Papers

Computing neutrino oscillation probabilities is a solved problem; computing their derivatives is not. We present MANGO (MANGO: A Neutrino Gradient Oscillator), a composable oscillation engine in which every computed quantity is differentiable with respect to all inputs, including propagation geometry, detector depth, and individual Earth-shell densities. None of these quantities appear in traditional analytic probability formulas. The engine supports vacuum, constant-density, layered-PREM, arbitrary-profile, and adiabatic solar propagation, alongside front-ends for non-standard interactions, 3+N sterile states, decoherence, and non-unitary mixing. Because reverse-mode cost depends on output rather than input dimension, evaluating sensitivities incurs a constant 2.5-3x forward-pass overhead. As a result, calculating sensitivities for all 369 density, electron-fraction, and shell-radius parameters of a layered Earth costs no more than the 6 standard oscillation parameters. By maintaining exact sensitivity signals, MANGO allows gradients to flow continuously past the probability stage and through detector response, event weighting, binning, and likelihoods. We demonstrate this on a stylized Earth-tomography analysis. In a single pass, MANGO computes the marginalized uncertainty on a six-zone radial density model and, by differentiating through the inverse Fisher matrix, evaluates its sensitivity with respect to detector angular resolution. This provides an experimental-design metric unreachable using traditional analytic probability formulas. Three-flavor and layered-Earth probabilities match external benchmarks (OscProb, NuFast-Earth) to within 10^-9 to 10^-5, while all forward models, BSM limits, and differentiation paths are verified against exact analytic solutions and finite differences.

Bond-dependent magnetic interactions, exemplified by the Kitaev model, are known to arise from the interplay between spin-orbit coupling (SOC) and specific coordination geometries, but have so far been almost exclusively identified in edge-sharing octahedral systems. Whether such interactions persist in edge-sharing tetrahedral environments, characteristic of the parent compounds of iron-based superconductors, remains an open question. Here, we construct a Kitaev-like model for monolayer FeTe and FeSe and demonstrate the presence of a previously unrecognized bond-dependent Ising-type interaction, induced jointly by chalcogen-mediated SOC and the tetrahedral crystal-field geometry. A microscopic spin model for these bond-dependent interactions is derived via strong-coupling perturbation theory, and the strengths of the individual exchange terms are extracted by partitioning the magnetic anisotropy energy calculated using density functional theory across various collinear magnetic orders. We reveal that the Kitaev-like interaction dominates the magnetic anisotropy in FeTe, whereas in FeSe, it strongly competes with a single-ion anisotropy of opposite sign. The resulting noncollinear local anisotropy axes generate intrinsic single-site spin frustration, providing a microscopic mechanism for magnetic disorder that transcends isotropic exchange models. Our results establish edge-sharing tetrahedral magnets as a new platform for bond-dependent interactions and extend the scope of Kitaev physics beyond octahedral coordination.

Aerodynamic unsteadiness is inherent to the operation of many engineering applications, especially those that involve large-scale rotating blades, such as modern wind turbines. Over the past few decades, wind turbine rotors have grown rapidly and are now exceeding 200 meters in diameter, causing them to operate in conditions where limited empirical data are available, and where models have not been validated. Here, we use a highly pressurized wind tunnel to probe these conditions and evaluate the quasi-steady approximation, often used to simplify the modeling of the unsteady aerodynamic response of an airfoil to slow changes in inflow conditions. We find that the quasi-steady approximation is not valid for a large range of frequencies where it is normally applied. This finding suggests that the loading on wind turbine blades will be significantly underestimated when using conventional models, especially near stalling conditions, which modern wind turbines typically encounter.

