Papers

We analyse solutions of the flow equations of the renormalisation group for the n-point Schwinger functions of scalar field theory in four-dimensional Euclidean space with nonpolynomial boundary conditions. We show that there exist UV asymptotically free solutions of this type which are Bose symmetric, invariant under the Euclidean group, analytic in the flow parameter and the momenta, and satisfy the Osterwalder-Schrader growth condition.

We solve the functional renormalization group flow of the two-flavor quark-meson model at finite temperature and quark chemical potential with Litim's regulator, using the Kurganov–Tadmor central scheme and the standard grid method, both in the local potential approximation (LPA) and in an LPA$'$ truncation with running wave function renormalization factors for the pion, sigma, and quark fields. Using the Kurganov–Tadmor scheme as a high-resolution benchmark down to very low temperatures, where the Fermi surface produces the sharpest fronts in the field derivative of the potential, we find that, with sufficiently fine resolution, the grid method gives virtually identical results in both truncations. We discuss the difficulties that the wave function renormalization factors bring into the parametrization of the model and into the flow at finite density, related to the choice of the expansion point. Contrary to some expectations, the peculiar backbending of the first-order phase boundary at low temperature, known from LPA, persists in our implementation of the LPA$'$ truncation, both with a fixed and with a running expansion point.

The long pulse of the European Spallation Source (ESS) offers unique opportunities to host more than one neutron instrument on a single beam-port. Here, we present two symbiotic instrument concepts designed for previously unexploited neutrons, without imposing significant perturbation on existing or planned beamlines. The first concept employs a doubly focusing dual-monochromator system to vertically translate the neutron beam, enabling compact instruments to be stacked within spatially constrained beam ports inaccessible to conventional instruments. The second extracts excess spectral bandwidth from an existing guide via Bragg reflection upstream of the flagship instrument's chopper system, feeding a second instrument. Both concepts are optimized using gradient-descent Monte Carlo ray-tracing simulations in McStas and benchmarked against existing productive instruments at other sources. Despite operating under significant geometric and flux constraints, the resulting instruments demonstrate performance comparable to well-established reference instruments at the ILL. The two concepts together illustrate a modular and cost-effective route to expanding ESS scientific capacity, using the facility's resources that would otherwise go unused.

We present a proof-of-concept study of neural ratio estimation (NRE) - a simulation-based inference algorithm - applied to WIMP direct detection using the XENONnT experiment as an example. A binary classifier is trained on simulated parameter-observation pairs to approximate the likelihood ratio for the WIMP mass $m_\chi$ and spin-independent proton coupling $c_p$, using realistic scintillation and ionization signals produced by the fuse detector simulation. We demonstrate that astrophysical uncertainties from halo model variations are marginalized over implicitly and at no additional inference cost by including multiple halo models in the training data. Using extreme $\pm5\sigma$ Standard Halo Model variations, we show that training on a combined dataset recovers well-calibrated posteriors even under severe misspecification, while more realistic halo models produce nearly indistinguishable results. The signal-plus-background classifier yields an exclusion limit that is both qualitatively and (after accounting for differences between frequentist and Bayesian approaches) quantitatively consistent with the XENONnT expected sensitivity. These results establish NRE as a scalable complement to the profile likelihood ratio approach, with particular advantages as experiments probe deeper into the neutrino fog.

We propose a parameter-reduced version of magnetic Moment Tensor Potential (mMTP) based on various matrix and tensor decompositions. The resulting compressed magnetic machine-learning potential reduces the number of parameters by a factor of approximately 1.5-3 without compromising predictive performance on the validation set. We evaluate the performance of the compressed potentials for magnetic, structural, and vibrational properties, as well as in molecular dynamics simulations of Fe-Al and CrN systems. We demonstrate that the simulation results obtained with the compressed mMTP are numerically consistent with those of the original uncompressed model and are in agreement with density functional theory calculations and experimental data.

