Papers

We present a simplified formalism for predicting infrared optical constants from first-principles calculations. Addressing limitations of the widely used four-parameter semi-quantum Lorentz model, the proposed approach bridges the gap between the harmonic three-parameter model and full self-energy-based methods. By incorporating essential anharmonic effects including four-phonon scattering and phonon renormalisation, the model provides an efficient and accurate alternative while maintaining low computational cost. The frequency-dependent refractive indices of MgO and rutile TiO$_2$ are computed and compared with experimental data, demonstrating good quantitative agreement. The framework offers a practical approach for predicting optical properties of materials across a wide range of materials.

Hard X-ray ptychography has become increasingly essential in both the life and physical sciences. However, pushing resolution down to a few nanometres often requires highly customized, chromatic diffractive or refractive X-ray nanofocusing optics, significantly limiting the practical broadband energy-scan applications. Here, we present the first known hard X-ray ptychographic imaging with a half-pitch resolution below 8 nm using total-reflection Advanced Kirkpatrick-Baez (AKB) mirror nanofocusing optics at the high energy photon source (HEPS), with clear potential for further extension. Despite leveraging the benefits of enhanced instrumentation, such as the high coherent flux of 4th-generation diffraction-limited storage rings (DLSR), state-of-the-art beamline X-ray optics and detectors, this is made possible by developing a reconstruction algorithm termed Generalized Wirtinger Projections (GWP). We derive the theory of GWP and experimentally demonstrate its capability for improved partial-coherence reconstruction and enhanced spatial resolution over conventional methods through imaging experiments on a Siemens star test chart at 12.4 keV. GWP provides a highly compact framework for jointly accounting for multiple coupled uncertainties that degrade resolution, enabling straightforward extension to other imaging modalities, such as burst ptychography, while delivering nearly an order-of-magnitude improvement in GPU memory efficiency. Furthermore, the ability to combine nanometre-scale spatial resolution with the inherently achromatic nanofocusing optics demonstrated in this work potentially opens new opportunities for in situ or operando broadband, energy-scan 3D spectroscopic imaging with element- or chemical-state specificity in complex environments at the nanoscale, holding significant promise for a wide range of applications from electronics and energy science to neuroscience.

Cable bacteria are multicellular bacteria capable of centimeter-scale conduction through a regular fiber network embedded in their cell envelope. The conductivity of these fibers is extremely high for biological materials, and rivals that of the best synthetic conductive polymers, but the underlying electron transport mechanism remains elusive. Recent microscopic and spectroscopic evidence indicates that each fiber embeds a bundle of intertwined nanoribbons as the conductive conduit. Each nanoribbon consists of a one-dimensional nickel-organic framework, built from stacked nickel bis(1,2-dithiolene) oligomers (NiBiD units) as molecular building blocks. Here we performed DFT calculations of nanoribbon model structures, in order to characterize their electronic properties, examine potential stacking configurations and verify whether these structures can support efficient conductance. Our simulations indicate that nanoribbons are comprised of tightly stacked AA or AB-type packings of NiBiD units. In the most energetically stable structure (AB-type) some Ni centers are predicted to be 5-fold coordinated due to formation of an inter-layer Ni-S coordination bond. In several energetically low-lying structures, the electronic coupling between neighboring molecules exceeds the critical threshold for charge delocalization permitting efficient charge transport beyond small polaron hopping. Our results hence reveal that nanoribbons based on NiBiD units exhibit favorable charge transfer properties that may explain the unusually high conductivities measured in the fibers of cable bacteria.