Transition metal borides are attracting increasing interest due to their unique properties. They are not only characterised by very high hardness, but also considerable chemical and thermal stability. Silver, on the other hand, is a good material for increasing electrical and thermal conductivity, wear resistance and has antibacterial properties due to its biological characteristics. Combining these two materials can provide superhard bilayers with increased functional properties. In this study, it was decided to synthesise Ag/WB2.5, Ag/W0.76Ti0.24B2.5 coatings and compare their properties to the individual components. The silver coating was produced by pulsed laser deposition (PLD), while the WB2.5 and W0.76Ti0.24B2.5 coatings were formed by high-power pulsed magnetron sputtering (HiPIMS). To determine the mechanical properties, nanoindentation tests, adhesion of the coatings by scratch -test and wear resistance by abrasion in reciprocating motion were tested. In all cases, the silver film contributed to an increase in the wear resistance of the materials without major changes in the hardness results of the materials. In addition, the Ag/W0.76Ti0.24B2.5 film showed very good adhesion to the substrate. Human hand wiping simulator was also carried out using - Tribotouch. After 36 000 cycles Ag/W0.76Ti0.24B2.5 coating was slightly deformed, which was not visible macroscopically. This result is more than three times greater than for the pure silver film. It was also decided to carry out corrosion tests in an environment of 0.9% NaCl. The Ag/W0.76Ti0.24B2.5 bilayer has very good corrosion resistance, similar to pure silver.

It has been known for a long time that the equation of motion for dissipative linear dynamical systems with constant coefficients cannot be derived from the classical principle of stationary action because the term proportional to velocity in the equation of motion leads to the time derivative of order one half in the Lagrangian. Thus, approaches utilising fractional calculus have been used; however, they suffer from deficiencies both from mathematical and physical points of view. We here present our version of such fractional calculus based approach that provides correct Euler-Lagrange and, ultimately, the Hamilton equations, energy change of the moving body, and an attempt for a geometric interpretation of how energy dissipates.

Context. Galaxy clusters are extreme environments where interactions with the hot intracluster medium drive rapid galaxy evolution. These processes can result in the formation of optically dark gas clouds, as previously observed in Virgo and other clusters. Aims. We investigate the distribution and properties of neutral hydrogen (HI) in two large adjoining regions of the Virgo cluster to understand how the cluster environment influences galaxy transformation. Specifically, we examine the gas content of both star-forming and quiescent populations and search for evidence of gas-loss driven evolution. Methods. We cataloged the 21cm HI Widefield Arecibo Virgo Extragalactic Survey (WAVES) South data using visual and automatic source extraction methods. By combining these results with an optically selected sample, we compared the HI properties of WAVES South with the previously studied VC1 region. To probe gas reservoirs below the nominal detection limit, we performed a stacking analysis of radio spectra across the WAVES South, VC1 and VC2 footprints. Results. We detected 56 HI sources with a median root mean square (rms) noise of 0.8 mJy, including 50 galaxies, two gas clouds (one being optically dark), and the ALFALFA Virgo 7 complex. Our results reveal a significantly lower detection fraction in WAVES South compared to the VC1 region. Stacking showed no new HI detection at a 0.080 mJy rms with a maximum of 157 stacked objects from WAVES South, VC1, and VC2. Conclusions. The lower HI detection fraction suggests that WAVES South is a more dynamically relaxed and evolved environment than the VC1 region. The presence of residual HI in a small subset of early-type galaxies supports a model of dwarf irregular to dwarf elliptical transformation via environmental stripping. Finally, we note a possible evolutionary link between optically dark clouds and recently discovered "blue blobs."

This article contrasts the concepts of a proper condensate and the Onsager-Penrose criterion for Bose-Einstein condensation in the form of a debate between two proponents of the respective concepts. The prologue briefly introduces the two criteria. The epilogue contains remarks on properties of the underlying resolvent algebra that are physically relevant in this context.

Recently we started building a bridge between two cases of Langlands duality. The latter is one of the most influential topics in mathematical research. It has many different appearances and influential subtopics. Yet there is a topic that until now seems unrelated to the Langlands program. That is the topic of invariant differential operators. That is strange since both items are deeply rooted in Harish-Chandra's representation theory of semisimple Lie groups. We started with the case of the group ~$SL(2n)$. In the present paper we deal with the group $SL(2n+1)$. The two mentioned groups are similar, but their representation theories is rather different.