We construct two superconducting pairing models on doped Kitaev honeycomb, whose microscopic kernels are derived rather than assumed. Both are driven by a bond-local glue neutral between the even- and odd-parity pairing channels; the chirality–parity linkage is set by bond-star geometry, not by the microscopic glue. (i) Model~1(odd-parity sector): the kernel follows from the flux-sector selection rule of the pure model, fixing its component-diagonal, nearest-neighbor separable, rank-one-per-bond form, with $w_\alpha=J_K^2\chi_\alpha\propto r_\alpha m_\alpha$, where $m_\alpha$ follows from the Hellmann–Feynman theorem and $r_\alpha\simeq0.24$ is computed numerically. The spin-vertex state is a unitary triplet with a bond-locked anisotropic $\mathbf d$ vector; its gap is a Gram sum of bond sines, so nodal directions are fixed by geometry. (ii) Model~2(even): the kernel is fixed by the $C_3$ little-group selection rule of a zone-corner chiral phonon, up to a Cooper-channel extension whose momentum constraint we state explicitly. The charge-vertex pairing is a $d+id$ singlet: the parity decomposition $f_\pm=g_\pm+p_\pm$ projects onto $g_\pm$, so chirality is slaved to the phonon polarization, with $C=\pm4$ and $\kappa_{xy}/T=2\kappa_0$. Reversing the pump helicity reverses the Chern number, Kerr rotation, and thermal Hall sign. (iii) General theorem: on odd-fold bond stars, the angular-momentum ladder of a single-star chiral form factor alternates in parity. Every chiral state selected by such a bond-local form factor is a geometrically enforced singlet–triplet composite with universal amplitude ratios ($n=3$: $d\oplus p$; $n=5$: $g\oplus p$ or $d\oplus f$); coherent doubled-star combinations can restore parity purity. The Chern number of the mixed state follows the dominant on-shell component across a topological boundary. The spin glue drives $C=\pm2$; the charge kernel $C=\pm4$.

We assess neutrino-assisted dark matter self-scattering in two scalar-mediator realizations by combining mediator-resolved potentials, numerical scattering calculations, thermal relic production, and the adopted observational constraints. In the $t$-channel case, the adopted laboratory and cosmological bounds suppress the neutrino force contribution at points reproducing the relic abundance and yielding sizable self-interactions, which are dominated by tree-level mediator exchange. Sommerfeld enhancement and early kinetic decoupling can change the relic abundance by up to 50% in the light mediator regime. In the $s$-channel case, thermal freeze-out fixes the coupling, leaving self-scattering well below the order of magnitude required for explanation of small-scale structure of the universe. An analytic upper envelope explains this shortfall of more than eleven orders of magnitude relative to the self-interacting dark matter benchmark. These results establish that, under the adopted constraints and thermal relic assumptions, the neutrino force cannot account for astrophysically relevant dark matter self-scattering in either realization.

We extend a time frequency framework previously developed for directly modulated lasers to external modulation of the continuous wave output of a 1550 nm DFB laser described by Langevin rate equations. Four modulators are considered an InP electro absorption modulator, a LiNbO3 dual drive Mach Zehnder modulator, a dual parallel Mach Zehnder modulator and a silicon carrier depletion modulator

We formulate equations of motion for uniform magnetization dynamics in multisublattice magnets, with emphasis on a recently proposed inertial damping torque. We include intra- and intersublattice contributions to Gilbert damping, reactive inertia, and inertial damping. For a two-sublattice uniaxial antiferromagnet in an easy-axis static magnetic field, we derive the dynamical magnetic susceptibilities and approximate eigenfrequencies across all field-dependent equilibrium phases. In particular, we show how inertial damping affects the relaxation of the nutational modes and propose an experimental protocol to determine the dynamical coefficients.

We study the influence of the ion magnetic-drift direction relative to the active X-point (favourable and unfavourable configurations) on edge turbulence, transport, and the radial electric field $E_r$ in ASDEX Upgrade and TCV. First-principles gyrokinetic simulations of the edge and scrape-off layer are performed in diverted X-point geometry using the spectral full-$f$ GENE-X code. Two matched pairs of L-mode discharges are simulated and validated against the available measurements in all four cases, showing good agreement, in particular for the $E_r$ profiles. A radial force-balance analysis shows that the deeper $E_r$ well in the favourable configuration is determined by the larger poloidal ion flow near the separatrix, which cannot be reproduced by neoclassical solvers and is identified in axisymmetric simulations as turbulence-driven. We then derive an exact evolution equation for the mean poloidal-flow acceleration from the full-$f$ gyrokinetic vorticity equation, which identifies the radial gradient of the total velocity stress as its nonlinear drive. The observed asymmetry is found to arise from stronger nonlinear energy transfer into the mean flow in the favourable configuration, associated with enhanced nonlinear $E\times B$ advection of vorticity near the separatrix and X-point. Flux-driven TCV simulations further show that the asymmetry persists at matched power more than six times the L-mode value. Assuming a critical $E_r$ at the L-H transition, this yields an estimated ratio of approximately 1.7 between the unfavourable and favourable L-H power thresholds, close to the experimental factor of two. Overall, the unfavourable configuration exhibits larger fluctuation amplitudes, a weaker $E_r$ well, stronger geodesic acoustic modes, and shorter energy confinement times for the same profiles, which may explain the observed difference in access to high-confinement regimes.