Machine learning and computational inference, coupled with experimental data, promise to significantly accelerate our rate of learning in most scientific disciplines. In this study, we develop tools that connect microscopic observations to macroscopic device behaviour, a capability that is essential for accelerating the design of durable energy materials. To this end, we introduce a novel approach that integrates photoluminescence imaging with drift diffusion simulations to understand operation and degradation in fully fabricated perovskite solar cells. By employing Bayesian inference, we generate "inferred maps" of parameters that govern recombination processes present in devices. We track these parameter maps while the devices are aged (70 {\deg}C, full spectrum sunlight) to analyse their temporal evolution during degradation. Notably, our approach allows us to distinguish between degradation occurring at the hole or electron transporting layer interface, or within the bulk. Our analysis reveals pronounced spatially non-uniform degradation, with significant macroscopic heterogeneity observed in the optoelectronic parameter maps. We pinpoint the greatest degradation observed in specific regions to stem from the perovskite/transport layer interfaces. Finally, we demonstrate that an amino-silane molecular passivation treatment suppresses this degradation, highlighting its specific role in enhancing device stability. Our approach offers valuable insights for future device fabrication and is a clear exemplification of how advanced Bayesian inference can significantly increase the value of experimental data.

We present a magnetic torsional pendulum that provides a unified experimental platform for investigating forced resonance, parametric resonance, and degenerate parametric amplification in the undergraduate laboratory. The system consists of a permanent magnet suspended by thin wires and driven by externally applied magnetic fields generated by Helmholtz coils. By independently controlling a direct driving field and a periodically modulated bias field, the apparatus can realize ordinary forced oscillations, parametric excitation, and phase-sensitive parametric amplification within the same physical system. A miniature wireless gyroscope embedded in the pendulum bob enables direct measurement of the angular velocity and provides convenient real-time acquisition of quantitative dynamical data. A unified equation of motion is derived to describe all three operating regimes. Experimental studies of forced resonance, parametric resonance, and phase-sensitive parametric amplification are compared with theoretical predictions and numerical simulations. The measurements reproduce the characteristic features of all three phenomena and illustrate the influence of nonlinear effects on the system dynamics. The apparatus combines a simple mechanical design, low-cost instrumentation, and highly visible motion. By allowing direct comparison of different resonance mechanisms and their underlying energy-transfer processes,, it provides an accessible platform for studying oscillation theory, nonlinear dynamics, and parametric phenomena in advanced undergraduate laboratories.

We theoretically investigate the transmission and diffraction of a weak probe field from an electromagnetically induced grating formed in a weakly driven two-level medium coupled to engineered quantum reservoirs. Using a perturbative solution of the optical Bloch equations in the weak-driving regime, we analyze how normal-vacuum, thermal, and broadband squeezed-vacuum environments modify the probe susceptibility and consequently reshape both the spatial transmission function and the far-field diffraction patterns. We show that reservoir statistics have a pronounced impact on the diffraction response by altering the amplitude and phase of the induced grating. Thermal reservoirs enhance the transmission modulation and increase the intensity of the dominant diffraction orders, whereas squeezed-vacuum reservoirs generate strongly phase-sensitive modifications that selectively redistribute optical power among diffraction channels. We further demonstrate that the detuning between the squeezed reservoir and the driving field provides an efficient mechanism for controlling diffraction directionality, leading to substantial amplification of selected angular orders. In two-dimensional geometries, squeezed-vacuum correlations produce highly structured phase landscapes and strongly anisotropic diffraction patterns, enabling directional enhancement of specific diffraction channels while suppressing others. These results establish reservoir engineering as a versatile approach for controlling transmission, diffraction efficiency, and angular selectivity in minimal two-level systems, with potential applications in programmable photonic devices, beam steering, and quantum optical platforms.

In this paper, we present an Intelligent Perception-Assisted Light Modulation (IPALM) technique, for femtosecond laser nanofabrication and particle manipulation. IPALM technique integrates real-time hand-motion recognition with dynamic spatial light modulation to achieve programming-free laser beam control. In contrast to the conventional programmed laser fabrication techniques which need setup a project prior to fabrication, IPALM offers a direct "mind-to-matter" pathway for laser nanostructuring and biological cells handling with high flexibility and multiple degree of freedom. In nanofabrication, IPALM provides high resolution with feature dimensions down to 280 nm. By mind-driven hand gesture control, the laser beam is regulated to enable direct writing of micro/nanostructures with a minimum feature size down to 280 nm via IPALM. In precise particle manipulation, multiple cells can be simultaneously moved to achieve cell coalescence. With these examples, IPALM showcases its potential for applications in photonics, biomedicine, and microfluidics, for high-dimension and flexible laser applications.

