Papers

Fault-tolerant quantum computation requires increasing the qubit count while maintaining high performance and connectivity. Semiconductor qubits have demonstrated high-fidelity operation, but growing the system size at sufficient connectivity remains challenging, such that scaling mainly occurred in one spatial direction to preserve access for control lines in the other. Here, we realise an approach that relaxes the requirements on fabrication and demonstrate a 6$\times$6 quantum dot array, defined by a shared barrier gate and individual plunger gates. The quantum dots are tuned through coherent spin shuttling over distances up to 5.2um into a sparse configuration of 10 simultaneously operated qubits, leaving space for shuttling connections. We reduce crosstalk by 42$\times$ in this separated regime, enabling high-fidelity simultaneous single-qubit control, while control-Z operations can be implemented through shuttling and plunger-only control. These results promise high-connectivity quantum circuits, enabled by scaling to two-dimensional geometries and exploiting shuttling.

Dipole-phonon quantum logic (DPQL) offers novel approaches for state preparation, measurement, and control of quantum information in molecular ion qubits. Here we report the first experimental demonstration of DPQL as a spectroscopic tool using the shared motional mode of a CaO$^+$-Ca$^+$ ion chain to measure the frequency splitting of the ground $\Omega$-doublet of CaO$^+$. By comparing the dipole-phonon signal across three trap-frequency ramp ranges, we determine the splitting to be $\omega_{mol}=2\pi\times454\pm1$ kHz and place a lower bound on the effective dipole-phonon coupling. The rate of observation is limited by the low thermal population in the molecular ground rotational state.

Accurate prediction of continuous molecular properties supports chemical discovery and design. Many recent approaches combine multiple molecular representations within increasingly complex neural architectures, aiming to achieve higher accuracy. However, classical machine-learning models remain competitive when trained on chemically meaningful molecular representations. We therefore constructed a chemistry-guided classical branch from Morgan fingerprints, RDKit molecular descriptors, and conformer-derived geometric features selected to provide complementary views of molecular structure. We combined four tree learners trained on these representations with a CoMPT graph predictor and integrated their out-of-fold predictions using Ridge regression. Across ESOL, FreeSolv, and Lipophilicity datasets, the fused model achieved lower mean root-mean-square error (RMSE) than Chemprop and competitive graph and multimodal methods, including CoMPT, MoleSG, KFLM2, and MCMPP. After retraining on the separately curated AqSolDB dataset, the same approach, without redesign or retuning, reduced mean absolute error (MAE) relative to the classical ensemble and achieved lower mean MAE than Chemprop. These results show that accurate and transferable molecular property regression does not necessarily require a complex joint multimodal architecture: classical learning remains competitive when chemical insight guides the choice of molecular representations, and a graph model can add complementary information through simple prediction-level fusion.

We establish when coarse-grained observables uniquely determine an expectation-based biological response in boron neutron capture therapy (BNCT). Microscopic target populations are represented by probability distributions, while retained observables are finitely many population-averaged linear descriptors. For an admissible class containing all finitely supported microscopic distributions, exact distribution-free identification holds if and only if the single-target response kernel lies in the span of the constant function and retained descriptors. Thus mean dose, mixed-field component means, and finite moment sets are not generally sufficient under unrestricted microscopic heterogeneity. We also derive irreducible ambiguity and approximation bounds, sharp partial-identification intervals for bounded non-increasing convex survival kernels, a treatment-ranking criterion, and lower-tail and high-exposure bounds. A fixed-total-exposure temporal model distinguishes transient re-sampling from persistent target-specific underexposure, and a marked-Poisson model shows that separate frequency and event-quality marginals need not determine survival. The framework clarifies which microscopic information is lost through BNCT coarse-graining while leaving room for approximation, partial identification, and prediction under independently justified model restrictions.

