Papers

Representing scientific papers as points in a space lets us search for similar papers and inquire about how fields relate to one another and drive innovation. Beyond search, the vector space of papers invites generation: mixing papers through simple vector operations creates new points, mirroring combinatorial novelty, the recombination of existing ideas into new ones. However, a mixed point often represents an idea no paper has yet realized, with no papers nearby to identify the idea. We propose representing each paper by a LoRA adapter generated by the Doc-to-LoRA hypernetwork. Every point in the space, including mixtures, thus represents a large language model (LLM) open to questions and instructions in natural language. On papers from the American Physical Society (APS), we instruct the LLM at the average of each subfield to name the field in a few words and obtain labels closer to the official names than the labels of five baselines, as judged by word overlap and a panel of five LLM judges. We also ask the LLMs at points between two APS papers to write an abstract and obtain descriptions shifting from one paper to the other in step with the mixing weight. While Doc-to-LoRA is trained for generation, a small invertible transform makes the embeddings competitive for search, on par with SPECTER2 and EmbeddingGemma and close to SBERT. Because the transform is invertible, every point in the transformed space still maps back to an LLM. The embeddings thus serve both search and generation, enabling researchers to question the idea at any point in the space as a starting point for generating new ideas.

Biological processes, from molecules diffusing to their regulatory destinations to whales pursuing food or mates, are widely exploratory. Such behaviors are effective when some verifiable functional state or outcome can be reached regardless of initial conditions. In these cases, systems repeatedly undergo distinct and abortive trajectories; the process only ends when the system finds “right” outcomes. This dominance of the terminal condition (and indifference to the initial state) provokes a very different perspective than the conventional “dynamical systems” framework that has been a centerpiece of the quantitative sciences for centuries. We hypothesize that many of these problems defy the initial-condition driven or gradients on landscapes so useful in problems ranging from mechanics to electrodynamics to chemical kinetics to mass and heat transport. We examine several mathematical frameworks that capture and unify key aspects of exploratory dynamics. One powerful way of thinking of such processes is the geometric distribution, where repeated failures are punctuated by a successful trajectory. We develop intuitions for how random walks with resets accelerate search processes. We highlight fresh and surprising behaviors of search under drift, cues, and checkpoints. Last, appreciating the probability of trajectories conditioned on satisfying macroscopic final outcomes reveals a language for the potency of variation sculpted by selection in their broadest forms. This can give the fictitious appearance of the future making itself known in the present, but we view this as conceptually similar to the way “fictitious forces” arise in non-inertial reference frames. These approaches stress unity, open questions, and applications across a range of biological phenomena.

Topology under non-Hermitian dynamics is encoded in the phase of the bulk evolution, yet strong dissipation suppresses the amplitudes carrying it. We resolve this using a programmable photonic integrated circuit that implements such dynamics in synthetic momentum space through unitary dilation, with the phase recovered by phase-shifted interferometry. For the non-Hermitian Su-Schrieffer-Heeger model, the method distinguishes trivial and non-trivial Zak phases and yields a coherence winding $q=\pm 1$ induced by an exceptional point. Extending to a synthetic torus via a Rice-Mele pump gives the first Chern number $\mathrm{Ch}_1=0,1$ for trivial and non-trivial cycles, showing a programmable route to momentum-space topology under strongly dissipative non-Hermitian dynamics.

Three-dimensional flood propagation through the Bhote Koshi–Langtang Khola junction at Syabrubesi, Nepal, is studied using an incompressible free-surface model. The calculation is motivated by the August 2026 flood and examines the passage of an imposed inflow through the local bends and changes in channel width. The Navier–Stokes equations and an interface transport equation are solved on unstructured tetrahedral meshes constructed from pre-event terrain data. For an inlet speed of $10\,\mathrm{m\,s^{-1}}$, the solution indicates surface speeds above $40\,\mathrm{m\,s^{-1}}$. The advancing front spreads across the junction; as the flow develops, water deepens and slows around the bend. Higher speeds persist in the confined upstream and downstream regions.

