Papers

The estimate of the bolometric luminosity and the radiative efficiency are two key aspects for understanding the properties of the accretion flow around a supermassive black hole (BH). In this paper, we focus on the estimate of the bolometric luminosity and the radiative efficiency of the early super-Eddington accretion flow in tidal disruption events (TDEs). Specifically, we first perform radiation hydrodynamic simulations of super-Eddington accretion flow in TDE environment, and then calculate the corresponding emergent spectra with the method of post processing for the simulation data. Based on the emergent spectra, we calculate the isotropic-equivalent X-ray bolometric correction factor $k_\mathrm{bol}$ and the radiative efficiency $\eta$ of the super-Eddington accretion flow. We find that both $k_\mathrm{bol}$ and $\eta$ are BH mass and viewing-angle dependent. $k_\mathrm{bol}$ is in the range of about a few tens to a few thousands, and $\eta$ is in the range of $\sim 10^{-3}-10^{-1}$ for BH mass in the range of $10^{6-7}M_\odot$ and the viewing angle in the range of $0^{\rm o}-90^{\rm o}$. Finally, we apply the derived $k_\mathrm{bol}$ and $\eta$ to some specific TDEs to estimate the accreted mass during an event, which can significantly alleviate the so-called missing energy problem in TDEs.

The instabilities of slender structures power biological locomotion across scales, and offer a compelling method to actuate soft robots. Nonreciprocal elastic solids have been found to amplify flexural waves in one direction only, but design principles to tune and stabilize these waves are missing. Here we develop a geometrically exact theory of nonreciprocal filaments and provide simulations that capture their post-instability nonlinear dynamics. We find that nonreciprocity, when coupled to inertia or pre-stress, amplifies and advects curvature variations. The resulting one-way patterns of shape morphing can then be selected via dissipative interactions with the environment. Our work offers a continuum-based strategy for how internal stresses can drive active unidirectional waves without need for additional degrees of freedom.

New dispersive optical model analyses of ${}^{54}$Fe and ${}^{90}$Zr together with updated results for ${}^{40}$Ca, ${}^{48}$Ca, and the earlier result for ${}^{208}$Pb shed light on the behavior of neutron skins in nuclei. Starting with a negative skin for ${}^{40}$Ca, a trend increasing somewhat stronger than linear emerges when the neutron skin of these nuclei is considered as a function of asymmetry, $(N-Z)/A$, and linked to the Green's function Monte Carlo results for asymmetric He nuclei. This general trend is consistent with the expectation that nuclei near the neutron drip line are expected to have very large neutron skins. The present analysis therefore motivates the question of which nuclei provide the most relevant link to neutron star physics.

The nonseparability of post-Newtonian (PN) Hamiltonian systems typically necessitates the use of computationally expensive implicit integrators. Recent research overcomes this limitation by embedding the dynamics into a doubled phase space, which enables the development of explicit symplectic methods. However, existing specially designed explicit integrators suffer from order reduction for high-order methods when the time stepsize is small, i.e., $h <\varepsilon^3$. In this paper, we propose a novel extension and splitting approach for the doubled Hamiltonian, under which specially designed explicit symplectic integrators can be constructed. It is shown that the proposed integrators achieve genuine high-order convergence without order reduction and take advantage of the small PN parameter $\varepsilon$. Numerical results from simulations with 2PN spinning binaries demonstrate superior long-term conservation of invariants and significantly higher computational efficiency compared to both implicit methods and existing explicit splitting techniques.