A vectorial discrete unified gas kinetic scheme (V-DUGKS) is proposed for continuum compressible flows. In the vectorial kinetic framework, mass, momentum, and total energy are represented by coupled distribution functions with separate relaxation processes for momentum and energy transport, enabling an adjustable Prandtl number. All equilibrium distributions are truncated at the second-order Hermite level. Since only second-order velocity moments are required to recover the compressible Navier-Stokes equations, fourth-order Gauss-Hermite quadrature is sufficient for exact moment evaluation. Eliminating third-order Hermite terms allows compact discrete velocity sets to be used uniformly for all distribution functions, reducing sensitivity to the numerical reference temperature and improving stability and efficiency over the scalar DUGKS. The scheme employs a finite-volume formulation with characteristic-based flux evaluation and trapezoidal collision integration. Numerical tests, including shock-tube, Shu-Osher, two-dimensional Riemann, and three-dimensional Taylor-Green vortex problems, demonstrate its accuracy and robustness. For the three-dimensional Taylor-Green vortex, V-DUGKS achieves a speed-up of about 2.2-2.9 under the same CFL constraint due to a larger allowable time step and simplified equilibrium formulation. These results show that V-DUGKS provides a robust and efficient kinetic framework for continuum compressible flow simulations.

This work develops a pressure-based coupled (PBC) GSIS. Within each GSIS iteration, a conventional kinetic solver advances the velocity distribution function, from which non-equilibrium constitutive relations are extracted. A PBC macroscopic solver then solves the steady macroscopic synthetic equations: continuity and momentum equations are solved as a coupled pressure-velocity system under fixed temperature, followed by a segregated temperature solve. A boundary treatment is constructed to maintain strict consistency between kinetic boundary fluxes and macroscopic boundary conditions throughout the macroscopic iterations. The proposed method is validated against direct simulation Monte Carlo (DSMC) data across multiple three-dimensional test cases, including tube-to-vacuum flows, a dynamic gas lock configuration for EUV lithography, divertors in nuclear fusion, and sphere flow at Mach numbers up to 10. Numerical results demonstrate that our GSIS-PBC preserves asymptotic-preserving properties and yields satisfactory accuracy across continuum-to-transitional flow regimes. For low-speed near-continuum internal flows, GSIS-PBC delivers wall clock time speed-ups of up to two orders of magnitude compared with the conventional iterative scheme, and substantially outperforms the original density-based GSIS for challenging low-Mach internal flow problems. For nuclear-fusion divertor flows, GSIS-PBC is faster than the DSMC by four orders of magnitude.

The discovery of high-temperature superconductivity in bilayer and trilayer nickelates has spurred intense interest in the Ruddlesden-Popper nickelates; yet the fundamental properties of the NiO2 layer remain obscured by interlayer coupling. It is therefore imperative to investigate the electronic properties of their single-layer counterpart to isolate the intrinsic physics of the NiO layer. In this work, we present a systematic study of the single-layer nickelate La1.4Sr0.6NiO4 using high-resolution angle-resolved photoemission spectroscopy (ARPES) and theoretical calculations. We reveal strong electron correlation effects, manifested by high-energy kinks in band dispersions and a pronounced orbital-dependent band renormalization. Interestingly, we observe a quasi-one-dimensional electronic structure characterized by straight Fermi surface sheets along the diagonal momentum directions. Such square Fermi surface topology facilitates non-Fermi liquid behavior consistent with the Luttinger liquid model, as evidenced by the power-law spectral function, robust temperature scaling, and the observation of spin-charge separation. Our results therefore not only unveil an exotic Luttinger liquid behavior emerging from the unexpected dimensional reduction in an intrinsically quasi-two-dimensional nickelate but also provide a new perspective for understanding the intriguing physics in multilayer nickelates.

Subradiant states of a finite subwavelength atomic chain in free space offer a powerful resource for photon storage. Yet their preparation and control remain challenging experimentally. A standard technique is to drive the atoms by a laser and observe the florescence light of the long-lived subradiant modes of excitation after the laser is switched off. However, these modes are highly degenerate and form an almost continuous band in the subradiant manifold. Here we propose a new method of exciting a given subradiant state by coupling atoms to a surface plasmon wave propagating along the interface with a metallic film. By controlling the chain/surface distance we may load, store and release photons in the atoms, making them a promising tool for future quantum memories.