Bacteria live in environments that are constantly changing. To survive, they rely on different motility systems that let them move, explore, and interact with their surroundings. These motility systems not only control the movement of individual cells but also give rise to collective behaviors such as coordinated spreading, cooperative predation, and multicellular development. Understanding these processes requires not only a description of the underlying molecular machines, but also quantitative observations spanning single-cell behavior and collective dynamics. Imaging approaches now make it possible to follow motility across scales, from molecular machines to bacterial communities, while computational analyses extract principles that link mechanisms to emergent dynamics. By combining molecular, behavioral, imaging, and analytical perspectives, this review provides an integrated view of bacterial motility that links single-cell behavior to community-level dynamics across scales.

TNM staging is essential for lung cancer management, but patients within the same anatomic stage often show heterogeneous survival outcomes. We developed a multimodal adaptive risk score (AMRS) that integrates radiology-report semantics with routinely available clinical laboratory biomarkers. In a retrospective two-center cohort, 1129 patients diagnosed between December 2017 and February 2026 were screened; 574 patients were included after exclusion for short follow-up or missing imaging reports and were split into training (n = 459) and test (n = 115) cohorts. Radiology reports were encoded with a domain-adapted MC-BERT branch to capture imaging-derived semantic information, while clinical and laboratory variables were modeled after Mahalanobis-distance-based imputation using random survival forests. Weighted risk fusion generated the final patient-level score. AMRS achieved C-index values of 0.920 in training and 0.849 in testing, and separated survival trajectories across clinical subgroups and TNM-related strata. SHAP analysis identified hematologic, inflammatory, coagulation, nutritional, tumor-marker, organ-function, and age-related contributors. AMRS may complement TNM staging in imaging-centered oncology workflows, but prospective validation, calibration, ablation testing, and clinical-utility assessment are required before deployment.

This short article - commissioned as part of the Quantum Flagship project OpenSuperQPlus - introduces the topic of fair access to quantum computing time and argues for its relevance in current European technology policy debates. Choices about access we make today affect which applications of quantum computing are developed in the future, and by whom. Among the issues at stake are: Europe's technological autonomy and sovereignty; Europe's future economic competitiveness; knowledge security and the future of open science; and delivering upon the EU's founding values and aims. The results of a survey of OpenSuperQPlus researchers reveal prevalent contractualist and transactional framings of access to European quantum computing capacity among those developing the technology. The article concludes with a call to go beyond framing access to quantum computing as a zero-sum-game, and to explore the possibility of an access regime premised on openness and solidarity.

Helical plasma plumes generated in pulsed radiofrequency atmospheric pressure plasma jets exhibit unique flow dynamics arising from the coupling between Kelvin-Helmholtz instabilities and baroclinic torque. While the fundamental mechanism responsible for helical plume formation has been established, the implications of this morphology for plasma-target interaction remain largely unexplored. In this study, we experimentally investigate the interaction area of helical plasma plumes with different target configurations and compare it with the conventional conical plume produced under continuous RF excitation. High-speed imaging reveals that the helical plume significantly enlarges the effective plasma-target interaction region due to its rotating trajectory and enhanced air entrainment. The effect of different target materials and boundary conditions, including dielectric surfaces and metal-backed substrates, is systematically examined. The results demonstrate that helical plumes provide superior surface coverage, improved spatial distribution of reactive species, and enhanced plasma-surface coupling. These findings highlight the advantages of helical plasma jets for applications requiring large-area plasma treatment, including plasma medicine, surface modification, and plasma-liquid interactions.

Specific heat treatments applied to superconducting radiofrequency (SRF) cavities, such as nitrogen infusion or Mid T baking, aim to improve the quality factor (Qo) at medium accelerating fields (10 to 20 MV/m). These treatments reduce the BCS surface resistance by tuning the mean free path of niobium over a few hundred na-nometers, either by diffusing oxygen from the native oxide layer or by diffusing nitrogen after the dissolution of the oxide layer. However, these treatments preclude the usual chemical polishing, as it would reverse the beneficial effects of the heat treatments, making the cavities highly sensitive to surface contamination. In particular, the formation of niobium carbides, which can mask the expected benefits, strongly depends on the annealing conditions, surface preparation, and the materials history. To better understand these phenomena, niobium samples was annealed under ultrahigh vacuum (Mid T baking) with Ar/O2 plasma treatment to investi-gate surface contamination with insitu heat treatment at 500 C and XPS analysis.

