Papers

Magnetic reconnection is seen as the lead mechanism to explain the persistent and bursty heating of the solar corona that keeps its thermal structure. Lately the observations and modelling of magnetic reconnection outflows, i.e. nanojets, has empowered our capabilities to scrutinise this mechanisms, however more needs to be understood on the relation between the energetic and kinematic events. The aim of this paper is to study in details the properties of the heating events (nanoflare) and the kinematic counterparts (nanojets) in order to augment detection capabilities of magnetic reconnection events. We use MHD simulations of the interaction of two magnetic flux tubes where magnetic reconnection occurs and such reconnection outflows are generated. We vary key parameters, such as the critical current and the size of the domain to study the heating and slingshot mechanisms. We find that the properties of the nanojets can give away much information on the magnetic reconnection that generated it, while it is difficult to directly link the amount of heating and the jet speeds. We also find that such reconnection model can explain a wide range of heating events. Magnetic reconnection still is invariably linked to both heating and outflows and our simulations show the complex interplay between these two byproducts of the magnetic reconnection and how their properties can be studied in observations.

We present a direct method of separating intra- (form factor) and inter-molecular (background) contri- butions in pulse EPR dipolar spectroscopy (PDS) experiments. The form factor/background separation is accomplished by rearranging data measured at two different biradical concentrations, without any fitting fundamentally required. This new data processing method allows to analyse PDS data from spin concen- trated samples for which background separation was previously unrealistic. In particular, the presented method would be of high importance for studies of spin labeled biomolecules, especially in respect to the liquid-liquid phase separation (LLPS). Furthermore, we propose a simple measurement and data processing protocol to separate the PDS contributions from each phase in LLPS samples. The protocol for the form factor/background separation for RIDME experiment is also discussed

We investigate the validity of the superposition principle and impedance additivity in AC circuits containing a memristive device connected in series with a resistor, capacitor, or inductor. While the series association of impedances is a cornerstone of linear circuit theory, its applicability to memory-bearing nonlinear systems remains largely unexplored. Using a state-dependent memristive model, we numerically analyze the stationary current response under sinusoidal excitation and characterize the resulting harmonic spectra, Bode diagrams, and Nyquist plots. To assess whether the fundamental response can still be interpreted through an equivalent-circuit framework, we introduce the concept of an apparent memristor, whose effective parameters are extracted directly from the composite impedance. We show that, although the fundamental harmonic can be accurately reproduced by an apparent equivalent circuit over selected parameter ranges, the effective parameters differ substantially from those of the isolated memristor, revealing a renormalization induced by the coupling to the passive element. More importantly, we identify parameter regimes in which the apparent-circuit description breaks down altogether, particularly for capacitor and inductor-coupled systems, demonstrating that the composite impedance cannot generally be expressed as the sum of independent impedances. These results establish boundaries for the use of equivalent-circuit models in memory-enabled electronic systems and provide practical guidelines for the interpretation of impedance spectroscopy in nonlinear devices exhibiting memory.

The cluster expansion is a widely used approach for predicting the finite-temperature thermodynamics of alloys from zero-kelvin first-principles calculations, but its conventional formulation becomes intractable for materials with more than three or four chemical species. High-entropy alloys have therefore remained largely out of reach. We present pyeCE, an open-source Python library that implements the embedded cluster expansion (eCE), in which machine learning maps many chemical species onto a smaller set of effective species and thereby limits the growth in the number of cluster functions. pyeCE provides the complete modeling workflow, including the construction of symmetry-adapted descriptors with a learnable per-sublattice chemical embedding, a neural-network energy model, ladder-based training, uncertainty quantification, and finite-temperature simulations through Monte Carlo sampling. Built on the PyTorch and pymatgen libraries, it supports systems with multiple species on multiple sublattices and runs on graphics processing units. We demonstrate the package on two material systems. In the first, a single model spanning the full composition space of a 9-component refractory alloy resolves short-range order and order–disorder behavior. This model enables rapid screening for compositions with strong Cr clustering, a feature linked to the formation of a continuous, corrosion-resistant oxide scale. In the second, a model of hydrogen dissolution in a Mo–Nb–W alloy reproduces the composition dependence of hydrogen uptake and resolves the interstitial environments that hydrogen occupies. The modular design of pyeCE allows it to be extended to problems beyond alloy thermodynamics, including kinetics, defect energetics, and the coupling of chemical order to magnetic and vibrational degrees of freedom.