Many real-world datasets exhibit unusually large values far more frequently than predicted by Gaussian models. Heavy-tailed distributions capture this behavior, yet evaluating learning performance under them remains challenging because rare, large feature entries retain non-vanishing effects even in high dimensions. Even in the canonical setting of empirical risk minimization for linear regression with entry-wise i.i.d. symmetric $\alpha$-stable data, a precise asymptotic characterization of prediction has been lacking. In this work, we introduce a functional order parameter that describes the random effective problem associated with each coefficient. Using the replica method, we fully characterize the generalization error in the proportional high-dimensional limit where the sample size and feature dimension diverge at a fixed ratio. Additionally, this analysis establishes a heavy-tail universality law, scaling laws relating typical errors to prediction reliability, and the Bayes-optimal prediction error. In addition to characterizing the effects of extreme entries on the learning process, our method applies broadly to other systems with persistent local heterogeneity.

Measurements from NASA's OSIRIS-REx spacecraft revealed (101955) Bennu as a member of the active asteroid class. These objects exhibit transient, comet-like activity, commonly producing particle trails best observed from a vantage point close to the projected orbit plane. Accordingly, we obtained deep, high resolution observations of Bennu at orbit plane crossing in 2023, using the Hubble Space Telescope. We find no evidence for ejected material, and place model-dependent limits to the mass loss of dM/dt < 0.12 kg/s from an analysis of the near-nucleus surface brightness profiles and dM/dt < 6e-3 kg/s from the absence of a measurable particle trail. These limits are one to two orders of magnitude smaller than rates of mass loss measured remotely in other active asteroids and raise the possibility that low activity in many or most asteroids might fall beneath the prevailing thresholds offered by remote observations. Taking a still smaller mass loss rate estimated from OSIRIS-REx data, we calculate a specific rate L = 1e-7 kg/km2/s and extrapolate to the entire main-belt asteroid population. We estimate a cumulative dust production rate 850/r_min**1/2 [kg/s], where r_min is the minimum asteroid radius in meters. For r_min > 1 m, this is <1% to 10% of the rate needed to sustain the Zodiacal cloud in steady state.

Metasurface heat absorption is conventionally characterized by far-field infra-red spectroscopy under equilibrium conditions. The approach provides information on the surface emissivity but does not directly reveal heat transferred by electromagnetic absorption. To understand the resulting temperature change, however, the associated heat transfer must be considered. Here, we directly observe heat extracted by electromagnetic absorption using infrared thermography. By monitoring the cooling dynamics of a copper plate placed in contact with a metasurface-integrated thermoelectric device, we show that the copper plate cools faster than one placed on an unstructured planar surface (control). This result provides direct evidence of heat transfer from the adjacent solid to the metasurface; revealing a metasurface-mediated electromagnetic absorption heat transfer mechanism. These findings provide new insight into nonequilibrium thermal processes enabled by metasurface absorbers.

Most cosmological simulations invoke quasar-driven winds as the primary mechanism quenching star formation in massive galaxies, assuming wind momentum flux approaches the radiation-pressure maximum, $L/c$. Using 81,388 broad absorption line troughs from the SDSS-IV DR16 quasar catalog and detailed mock trough spectra, we detect line locking, a spectral signature of radiation-pressure-driven outflows, in 60 to 70 percent of troughs, demonstrating that radiative line driving dominates wind acceleration and ruling out alternative mechanisms. Direct measurement of the wind energy budget yields a median kinetic luminosity of only 0.01 percent of bolometric luminosity, 50 times below the level required for effective feedback. Line-driven quasar winds are therefore insufficiently powerful to quench star formation, challenging the primary physical mechanism invoked for black hole feedback in galaxy formation models.