First-principles calculations of scattering off quantum many-body systems such as atoms and nuclei is important but nontrivial, requiring large-dimension ($10^3$ to $10^8$ or more) bases. For the first time we apply to many-body targets a recently developed approach to find phase shifts in $L^2$-integrable bases, computing neutron-nucleus scattering using the same interactions as ab initio models of nuclei, in very small (dimension 3-6) bases. Our work shows the mean field dominates low-energy nuclear scattering; it also provides a foundation for more efficient future methodologies.

Multi-agent systems of LLMs add discussion to majority voting and are therefore expected to be more capable. However, empirical reports conflict on whether discussion improves accuracy or leads to an incorrect consensus. Here, we introduce a parsimonious model that explains when discussion improves accuracy and when it ends in an incorrect consensus, built from four behaviors repeatedly observed in LLM agents: (1) withholding dissent, (2) internalizing a stated answer, (3) reconsidering after seeing dissent, and (4) correcting toward the correct answer. The model shows that discussion can overturn an incorrect initial majority only when the withholding rate $c$ is below a critical rate $c^* = \gamma/(\gamma + a)$, set by the net correction rate $\gamma$ and the internalization rate $a$. We estimate these rates from conversation logs with a Bayesian method and place LLM teams relative to $c^*$. As the model predicts, the gain from discussion shrinks as withholding rises, across LLMs and on a hidden profile benchmark, HiddenBench, and MedEInst. Instructing agents not to withhold dissent increases this gain. Turning reasoning off also increases the gain, because reasoning raises the internalization rate $a$ and keeps agents from reconsidering a minority answer. These findings reconcile the conflicting reports and identify when discussion outperforms majority voting.

Claims concerning a dynamical equivalence between general relativity and two reformulations of it, in which gravity is encoded in torsion and non-metricity respectively, have attracted some attention. If taken to be true, this 'Geometric Trinity' suggests that it is impossible to determine, even in principle, whether one inhabits a spacetime solution possessing curvature, torsion or non-metricity (insofar as the probes of geometry are paths of test particles). This claim is in direct tension with the long tradition of studying gravity as a gauge theory, in which distinct geometric attributes couple to distinct properties of matter (such as energy-momentum to curvature and spin angular momentum to torsion). In this short paper, I compare these two conflicting frameworks for geometrizing spacetime and describe the precise source, nature and implications of their disagreement. The equivalence claim holds only under a substantive restriction on the matter sector, namely that matter does not couple to an independent affine connection. Because the relevant couplings remain beyond current empirical reach, the choice between the frameworks turns on a trade-off among ontological, epistemic, and methodological forms of parsimony.

Recent progress in network renormalization has identified various ways to transform network representations consistently across resolution levels. In particular, the renormalization flow describing how random graph models transform under node aggregation has identified a fixed point corresponding to an aggregation-invariant model that preserves the form of the connection probability across arbitrary scales. While this probabilistic multiscale approach has successfully been used to model real-world networks, construct latent-space node embeddings, and reconstruct finer-grained versions of aggregate network data in a principled resolution-invariant way, it has so far been restricted to binary graphs. Here we reformulate multiscale network renormalization for weighted random graphs. Via a generating-function approach, we identify a weighted multiscale model whose full probability law, encoding both link creation and weight assignment, has an invariant compound-Poisson form under arbitrary node aggregation. The renormalization rules that transform parameters across aggregation levels allow the ensemble to be calibrated at one level and applied at another, enabling consistent modeling and reconstruction of weighted networks across arbitrary scales.