Interference of optical signals in free-space channels requires optical receivers to support many spatial modes due to atmospheric turbulence, typically necessitating adaptive optics systems. Angle-compensated interferometers offer a passive alternative, making them particularly attractive for time-bin encoded signals with delays on the order of one nanosecond. Here, we demonstrate a multimode angle-compensated interferometer design that achieves a high interference visibility for spatially multimode beams with large time bin separations. The interference of the multimode beams is enabled using an imaging multi-pass Herriott cell that enables a very long path separation with a small form-factor. The design is tested using both numerical ray-tracing simulations and proof-of-principle demonstrations. We create a prototype interferometer with a path length difference of 12ns and determine that it maintains a high interference visibility with a large field-of-view of $0.4^{\circ}$.

Intermittent departures from nominal Kelvin–Helmholtz shedding can produce rare and pronounced drag excursions in transitional airfoil flow. We examine these events using two-dimensional direct numerical simulations of flow over a NACA0012 airfoil at an angle of attack of $5^\circ$, a freestream Mach number of $0.4$, and chord-based Reynolds numbers of $5\times10^4$ and $5\times10^5$. At the lower Reynolds number, event-resolved analysis shows that individual primary vortices are released from the separated shear layer through the eruption of wall-generated, opposite-signed secondary vorticity. Each eruption interrupts the connection between a developing primary vortex and its feeding shear layer, releasing the vortex downstream. During nominal shedding, the vortex reaching the trailing-edge region is associated with a single such release and remains sufficiently isolated to pass the trailing edge without strong collective interaction. Extreme events instead arise through clustered vortex release, in which several secondary-vorticity eruptions occur within a short interval and produce a compact group of primary vortices with small initial streamwise spacing. Differential convection further reduces their spacing and promotes strong near-trailing-edge interactions, where the combined pressure footprint of these vortices produces a localized suction peak and a sharp increase in drag. These interactions range from prolonged deformation and filamentation to rapid core coalescence. Similar compact vortex organization and near-trailing-edge interactions are recovered at $Re=5\times10^5$, indicating that the downstream event pathway persists despite the smaller vortical scales.These findings suggest that controlling vortex-release timing through secondary-vorticity dynamics may provide a route to disrupt clustered release and mitigate extreme aerodynamic loading.

We study non-perturbative quark-antiquark pair production and the subsequent quark dynamics in the earliest glasma stage of relativistic heavy-ion collisions. For that, we develop a new model, WAGASHI (Wong-precessing Anisotropic Glasma And ScHwinger-produced Initial-conditions), which combines classical Yang-Mills glasma evolution, Wong-equation transport, and Schwinger pair production on an event-by-event basis. We find that a sizeable number of quarks, comparable to the final hadron yields, are produced already during the glasma stage and subsequently undergo substantial momentum broadening and spin randomization, suggesting a significant contribution toward the early equilibration of the quark-gluon plasma. We also determine the event-by-event distributions of baryon number, electric charge, strangeness, and spin polarization in Pb-Pb and O-O collisions at LHC energies, finding particularly large fluctuations in the smaller O-O system. These results provide dynamical initial conditions for the subsequent hydrodynamic evolution of the quark-gluon plasma.

We investigate the thermodynamic behaviour of an AdS black hole arising from nonlinear electrodynamics-corrected gravity, incorporating quantum effects through thermal fluctuations. From the Einstein–Euler–Heisenberg framework, we consider the modified black hole solution and analyse its thermodynamic properties in the extended phase space. Logarithmic and inverse-area corrections to the entropy are obtained, leading to modified expressions for enthalpy, internal energy, Helmholtz free energy and Gibbs free energy. The corrected specific heat exhibits multiple divergences and sign changes, signalling genuine second-order phase transitions and revealing a quantum-stabilized microscopic phase followed by universal macroscopic instability. Our results demonstrate that thermal fluctuations qualitatively restructure the thermodynamic phase space and highlight the dominant role of quantum corrections in governing the black hole stability.