An impedance model for the cathode catalyst layer (CCL) in a PEM fuel cell demonstrates that in-phase harmonic perturbations to the cell current density and CCL temperature lower both CCL impedance and static resistivity. This mitigation is primarily driven by the oscillating exchange current density of the oxygen reduction reaction.

Plasmonic metasurface-driven Optical Solar Reflectors (m-OSRs) offer a promising route towards lightweight and high-performance thermal management. By exploiting subwavelength structuring and intrinsic material losses, such systems enable tailored absorptance spectrum across the solar and thermal infrared domains, respectively. Here, a plasmonic m-OSR composed of an aluminum back-reflector, a silicon dioxide dielectric spacer, and a nanostructured aluminum-doped zinc oxide (AZO) layer is investigated. The optical response of the structure is governed by the interplay between reflection, localized surface plasmon resonances and Fabry-Perot cavity effects, leading to efficient spectral selectivity. An optimization performed with a multi-objective genetic algorithm yields a low solar absorptance of alpha = 0.16 combined with a high thermal emissivity of epsilon = 0.83, providing an alpha/epsilon ratio of 0.19. These results highlight the potential of plasmonic meta-OSRs as ultrathin, high-performance solutions for thermal management and in particular for the next-generation advanced spacecraft.

We design the first neural quantum state for continuum particles that, for any chosen allowed momentum $\mathbf{k}$, is by construction an exact eigenstate of total momentum with eigenvalue $\mathbf{k}$. Our architecture, EVE, enables off-the-shelf VMC to solve for momentum-sector ground states. We test EVE on 2D bosons with mutual $1/r$ interactions, finding that a single unified ansatz is capable of describing four qualitatively different states: superfluid, roton, crystal, and phonon. At different densities, we extract the underlying phase of matter from the dispersion's shape. At $r_s = 20.0$, we see the roton minimum at finite $k$ expected of a superfluid. At $r_s = 100.0$, we see striking zone folding indicative of crystalline order, with periodically spaced minima representing floating crystals connected by phonon arcs in between. Using density-density correlation functions, we confirm the phase diagnoses and probe the excitations' correlation structures. Finally, we analyze the roton's phase texture and find unexpected multi-particle phase strings, formed when several vortex dipoles merge, leaving two vortices connected by a phase slip.

Using the Keldysh non-equilibrium Green's function approach, we investigate charge pumping through a single-stranded helical structure described by a tight-binding model that includes either short-range hopping (SRH) or long-range hopping (LRH). While quantum pumping has been studied in various low-dimensional systems, the detailed behavior of the spectral current and the pumped dc current in helical geometries in the presence of higher-order electron hopping (beyond nearest neighbors) has not yet been systematically explored. Here, we focus on the interplay between helicity and extended hopping ranges, analyzing how they jointly control the energy-resolved and dc pumped currents under time-periodic end potentials. For LRH, the pumped dc current exhibits pronounced plateau-like regions as a function of chemical potential when energy levels are sparsely spaced – consistent with adiabatic transport – whereas SRH yields more parameter-sensitive currents without clear plateaus. The plateau stability is controlled by the drive frequency: at higher frequencies, Floquet side-band mixing destroys the plateaus, leading to oscillatory currents. The phase dependence remains nearly sinusoidal, and the current vanishes at zero phase lag, confirming the necessity of out-of-phase potentials. Crucially, in helical systems, the decay exponent $(\ell_c)$ acts as an effective structural parameter that can tune both the magnitude and sign of the pumped current, offering a geometric knob for controlling quantum pumping. Our findings not only fill a gap in the understanding of spectral and pumped currents in helical systems with extended hopping but also provide tools that can be applied to analyze similar phenomena in other chiral or quasi-one-dimensional systems.