Reliable multistep quantum lattice-Boltzmann evolution requires controlling computational faults. When ideal collision preserves encoded mass and momentum exactly, changes in those charges can provide syndromes for selected faults at the post-collision checkpoint. A fault that shifts one population then leaves a unique mass-momentum residual labeled by the lattice velocity. A coherent reference register stores the expected charges, so the same test remains valid while the physical fluid charges vary across the lattice. Single bit flips on population number registers occupy disjoint syndrome sectors and satisfy the Knill-Laflamme condition. A state-vector demonstration on eighteen data qubits of the two-dimensional nine-velocity lattice (D2Q9) recovers that single-bit family to double-precision roundoff. Conservation still leaves a fifteen-dimensional kinetic nullspace on the three-dimensional nineteen-velocity lattice (D3Q19). Exact multiple-relaxation-time (MRT) streaming analysis ranks those charge-preserving modes by the order at which they return to density or momentum. A classical D3Q19 decaying-flow simulation at moderate Reynolds number then injects about $1.75\times10^4$ selected single-population shifts per realization. Recovery of that alphabet returns the trajectory to floating-point roundoff. The quantum statements assume an ideal charge-preserving collision and a reliable reference. The result is an inner recovery map for a stated charge-changing alphabet together with a kinetic classification of the unresolved sector.

Time-variable stellar heating may create new climate states, such as permanently hot or cold hemispheres, on asynchronous planets. Planets on eccentric orbits, circumbinary planets and planets on polar orbits around gravity-darkened stars all receive variable irradiation, yet variably irradiated planets (VIPs) have not been studied from a fundamental dynamical perspective. We present the first generalized study of the atmospheric response of variably irradiated tidally locked planets, using a 1.5-layer shallow-water model forced towards a time-dependent radiative equilibrium. We derive linearized analytic expressions for the mean, amplitude and phase lag of the response, which is that of a forced damped harmonic oscillator, and recover the established trends of tidally locked planets in the limit of steady forcing. When the instellation variation and wave timescales match and the damping is weak, a resonance occurs because waves propagate and interfere freely. The resonance produces a global standing wave mode and consequently a temporarily warmer nightside. Linear and nonlinear simulations reproduce these results and show that the hotspot oscillates longitudinally at the forcing frequency and reaches the antistellar point at resonance. The oscillation is eastward or westward of the substellar longitude depending on the rotation rate and the nonlinearity of the system. Synthetic phase curves carry signatures of this variability and invert in shape at resonance because of nightside warming. Among observed systems, we find 11 planets with at least 10% phase curve modulation from variable irradiation. Eccentric, pseudo-synchronous giants are the most promising targets, with HAT-P-2b having the largest predicted modulation.

Multimode optomechanical scattering is ubiquitous in free-space imaging protocols, but its radiation pressure counterpart is challenging to detect with extended objects. Here we demonstrate radiation pressure actuation of a nanomechanical membrane using dynamically structured light from a spatial mode demultiplexer (SPADE). Using single- and two-mode illumination, we directly image the position-dependent intermodal coupling between Hermite-Gauss (HG) modes as mediated by the membrane's motion. As an application, we use multimode radiation pressure feedback to simultaneously cool two nearly degenerate membrane modes. Our results are applicable to diverse mechanical systems and serve as a stepping stone to SPADE-based quantum optomechanics.

We introduce and numerically demonstrate receiver-informed transmitter (RITX) waveform design for 200 Gb/s PAM-4 C-band direct-detection PON. Using 50 GHz optoelectronics, RITX achieves N1/E1 loss classes with FFE-Free ONU, enabling 40 km reach and 48.1%/66.7% network-wide complexity savings at 1:64/1:128 splits

Ship structural vibrations contribute to noise, fatigue, and equipment damage, while dynamic-compliance topology optimization can produce pathological designs near resonance. This study extends neural-reparameterized topology optimization using a convolutional Kolmogorov-Arnold network (KATO) to forced-vibration design with active input power (AIP) as the objective. Applications include a 100 Hz engine-supporting deck panel and an 18 Hz thruster foundation frame. Helmholtz PDE filtering and Heaviside projection control feature sizes and manufacturing tolerance. Across both deck families, all eight optimized layouts reduce AIP relative to size-optimized references and, after finite-depth extrusion, also achieve lower static compliance. For unrestricted, manufacturing-aware, and stress-aware frame variants, KATO matches GCMMA in AIP within 0.5 dB while yielding 22-36x lower static compliance after matched-volume binary re-analysis. In a near-resonant 300 Hz case, both methods reduce initial AIP by more than 32 dB; KATO maintains a connected design, achieves 59x lower binary static compliance, and reduces maximum AIP over 1-500 Hz by 2.7 dB. KATO runs 6.4-10.4x faster than GCMMA for the implemented stress-aware formulations. The results demonstrate neural AIP-driven topology optimization as an efficient approach for designing connected, feature-size-controlled ship structures with improved forced-vibration performance.