Objective. Gold-standard depth-of-interaction (DOI) calibration using collimated gamma-ray irradiation is time-consuming and impractical for system-level calibration of detector arrays. This work investigates an efficient DOI and energy calibration method for detector panels using uncollimated irradiation, with gamma rays incident nearly parallel to the crystal depth direction. Approach. The 511-keV photopeak location in a dual-ended readout PET detector block was evaluated as a function of crystal depth using collimated and uncollimated $^{22}$Na irradiation. A $4\times4$ dual-ended readout PET detector panel was then assembled. Three detector blocks were calibrated using the gold-standard method, and two uncollimated-irradiation DOI calibration approaches–a physics-informed model and a multilayer perceptron (MLP)–were compared against it. Finally, the full panel was calibrated for DOI and energy using the MLP-based approach. Main Results. The median relative RMSE between second-order polynomial fits from collimated and uncollimated irradiation was 1%, showing that uncollimated irradiation can provide reliable estimates when accurate DOI calibration parameters are available. Compared with gold-standard DOI calibration, the physics-informed and MLP-based approaches achieved RMSEs of 0.38-0.58 mm and 0.36-0.61 mm, respectively. The MLP-based approach provided better DOI resolution estimates and was therefore used for full-panel calibration. After saturation correction, the panel achieved a mean energy resolution of 15.6% and a DOI resolution of 2.0 mm. Significance. The proposed MLP-based calibration requires only a single uniform 511-keV irradiation, making it simple to implement and suitable for in situ calibration of DOI-capable PET detector arrays.

High-fidelity neutronic analyses of advanced reactors require deterministic transport solvers capable of handling complex unstructured geometries while maintaining computational efficiency. This work presents the development and verification of three GPU-accelerated deterministic solvers implemented within a unified framework, Neutronics using Deterministic Finite Element Algorithm (NuDEAL): the planar Method of Characteristics coupled with the Hybrid Finite Element Method (MOC/HFEM), the Discontinuous Galerkin Method of Characteristics (DGMOC), and the Discontinuous Finite Element discrete ordinate method (DFEM-SN). These solvers provide complementary capabilities for consistently solving the multigroup transport equation and can be selectively employed to balance accuracy, computational cost, and memory requirements for a given problem. All methods emphasize efficient GPU execution by leveraging memory alignment, compressed-flux storage, and sequential azimuthal sweeps. The solvers are validated on the C5G7 benchmark and applied to advanced reactor problems, including the ABTR, Empire microreactor, and MSRE. DFEM-SN achieved the highest accuracy, with eigenvalue errors below 50 pcm, while MOC/HFEM and DGMOC provided superior efficiency, with single-GPU runtimes comparable to those of large CPU clusters. The results demonstrate that deterministic GPU solvers on unstructured meshes can deliver both accuracy and scalability, enabling practical whole-core simulations for heterogeneous advanced reactors. The unified NuDEAL framework establishes a foundation for future extensions toward transient and multiphysics analyses on large-scale GPU architectures.

A study of the production of pairs of Z bosons (ZZ) and of the associated production of a Z boson and a Higgs boson (ZH) in final states containing two b quarks and two tau leptons (bb$\tau\tau$) is presented. The analysis is based on proton-proton collisions collected at $\sqrt{s}$ = 13 TeV by the CMS experiment at the LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. The nonresonant analysis targets the standard model ZZ and ZH processes in the bb$\tau\tau$ final state, motivated by the prominent role of this channel in searches for nonresonant Higgs boson pair production. The resonant searches target physics beyond the standard model, probing heavy spin-0 resonances X that decay into ZZ and spin-1 resonances Z' that decay into ZH, with masses in the 0.2$-$5 and 0.5$-$6 TeV ranges, respectively. Upper limits at 95% confidence level are set on the product of production rate and branching fraction $\sigma$(X)$\mathcal{B}$(X $\to$ ZZ), ranging from 300 pb to 24 fb, and $\sigma$(Z')$\mathcal{B}$(Z' $\to$ ZH), ranging from 0.4 pb to 12 fb. These are the first measurements to probe the ZZ/ZH $\to$ bb$\tau\tau$ processes. No deviation from standard model expectations is observed.