We develop a time frequency framework for the dynamics of directly modulated semiconductor lasers in which the optical field obtained from the singlemode rate equations is represented by distributions of Cohen class. Closed form small signal solutions are derived for RC filtered square current pulses and for sinusoidal modulation, including the exact chirp to power ratio with gain compression and spontaneous emission and a line expansion of the Wigner distribution of the sinusoidally modulated field. Kernels satisfying two known conditions return the laser chirp as the first conditional moment.

Quantum compilers synthesize high-level operations, such as the quantum Fourier transform and multi-controlled X gates, into gate-level circuits. Across compilation stages, a circuit may be serialized, exchanged as OpenQASM, converted between compilers, or lowered to gates. These representation changes can preserve computation while removing the high-level operation itself, leaving the receiving compiler unable to apply a requested synthesis method. We call this loss synthesis availability. We study synthesis availability in Qiskit, TKET, and Cirq through controlled experiments, repository analysis, circuits captured from project tests, and a Munich Quantum Toolkit pipeline. Synthesis availability survives serialization when deserialization restores the high-level operation and survives compiler conversion only when the receiving compiler supports that operation. It does not survive the evaluated OpenQASM routes. After a direct OpenQASM 3 round trip, requested synthesis has no effect in all 360 delivered conditions even though compilation succeeds. In the MQT pipeline, OpenQASM 2 interchange increases the two-qubit gate count by 37.2 percent for an eight-qubit Grover circuit. We also introduce Verified, which records high-level operations before a representation change and reconstructs them only when a check confirms that the record still matches the delivered circuit. Verified restores requested synthesis in all 830 recovery runs, with median verification times from 2.0 to 638 ms per operation family. The check rejects every stale record but also some valid records. These results show that preserving functional equivalence alone is insufficient when later synthesis choices depend on retained high-level structure.

A Lifshitz transition is a class of non-symmetry-breaking transitions typically associated with metallic systems wherein the Fermi surface changes its connectivity as the chemical potential sweeps through a band extremum or a saddle point. The phenomenology naturally adapts itself to the superconducting state, where the object that reconstructs is the manifold of minimum quasiparticle energy rather than the Fermi surface. This paper concerns Lifshitz-type transitions in multi-band superconductors. Thus, we focus on the attractive Hubbard–Kondo model on the two-dimensional Lieb lattice, with classical core spins coupled to the itinerant electrons, by laying recourse to a real-space Bogoliubov–de Gennes mean-field theory and an analytic Green's function calculation. The competition between the Kondo and pairing channels yields a magnetic superconductor throughout, with $(\pi,\pi)$ order near half filling giving way to $(0,\pi)$ and then, at stronger Kondo coupling, to an incommensurate spiral $(0,q)$. In such a multiband superconductor hosting a flat band, we identify two inequivalent Lifshitz-type transitions. With the core spins decoupled (the Kondo coupling set to zero), the minimum energy contour deforms with chemical potential, a hole pocket about $M$ opening into a perfectly nested square at $\mu=-2t$ and reconnecting into pockets about $\Gamma$; this nesting fixes where $(\pi,\pi)$ order sets in. At finite Kondo coupling, for certain chemical potential, the dimension of the manifold itself drops. We obtain it analytically for each magnetic order and show that only the spiral carries the minimum energy through zero, nucleating nodes and leaving a gapless magnetic superconductor, with clear signatures in the density of states and the spectral function.