Scientific foundation models are commonly evaluated after heterogeneous physical problems have already been translated into a compatible gridded, tokenized or symbolic representation. This leaves the scientific interface outside both the pretrained model and the audit of what is actually reused. We study the complementary setting in which boundary histories, sparse monitor records and loading histories retain their native inference classes and their outputs remain on Cartesian, latitude-longitude and unstructured domains. GEODE couples task-specific scientific interfaces to a shared routed library of wavelet operators. A single jointly pretrained model represents cavity flow, radiation dose and elastoplastic stress, then acquires a heat exchanger and a reactor subchannel by training a private interface containing 2.1% of its parameters. Earlier predictions remain unchanged by parameter isolation, whereas unrestricted fine-tuning degrades them by factors of 14-29. Crucially, preservation alone does not establish reuse: norm-matched randomized-library controls show that the contribution of pretrained computation is conditional on the task and data regime. A separate decomposition shows that full-field relative L2 error can substantially understate error relative to spatial variation when field level dominates the norm. Task-specific operators remain more accurate on three of the five problems. These results distinguish multi-task coverage, preservation and pretrained reuse as separate properties that must be tested independently when scientific foundation models span heterogeneous interfaces.

A simple model gives good agreement between observed emissions of CO2 into the atmosphere from the combustion of fossil fuels and observed increases of the atmospheric concentrations C of CO2 and decreases of the isotope delta value delta13C. If fossil fuel emissions were to cease the model predicts that: (1) the difference between the CO2 concentration C and the preindustrial value, Co = 280 ppm, would decay exponentially with time constant of 60 y; (2) the difference between the concentration-delta-value product C x delta13C and the preindustrial value Co x delta13Co = (280 ppm) x (-6.5%%), would decay exponentially with a time constant of 8 y. The decay times are different because of isotopic exchange, largely driven by photosynthesis and respiration on the land.

We report the experimental observation of the $^{\text{133}}$Cs 6S$_{\text{1/2}}$ to 6D$_{\text{5/2}}$ single-frequency two-photon transition at low excitation power using an optical nanofiber embedded in a cold atom cloud. We investigate the 917 nm fluorescence spectra modified by the surface-induced interaction of the nanofiber, which exhibits a pronounced asymmetric broadening with a distinct red-shifted tail. We present a systematic theoretical description of the two-photon transition process of atoms near a nanofiber surface, considering atomic angular momentum coupling, guided-mode decay rate, and surface-induced van der Waals interactions. Owing to the tight spatial confinement provided by the guided evanescent field, efficient nonlinear excitation is realized at excitation powers down to tens of microwatts, corresponding to a reduction of approximately four orders of magnitude relative to typical free-space implementations. Our work reveals the interplay among waveguide-modified radiative dynamics, surface-induced interactions, and the spatial distribution of atoms around the nanofiber, and provides insights into further studies on nonlinear optical transitions and surface-mediated atomic dynamics in waveguide quantum electrodynamics systems.

Emergence, features of a whole that no part shows alone, is central to complex systems but rarely measured so as to locate its source. Viewing a system structurally, as a network of interacting parts, we evaluate emergence as what observing the coupled whole reveals beyond, or erases from, the combined observations of the parts. For observations that build what they see route by route, we show that every emergent feature is produced by its own route across the interface between parts, a route that traces it to the components and interactions responsible. We show the number of all such boundary-crossing paths bounds the total emergence discrepancy, and equals the emergence of measures that count routes. The bound is computed locally around the interface, validated through network examples, and in a nervous system the routes show that interneurons relay most of the emergence. Our work associates emergence with path structure in the network system that can be anticipated, attributed, and engineered.