A comprehensive analysis of the energy and waiting time distributions of the bursts from FRB 20240114A detected by the Five-hundred-meter Aperture Spherical Radio Telescope between 28 January and 29 August 2024 is presented. For the full sample, its energy distribution cannot be fitted with the simple power-law (SPL),bent power-law (BPL), thresholded power-law (TPL) or Band function models, and its waiting time distribution excluding intervals shorter than 0.5 s cannot be fitted with the Poisson or Weibull models. Nevertheless, for the subsamples with more than 50 bursts in single-day observations, their energy distributions can be fitted with the BPL or TPL models, and their waiting time distributions are better described by a Weibull model. It is noted that the best-fitting BPL parameter $\beta$ is approximately invariant within the epochs before and after 21 March 2024, with an average of $\bar \beta_b = 1.006 \pm 0.074$ and $\bar \beta_a = 1.236 \pm 0.183$ (one standard deviation), respectively. Most subsamples from the later epoch have a smaller burst rate parameter $r$ in the Weibull model than those from the earlier epoch. The majority of bursts with $E>10^{39}$ erg occurred in the earlier epoch. The energy distributions in the high-energy range ($> 6\times10^{37}$ erg) differ significantly between the two epochs, and power-law fits to $dN/dE$ yield indices of $-1.97_{-0.02}^{+0.02}$ and $-2.34_{-0.06}^{+0.06}$, respectively. The median of the waiting time distribution of the later epoch is larger than that in the earlier epoch. These results suggest that the two epochs may be dominated by different types of bursts, possibly attributed to changes in the physical properties of the emission region.

Accurately resolving interfacial gradients is critical for simulating two-phase flows, particularly those involving phase transitions or active matter. The traditional diffuse-interface immersed boundary methods (IBMs) are highly efficient for such problems, but they typically suffer from a reduction to first-order accuracy near the phase-changing boundaries. We clarify that the main reason is the local derivative discontinuities. Here, we propose a smooth extension strategy to restore formal second-order spatial accuracy. By extrapolating the scalar field across the interface, the method structurally ensures derivative continuity. To preserve the divergence-free condition in incompressible fluid solvers, this smooth extension is applied exclusively to the scalar transport equations. The velocity field retains the standard diffuse-interface treatment. The proposed framework is systematically validated against classical phase-change benchmarks, specifically one-dimensional evaporation and boiling problems. Additionally, the method is applied to the spontaneous autophoretic motion of isotropic particles. The numerical results confirm the capability of our method in resolving the complex multi-physics boundary couplings.

We performed a spectroscopic observation of an erupting prominence occurred on the solar limb on 2015 May 8th in He I 706.5 nm, O I 777.2 nm triplet and Ca II 849.8 nm lines to investigate differences in the Doppler velocity between ions and neutrals in a plasma strongly accelerated by the Lorentz force. We found that the ion-neutral velocity difference between Ca II and He I reached an order of 15 km s-1. On the other hand, the velocity difference between Ca II and O I was significantly smaller than that between Ca II and He I. This result can be interpreted as the formation of O I 777.2 nm lines in the erupting prominence is mainly contributed by the recombination from O II ions through charge transfer with hydrogen atoms, resulting in a behavior close to ions. According to an order estimate of the collisional friction among He I atoms and protons, the observed velocity difference between Ca II and He I implies the acceleration of the eruption reaching about 150 times of solar gravity. We propose a new method to evaluate the ionization degree of hydrogen from the velocity differences observed in Ca II, He I and O I lines.

Establishing quantum simulations as reliable tools for materials research requires quantitative validation against experiments and, where available, classical many-body calculations. For dynamical spin response, such validation remains challenging because experiment, classical simulation, and quantum simulation do not produce the same native observables. This challenge is increasingly relevant as quantum simulation protocols for dynamical response progress from theory to hardware-level benchmarking against neutron scattering data. The longer-term goal is to extend validation to classically intractable regimes accessible through future fault-tolerant implementations. Here, we develop a cross-pipeline validation framework for quantum simulation of dynamical spin response, using inelastic neutron scattering and classical many-body simulation as complementary experimental and computational anchors. The framework brings these pipelines to common momentum- and energy-resolved comparison levels through explicit forward and inverse observable maps, propagates uncertainty via covariance matrices or resampling, tests robustness to structured distortion, and evaluates agreement using a hierarchy of complementary metric families. It distinguishes stochastic uncertainty from robustness-induced distortion, carries both through the comparison chain, and uses the resulting metric-level uncertainty and distortion information to support layered validation at the pipeline, solver, and model levels. We also introduce actuator-aware feedback logic to improve agreement without obscuring the physical origin of any remaining mismatch. We close by outlining future extensions of this methodology, including upstream uncertainty and distortion modeling, adaptive feedback, asymmetric validation beyond full classical benchmarking, fault-tolerant workflows, and community infrastructure for reproducible validation.