Magic plays a dual role in quantum computation: it promotes stabilizer dynamics from efficient classical simulability to computational universality, but also challenges fault-tolerant architectures, since non-stabilizer operations are harder to protect against noise. Magic state distillation addresses this issue, yet existing protocols remain largely tailored to specific assumptions about the input or noise model and, more fundamentally, no general information-theoretic theory of optimal magic-state conversion currently exists. Here we develop such a characterization for pure qubit states through universal magic state concentration: a fixed stabilizer protocol that converts a few copies of an unknown pure non-stabilizer qubit state into an exact target magic state. Motivated by the impossibility of exact $T$-state concentration, we build six- and eight-copy protocols producing an exact $\mathrm{CCZ}$ state, with six copies being minimal. Their success probabilities are governed by the linearized order-three stabilizer Rényi entropy $M^{\mathrm{lin}}_3$. We show that this connection is structural: for up to nine input copies, $M^{\mathrm{lin}}_3$ fully determines the success probability of every universal Clifford-invariant stabilizer protocol. Remarkably, this characterization persists asymptotically: our constructions achieve optimal rates among universal single-output protocols and remain optimal up to logarithmic factors among arbitrary stabilizer protocols. As a corollary, we show that any unknown pure non-stabilizer state suffices for universal quantum computation via probabilistic $\mathrm{CCZ}$-state injection. Together, these results identify the stabilizer Rényi entropy as a fundamental operational quantity in magic state distillation.

The Dynamic Mode Decomposition (DMD) has been consolidated as a basic tool for data-driven analysis of dynamical systems, allowing simultaneous identification of coherent structures and their dynamics from time-resolved measurements. However, with a linear regression at its core, DMD is unable to produce accurate models from recordings of dynamics that are inherently nonlinear, such as the response to large perturbations and the evolution on chaotic attractors. Recent approaches attempt to simultaneously fit the linear and nonlinear contributions to the dynamics by performing a regression onto a physically motivated model structure. However, although the resulting nonlinear models can produce accurate short-term predictions, their linearization does not necessarily agree with that of the original system. In this work, we introduce a novel data-driven method — nonlinearity-subtracted DMD (NSDMD) — that focuses on producing an accurate linearization of a system when the nonlinear contribution to its dynamics are available while the linear part is not. This scenario is encountered, for example, when the nonlinear terms in the governing equations are known, while the linear operator contains uncertain material properties or it accounts for the closure of unresolved dynamics. This also arises when the data is generated by a black-box simulation code that is able to output the nonlinearity, but not the action of the linear operator on the snapshots. NSDMD leverages data snapshots of the nonlinearity to explicitly account for the purely nonlinear contributions to the dynamics and formulate a regression problem that finds a low-rank approximation of the underlying linear operator. We demonstrate the approach on several numerical examples, showcasing its improved capabilities for data-driven linear analysis of chaotic, partially observed, advection-dominated, and high-dimensional dynamics.

Time-domain inverse design in photonics is known to be suitable for maximizing the efficiency of optical devices over broad frequency ranges. Objectives commonly used in this context include time-integrated field quantities derived from Poynting's theorem, such as energy, flux, or dissipated power, which can be directly linked to integrated frequency-domain responses via Parseval's theorem. While computationally efficient, these objectives measure only the total response over the targeted bandwidth and, as we demonstrate, are insufficient to capture undesired in-band ripple, narrow spectral features, or sidelobes. We overcome this limitation by introducing a time-domain metric quantifying such spectral variations based on the weighted long-lag autocorrelation energy of the optical response. We incorporate this metric into an FDTD-based topology-optimization framework and demonstrate its beneficial effect on the example of inverse designing one-dimensional dielectric Bragg mirrors via the time-domain adjoint method.

We investigate thermal photon emission from magnetized quark-gluon plasma (QGP) within (1+1)-dimensional relativistic magnetohydrodynamics (MHD), systematically incorporating magnetic susceptibility $\chi_m$—encompassing both constant and lattice-QCD-derived temperature-dependent $\chi_m(T)$ parametrizations—and weak-field quantum corrections to quark distribution functions $f_{\rm EM}$. Employing the Pu-Bjorken MHD framework, we calculate photon production rates from Compton scattering, $q\bar{q}$ annihilation, bremsstrahlung, and annihilation with rescattering, and integrate these over the QGP spacetime evolution to obtain transverse momentum ($p_T$) spectra. Our results demonstrate that photon yields are predominantly governed by the initial magnetic field strength and its temporal decay profile, with $\chi_m$ exerting negligible influence in the explored parameter space. In contrast, the weak-field correction $f_{\rm EM}$ induces a distinct enhancement in thermal photon production at intermediate $p_T$. This work establishes a rigorous theoretical framework for quantifying electromagnetic observables in magnetized QGP and provides the foundation for future dissipative MHD studies incorporating spin-magnetization dynamics.