Interlayer excitons in transition metal dichalcogenide (TMD) heterostructures exhibit long lifetimes and long-range transport, making them promising for excitonic devices and quantum many-body phases, such as Bose-Einstein condensates. Achieving these goals requires a precise understanding of spin-allowed bright and nominally spin-forbidden dark excitons, because the lowest-energy exciton species governs population, transport, and condensation. Despite substantial progress, unambiguously distinguishing singlet and triplet interlayer excitons has been challenging, as moiré excitons in these heterostructures can mimic their optical signatures. Here, we report the direct spectroscopic identification of bright (singlet) and dark (triplet) interlayer excitons in high-quality, dual-gated WSe$_2$/hBN/WSe$_2$ homobilayers. Electric-field-dependent photoluminescence and reflectance reveal two momentum-direct interlayer transitions with distinct spin configurations. The interlayer dark excitons obey selection rules that differ from those of bright excitons. Strikingly, interlayer dark excitons retain strong valley polarization, even with their ultralong lifetime exceeding microseconds. Finally, we demonstrate twist-angle control, wherein twist-induced electron-hole momentum mismatch modulates interlayer exciton emission. These results provide critical insights into the electronic and excitonic structure of TMD heterostructures, opening new avenues for excitonic many-body physics and optoelectronic devices.

Pulsed light is represented by density matrices whose correlation functions have different properties of stationarity and coherence. We show that these density matrices yield equivalent measurement results after accounting for finite detection times. This in turn reveals a physical meaning to the length of a quantization cavity and explains the origin of the physical spectrum for pulsed light. By generalizing the density matrices for pulsed Gaussian states of light, we can describe pulsed light of varying statistics in the same basis and relate the photocount rate to the pulse spectrum.

Turbulent flows are highly chaotic, which makes their instantaneous states difficult to predict. Data assimilation aims to reduce this predictive uncertainty by synthesizing the predictions of a physical solver with partial observations of the system. Traditional data assimilation methods such as ensemble and variational approaches can incur substantial computational cost through evaluations of high-fidelity solvers and, for variational methods, adjoint calculations. Recently, generative diffusion models have been explored in the solution of inverse problems in fluid mechanics, demonstrating their potential for data assimilation. However, existing diffusion-based methods often use free parameters instead of the prescribed observation-error covariance to control the balance between the prior and likelihood, departing from the Bayesian formulation of data assimilation. We propose a framework for principled generative data assimilation in which observations are assimilated in the clean-state space and the prescribed observation-error covariance enters explicitly through an ensemble Kalman update. In the Lorenz-63 system, the proposed method yields a lower trajectory error and equation residual than the other diffusion-based posterior sampling methods considered, although its ensemble underestimates the posterior uncertainty. In two-dimensional Rayleigh-Bénard convection, the generated fields recover the statistics of the direct numerical simulation reference at large scales, with deviations confined to the smaller scales. These results suggest that the framework can produce physically plausible turbulent flow fields, indicating its potential for more challenging turbulent flow applications.

Network reconstruction from partial information is usually performed at the same resolution level at which constraints are observable. This becomes problematic when only coarse-grained information is available, while the relevant process occurs at a finer scale. Here we employ the multiscale model of weighted networks introduced in a companion paper and turn it into a probabilistic framework for reconstructing weighted networks across arbitrary aggregation levels. The model is built to preserve its functional form under coarse-graining, so that global parameters calibrated on an observable aggregate layer can be transferred to finer layers without refitting. We test the method on two empirical systems with different aggregation mechanisms. In the International Trade Network, countries are aggregated into geographic macro-regions and the observed coarse-grained layer is used to infer the underlying country-level network. In the Dutch production network, sectoral flows are reconstructed across the hierarchical industrial classification, using coarser sectoral layers to infer finer ones. In both geographical and sectoral settings, we benchmark our genuinely multiscale reconstruction method against a state-of-the-art weighted reconstruction model calibrated directly at the target resolution, and therefore using additional information available at the same (finer) scale at which performance is evaluated. Remarkably, despite this informational disadvantage, our method recovers the fine-scale binary structure with high accuracy, improving precision, specificity, accuracy and maximum degree-error diagnostics, while remaining nearly equivalent in sensitivity.