Optimal encoding of classical data for quantum-assisted statistical inference is investigated from an information-theoretic perspective. We prove that the accuracy of any quantum-computing inference procedure is upper bounded by the maximal quantum leakage from the classical data through its quantum encoding, establishing leakage as a universal, task-agnostic quality measure for encoders. The optimal encoding strategy, i.e., an encoding strategy that maximizes the maximal quantum leakage, is proved to be attained by pure states. When there are enough qubits, basis encoding is proved to be universally optimal. However, when the dimension of the system is small, phase encoding is optimal. For the latter, the optimal encoding is not unique. That is, any tight frame, any ensemble whose average state is the maximally mixed state, is in fact optimal. Within tight frames, equiangular tight frames (ETFs) are distinguished as the uniquely symmetric optimal encodings, i.e., they saturate the Welch lower bound on pairwise overlaps. Prominent special cases are the qubit trine, the regular simplex, and symmetric informationally complete positive operator-valued measures (SIC-POVMs), for which the ETF structure and explicit codeword constructions are provided. Numerical examples are presented to validate the theoretical predictions.

Quantum algorithms for quantum chemistry and other many-body fermionic systems work by expressing the Hamiltonian in a basis of qubits and fragmenting the Hamiltonian into a sum of products of Pauli operators whose exponentials are easily encoded on a quantum device. Applying the product of exponentials, known as Trotterization, leads to an error associated with the non-commutativity of operators. This error can lead to breaking the symmetries of the Hamiltonian because the fragments are not symmetry conserving in general. Nonetheless, many algorithms for time evolution rely on Trotterization, including time evolution and quantum phase estimation. We show that we can express the Hamiltonian in terms of Hermitian excitation operators which map to sums of commuting Pauli strings for any encoding and conserve symmetries corresponding to Abelian groups of symmetry operators. Symmetries corresponding to non-Abelian groups, on the other hand, are not fully conserved by Trotterized Hermitian excitation operators, so we developed “operator kirigami” to cut the sum of non-commuting operators by orthogonal projection and to fold terms together using unitary rotations. We tested pools of operators for small molecules and basis sets, and found that electron number and spin symmetry conserving pools led to greater errors that decreased for larger molecules and were negated with second-order Trotterization. Our work shows the potential for testing quantum computing algorithms on classical computers by adapting tools used in electronic structure theory with conserved symmetries.

The young (10-30 Myr) multi-planet system V1298 Tau presents a unique opportunity to probe the early formation and evolution of young systems. We present new CHEOPS observations of the three innermost planets, yielding high-precision planetary radii ($\sim$5-11 $R_\oplus$ ) and improving the radius ratios (Rp/Rs) by 30-71% compared to previous multiple TESS observations. Combined with refined period and mass determinations from transit-timing variation (TTV) measurements, we derive revised bulk densities (0.06-0.23 g/cm$^3$) for these planets. We find that the innermost planet c is denser compared to the outermost planet at the 3.4-$\sigma$ level, while the bulk densities of the three outermost planets are consistent within the reported uncertainties. These bulk densities suggest differing envelope mass fraction across the system, indicating differential atmospheric evolution in the young system. We further assess the early dynamical state of the V1298 Tau system and find that within the range of simulations performed we find no evidence for present-day mean-motion resonance trapping. As an independent diagnostic, we compute the forced eccentricities and low Normalized Angular Momentum Deficit (NAMD) exhibited by the system. Our simulations suggest that no past dynamical excitation is required to explain the present orbital architecture.