Scientific law discovery requires selecting measurements and converting evidence into a governing equation. We evaluate an explore-then-commit protocol in which a large language model proposes hypotheses, a programmatic planner gathers measurements, and a fresh prompt synthesizes the final law from fixed observations. The protocol combines structured probes, automatic numerical diagnostics, restricted measurement batches, and optional interpreter access. Across 576 NewtonBench trials, we compare eight configurations on 12 physics modules using GPT-4.1-mini and a medium-difficulty GPT-4.1 replication. On medium tasks, interpreter-enabled planners use 8.6 versus 22.5 measurements per trial for GPT-4.1-mini and 8.9 versus 43.0 for GPT-4.1. Their mean magnitude-based root-mean-squared logarithmic error falls from 2.514 to 0.202 and from 0.626 to 0.149, respectively. An additional audit retains incomplete and invalid submissions in a coverage-sensitive analysis. Observed symbolic-accuracy gains are less consistent across modules, and random acquisition is competitive with disagreement scoring. Measurement savings occur in every module, but unequal batch constraints prevent attributing them solely to acquisition quality. These results support the complete protocol as a promising measurement-efficient configuration, while leaving its causal components and generalization beyond noiseless direct-equation tasks unresolved.

In this study, the lean extinction behaviors of CH4 and a 16% cracked ammonia surrogate fuel, CR16, in counterflow premixed flames were compared. Experiments were conducted along with one-dimensional simulations using OPPDIF; the GRI-Mech 3.0 and UCSD mechanisms were applied to CH4 and CR16, respectively. CR16 exhibited higher extinction strain rates and resilience to strain-induced blow-out (RSIB) than those of CH4 under lean conditions. At Phi = 0.66, although both flames had the same extinction strain rate, CR16 showed a higher RSIB because of its longer flame time. Near its extinction, CR16 sustained H2 consumption, radical reactions, and heat release through the interflame region toward the stagnation plane. Hydrogen oxidation coupled with nitrogen-related pathways, including NH2 + NO and HNO reactions, supported this behavior. These results clarify the chemical basis for the superior extinction resistance of economically favorable low-cracking-ratio ammonia fuel.

A very-high-frequency (VHF) electron gun operating at a resonant frequency of 216.667 MHz has been developed at Tsinghua University for the Shenzhen Superconducting Soft X-ray Free-Electron Laser ($\rm S^3FEL$) facility. Building upon the SHINE gun design, the cavity profile was optimized to achieve a higher cathode electric-field gradient and a higher accelerating voltage at comparable input power. The revised cavity geometry also yields improved multipacting performance. In addition, thermal analysis was carried out to guide the water-cooling design, and enhanced cooling was implemented in the vicinity of the cathode. During high-power conditioning, 82 kW of continuous-wave radio-frequency power was successfully coupled into the gun, corresponding to a cathode gradient of 29.9 MV/m and an accelerating voltage of 856 kV. The gun voltage surpasses the previous world record for room-temperature VHF guns. The maximum dark current measured by the Faraday cup at the gun exit was only 6.8 nA.

Miniaturized magnetic components play an important role in achieving high efficiency and high power density in power converters. Accurate core loss data are essential when optimizing magnetic components, but making accurate core loss measurements remains challenging, especially at MHz frequencies. As a result, many research groups have developed their own testers in pursuit of improved accuracy, and the amount of published core loss data has increased. However, large variations in these data shed light on fundamental barriers to accurate MHz core loss measurement. This paper identifies these barriers and presents methods for overcoming them.

This work presents a comprehensive macroscopic electrodynamic framework isolating the magnetodipole (MD) and electrodipole (ED) contributions to the magneto-optical effects in bismuth-substituted iron garnet. By rigorously incorporating the dispersive magnetic permeability tensor, the dominance of the MD mechanism in the terahertz (THz) gap is demonstrated. In the mid-infrared (MIR) to near-infrared (NIR) domain, a fundamental spectral crossover is revealed where the magnitudes of the MD and ED contributions exactly equalize, invalidating the widespread assumption that magnetic contributions vanish uniformly at infrared frequencies. Furthermore, it is shown that interfacial phase shifts uniquely dictate how these competing mechanisms project onto observable rotation and ellipticity, yielding an inverted spectral hierarchy between transmission (Faraday) and reflection (polar and longitudinal Kerr) geometries. Most notably, the transverse Kerr effect for s-polarized light is established to be exclusively driven by the off-diagonal magnetic permeability. While strictly zero under the conventional ED approximation, the s-polarized transverse Kerr effect emerges as a robust, free of the gyroelectric contribution probe of MD activity in the THz and MIR–NIR regimes, yielding a THz response two orders of magnitude larger than its p-polarized counterpart.