Alchemical relative binding free energy (RBFE) calculations are limited by the fixed-charge approximation of classical force fields. Hybrid machine learning interatomic potential/molecular mechanics (MLIP/MM) schemes correct ligand strain, but under mechanical embedding still describe ligand–environment electrostatics with static point charges. Electrostatic embedding schemes coupling machine-learned charges to the MM environment have been proposed and validated against QM/MM for simple systems, but not tested in a production alchemical workflow. We take the electrostatic embedding scheme of Semelak et al.\ and evaluate it on protein–ligand RBFE. We trained a TensorNet2 model, AceFF-2-RESP-1, on $10^{6}$ conformations from the AceFF dataset, jointly predicting energies, forces and Restrained Electrostatic Potential (RESP) charges. We chose RESP over MBIS for commensurability with the AMBER-family force field it couples to. The predicted charges enter the short-range direct-space part of the particle mesh Ewald sum, with Thole damping to prevent polarization catastrophes during alchemical transformations. We tested the scheme across five targets from the Wang et al.\ benchmark set, fixed in advance by a prior study, with three replicates per edge and matched protocols. Electrostatic embedding improved every accuracy and correlation metric for TYK2 ($\Delta\Delta G$ RMSE $0.86 \rightarrow 0.45$~kcal/mol against GAFF2), but performed comparably to the classical and mechanical-embedding baselines for CDK2, thrombin, p38 and JNK1. Standard single-molecule energy and charge benchmarks were not good predictors of this target-dependent outcome. TYK2 combined good $\Delta\Delta G$ accuracy with the lowest force error on the Schrödinger benchmark, but this pattern did not hold for the other targets.

Mesoscale self-assembly provides a route toward the design of programmable microsystems. Here, we construct flexible chains of floating monomers whose curved branches impose upward or downward deformations of the liquid interface, corresponding to effective positive or negative capillary charges. These geometrically encoded deformations generate local attractive or repulsive interactions along the chain. By tuning the capillary sequence, we obtain distinct folded configurations, including straight lines, zigzag patterns, and loops. For short chains, folding is largely governed by nearest-neighbor interactions and leads to well-defined structures. As the chain length increases and non-neighboring segments come into proximity and interact, however, the folding landscape becomes increasingly complex, with multiple metastable states whose number grows exponentially with chain length. We map these landscapes numerically and demonstrate experimentally that mechanical agitation allows the chains to transition between metastable configurations. Beyond encoding a target geometry, the capillary sequence therefore controls the complexity of the folding landscape as well as the degeneracy and mutational robustness of folded structures. These results establish capillary chains as a controllable mesoscale platform for investigating how local interaction rules give rise to collective folding and complex sequence-to-structure relationships reminiscent of those encountered in biomolecular systems.

Measurements of the turnaround radius around galaxy clusters can be used to break the degeneracy between measurements of the present day energy density of matter and dark energy. Korkidis & Pavlidou showed that the turnaround radius coincides with the first point of deviation between outer density profiles in N-body simulations and the analytic profile predicted by excursion set theory. However, their analytic profile relied on a number of simplifying assumptions, which may each introduce systematic error. We evaluate the effect of these assumptions on the shape of the analytic profile and its correspondence with simulated outer density profiles. We relax the key simplifying assumptions and re-derive the mode of the outer density profile from excursion set theory. We then numerically resolve the double distribution (DD) across a range of masses and clustering parameters, and compare the numerical mode estimate to the re-derived analytic profile. We find excellent agreement between our analytic profile and the numerically-realized DD. However, our analytic profiles diverge from N-body profiles, and this divergence grows as we relax successive assumptions. We relate this mismatch to the differing window functions used in the analytic and simulation-based approaches, which respectively yield Markovian and correlated density trajectories. We conclude that the analytic profile proposed by Korkidis & Pavlidou should only be used as a few-parameter effective description of the most-probable outer density profile, with parameters fitted to results of cosmological simulations.