Physics-informed neural networks (PINNs) provide a mesh-free framework for solving partial differential equations, yet their performance in nonlinear problems is often limited by slow convergence, gradient imbalance, and insufficient resolution to capture localized intermittent structures such as shock waves[1]. These issues arise primarily from the use of fixed weights of loss and uniform collocation point distributions, which cannot adapt to the evolving complexity of the solution field during training. To address these challenges, Gradient-Guided Gaussian Adaptive Sampling Physics-Informed Neural Networks (3GAS-PINNs) is proposed in this paper, which combines uniform probability distribution and Gaussian-smoothed probability distribution derived from the spatial gradients of solution, to maintain global constraint satisfaction as well as concentrating collocation points in regions of high gradient. Thus, intermittency structures like shock wave and solitons can be accurately captured. The method is evaluated on three benchmark nonlinear problems, including one-dimensional forced Burgers equation, Korteweg-de Vries (KdV) equation and nonlinear Schrodinger equation, all of which exhibit steep gradients or strong nonlinearity. In comparison with baseline PINNs, 3GAS-PINNs can effectively promote the physical consistency in intermittent regions. The accuracy of the numerical simulation can be improved by a factor of up to 14.

In association football, collective player motion is organized around the ball. We ask whether this many-agent motion can be described by an effective field analogous to gravitational attraction, emphasizing that the measured quantity is a radial drift velocity, as in overdamped dynamics, rather than a Newtonian acceleration. Using public tracking data from ten matches, we characterize this radial drift velocity through the distance-dependent mean D(r) and the ball-position-dependent field K(x,y). After excluding restarts and other constrained phases of play, both goalkeepers, the player nearest to the ball, and small player-ball separations, a persistent inward drift velocity remains, with a global mean of about 0.9 m/s. The distance dependence is not described by an inverse power of r: D(r) decreases at short range and then forms a broad plateau that persists to the largest measured separations. The mean K(x,y) is positive over most of the pitch, with a central depression about 15 percent below the non-goalmouth average and stronger suppression near the goalmouths, where the mean drift velocity becomes slightly negative, corresponding to weak effective repulsion. The role-resolved D(r) shows a pronounced defender minimum near 12 m and a pronounced attacker maximum near 60 m, whereas only defenders produce effective repulsion near the goals in K(x,y). These results show that football tracking data can reveal simple effective laws of active many-body motion while retaining clear signatures of player role and pitch geometry.

Galaxy clusters act as powerful gravitational lenses that provide a unique laboratory for studying the distribution of dark matter and the properties of faint background galaxies. In the radio regime, cluster lensing studies remain largely unexplored due to the intrinsically low surface density of background radio sources, which limits the number of detectable lensed systems and constrains the application of cluster-scale lensing to cosmological and astrophysical investigations. In this paper, we outline how the SKA will transform cluster lensing studies through its unprecedented sensitivity, angular resolution, and survey speed. These capabilities will enable dense sampling of lensed background radio sources and high-fidelity reconstruction of cluster mass distributions, while revealing a previously inaccessible population of faint ($\mu$Jy-level) galaxies, primarily at $z \sim 1-5$. We focus on three key science goals: (i) constraining dark matter substructure in galaxy clusters through improved strong-lensing constraints, (ii) characterising the non-thermal baryonic components of the intracluster medium, and (iii) building statistically significant samples of $\mu$Jy-level lensed galaxies to study star formation and active galactic nuclei activity across cosmic time (primarily at $z \sim 1-5$). Together, these advances will establish cluster-scale radio lensing as a powerful probe of structure formation and galaxy evolution in the SKA era.