In this contribution we provide a compact model for the description of inelastic x-ray scattering of spatially localized excitons. We combine our analytical theory with first principles calculations and apply it to the material lithium fluoride (LiF). A comparison of two different approaches for the underlying single-particle wave functions to calculate the spectrum yield a qualitatively good agreement with experimental data but also shows that a detailed description of the wave functions is essential to obtain qualitative results.

The dynamics of chemical reaction systems with two chemical species can be described (under mass-action kinetics) by planar autonomous systems of ordinary differential equations (ODEs) with right-hand sides containing polynomials. While their behaviour close to hyperbolic critical points is well understood, their dynamics has not been fully characterized for strongly non-hyperbolic critical points, where the linearization close to the equilibrium is given by the zero matrix. In this paper, the behaviour of such chemical reaction systems is investigated. Considering second-order chemical reaction networks with a positive equilibrium point, we show that only nine geometric equivalence classes are possible out of the sixteen classes for general ODE systems. Examples of chemical reaction networks in each class are presented. All sixteen geometric equivalence classes can be realized by chemical systems if the non-hyperbolic equilibrium point is located at the origin.

The geometric measure of entanglement of mixed states is investigated based on its relation to spin correlations. We derive an analytical expression for the entanglement of rank-2 mixed states composed of arbitrary multiqubit pure states within a two-dimensional Hilbert subspace. The dependence of the entanglement of rank-2 mixed multiqubit states on the parameters characterizing arbitrary pure states in the mixture is studied both analytically and using quantum computing. For a particular class of mixed states, namely, equal-probability mixtures of an arbitrary multiqubit state and the Schrödinger cat state, we construct quantum protocols for detecting the geometric measure of entanglement based on its relation to spin correlations. We quantify the entanglement using both the AerSimulator and the ibm_marrakesh quantum computer. The effects of quantum-computing errors are also analyzed. The simulation results reproduce the analytical dependencies, while measurements on the quantum device demonstrate good agreement with theoretical predictions within estimated error bounds.

Dense cores and clumps in massive star-forming regions are studied through (sub-)millimetre continuum observations, but inferred masses and temperatures can be biased by limited resolution, interferometric filtering, projection, and uncertain dust temperatures. We quantify how reliably core masses and temperatures can be inferred from ALMA-like continuum data using synthetic observations of such clumps. We post-processed radiation-hydrodynamic simulations of collapsing 1000 M$_\odot$ clumps with RADMC-3D and CASA to generate synthetic ALMAGAL-like images. Cores were defined around sink particles, enabling comparison of masses from the 3D simulations, idealised RADMC-3D maps, and synthetic ALMA images. We quantified how resolution, projection, and viewing angle affect core masses, and tested three dust-temperature estimators (clump-scale L/M, a L/M+flux model, and a supervised machine-learning estimate). Projection effects cause line-of-sight integrated core masses within 1500 au to exceed spherical masses by factors of two to three. The empirical L/M temperature prescription follows the global thermal evolution but misses the core-to-core scatter, producing core-mass errors of a factor of a few. Including local flux improves temperature and mass estimates, while a gradient-boosting machine-learning model suggests further improvement. Synthetic ALMAGAL-like images recover the global core structure, but flux-reconstruction uncertainties introduce mass errors up to a factor of three and limit reliable core-mass recovery to $\gtrsim 0.3$ M$_\odot$, comparable to the ALMAGAL completeness limit. Individual core masses are typically uncertain by a factor of three to five, mainly due to dust-temperature assumptions and flux reconstruction. Reducing these biases requires temperature estimates that include local core information rather than a single clump-scale L/M-based prescription.

Preferential centrality (Hellervik, Nilsson and Andersson, 2019) models spatial activity through feedback between activity and attraction. We extend it with a density penalty. The local response depends on activity per unit of capacity and scales with capacity. A correction that is uniform per unit of capacity preserves total activity, and for a chosen response function and penalty strength, conservation determines this correction. We provide prefcent, an open-source reference implementation with convergence and feasibility checks and records of each run's inputs and settings. It reproduces the 200-iteration outputs of a companion Porto Alegre study across all 65,357 network segments, with median relative differences of order $10^{-14}$. In a strong-feedback example, the penalty reduces concentration and reaches the stopping tolerance in fewer iterations. Other synthetic examples show how penalty strength changes the relative prominence of centers and how their number varies with transport costs. A further example reaches different numerical equilibria from different initial states on the same network and capacity landscape. In multi-start sweeps on three synthetic two-dimensional landscapes, distinct converged states occur over a range of parameter values: at 172 of 420 points of a grid in feedback strength and transport cost, including 75 where the states differ in their number of centers. The note provides a model specification and a reproducible computational basis for further theoretical and empirical work.