Time-resolved photometry from large surveys can yield rotation periods for huge numbers of asteroids, but only if the reliability of each period is assessed automatically, since sparse and irregular sampling produces many false periodogram minima. We present an improved method that determines asteroid rotation periods with a Fourier series whose order is chosen for each object individually. This has substantial advantages over lower order methods, especially when unique solutions for the spin period cannot be reliably determined. In such cases, the method reports the set of alternative periods together with the corresponding probability estimates. We apply the improved spin period determination method to the NSF-DOE Vera C. Rubin Observatory Data Preview 2 (DP2) catalog of solar system objects and determine reliable periods for a large sample of asteroids. Among them we find 66 super-fast rotators, which spin faster than the classical 2.2 h spin barrier. Two of them are remarkable: asteroids 491384 and 566130 are both larger than 2 km, yet they complete a full rotation in only about five minutes. To survive such a fast spin, they must have significant internal cohesion. At a diameter of about 2.5 km, asteroid 491384 is the largest ultra-fast rotator known so far.

We test the idea proposed by Laporte & Orkney that $\omega$ Centauri ($\omega$Cen) is the central nuclear star cluster of the Gaia-Sausage-Enceladus galaxy (GSE) which got dislodged by the bar. We run a series of simulations in time-evolving bar potentials with present-day pattern speeds within Portail et al's $\Omega_{b}=39\pm3.5\,\rm{km\,s^{-1}\,kpc^{-1}}$ and rate of slow-down $\dot{\Omega}_{\rm b}= 4.5 \pm 1.4 \,\rm{km \,s^{-1}\,kpc^{-1}\, Gyr^{-1}}$ to study how bar resonances modulate the angular momentum and energies of both GSE-debris and $\omega$Cen's location in $(E,L_{z})$ space. We find that the retrograde $3:2$ resonance is capable of inflicting changes of $\Delta E\approx0.4\times10^{5}\,\rm{km^{2}\, s^{-2}}$, $\Delta L_{z}\approx0.3-0.5\times10^{3}\, \rm{km \, s^{-1}\, kpc^{-1}}$ within timescales of $\Delta t\approx 0.5-1\,\rm{Gyr}$, well within the bar's lifespan $t_{\rm{bar}}\approx10-8\,\rm{Gyr}$. These results are independent of the choice of potential or modelling. We uncover a sample of N-rich stars with metallicities $-2.0<[\rm{Fe/H}]<-1.0$ and aluminium enrichments consistent with $\omega$Cen. In ($E,L_{z}$) space, the map reveals a corridor of trailing N-rich stars clustered about the region connecting $\omega$Cen to the GSE's debris centroid, matching $\omega$Cen's past predicted track. This provides the best evidence yet that $\omega$Cen is the nuclear star cluster of the GSE. Using M54 and $\omega$Cen's chemistry we show that neither first nor second generations follow general galaxy-wide scale chemical enrichment trends. This is empirical evidence that GC chemical trends are a cluster-scale physics problem, not a galaxy-wide one.

The world's first Compton scattering measurements on a $^3$He target were performed to probe neutron electromagnetic polarizabilities. Differential cross sections were measured at laboratory angles of $40^\circ$, $55^\circ$, $90^\circ$, $115^\circ$, $150^\circ$, using circularly polarized, quasi-monoenergetic photon beams at weighted mean energy values of 61.5 and 97.1 MeV from the High Intensity $\gamma$-ray Source at the Triangle Universities Nuclear Laboratory. Comparisons with chiral effective field theory show good agreement at 97.1 MeV but over-prediction at 61.5 MeV, motivating further theoretical development.

Quantum Darwinism explains classical objectivity through redundant environmental records of a system's pointer states. We show that these records can be established through an intermediate measurement apparatus without direct system–environment interactions. Using exact analytical solutions of quantum circuit models, we compare system monitoring with apparatus monitoring, where the environment interacts only with the apparatus. During encoding, system–apparatus correlations decrease as system–environment correlations grow. Without noise, both models yield identical accessible pointer information and redundancy, while the discord accounts for their different mutual information. The reliability of these records depends on where noise acts. Apparatus bit flips introduce errors shared by successive records, limiting the information recoverable even from the complete environment. In contrast, larger fragments can mitigate independent noise on environment qubits after encoding. Dephasing in the pointer basis leaves the record information unchanged in the model considered. These results extend the description of quantum Darwinism to indirect measurements and clarify the conditions for reliable environmental records.