Physics-informed neural networks (PINNs) provide a mesh-free framework for solving partial differential equations, but their training is often affected by loss imbalance, optimization stiffness, and difficulty in capturing localized or multi-mode solution structures. Hard-soft PINNs (HSPINN) alleviate part of this difficulty by embedding Dirichlet or periodic constraints directly into the trial space, but the resulting fixed admissible representation can still be poorly conditioned for sharp or heterogeneous residual fields. This paper proposes a reliability-aware hard-soft PINN (RA-HSPINN) that preserves exact embedded constraints while introducing a bounded learnable reliability field to modulate the interior representation. The method combines this reliability-aware ansatz with inverse-EMA global loss balancing and lightweight regularization, while retaining the standard mean-square residual form. The reliability field is a numerical modulation variable, not a physical parameter or calibrated probability. RA-HSPINN is evaluated on nonlinear Burgers equations, periodic convection, a mixed-boundary Poisson problem, and a mixed first-order Poisson system. Compared with HSPINN, it reduces the relative error by $98.65%$ for sharp-gradient Burgers, $72.42%$ for Burgers data with noisy and incompatible initial conditions, $61.18%$ for smooth periodic convection, $60.02%$ for localized periodic convection, $29.36%$ for mixed-boundary Poisson, and $82.17%$ for a multi-mode mixed first-order Poisson system. The results show that reliability-aware modulation is most beneficial when hard-soft trial spaces are admissible but difficult to optimize, especially in localized, unreliable-data, and multi-mode PDE regimes.

Motivated by dry dambreak flows, a perturbative framework for solving the 1D shallow water equations (SWE) over parabolic bathymetry, together with the inviscid Burgers' equation, is developed. Expressed in Riemann variables, the solutions are expanded as analytic power series in the bathymetric curvature $\omega^2$ and summed in closed form in terms of trigonometric functions. The solutions, termed generalised rarefaction waves (GRWs), exhibit finite-time singularities and are shown to describe the asymptotic behaviour of the fluid near dry (vacuum) points. The GRWs bear direct relevance to wave run-up at a shore. A repulsive parabolic hill bathymetry is also considered, yielding solutions in terms of hyperbolic functions. The connection to the nonlinear Schrödinger/Gross-Pitaevskii equation that models Bose-Einstein condensates confined in a harmonic potential is discussed. The analytical results agree with direct numerical simulations of the Burgers' equation and of the SWE in different scenarios.

We prove a complete asymptotic expansion for quantum neural network operators when they approximate arbitrary quantum channels. This is the non-commutative analogue of the classical Voronovskaya theorem. The expansion reveals that the approximation error splits into three fundamentally different parts: integer powers of \(1/n\) involving ordinary Fréchet derivatives; fractional powers governed by Marchaud fractional derivatives, which capture the Hölder smoothness of the channel; and purely quantum commutator terms that have no classical counterpart. The remainder is bounded sharply by an explicit constant: \[ \norm{R_{m,n}(\Phi,\bullet)}_\diamond \le C_{m,\gamma,d} \|\Phi\|_{\cC^{m,\gamma}} \, n^{-(m+\gamma)} (\log n)^{3m/2}. \] We present a numerical test for a classical analogue that confirms the predicted convergence rate and the logarithmic correction, directly validating the asymptotic theory. Based on this expansion, we obtain three major advances: a quantum central limit theorem for the fluctuations of quantum neural network operators, a method to construct optimal interpolation geodesics between quantum channels via Kubo-Ando means, and a systematic understanding of how fractional smoothness limits the acceleration of quantum neural network approximations. The numerical test further demonstrates that the theoretical rates are sharp and that logarithmic enhancements are unavoidable. Altogether, our work builds a rigorous bridge between classical approximation theory, fractional calculus, and quantum machine learning, offering both theoretical insight and practical tools for designing and analyzing quantum neural networks in finite dimensions.

In this study, we reconstruct the dark energy (DE) as a Dirac-Born-Infeld (DBI) scalar field from the Hubble dataset (32 CC + 26 BAO) and the DESI dataset using the Gaussian process (GP). As the GP is a non-parametric and model-independent way to reconstruct a function and its derivative using the data, our reconstruction of the DE equation of state, the DE density parameter, and the potential does not assume any particular model of cosmology. Using Monte Carlo realizations of the GP-reconstructed expansion history, we derive a posterior estimate of the Hubble constant, obtaining $H_0 = 69.53 \pm 2.68$ km s$^{-1}$ Mpc$^{-1}$. This method offers a fully model-independent estimate of $H_0$, relying only on data and GP priors, and provides an unbiased intermediate value useful for reassessing the Planck-SH0ES tension. Using the reconstructed profiles of the scalar potential as a function of the field $\phi$, along with their associated uncertainties, we perform a chi-square curve fitting procedure to assess the viability of four different scalar field potentials, such as Exponential, Power-law, Free Field (quadratic), and Higgs-like potential. This allows us to identify which potential best fits the reconstructed data. We also employ MCMC analysis to place quantitative constraints on the model parameters associated with each potential. Furthermore, we do a $\chi^2$ analysis for all four potentials and comment on the goodness of the fit for each of them. Finally, we discuss possible generalizations of our model-independent framework and outline the phenomenological implications of our findings.