We study the controllability of a system of qubits under global control, where control pulses act identically on all qubits. Specifically, we consider a collection of qubits identically coupled to a single bosonic mode, or harmonic oscillator, via the Jaynes-Cummings interaction. This collective coupling, known as the Tavis-Cummings (TC) interaction, has been realized in several quantum computing platforms, including superconducting and atomic qubit systems. Although the qubits do not interact directly with one another, they can become entangled through their common coupling to the bosonic mode. We characterize the group of unitaries that can be implemented on the joint Hilbert space of the qubits and bosonic mode using the TC interaction together with a global $z$ field $J_z$, corresponding to identical z rotations on all qubits. We show that for n>2 qubits the set of realizable unitaries is restricted by an "accidental" symmetry of the TC Hamiltonian, distinct from its "standard" U(1) and permutational symmetries. On the other hand, we find that the Hamiltonian $J_z^2$ breaks this accidental symmetry and, together with the TC interaction and $J_z$, achieves semi-universality: it allows the implementation of arbitrary unitaries that respect permutational and U(1) symmetry, up to certain constraints on the center of the group. In a companion paper, we further analyze this remarkable accidental symmetry and show that it can be understood through Schwinger's bosonic model of angular momentum.

Owing to inertial effects, the flow through a three-dimensional curved duct focuses finite-sized spherical particles in the two-dimensional cross-section onto either stable equilibrium points or limit cycles. This hydrodynamic inertial focusing underpins various biomedical and industrial applications for size-based particle and cell sorting. Departing from conventional particle separation in the channel cross-section, we instead focus on particle separation in the primary flow direction, i.e., longitudinal separation. We consider a duct with an elliptical centreline and a tall rectangular cross-section. For a given particle size, the nature of the cross-sectional equilibrium points depends on the local radius of curvature of the duct, and a periodical variation of the radius of curvature can result in a periodical bifurcation behaviour along its length. In particular, a duct geometry that undergoes a periodically varying saddle-node infinite-period (SNIPER) bifurcation can be used to improve longitudinal, at the expense of cross-sectional, particle clustering. For sufficiently large particles, this longitudinal clustering weakens at higher Reynolds numbers and with decreasing eccentricity, in contrast to small particles whose longitudinal clustering remains unaffected across a wide range of geometric configurations and flow conditions. Then, ducts with smaller eccentricities enable simultaneous separation along both the flow direction and the cross-section. In contrast, for larger eccentricities, the emergence of a SNIPER bifurcation promotes more pronounced longitudinal separation while compromising cross-sectional separation. These preliminary findings suggest that elliptically wound microfluidic devices might be used for longitudinal separation of particles by size, with potential biomedical and industrial applications.

Omnidirectional flat-band resonances, characterized by an enhanced photonic density of states and inherent angular robustness, are highly sought-after in integrated nanophotonic devices, particularly when integrated with chiral functionality. Here we realize such resonances in a nonlocal silicon membrane metasurface patterned with periodic square-lattice air-hole arrays. Increasing the lattice period not only compresses the Brillouin zone but, crucially, weakens the evanescent coupling between neighbouring Bloch modes associated with the same-order guided resonances. Driven by the tight-binding model in the limit of weak inter-unit-cell coupling, the pronounced band flattening of the degenerate guided resonance along both $k_{x}$ and $k_{y}$ yields, giving rise to an omnidirectional flat-band resonance. Remarkably, both numerical simulations and experiments reveal a universal route for endowing flat-band guided resonances with optical chirality through the deliberate breaking of the mirror symmetry of air holes. As a result, the omnidirectional chiral flat-band resonance emerges along both principal in-plane directions, with $Q$-factors exceeding 10$^{3}$ and circular dichroism greater than 0.9 over a wide angular range of $\pm 5^{\circ}$. Nonlinear measurements further show that the resulting resonance not only drives highly efficient third-harmonic generation but also imparts a pronounced spin-selective character to the nonlinear process. Simultaneously, the highly efficient nonlinear process also enables chirality-controlled frequency-upconversion imaging. Our results establish a general paradigm for engineering omnidirectional chiral flat-band resonances in planar silicon platforms, opening new opportunities for nonlinear nanophotonics and chiral imaging.