A droplet breaks up in tens of microseconds, and a recording captures perhaps a dozen frames. The states in between cannot be recovered without repeating the experiment, and simulating them is too costly to sweep an operating envelope. Yet they are present in the corpus as a whole: a campaign spanning a device's actuation range produces morphologies resembling those any single recording missed. Exploiting that requires a representation that is low-dimensional, invertible, and faithful to shape rather than to sampling. Proper orthogonal decomposition supplies the first two but measures distance in sampled coordinates; manifold learning supplies the third but no map back to a shape; elastic shape analysis supplies a shape metric but no reduced coordinates. SHROM composes all three. Interfaces are represented by their square-root velocity functions, a neighbour graph is built over that shape space, and an autoencoder is trained to reconstruct while penalising latents in which graph neighbours are not latent neighbours. The demonstration uses 301,539 inkjet droplet contours and four filmed break-up sequences. The graph term does not improve reconstruction. It determines whether position in the latent carries meaning: clustering the latent of an otherwise identical model recovers the shape-space partition at chance level (ARI = 0.063 +/- 0.059), and at 0.781 +/- 0.049 with the term active. Waveform parameters predict the full contour at R^2 = 0.878 +/- 0.026. Negative results are reported in the same terms. The graph metric proved immaterial across five choices, and interpolation error saturates at the reconstruction limit, so a plain autoencoder leads that task. The main limitation is interpolation across a topology change: no component of the regularised latent holds both a single-component and a post-break-up shape, whereas an unregularised autoencoder mixes them freely.

This study provides a data-driven analysis of a novel dataset of single-cell Anion Exchange Membrane water electrolyzers (AEMWE), operated under constant current load across multiple heterogeneous experimental campaigns. We train and evaluate a range of machine learning models with different complexity, including linear baselines, LSTMs and CNNs, to perform medium-term forecasting of the cell voltage degradation curve. The models are assessed within a rigorous training and evaluation framework specifically designed for heterogeneous industrial data.

A key objective in Weyl-semimetal (WSM) research is to identify phases built from minimal configurations of Weyl points (WPs), which provide the simplest settings for investigating the intrinsic physics of chiral topological charges. Pang et al. [Phys. Rev. Res. 8, 033304 (2026)] recently established that crystallographically realizable WSMs can be decomposed into linear combinations of 16 minimal "irreducible Weyl molecules" (IWMs). A fundamental question remains unresolved: which of these non-decomposable configurations can themselves form standalone crystalline phases? Here we introduce irreducible Weyl semimetals (IWSMs), in which two bands crossing near the Fermi level form an elementary symmetry-compatible complex whose complete Weyl-node configuration is charge neutral and crystallographically indivisible. Combining all 1651 magnetic space groups with Weyl-orbit multiplicities and band-compatibility relations, we classify IWSMs formed by crystalline-symmetry-protected twofold WPs. Only ten of the sixteen primitive inventories admit one-copy realizations, comprising four Pair, four Split, and two Mixed charge-node architectures. Remarkably, this classification uncovers five unconventional and previously unrecognized topological phases: the charge-three Pair IWSM {3, -3}; the Split IWSMs {3, -1, -1, -1}, and {4, -1, -1, -1, -1}; and the Mixed IWSMs {3, 1, -2, -2} and {3, 3, -2, -2, -2}. For all ten classes, symmetry-constrained lattice models verify the complete node inventories, Chern charges, and surface chiral-flow incidence. Our results establish crystalline irreducibility as a phase-level organizing principle beyond individual Weyl nodes and provide a symmetry-resolved framework for identifying minimal Weyl complexes in electronic, phononic, and photonic systems.