The Jx-Jy Blume-Capel model, with and without an external magnetic field, is investigated using the Monte Carlo method. Our aim is to verify the location of the tricritical point, examine the existence of reentrant behavior, and study the magnetocaloric properties of this specifically designed system. In the non-field case, the critical temperature given by the Monte Carlo simulations is lower compared to the conventional antiferromagnetic square lattice. When an external magnetic field is applied, we observed signs of a one-dimensional spontaneous symmetry-breaking phase in the mixed-states regime, which is counterintuitive with secondary specific-heat peak. We take the snapshot of this state and elucidated the underlying mechanisms using mean field theory in the field of spin-1 spinor Bose-Einstein condensate . Regarding reentrant behavior, we confirmed its occurrence as the magnetic field varies, but only when the temperature is kept constant. Temperature-dependent reentrant behavior could not be identified within this system. Finally, we examined the magnetocaloric properties and found no evidence of first-order phase transitions within the region of the considered phase-transition point. Although both inverse and direct magnetocaloric effects are present and related to the mixed state, we identified that the relevant phase transitions are all of the second order.

The rapid growth of AI/ML methods for materials discovery has increased the importance of the quality, physical completeness, and information content of computational databases. We examine these issues for magnetic materials, where incomplete sampling of competing magnetic states, chemical disorder, and finite-temperature properties can lead to apparently accurate but physically unreliable predictions. We propose a hierarchical discovery workflow combining independent ML models with explicit electronic-structure, magnetic, dynamical, thermodynamic, kinetic, and experimental validation. To incorporate kinetic accessibility into high-throughput screening, we introduce a dimensionless synthesis-window descriptor based on the relation between the chemical order-disorder and Tammann temperatures. A cluster-expansion analysis of Fe-Co-B illustrates the importance of this criterion: although ordered Fe3CoB2 is energetically favored at T=0, its small ordering energy produces an order-disorder temperature far below room temperature, making long-range Fe/Co ordering kinetically unachievable. These results demonstrate that reliable AI/ML discovery of magnetic materials requires databases and validation procedures that contain physical information relevant to the target functionality, rather than simply larger numbers of calculated structures.

The basic hypergeometric series ${}_{n+1}\phi_{n}$ whose upper and lower parameters are non-negative integer powers of $q$ satisfying a certain constraint can be, after a normalisation, computed as a positive polynomial. We derive three formulas for this polynomial. The first formula is a generalisation of the MacMahon identity in which an infinite binomial series is identified with a normalised generating function of des and maj statistics of multiset permutations. The second formula is a generating function of multiset permutations for the inversion statistic and a generalisation of the statistic mstc. The third formula is a finite sum containing $2n$ $q$-binomial coefficients.

We construct the bulk local states of a massive spin-1 field in AdS$_3$/CFT$_2$ and three-dimensional Carrollian holography. In AdS, covariance under the isometries that leave a bulk point invariant determines the three components of the vector there and splits the solution into two branches of definite helicity, whose inner products reproduce the massive vector two-point function of AdS$_3$. By expanding the massive vector HKLL representation in boundary descendants, one can reproduce the three component states term by term. The two branches together describe the parity-invariant Proca field, and one alone the single propagating mode of Maxwell–Chern–Simons theory. The same conditions are solved in the induced representation of the Carrollian theory, where the solution again splits into two branches. Under the flat limit of the generators the highest weight module becomes the induced module, and the AdS states and Green's functions become their Carrollian counterparts, which supports the induced representation as the home of massive bulk excitations in Carrollian holography. This is the first bulk local state built with spin, complete from the state itself to its bulk-to-bulk propagator and to the limit relating the two descriptions.