The merits of thin-film surface acoustic wave (SAW) devices are pivotal to develop the high-performance intermodal acousto-optic modulators. In this work, we have proposed shear-horizontal (SH) SAW resonators for anticipated intermodal acousto-optic modulation on the thin-film lithium niobate platform. Through optimization of the cut angle of LN films, the SAW wavelength, and the thickness of interdigital transducer (IDT) electrodes, the calculated acousto-optic overlap factors utilizing SH0 modes are improved by more than an order of magnitude compared with those of Rayleigh modes. Furthermore, we have fabricated and characterized three kinds of proof-of-principle SH0 mode devices without/with grating reflectors. The electromechanical coupling coefficients (keff^2) and quality factors (Q) in the overtone resonators with grating reflectors are systematically evaluated, featuring the highest Q of 843 with the compromised keff^2 of 0.96%-4.72%. The results reveal that the temperature coefficients of frequency (TCF) of Rayleigh modes vary across various overtones, whereas the SH0 modes exhibit TCFs in the range of 32.3-68.9 ppm/C. Our fabricated SH0-mode overtone resonators demonstrate the capability of operating at power levels up to 29 dBm without electrode damage, offering a promising paradigm for robust and high-efficiency intermodal acousto-optic modulators with potential applications in integrated optical signal processing, microwave photonics,and quantum information technologies.

Here we address the problem of estimating the dimensionality and nature of parametric variation in an unknown generative process directly from time-series data, without specifying or fitting a model. In particular we suppose that inter-instance variation in collections of time series is caused by parametric variation in the generating model. We hypothesize that, given a sufficiently large library of time-series features, low-dimensional parametric variation will manifest as low-dimensional structure in feature space, enabling interpretable estimators of the underlying degrees of freedom to be constructed. We test our hypothesis using a library of over 7000 diverse and interpretable time-series statistics and thirteen simulated systems with known parametric variation, spanning linear stochastic processes, nonlinear oscillators, and chaotic dynamics. Our unsupervised, data-driven approach often reconstructs the underlying parametric variation across this extensive range of simulated dynamical systems while also yielding interpretable estimators for each underlying dimension. Applied to the movement dynamics of 1143 fruit flies, we use this method to extract biologically meaningful components corresponding to sex and circadian rhythmicity. Our results pave the way for much-needed data-driven methods to bridge the gap between interpretable theoretical understanding of dynamics and the large and complex datasets that characterize modern scientific problems.

AI governance for medical imaging is formalizing: the 2026 ACR-SIIM Practice Parameter recommends local acceptance testing and ongoing drift monitoring, and the ACR Assess-AI registry monitors AI outputs using DICOM metadata for context. We argue that a necessary, currently unmonitored layer sits beneath output metrics: whether incoming studies remain within the acquisition envelope a model was validated on. Using a LUNA16-trained MONAI RetinaNet lung-nodule detector, we test whether acquisition state behaves as a structured, measurable variable. On real paired CT differing only in reconstruction kernel (NLST B30f vs B80f), kernel alone shifted AI-measured diameter and flipped a Fleischner size category in 5.2% (8 of 155) of nodules at fixed patient and acquisition, while detection confidence was unchanged (Wilcoxon p=0.22). Under controlled LIDC-IDRI perturbations the effects dissociated by axis: the noise axis degraded detection confidence (p=5.9e-32, concentrated in nodules under 6 mm) but not measurement, while the frequency/kernel axis corrupted measurement (p=8.6e-13) but not detection. A 4-feature pixel fingerprint recovered reconstruction identity (patient-level AUC about 0.95 on real CT, 0.995 on a QIBA phantom) where the ConvolutionKernel DICOM tag was uninformative (identical labels across reconstructions). The kernel axis transported across four manufacturers (leave-one-vendor-out AUC 0.94-0.98, matching the within-vendor ceiling). Acquisition state thus maps to distinct AI failure modes, frequency content to measurement reliability and noise to detection sensitivity, and is not recoverable from metadata. Acquisition-aware, input-side validation is the missing layer for the acceptance-testing and drift-monitoring requirements now entering imaging-AI accreditation.