Propagating systematic uncertainties from correction weights into templates generated from simulated data while preserving correlations in the signal extraction variables becomes increasingly challenging as analyses scale in size. SysVar's lightweight API hides most of the bookkeeping complexity of applying correction weights, building systematic variations, and histogramming nominal and varied templates. This streamlines workflows that are otherwise error-prone but essential for high-precision measurements. Correlations are preserved by propagating the full covariance across the analysis and compressing it into a small set of orthogonal eigenvariations, each defining an ordinary shape nuisance parameter. In this work, we demonstrate SysVar's workflow and impact by combining two independent pseudo-measurements that benefit from consistently correlated systematic uncertainties encoded in the template shapes. SysVar is open-source, pip-installable, and experiment-agnostic.

Quantum state preparation is a basic primitive of quantum computation and control, but its resource cost is usually analyzed for one target state or under an independent-copy construction. Here we study the many-copy problem under weighted Pauli control, where a Pauli-product rotation $e^{i\phi P}$ is charged by its rotation angle $|\phi|$, independently of the weight of $P$. We derive the exact single-qubit preparation cost and show that it is strictly nonadditive: a four-pulse collective protocol prepares two $T$ states at lower cost than two optimal one-copy protocols. We further identify finite regions of the Bloch sphere with collective saving, including trajectories that remain product throughout, showing that transient entanglement is not the only mechanism behind the advantage. Complementarily, a dimension-independent Rényi-entropy speed limit gives an extensive lower bound for every coherent target and an exponential fidelity penalty below a finite preparation rate. These results establish a many-copy geometry of state synthesis in which uncorrelated outputs can nevertheless benefit from collective control.

The realization of fractional Chern insulators has largely relied on isolated flat bands in complex bilayer or multilayer moiré systems with ideal quantum geometry. Whether such phases can emerge in genuinely dispersive bands, and by what mechanism, remains an open question. Here, we propose a mechanism for magnetic-field-induced strong correlations in the highly dispersive bands of monolayer graphene on hexagonal boron nitride. In the low-field classical-to-quantum crossover regime of the second moiré miniband, we show that the interplay of the moiré potential and weak magnetic fields (B < 1.5 T) profoundly alters electron dynamics. Saddle-point van Hove singularities produce extended open orbits that strongly suppress carrier propagation, potentially favoring a regime in which Coulomb interactions become comparatively more important, while weak magnetic fields lift valley degeneracy and trigonal warping redistributes Berry curvature. High-resolution magnetotransport and temperature-dependent measurements reveal fractional-slope transport features and signatures of interaction-driven incompressibility. Because the Hall conductivity is not fully quantized and the longitudinal resistance remains finite, we describe these observations as incipient FCI behavior: transport signatures consistent with a developing fractional Chern insulating state, without claiming a fully developed FCI phase established by complete Hall quantization and vanishing longitudinal resistance. Our results suggest a possible fermiology-driven route toward correlated topological states in dispersive bands in the classical-to-quantum crossover, distinct from the conventional flat-band scenario.

We establish a criterion for the irreducibility of Verma modules over symmetrizable Kac–Moody superalgebras. Our main tool is the Weyl-Kac denominator identity.

This study combines a stochastic renormalization group (RG) in space with a path-integral description of the time evolution, giving a spatial hierarchy of coarse-grained dynamics together with the distribution over spatiotemporal paths. The RG is defined as a diffusion process that applies scale-dependent Laplacian damping together with additive Gaussian noise. The time evolution at each spatial scale is formulated as an Onsager–Machlup action, with a drift (i.e., the predictor) and white noise whose amplitude is fixed by the RG. The predictor of these dynamics is optimized by minimizing the Kullback–Leibler divergence between the path distributions from the RG and from the path-integral description. The optimal predictor contains the score function that connects the spatial scales, so the predictor and the score are two aspects of the same multiscale path formulation. The formulation unifies simulation using the predictor, unconditional generation using the score, and super-resolution using both. The predictor has no closed form, so it is computed by a neural network in two realizations that differ only in how the score is computed. The first realization obtains the score by automatic differentiation of the path distribution, remaining faithful to that formulation. The second obtains the score as an additional network output trained by denoising, at a lower computational cost. These two realizations are validated through numerical experiments on two representative multiscale systems, the Kolmogorov flow and the two-timescale Lorenz-96 model.