It is well known that a scalar field dark matter with a quadratic potential undergoes fast oscillations when the time period represented by the mass scale in the Klein-Gordon equation becomes much smaller than that set by the Hubble parameter. This makes a solution to the equation numerically intractable. Many works in the literature have addressed the problem by either switching between solving the Klein-Gordon equation in the well-behaved regime to solving the fluid equations at the onset of oscillations, or by introducing a new set of variables that can absorb these oscillations. Despite being successful, these techniques rely on an estimate of when the oscillations start. For large scale scans of a model's parameter space, this can become cumbersome. Furthermore, the techniques have been used mainly for non-interacting dark matter models. In this work, we introduce an averaging technique with an automatic detection of the onset of oscillations, capable of capturing the non-interacting as well as the interacting dark matter scenarios. The technique, implemented in CLASS, is tested on the QCDM model and shows excellent detection and averaging abilities. We also update the cosmological constraints on the model using the most recent public data.

Classical image analysis routinely discards structurally meaningful orientation signatures encoded within Fourier phase, which are easily corrupted by local cellular rotation. Although quantum-inspired data processing offers new avenues for complex signal characterization, practical tools for directly extracting gauge-invariant angular correlations without explicit phase reconstruction remain scarce. Here we introduce Quantum Phase Bicoherence (QPBC) spectroscopy, a novel quantum-interferometric framework for capturing gauge-invariant angular order. The method embeds image angular sectors into a nine-qubit entangled state and probes three-body bicoherence via an ancilla, yielding 16 interpretable readout channels. We validate our framework on three independent public multi-modal imaging datasets covering fluorescence (BBBC021), bright-field (BBBC041) and histopathology (PathMNIST). QPBC consistently resolves angular-phase order and discriminates distinct biological phenotypes with high statistical significance. After principal-axis alignment, the optimal probing frequency universally converges, driven by Fourier directional sensitivity; negative-control experiments fully eliminate discriminative capacity, demonstrating frequency tuning acts as an on-off switch. Cross-dataset benchmarks confirm QPBC outperforms conventional Fourier-phase statistics, where inherent inversion symmetry serves as a built-in pipeline self-check. QPBC delivers a universal, classically unachievable quantitative texture observable, establishes interpretable quantum morphometry, and broadens the toolbox for quantum-inspired analysis applicable to diverse multi-modal microscopic measurements.

Thermal transport in dielectric, non-magnetic crystals is mediated by quantized lattice vibrations, which drift and interact when driven out of equilibrium by a temperature gradient. This phenomenon can be described at multiple theoretical levels, ranging from fully quantum descriptions to semiclassical and mesoscopic continuum approaches. This review rigorously discusses the theoretical steps and approximations connecting these levels, bridging quantum phonon Dyson and Kadanoff-Baym equations and semiclassical Boltzmann transport formalism, and discussing the coarse-graining procedures that yield mesoscopic viscous heat equations for non-diffusive, hydrodynamic heat transport in devices. We show how the Guyer-Krumhansl and dual-phase-lag equations emerge as special linear-isotropic-band and inviscid limits of the viscous heat equations, respectively; most importantly, we demonstrate that these equations predict not only Poiseuille flow and second sound, but also more exotic effects such as negative thermal resistance, steady-state thermal backflow and vortices. We highlight how combining these frameworks with first-principles simulations connects microscopic phonon physics to observable non-diffusive heat-transport phenomena and guides their detection, amplification, and control. We recast the viscous heat equations in terms of Helmholtz and biharmonic equations solved analytically, and use this to discuss similarities and differences between the macroscopic behavior of the phonon fluid and other hydrodynamic systems, such as classical and electron fluids, focusing on compressibility, vorticity, and their influence on phonon hydrodynamics. We conclude with a roadmap to generalize the tools used to describe phonon hydrodynamics to other quasiparticles, motivating future advances in collective quantum transport phenomena in solids.