In homogeneous magnetohydrodynamic (MHD) turbulence without a background magnetic field driven by mechanical forces, an exact decomposition of the energy fluxes (D. Capocci et al., Journal of Plasma Physics, 91(1), E11 (2025)) has shown that current-sheet thinning is the dominant physical mechanism responsible for transferring energy from large to small scales. In contrast, mechanisms that are characteristic of hydrodynamic turbulence, such as vortex stretching and strain self-amplification, are strongly suppressed. Here, we extend this analysis to MHD turbulence in the presence of weak and strong imposed magnetic field, as previously driven by mechanical forces, and confirm that current-sheet thinning remains the leading process driving the energy cascade toward smaller scales in these more realistic configurations, and find enhanced scale invariance in the subfluxes. In addition to that, a decomposition of the contributions from the fluctuating and the background magnetic field to the conversion between kinetic and magnetic energies shows that the background-field-dependent contribution results in a nonlinear dynamo, that is an effective kinetic-to-magnetic conversion at large and intermediate scales. However, at small scales, it has the opposite effect, resulting in a net conversion of magnetic to kinetic energy.

In our previous work [arXiv:2504.06248], we adopted Koopman theory to link the existence of different constants of motion to the presence of specific network motifs of Kuramoto oscillators. Yet, it remains to be shown how the partial integration can be carried out using the Koopman generator and its eigenfunctions. In this paper, we construct a random graph from network motifs that admit Koopman eigenfunctions and conserved quantities, and use it to define a partially integrable Kuramoto model. We perform the partial integration of the introduced model when there are monomial eigenfunctions and conserved cross-ratios, while providing an operator-theoretic derivation of the Watanabe-Strogatz transformation based on Magnus expansion and a recent result on closed forms of the Baker-Campbell-Hausdorff formula [arXiv:1502.06589].

The Multi-Level Intermediate Representation (MLIR) framework has become a cornerstone for building extensible, domain-specific compilers, with the quantum computing community already leveraging it to model quantum programs and implement basic optimizations. However, computationally intensive tasks in the quantum compilation pipeline, such as quantum circuit mapping, remain underexplored within the MLIR ecosystem. This paper proposes an MLIR-native blueprint for these non-local, quantum-specific optimization routines by reimplementing a well-established, state-of-the-art mapping A* search algorithm for qubit routing and SWAP insertion. Our evaluation demonstrates that this approach not only integrates seamlessly into an MLIR-based quantum compiler collection but also surpasses previous non-MLIR solutions in both solution quality and runtime. The implementation is open-source and publicly available at https://github.com/munich-quantum-toolkit/core.

At first glance, combining Newton's laws of motion with his law of gravitation seems straightforward. Students learn to distinguish inertial from gravitational mass and that their empirical equality is a remarkable fact about nature that will later serve as the conceptual gateway to general relativity. However, a closer look reveals a further and often neglected distinction within Newtonian gravity: that between active and passive gravitational mass. A common textbook argument maintains that these must be equal, for otherwise Newton's third law would be violated. We review and critically re-examine this familiar reasoning and show that the supposed theoretical proof is not compelling. Our analysis highlights subtle structural assumptions within Newtonian mechanics and offers physics teachers and researchers a fresh opportunity to explore foundational questions with potentially interesting applications in observational astronomy. In addition, an extended appendix, which is not part of the published AJP paper, offers some mathematical background material on the Galilean group and its action as group of dynamical symmetries for the type of dynamical equations considered here.