The Jaynes-Cummings (JC) Hamiltonian is a paradigmatic model of light-matter interaction and, more generally, qubit-boson interactions, widely used across atomic, optical, and superconducting qubit platforms. In the multi-qubit setting, where n qubits are identically coupled to a single boson mode, this interaction is known as the Tavis-Cummings (TC) Hamiltonian. The structure of the TC model is usually understood in terms of two standard symmetries: permutation invariance of the qubits and a U(1) symmetry associated with conservation of the total excitation number. Here we identify an additional, independent "accidental" symmetry of the TC Hamiltonian and construct the corresponding conserved observable. We show that, for n>2 qubits, this symmetry imposes strong constraints on the realizable unitary transformations. These constraints persist in the presence of the global $J_z$ Hamiltonian, but are removed by adding $J_z^2$, even though $J_z^2$ preserves both permutation invariance and the U(1) symmetry. Finally, we explain the origin of this previously unnoticed symmetry using Schwinger's boson representation of angular momentum. These restrictions have important implications for controllability of the TC system and for its applications to quantum computing, which are investigated further in a companion paper.

Proofreading is generally thought to improve accuracy at the expense of speed. We show that this trade-off can be reversed in stochastic processes with long-lived stalled states. Using a non-Markovian renewal framework, we derive exact expressions for the error rate and completion time under proofreading for arbitrary stall-time distributions. Our analysis reveals that fluctuations in stall durations, rather than their mean alone, determine whether proofreading can simultaneously increase speed and accuracy. In the limit of strong stalling, this regime emerges when the coefficient of variation of the stall time exceeds a threshold set by the intrinsic error rate. These results provide a general criterion for proofreading in systems ranging from self-assembly and polymer replication to immune recognition and other nonequilibrium information-processing systems.

A central challenge in nonlinear spectroscopy is the order-selective readout of weak higher-order responses that spectrally overlap with dominant lower-order signals. This bottleneck is particularly severe in two-dimensional (2D) spectroscopy, where extending conventional phase-cycling schemes to higher orders rapidly increases measurement and analysis complexity. Here we introduce a computation-assisted strategy that combines rotating-frame acquisition with a frame-shift tracking algorithm to separate signals by their frame-dependent spectral shifts. In a rubidium vapor experiment, we use this approach to isolate a 7th-order nonlinear contribution from coexisting 3rd-order components, enabling direct access to higher-order quantum-coherence dynamics without sacrificing operation at comparatively high pulse intensities. The method is broadly compatible with multidimensional spectroscopy platforms and provides a practical route to probing many-body and collective ultrafast dynamics beyond third order.

The high computational cost of periodic coupled-cluster theory has limited the density of Brillouin zone sampling, yielding finite-size errors that need to be removed by extrapolation. Here we report the development and application of a distributed-memory software implementation of periodic coupled-cluster theory with single and double excitations (CCSD) that runs efficiently on up to 12 nodes with 96 cores each. This new implementation allows ground-state and excited-state calculations in which the Brillouin zone is sampled with up to $6^3=216$ $k$-points, allowing us to reliably extrapolate to the thermodynamic limit. For eight simple semiconductors and insulators, we report the cohesive energy and band gap, which are converged to 0.1 eV, providing definitive benchmark numbers for the CCSD level of theory. Compared to experimental values, average errors for the cohesive energy are 0.1-0.2 eV (typically an underestimate), and average errors for the band gap are about 0.4 eV (typically an overestimate).

