaging. However, the intrinsic field of view (FOV) is typically limited by the phase-matching condition, thus imposing a remaining challenge to promote subsequent applications. Here, we demonstrate a wide-field upconversion imaging based on the aperiodic quasi-phase-matching configuration. The acceptance angle is significantly expanded to about 30$^\circ$, over tenfold larger than that with the periodical poling crystal. The extended FOV is realized in one shot without the need of parameter scanning or post-processing. Consequently, a fast snapshot allows to facilitate high-speed imaging at a frame rate up to 216 kHz. Alternatively, single-photon imaging at room temperature is permitted due to the substantially suppressed background noise by the spectro-temporal filtering. Furthermore, we have implemented high-resolution time-of-flight 3D imaging based on the picosecond optical gating. These presented MIR imaging features with wide field, fast speed, and high sensitivity might stimulate immediate applications, such as non-destructive defect inspection, in-vivo biomedical examination, and high-speed volumetric tomography.

Optimizing energy conversion in active matter remains a central challenge in nonequilibrium physics. Here, we develop a unified thermodynamic framework that characterizes the finite-time performance of interacting active machines. We show that cyclic work admits a geometric decomposition into an antisymmetric thermodynamic curvature, governing work extraction, and a symmetric metric, controlling dissipation. Minimal-dissipation protocols follow geodesics in parameter space, while optimal work extraction deviates from them due to a curvature-induced, Lorentz-like effect. This geometric structure directly determines the finite-time scaling of work and dissipation, enabling a mapping onto Onsager-type quasi-linear current–force relations. We show that both the maximal efficiency and the efficiency at maximum power are governed by an asymmetry parameter and a figure of merit, establishing a formal correspondence between active machines and thermoelectric devices with broken time-reversal symmetry. Our results reveal a fundamental geometric origin of energy-conversion performance and provide a general framework for optimizing active machines.

We theoretically and numerically investigate the formation of soliton crystals in Kerr microresonators in the presence of an avoided mode crossing (AMX). Our study combines dynamical simulations based on a modified Lugiato-Lefever equation (LLE) with a stability analysis of its stationary solutions. We show that, depending on its strength and spectral position, the AMX can either stabilize otherwise unstable soliton crystals or induce Turing patterns which subsequently seeds soliton crystal formation. Both perfect and imperfect soliton crystals can form below the pump threshold for spatiotemporal chaos, and we identify the conditions required for perfect crystals. Finally, we investigate modulation instability in the presence of an AMX, showing that it modifies the parametric gain and can suppress or promote Turing pattern formation depending on its spectral position.

Organic crystal structure prediction (CSP) is a requirement for computational modelling of organic solids, but traditionally costs several CPU-years per molecule. Generative models such as OXtal dramatically reduce this cost by sampling stable organic crystal structures directly. However, OXtal forgoes explicit lattice parametrization in favour of modelling large crops of the bulk material with expensive triangle layers, which can incur a computational cost of minutes per molecule. In this paper, we reduce this to seconds with Clari, a large-scale flow matching model that generates redundancy-free unit cells and replaces triangle layers with pure pair-bias attention. Clari requires only atom types and bonds as input and does not need an RDKit-sanitizable input molecule, which expands its applicability to challenging chemistries such as fullerenes, metal complexes, and atom clusters. We further ablate key design choices such as auxiliary losses, timestep distributions, noise priors, and self-conditioning. On OXtal's test sets, we surpass OXtal's solve rate while obtaining a speedup of $15$-$30\times$. Because Clari also models explicit hydrogens, it supports inference-time scaling via direct energy ranking, without any decoration or relaxation step. When generating 150 crystals and selecting the top-30 by energy, we further improve solve rate while maintaining a speedup of $5$-$8\times$. We also introduce the CSD Teaching Subset as a new test split of diverse and complex molecules for future benchmarking. Our contributions enable CSP within seconds, making large-scale virtual screening of organic solids practical. Code is available at https://github.com/aspuru-guzik-group/clari.

The stochastic incompressible Navier-Stokes equations on $\TT^3$, completed by the fluctuation-dissipation noise, have a Fokker-Planck generator that decomposes into a self-adjoint Ornstein-Uhlenbeck (dissipative) part and an antisymmetric (convective) part. We prove two results about this generator. First, the logarithmic Sobolev inequality holds with the same optimal constant as the pure Ornstein-Uhlenbeck operator, $c_\mathrm{LSI} = \nu\lambda_1$ (where $\nu$ is the viscosity and $\lambda_1$ is the smallest nonzero eigenvalue of the Laplacian on $\TT^3$), independent of the number of retained Fourier modes. Second, the full semigroup is hypercontractive with the same rate as the Ornstein-Uhlenbeck semigroup. Both results follow from a single structural property: the convective generator is antisymmetric in $L^2(P_\mathrm{eq})$ (where $P_\mathrm{eq}$ is the Gibbs measure), and therefore contributes nothing to the Dirichlet form or the $L^q$ norm evolution. The antisymmetry is a consequence of two properties of the incompressible Navier-Stokes nonlinearity: energy conservation and phase-space volume preservation (the Liouville property). These are the same properties that underpin the fluctuation-dissipation theorem for the nonlinear Navier-Stokes equations.

Multiheme cytochromes, located on the bacterial cell surface, function as long-distance (> 10 nm) electron conduits linking intracellular reactions to external surfaces. This extracellular electron transfer process, which allows microorganisms to gain energy by respiring solid redox-active minerals, also facilitates the wiring of cells to electrodes. While recent studies suggested that a chiral induced spin selectivity effect is linked to efficient electron transmission through biomolecules, this phenomenon has not been investigated in the extracellular electron conduits. Using magnetic conductive probe atomic force microscopy, Hall voltage measurements, and spin-dependent electrochemistry of the decaheme cytochromes MtrF and OmcA from the metal-reducing bacterium Shewanella oneidensis MR-1, we show that electron transport through these extracellular conduits is spin-selective. Our study has implications for understanding how spin-dependent interactions and magnetic fields may control electron transport across biotic-abiotic interfaces in both natural and biotechnological systems. Electron