We introduce chiral rotational wavepackets: coherent superpositions of a few low-lying rotational states of a molecule for which the expectation value of a molecular axis traces a three-dimensional chiral trajectory in the laboratory frame. The handedness is a dynamical property of the quantum state rather than of the equilibrium structure, and we show that it can be imprinted on linear rotors as well as on spherical and symmetric tops. We derive the action of space inversion, time reversal, and their product on such wavepackets in the Wigner $D^J_{MK}$ basis, and define the rotational enantiomers of a given wavepacket. To quantify their handedness we introduce two derivative-based pseudoscalar measures: a geometrical measure built from the curvature and torsion of the trajectory, which is even under time reversal, and a dynamical measure, which is odd under time reversal. The latter is shown to be proportional to the geodesic curvature of the trajectory projected onto the unit sphere, which links it, via the Gauss–Bonnet theorem, to the solid angle enclosed by the projected trajectory and to the parallel-transport holonomy of a molecule-fixed vector. Finally we show that a nonzero geometrical measure is a sufficient condition for the wavepacket to exhibit true chirality through its orientation trajectory in the sense of Barron.

Optical anapoles have attracted significant interest as a promising platform for enhancing light-matter interactions at the nanoscale. An ideal anapole is a localized excitation of electromagnetic fields that does not produce any far-field radiation. In practice, anapoles are not ideal due to the parasitic scattered fields associated with higher-order multipoles. Here, we use the recently established exact current multipole expansion and the exact anapole condition to design an ideal anapole in which radiation due to the multipole orders up to the electric and magnetic octupoles is either eliminated or strongly suppressed, reducing the total radiated power by orders of magnitude. We also propose and study realistic photonic structures in which such anapoles can be excited by a uniform linearly polarized plane wave through second-harmonic generation that involves the off-diagonal elements of the second-order susceptibility tensor. In this case, the anapole condition is reached off-resonantly by adjusting the polarization angle of the incident field, which allows for the anapoles to be excited over a wide spectral range in scatterers of different sizes. Using this approach, we achieve scattering suppression on the order of $10^{-4}$ in photonic structures that are half a wavelength in size. The method offers the possibility to realize localized electromagnetic excitations that are truly isolated from the surroundings.

Multicomponent methods treat both electrons and nuclei quantum mechanically using the standard machinery of electronic structure theory. Previous work has demonstrated that quantitatively describing electron-nuclear correlation in multicomponent many-body perturbation theory methods requires large electronic basis sets with high-angular momentum atomic orbitals, and calculations on large systems can therefore become impractical. Similarly, the slow convergence of the electron-electron correlation energy with respect to highest atomic-orbital angular momentum is a well-known issue in standard electronic structure theory in which only the electrons are treated quantum mechanically, and numerous explicitly correlated methods have been introduced to mitigate this poor convergence. Motivated by the success of single-component explicitly correlated methods, we generalize the single-component MP2-F12/3C(FIX) approach for electron-electron correlation to electron-proton correlation to reduce the need for large electronic basis sets in multicomponent calculations. We also implement the complementary auxiliary basis set (CABS) singles correction for the electrons and protons. Our calculations show that the multicomponent MP2-F12 electron-proton correlation energy is within a few percent of the complete-basis-set (CBS) estimate obtained by QZ-5Z inverse-cubic extrapolation with PB4-D held fixed at every electronic basis-set cardinality tested, with the aug-cc-pVDZ basis set recovering 96-98% of the extrapolated CBS electron-proton correlation energy and exceeding the conventional multicomponent MP2 value at the aug-cc-pV5Z level. These results indicate that explicitly correlated methods can substantially reduce the electronic basis-set requirements of multicomponent calculations.