A growing brain tumor mechanically deforms the surrounding healthy brain through mass effect. This compression and displacement of tissue affects both patient prognosis and treatment planning, so biophysical models of tumor growth must account for this deformation. Established mass-effect models are partial differential equation (PDE) solvers that couple growth to elasticity and calibrate parameters per patient, at substantial implementation, runtime, and calibration cost. We ask how much of this deformation a fully differentiable energy-based model can recover, and introduce a potential-spring model: a regular grid over the brain is driven outward by a tumor-concentration potential and held by an elastic spring lattice with tissue-specific stiffness. It shares the tumor-gradient driving force of continuum elasticity but uses a single global parameter and no per-patient inversion, minimized end-to-end by gradient descent. We benchmark it against established solvers by applying each displacement field to a healthy atlas and measuring tissue overlap with the patient's own segmentation on 134 BraTS patients. Our model yields the largest overall local overlap improvement at up to 100$\times$ shorter computation time, establishing a lightweight, differentiable solver for tumor mass effect. Because our model obeys mechanical laws and reflects the tumor-induced tissue loading, it remains physically plausible, a prerequisite for clinical use.

We present here the FetalSenseM V2 (FSM V2), a wireless and wearable, multi-wavelength, NIRS device, based on LED illumination at six NIR wavelengths (782, 800, 818, 830, 848 and 888 nm). It utilises two sources located on the flexible wings of the sensor body, and three photodiodes placed symmetrically in its centre at 1 cm from each other. The configuration provides two sets of three source-to-detector distances (SDS) at 3, 4 and 5 cm. FSM V2 allows estimation of dynamic, relative changes in placental concentrations of HbO2, HHb and oxCCO. At the same time, the dual set of SDS also enables the use of multi-distance algorithms, such as spatially-resolved spectroscopy (SRS) and Dual Slope (DS), for estimating placental oxygen saturation (PlO2). FSM V2 is the first example of a new generation of wearable NIRS devices, paving the way for smart and advanced monitoring of placental health at bedside. The FSM V2 was successfully validated on a bench-testing, metrological platform based on optical phantoms, as well as against a gold-standard, time-domain (TD) NIRS system, before moving to preliminary examples of clinical application and usability on pregnancy monitoring trials at University College Lon-don Hospital (UCLH), conducted as part of an in vivo proof-of-concept study.

We present a computational design study of a stellarator-mirror hybrid concept, Stellarators Linking Axisymmetric Mirrors (SLAMs), in which an optimized poloidally omnigenous (OP or QI) stellarator serves as the rotational-transform-generating element that links long, axisymmetric (circular cross-section) magnetic mirrors. Starting from an OP precursor configuration obtained from the DESC omnigenity database, we construct hybrid coil sets for field period nFP = 2 SLAMs by separating the OP modular coils along the device midplane and inserting axisymmetric planar mirror coils into the resulting gap. Field-line tracing shows that nested vacuum flux surfaces survive this extrusion across a range of mirror-section lengths, with the cross-section qualitatively preserved at the point where the mirror is inserted. We use the field-line tracing data to map the shape of a surface and use the GVEC fixed-boundary solver to calculate an ideal magnetohydrodynamic (MHD) equilibrium and evaluate physics metrics such as the neoclassical transport proxy (eps_eff), the vacuum magnetic well (W), and the gyrokinetic heat fluxes (Q), providing a first-principles analysis of such concepts using modern stellarator analysis tools.