Accurate surface thermochemistry requires balanced error cancellation between extended slabs and molecular reference states. This balance can fail whenever the electronic-structure error is not transferable across the chemically distinct species entering a thermodynamic cycle. Here we examine this problem in single-determinant fixed-node diffusion Monte Carlo (SD-FNDMC) for oxygen-reduction intermediates on Pt(111) and selected CO-reduction intermediates on Cu(111). Gas-phase thermochemistry is used to diagnose the reference-state imbalance, and a hybrid cycle is introduced to separate slab–adsorbate binding from molecular formation. The hybrid cycle keeps the surface binding term at the SD-FNDMC level, where cancellation is expected to be most favorable, and replaces the molecular formation contribution with a benchmark coupled cluster reference. For Pt(111), the resulting correction is small for O and OH but larger for OOH, while the geometry-matched refinement gives only a secondary correction. Applying the same cycle to $^\ast$CHO and $^\ast$COH adsorption on Cu(111) gives corrections of opposite sign, showing that the bias is controlled primarily by the electronic structure of the corresponding HCO and COH molecular references rather than by adsorbate geometry alone. This decomposition identifies molecular reference imbalance as a separable source of error in SD-FNDMC surface thermochemistry and reduces the corresponding bias without modifying the SD-FNDMC slab-binding contribution.

Quantum computation of fluid dynamics has attracted growing attention as a key application of fault-tolerant quantum computers anticipated in the coming decade, with lattice Boltzmann methods emerging as a particularly promising approach. Explicit and efficient elementary-gate-level circuit simulations, however, have so far been demonstrated only in the linear case. Here we include the leading nonlinearity through second-order Carleman linearization of the one-dimensional Boltzmann equation, and demonstrate, via explicit quantum-circuit simulation, the preparation of the final-time state using a Taylor-expansion-based ODE solver based on the quantum singular value transformation. With this construction, we analyze the gate and qubit complexities, which scale logarithmically with the grid size, the nonlinearity captured by the higher-order Carleman linearization, and the practical utility of higher-order expansions in the Taylor ODE solver. The construction provides a concrete baseline for computational cost reduction and further developments such as extensions to higher dimensions, complex geometries, and the extraction of physical quantities, towards industrially useful quantum CFD.

Accurately representing convection and precipitation remains a persistent challenge for Numerical Weather Prediction (NWP) models due to biases in convective initiation, storm organization, and rainfall distribution, particularly in subtropical/tropical environments. This study evaluated how microphysics parameterizations influence convective organization and precipitation using hindcasts with the Model for Prediction Across Scales - Atmosphere (MPAS-A) on a variable-resolution mesh down to 1-km resolution. Two operational microphysics schemes, National Severe Storm Labs (NSSL) microphysics and Thompson-Eidhammer Microphysics Parameterization for Operations (TEMPO), were examined across three subtropical/tropical regions during boreal summer under strongly- and weakly-forced regimes. Both schemes captured the general timing and placement of convection, but differed in storm structure and rainfall distribution. TEMPO produced more numerous, weaker convective cores with earlier, more widespread precipitation and cooler surface conditions, while NSSL favored fewer, stronger cores and updrafts with more cloud water, ice, and graupel hydrometeors, though less snow, and more spatially concentrated, intense rainfall. Despite these structural differences, both schemes diverged more from observations than from each other, producing scattered convective cells with minimal mesoscale organization and insufficient stratiform precipitation. The simulations also exhibited regime-dependent errors, with rainfall under- (over)-represented in strongly- (weakly)-forced regimes and forecast skill notably lower in the latter. Improving representation of localized precipitation processes remains essential for capturing convection across a wider range of scales and regimes. Future work should target microphysics evaluation across regimes and regions, with process-level improvements reducing convective biases.

An implication of Faraday's Law is thst the rate of change of the poloidal flux relative to the toroidal flux associated with a magnetic surface is given by the loop voltage. The emphasis in the tokamak literature on the poloidal almost to the exclusion of the toroidal magnetic flux has led to fundamental mistakes in understanding magnetic field evolution, especially as it affects plasma disuptivity. Designs of tokamak power plants include a divertor that is defined by a separatrix at the plasma edge. The use of the toroidal flux clarifies the descriptions of such plasmas. This paper explores the effects of a separatrix on plasma parameters that are used for assessing disruptivity: the edge safety factor and the internal inductance. The exploration of these effects includes an analytic model, which illustrates why the use of the poloidal instead of the toroidal flux introduces a significant definitional uncertainty in what is meant by the edge safety factor and the internal inductance.