Discrete-time quantum walks provide a versatile framework for investigating the generation, redistribution, and transport of quantum correlations in composite quantum systems. Here, we study the dynamics of bipartite and genuine multipartite entanglement in a two-walker discrete-time quantum walk on a one-dimensional lattice. By employing logarithmic negativity and the generalized geometric measure (GGM), we systematically characterize the redistribution of bipartite entanglement among different subsystem partitions and the emergence of genuine multipartite entanglement involving the two coin and two position degrees of freedom. We show that the entanglement dynamics are strongly influenced by the lattice topology. The open-boundary regime exhibits a monotonic redistribution of quantum correlations, whereas the closed-boundary regime gives rise to pronounced oscillatory behavior due to boundary-induced interference and recurrent wave-packet overlap. In the open-boundary regime, the GGM rapidly approaches its theoretical maximum value of $1/2$ and remains largely insensitive to the choice of the initial Bell state as well as to continuous variations of the local coin operator over a broad parameter range, except near the Pauli-$X$ coin. These results demonstrate that maximal genuine multipartite entanglement generation is a robust and generic feature of open-boundary two-walker discrete-time quantum walks, establishing them as promising platforms for engineering multipartite quantum correlations in quantum information processing and quantum simulation.

Phenomenological models of non-Fourier heat conduction often lack a strict microstructural foundation, leading to ambiguities when modeling complex heterogeneous materials. In this study, we derive a continuum heat equation beyond Fourier's law using spatial volume averaging for a two-component system. We analytically prove that the experimentally observed static and dynamic thermal diffusivity arise directly from the distinct material properties, concluding that heterogeneous media are inherently over-diffusive. The resulting heat equation is thermodynamically compatible, and the microstructural origin allows the calculation of non-Fourier transport coefficients. Furthermore, we demonstrate that finite-sample boundaries introduce higher-order spatial non-localities, thereby explaining the size dependence of over-diffusion. We validate the model against experimental data across metal and carbon foams, rocks, and metal-organic frameworks.

Neural networks trained by gradient descent on a smooth cost function can nevertheless learn in steps: the cost holds on long plateaus and then drops abruptly. Meanwhile, training losses instead follow smooth power laws. Variants of both behaviors occur in architectures with very different microscopic structures, which is the signature of a few relevant collective variables. We show that a symmetry fixes what those variables are: a network layer is a sum over interchangeable units, so relabeling the units leaves it unchanged; given smoothness and the condition that a unit's gradient vanish at the origin, symmetry then enforces a universal leading form for the expansion about the near-zero weights present at the start of training, the quadratic $\Tr[WW^{\top}A(x)]$, in which every architectural detail is confined to a single “structure matrix" $A(x)$ that we compute for each architecture. Perceptrons, attention layers, mixtures of experts, and convolutions become one model at different $A$. Its training dynamics then close on the “order parameter" $M=WW^{\top}$ and, whenever the data matrices share an eigenbasis, reduce to a Lotka–Volterra equation whose modes switch on one after another. The smaller the initial weights, the further apart the switch-on times, and the plateaus appear as a singular limit of a smooth flow; when many modes are unresolved the same events merge into a power law in training time whose exponent the theory predicts. We confirm both numerically across training methods and architectures.

The existence of global classical solutions for reaction-diffusion systems arising from chemical reaction networks remains a major open problem in the deterministic setting, especially for reactions with high polynomial growth. We prove that a suitably chosen, physically motivated transport noise yields unique strong solutions for complex balanced chemical reaction networks that are global in time with arbitrarily high probability. These solutions possess paths in $C^{\theta}_t C^{\infty}_x$ for all $\theta<1/2$ and are, in particular, classical in space. Furthermore, we show that a suitable transport noise can enhance the dissipation of spatial fluctuations at an arbitrarily prescribed exponential rate. Our proofs rely on a combination of scaling-limit arguments, maximal $L^p(L^q)$-regularity, and entropy-entropy dissipation estimates.

We present a search for radio emission from classical novae at 887.5 MHz using data from the Australian SKA Pathfinder Variable And Slow Transient (VAST) survey. We cross-matched 43 optically discovered classical novae that erupted between 2021 September and 2025 November within the 1200-square-degree Galactic survey footprint, and found three which show significant radio emission: V6598 Sgr, V1716 Sco, and V1723 Sco. To analyse their radio light curves, we use both thermal free-free and non-thermal synchrotron emission models. We fit the data using the Markov chain Monte Carlo (MCMC) method to constrain parameters, including the ejected mass and ejecta velocities for the thermal models, and mass-loss rate, explosion energy, wind velocity, and filling factor for the non-thermal model. All three novae show evidence of non-thermal synchrotron emission as the dominant emission mechanism at this frequency. We use a broken power law to describe the radial density structure of a non-uniform circumbinary material, which provides a better fit than a standard wind density profile. This strong early-time synchrotron emission is strong evidence of shock-driven particle acceleration, which may be related to detections of gamma-rays from all three novae as well. In contrast to earlier studies that used multi-frequency data to distinguish between emission models, our analysis is based on single-frequency radio light curves, which can still provide useful constraints on the dominant emission mechanism when interpreted with physically motivated models