Atomic oxygen (AO) erodes polymer surfaces in low Earth orbit, but durability data are limited. We evaluated a regression ensemble trained on 37 MISSE-2 polymers using eight selected bulk properties and five elemental-composition ratios. Its archived leave-one-out R^2(log) was 0.768; this estimate is conditional on feature selection using the complete training table. For nine post-MISSE-2 polymers, the ensemble gave R^2(log) = -0.037 and all predictions were within a factor of two. The training arithmetic-mean baseline also met that tolerance for all nine, highlighting the limited discrimination provided by their narrow target range. Ground-based comparisons included four PLAVIS grades. For an out-of-training mystery polymer with undisclosed composition, the predicted erosion yield was within a factor of 1.92 of the ground-based measurement. Conflicting PLAVIS measurement records prevent a definitive residue-erosion ordering or ground-validation score. Thermal residue, SEM contrast and surface chemistry provide distinct observational evidence; they do not establish a protective-layer mechanism. The results support further evaluation of orbital-data screening models with reconciled measurement records and prospectively fixed inputs..

The production of adipic acid generates nitrous oxide as a by-product, which, if emitted, very effectively warms the climate and depletes the stratospheric ozone layer. There exists cost-effective technology to mitigate these nitrous oxide emissions from adipic acid production, but the degree of implementation of this technology, most notably at sites in China, is uncertain. Using satellite observations from summer 2026, we quantify nitrous oxide emissions from three adipic acid production sites in China, finding emissions that total over half a million tonnes per year, a rate that implies limited emissions abatement. With respect to climate change, eliminating the annual emissions from just these three sites would be equivalent to eliminating the annual emissions from 49 coal-fired power plants or 43 million gas-powered vehicles in the United States.

Consider a finite planar graph with positive real edge weights and designated boundary vertices, called nodes. Such a graph is called a circular planar electrical network. A grove is a spanning forest in which every component contains at least one node. The connected components of a grove determine a partition of the nodes. We relate weighted grove counts to invariant theory for the symplectic group. To a planar electrical network $G$, we associate an $\mathrm{Sp}(2n)$-invariant tensor $Z_G$. For $\mathrm{Sp}(2)=\mathrm{SL}(2)$, we expand $Z_G$ in the Temperley–Lieb basis indexed by noncrossing matchings and relate its coefficients to the Kenyon–Wilson grove formulas. For $\mathrm{Sp}(4)$, we give reduction rules for superpositions of two groves and prove that the tensors indexed by $3$-noncrossing matchings form a basis of the space of $\mathrm{Sp}(4)$-invariant tensors. The coefficients of $Z_G$ in this basis are weighted counts of reduced double groves, up to normalization.

Artificial viscosity can be used to deal with shocks and other discontinuities such as star surfaces, that can arise in matter. We explain in detail how a local discontinuous Galerkin method can be used to add artificial viscosity terms to hyperbolic evolution equations. These artificial terms are multiplied by a viscosity that is non-zero only in elements that are flagged as non-smooth by a newly developed smoothness indicator. Our artificial viscosity method works well in several simple shock test cases such as with Burgers' equation and blast wave tests. For the first time, we are also able to evolve single neutron star in full general relativistic hydrodynamics. To achieve this, we use different viscosities for the momentum density than for the rest of the matter variables.

The origin of segregated axial bands for size-bidisperse particles in long rotating tumblers is a long-standing question in granular flows and a problem of both fundamental and practical interest. Using DEM simulations, we consider the streamwise and time-dependent development of the underlying instability as well as performing a broad parametric study over a wide range of particle size ratios, tumbler lengths and diameters, species fractions, and fill levels to determine the conditions under which axially segregated bands appear. We show that initial radial segregation of the small and large particles in the surface flowing layer results in a layer of mixed particles with a higher bulk density due to more efficient packing over a layer of nearly monodisperse small particles with a lower bulk density. This leads to a granular Rayleigh-Taylor-like instability that produces recirculation cells driving axial band formation. The appearance of a layer of high-density mixed particles over a layer of lower-density monodisperse particles can be directly connected to the operating conditions, explaining why axially segregated bands appear only under certain conditions. Typically, increasing the particle size ratio improves packing and increases the density of the mixed layer, enhancing the Rayleigh-Taylor instability and accelerating axial segregation.