It was observed [2606.30426] that our recently constructed electrovacuum [2606.23782], supported by electromagnetic fields, can be locally transformed to a special Petrov type D solution within the general Kundt class, which is not an electrovacuum but instead describes a spacetime generated by (accelerating) electric and magnetic charges. In this short note, which serves as a supplemental to [2606.23782], we analyse the major global differences between the two locally-equivalent solutions.

Matter inside neutron stars is compressed to densities several times greater than nuclear saturation density, while maintaining low temperatures and large asymmetries between neutrons and protons. Neutron stars, therefore, provide a unique laboratory for testing physics in environments that cannot be recreated on Earth. To uncover the highly uncertain nature of cold, ultra-dense matter, discovering and monitoring pulsars is essential, and SKAO will play a crucial role in this endeavour. In this chapter, we will present the current state-of-the-art in dense matter physics and dense matter superfluidity, and discuss recent advances in measuring global neutron star properties (masses, moments of inertia, and maximum rotation frequencies) as well as non-global observables (pulsar glitches and free precession). We will specifically highlight how radio observations of isolated neutron stars and those in binaries – such as those performed with SKAO in the near future – inform our understanding of ultra-dense physics and address in detail how SKAO's telescopes unprecedented sensitivity, large-scale survey and sub-arraying capabilities will enable novel dense matter constraints. We will also address the potential impact of dark matter and modified gravity models on these constraints and emphasise the role of synergies between SKAO and other facilities, specifically X-ray telescopes and next-generation gravitational wave observatories.

Width-balance conditions at a junction are often associated with reflectionless transmission, or transparency, in some one-dimensional wave models on networks. We show that, on cyclic networks, this identification is incomplete: local balance is a vertex-level condition, while transparency also requires synchronization of the path travel times. To make this precise, we consider a shallow-water wave model and derive the channel-width-weighted scattering law for a vertex of arbitrary degree and introduce a source-relative definition of balance, reflecting the fact that the same junction may be reflective or reflectionless depending on which edges carry incoming waves. Under this definition, a balanced vertex is transparent only to the synchronized incoming-amplitude direction. For an \(N\)-path island, the resulting first-generation upstream reflection is governed in frequency space by the width-weighted distribution of path delays. Exact broadband cancellation requires all path travel times to agree; when they do not, commensurability of the path-length differences produces a periodic comb of frequency-selective zeros, independent of channel widths. At $N\ge 4$ we further exhibit a hybrid regime in which the reflection factor vanishes without commensurability among the path lengths.

We investigate fluid mixing induced by microswimmers using mutual information as a global, information-theoretic measure of mixing efficiency. For a two-dimensional squirmer model in a confined domain, we compute numerically the swimmer-generated flows and solve the advection-diffusion equation for the transport of tracer particles in the fluid. We show that the spatial distribution of swimmers strongly affects mixing, which is suppressed by swimmer aggregation and enhanced by positional and orientational disorder. At fixed energy dissipation, mixing efficiency depends non-monotonically on the squirmer parameter, with an optimal finite value arising from the balance between swimmer translation and dipolar flow generation. When hydrodynamic interactions are included, pushers outperform pullers. The mutual information as a function of time decays in three stages: an initial diffusion-dominated stage, an intermediate advection enhanced regime, and a final relaxation stage controlled by system size. Our results demonstrate that mutual information, previously validated as a measure of mixing efficiency only in simplified model systems, can equally be used in complex flows. Its application reveals that mixing by microswimmers is subject to a trade-off between the generation of strong shear flows and achieving optimal dispersion across the fluid domain.

The inverse scattering transform (IST) provides the standard theoretical framework for deriving soliton dynamics. Traditionally, such derivations have been of an analytical, rather than data-driven, nature. In this paper, we combine the conceptual framework of the IST with weak-form system identification methods to discover effective soliton dynamics directly from observed scattering data, without assuming prior knowledge of the scattering equations. Our method avoids parameterizing solitary waves via ad hoc curve-fitting by working in the scattering domain, yielding interpretable low-dimensional models that remain valid in perturbed and near-integrable regimes. We demonstrate the performance of the proposed approach on synthetic and experimental data governed by shallow-water equations of Korteweg–de Vries-type and recover models that are consistent with canonical IST theory.