Quantum information transfer between light-matter-type systems is poised to enable important applications, while also serving as a testbed for theoretical investigation. Such systems can be realized with spins coupled to a mechanical oscillator, a platform that has been extensively studied both theoretically and experimentally. Early demonstrations of quantum information transfer have relied mostly on coherent control. However, measurement-induced backaction has emerged as a strong alternative for quantum control. In this work we use post-selection on the spin system as a selective backaction to refocus spin's phase information onto the mechanical oscillator. We identify physical resources and operating regimes that govern conditional phase transfer, including oscillator quantum coherence, the number of spins, the mechanical initial state, coupling strength, oscillator amplitude, and relaxation. We benchmark different scenarios using the variance as the figure of merit, estimated via two complementary approaches: a semiclassical variance estimator and a Pegg-Barnett quantum estimator. The Cramér-Rao bound is also computed for comparison. The analysis provides a framework for understanding phase transfer in high-dimensional hybrid quantum systems and for measurement-induced backaction used in quantum magnetometry.

Supernova (SN) 2026sqf recently appeared in the nearby face-on spiral galaxy NGC 3310 and has shown signs of strong interaction with a circumstellar medium (CSM). Such intense interaction, rare among nearby SNe, offers a valuable opportunity to reveal details on the origin and nature of its progenitor system. We analyzed the early-phase spectra and light curves (LCs) of SN 2026sqf. The general shapes of the observed spectra, the strengths of the emission lines, and the LC evolution all suggest that SN 2026sqf belongs to the rare SN Ia-CSM subclass. If confirmed, this would be the closest known member of this class, at D~19 Mpc. We also report the first candidate progenitor system for a thermonuclear supernova identified in JWST pre-explosion imaging, and the first evidence for a (probable) carbon-rich AGB donor to the exploding white dwarf (WD). Our results are consistent with the expectation that SNe Ia-CSM emerge from a system consisting of a WD and an AGB star undergoing a common-envelope phase. The CSM mass and dust content are consistent with expectations for an AGB environment, but the narrow-line width exceeds superwind expansion velocities, favoring an episodic ejection. Binary interaction shortly before the explosion is a natural explanation, though the channel and timescale remain uncertain. Late-time follow-up, especially with JWST, will test the identification and the conclusions of our early-phase analysis.

String-derived higher-curvature scalar–tensor gravities encode microscopic coupling data in boundary response, raising the question of whether holographic observables can reconstruct the underlying higher-dimensional parameters. We answer this question for the five-dimensional string-derived Lovelock–Horndeski (SDLH) theory on its exact linear-dilaton asymptotically locally AdS branch, constructing the renormalized generating functional for an arbitrary boundary metric and spacetime-dependent scalar source. A boundary-covariant radial hierarchy unifies the variational problem, local backreaction, logarithmic obstruction, finite one-point functions, and Ward identities. Two response determinants organize the recursion, resonant obstructions, and metric–scalar mixing. The Weyl anomaly condenses into an Euler density, a Weyl-squared density, and a single curvature–scalar square whose paired variations generate the metric and scalar obstructions. The resulting renormalized functional carries string-selected coupling data into boundary geometry, operator response, anomaly coefficients, and a calculable interface with gravitational observables. On the regular branch, four scalar-normalization-invariant holographic combinations admit a global rational inverse to the continuous reduced couplings. At fixed compactification dimension the map has maximal rank, while the curvature-anomaly sum reconstructs the higher-dimensional Gauss–Bonnet coefficient without sign ambiguity. Holographic response thus provides an explicit, overdetermined boundary fingerprint of the underlying string reduction.