Modern asteroid surveys routinely acquire sparse photometric measurements for hundreds of thousands of asteroids. These data can be exploited to reconstruct asteroid spin states and shapes, providing statistical constraints on the rotational evolution of different dynamical populations.Our goal is to derive spin-state and shape models from publicly available survey photometry and use the enlarged sample to investigate the distributions of asteroid physical properties across the Solar System. We combined sparse photometry from Catalina, Mt. Lemmon, Pan-STARRS, ZTF, USNO, ATLAS, ASAS-SN, TESS, and Gaia and applied convex light-curve inversion to determine sidereal rotation periods, spin-axis orientations, convex shapes, phase-function parameters, and colors. The extensive parameter-space search was performed using the distributed-computing project Asteroids@home.We derived approximately 30000 asteroid models, including about 22000 unique spin-state solutions and almost 10000 partial pole solutions, tripling the number of available asteroid models. The enlarged sample confirms the dependence of the rotation-period distribution on taxonomic class, reveals a pronounced lack of elongated asteroids near the spin barrier, and shows that slow rotators exhibit systematically larger photometric residuals, supporting the interpretation that many are in non-principal-axis rotation. We derived spin-state distributions for 47 near-Earth asteroids, 247 Jupiter Trojans, and 157 Hildas. The expanded Trojan sample no longer shows a statistically significant excess of prograde rotators. The combination of modern survey photometry and large-scale light-curve inversion enables population studies based on tens of thousands of asteroid models. The resulting database provides improved constraints on the rotational evolution of asteroids

Gaussian-process limits are powerful in describing overparameterized machine learning models, yet their validity in structured tensor-network architectures remains unclear. Here we analytically present a moment-based approach that identifies precise conditions for the emergence and breakdown of Gaussian universality in tensor-network learning models, with a focus on matrix product states. We prove that in the large bond dimension limit, the learning models with both local and global observables converge to Gaussian processes, with explicit finite-size bounds on higher-order moment deviations. Whereas in the large physical dimension limit, the Gaussian universality no longer persists: while the models with local observables retain Gaussian-process behavior, those global cases exhibit persistent non-Gaussian corrections. Our results reveal that Gaussian-process behavior in tensor-network learning is controlled not only by parameter number, but also by architectural scaling, observable locality, and the spectral properties.

To account for the soft transverse dynamics overlooked by the $k_T$ factorization formalism of exclusive QCD processes, we propose introducing the intrinsic transversal momentum distribution functions (iTMDs), in conjunction with the light-cone distribution amplitudes (LCDAs), to define the probability amplitude for finding a hadron state where partons move fast along the longitudinal axis while undergoing gentle oscillations in the transverse plane. We implement this framework in the calculation of the electromagnetic form factors of the pion and the proton. Our iTMDs-improved perturbative QCD predictions show good agreement with available experimental data and lattice QCD results. More importantly, we find that higher-twist, especially subleading-twist contributions, are indispensable for explaining the scaling behavior of both pion and proton form factors at intermediate momentum transfers. Furthermore, the inclusion of iTMD effects significantly improves the perturbative QCD predictions for the pion form factor in the few GeV$^2$.

Impact-driven atmospheric loss plays a key role in shaping the diversity of planetary atmospheres. However, existing prescriptions for calculating loss from a given impact neglect the critical role of atmospheric mass on loss, and thus often severely miscalculate the extent of loss. Using 3D smoothed particle hydrodynamics simulations, we quantify atmospheric loss during giant impacts onto planets with 1-20% mass fraction atmospheres and show that less massive (lower-pressure) atmospheres are significantly easier to remove. We derive a new scaling law for atmospheric loss that includes the effects of atmospheric mass and is applicable to collisions between volatile-poor planetary embryos through to super-Earths and sub-Neptunes. Applying our scaling law to $N$-body simulations of solar system formation, we show that including the coupling between atmospheric mass and loss efficiency results in significantly more atmosphere removal. Substantial atmospheric loss events are common for smaller planets ($\lesssim$0.6 M$_{\oplus}$), whilst even roughly Earth mass bodies lose 30-100% of their atmospheres through multiple impacts. We also show that atmospheric loss during the Moon-forming impact strongly depends on both the pre-impact atmospheric mass and impact style. For a representative $\sim$100 bar pre-impact atmosphere, Earth could have lost between 20-80% of its atmosphere. In any system that undergoes a phase of giant impacts, the atmospheres of its host planets will be unavoidably shaped by the stochasticity of impacts. Our new scaling law can be readily incorporated into models of planet formation and system-wide evolution, offering new insights into the origins of planetary diversity.