Adsorption and desorption redistribute soluble surfactant between a liquid film and its free surface, but cannot change the total inventory in a closed periodic domain. We audit this requirement in nonlinear weighted-residual models for soluble-surfactant-laden falling films. Although a previous correction restores conservation of the nonlinear surface Marangoni flux, a separate inconsistency remains in the depth-integrated bulk diffusion. We derive the resulting mass imbalance and construct explicit positive periodic concentration fields that exhibit it. The missing contribution arises from the streamwise concentration gradient appearing in the normal diffusive flux at a sloping interface. Including this contribution restores local conservation of the coupled bulk-surface transport system while leaving the hydrodynamic equations, the leading-order adsorption-desorption closure, and the linear stability properties of the uniform equilibrium unchanged. In an independent no-slip calculation using the parameters of an earlier travelling-wave study, the reference model loses $0.0228832\%$ of its initial surfactant mass by $t=4500$, whereas the corrected run has an absolute relative mass change of $1.2\times10^{-15}$. The main hump and capillary ripples remain closely comparable at $t\approx4500$. This benchmark therefore shows that agreement with travelling-wave calculations does not, by itself, guarantee that a reduced model respects the conservation laws inherited from the underlying transport problem. Although the drift is small in this case, the corrected equations conserve the reduced total inventory for every smooth periodic solution. We also distinguish this exact conservation property from higher-order compatibility with the full curved-interface boundary conditions.

The compressible MHD energy cascade in the solar wind is shaped by Alfvénicity, plasma fluctuations, and proton temperature, yet how these factors regulate the relative weight of compressible and incompressible energy transfer across heliocentric distances remains poorly understood. We apply compressible and incompressible exact relations to a large sample of 2-hour intervals from WIND (1~au), Parker Solar Probe ($<0.25$~au), and Solar Orbiter (0.3–1~au), classifying intervals as Alfvénic ($|\sigma_c|>0.75$) or non-Alfvénic ($|\sigma_c|<0.25$) and by wind speed, and examine the Yaglom-like and purely compressible components of the compressible cascade. Velocity fluctuation amplitude is the strongest predictor of the compressible cascade rate $\langle|\varepsilon_c|\rangle$, followed by density and magnetic field fluctuations. $\langle|\varepsilon_c|\rangle$ and $\langle|\varepsilon_i|\rangle$ are tightly correlated in all regimes, with their ratio organized by Alfvénicity and wind speed: non-Alfvénic and Alfvénic fast winds cluster along $\langle|\varepsilon_c|\rangle=\langle|\varepsilon_i|\rangle$, while Alfvénic slow wind shows a systematic excess consistent with internal energy contributions. The largest $\langle|\varepsilon_c|\rangle$ systematically occur in hotter intervals, with a two-decade increase from cool to hot events in Alfvénic slow and non-Alfvénic wind, a trend carried mainly by the purely compressible term, while the dominant Yaglom-like term controls the overall cascade magnitude. Alfvénicity and wind speed thus govern the efficiency of turbulent energy transfer across heliocentric distances, and the tight coupling between compressible and incompressible rates points to the need for compressible, multi-fluid descriptions of the solar wind dissipation budget.

We present an equivalent-circuit analysis that simultaneously considers the photoluminescence and electrical responses of valley photovoltaic devices. Valley photovoltaics (VPV) are a novel concept for hot-carrier solar cells, where intervalley scattering of electrons in the absorbing material helps maintain the conduction-band electron populations at metastable satellite valleys, which are at energies higher than the conduction-band minimum. We measure intensity- and voltage-dependent photoluminescence and electrical signals of a VPV device, which has previously shown S-shaped current-voltage characteristics and thus low efficiency. We present an equivalent circuit that captures the S-shaped current-voltage curves and simultaneously describes our photoluminescence and electric measurements. The equivalent-circuit model indicates that a reverse diode causes inefficient extraction of electrons and thus the S shape. We use a Poisson/drift-diffusion model to demonstrate that the reverse diode can be either explained by the valley-scattering process itself or a heterojunction barrier. The reverse diode must be eliminated before VPV devices can achieve high efficiency.