We present an efficient mixed deterministic-stochastic approach for constructing the Coulomb operator in real space that preserves accuracy across the full spectral range. The dominant long-range components of the interaction are captured deterministically via a compact, low-rank approximation, constructed using Chebyshev-filtered subspace iteration, while the remaining spectral tail is treated using unbiased probing with a small number of stochastic vectors. The resulting operator is benchmarked within self-consistent field calculations for the extended Hubbard Hamiltonian on periodic, perturbed, and non-periodic three-dimensional lattices. We account for stochastic bias in observables by implementing a jackknife correction. The method systematically improves with deterministic rank and stochastic sample count, while substantially reducing the computational cost of constructing the Coulomb matrix.

The organization of multiple knots along a polymer contour can depend sensitively on the topology of the constituent knots. Using coarse-grained Brownian-dynamics simulations, we investigate topology-dependent mixing of two knots in a flexible polymer at controlled normalized wall separation. We compare homogeneous ($3_1\otimes 3_1$) and heterogeneous ($3_1\otimes 5_1$) knot pairs using a contour-based coordinate that distinguishes mixed and demixed configurations. Starting from partially overlapping configurations, the $3_1\otimes 5_1$ pair is observed in mixed configurations more frequently over the simulation time window than the $3_1\otimes 3_1$ pair at intermediate wall separation. We further find that, over the intermediate range of normalized wall separation, mixing of the $3_1\otimes5_1$ pair produces a composite knotted region that occupies substantially less polymer contour than the two constituent knots collectively occupy in demixed configurations. The corresponding reduction in contour occupancy is much smaller for the $3_1\otimes3_1$ pair. This indicates that the heterogeneous constituent topologies can be accommodated within a smaller portion of the polymer contour in the composite configuration. These results establish that constituent topology can strongly influence multiple-knot organization in flexible polymers.

We demonstrate that designing a neural quantum state to be an exact eigenstate of the Hamiltonian's symmetries significantly improves both training speed and final variational energy. For the 2D electron gas, we design TorFormer, a neural network wavefunction which is an exact eigenstate of the total momentum. TorFormer describes both the Fermi liquid and Wigner crystal with no supervision and significantly outperforms Psiformer-based references up to large system sizes. For $r_s = 30.0$ and $40.0$ at $N=91$, we compare TorFormer trained for $8\mathrm{K}$ steps against the previous best NQS, which required $100\mathrm{K}$ training steps. Our improvement to the total energy at $r_s = 40.0$, excluding the trivial Madelung part, is $0.12\%$—enormous compared to the tiny differences separating phases. Relative to Slater-Jastrow-backflow diffusion Monte Carlo, TorFormer's energy decrease is roughly $9.8$ times that of the previous best NQS. Our work demonstrates that neural quantum states can both accurately and efficiently solve large-scale problems.

Globular clusters are efficient factories of recycled pulsars, but searches toward high-dispersion-measure (DM) clusters can be strongly limited near 1 GHz by dispersive smearing and interstellar scattering. We present the first MeerKAT S-band (nu ~ 2.4 GHz) pulsar survey of 14 globular clusters. High time- and frequency-resolution observations were searched using segmented acceleration and jerk techniques, followed by candidate folding and targeted folding with available timing ephemerides. We re-detected 39 known pulsars and discovered four new millisecond pulsars in Glimpse-C01: J1848-0129C, D, E, and F. Multi-epoch follow-up enabled preliminary Keplerian orbital fits for J1848-0129C and J1848-0129D. J1848-0129C is an eclipsing MSP in a ~5 d orbit, placing it among long-period eclipsing systems known as huntsman binaries, while J1848-0129D is in a ~3.4 d nearly circular orbit with a massive white-dwarf companion of about 1 solar mass. Two Glimpse-C01 pulsars show large DM offsets from the cluster average. Comparison with other Galactic globular clusters indicates that intracluster DM spreads tend to increase with foreground DM, implying that narrow DM search windows may be sub-optimal for high-DM clusters. From detections and non-detections, we infer a practical single-epoch MeerKAT S-band tied-array detectability scale of about 10-20 microJy. These results demonstrate the value of high-frequency searches for pulsars in strongly dispersed and scattered cluster environments.

There is growing evidence for cosmic-ray acceleration in massive stellar clusters. Furthermore, extended gamma-ray emission suggests that particle transport in the vicinity of their sources is influenced by physical processes markedly different from large-scale diffusion in the Milky Way. We characterize extended gamma-ray emission in the direction of the Westerlund 1 stellar cluster and Kes 41 supernova remnant using > 16 years of data from the Fermi Large Area Telescope (LAT) at energies > 0.8 GeV. We test whether clusters of gamma-ray sources not associated to multiwavelength counterparts are better described by extended emission components. We report the detection of three new extended emission components with soft spectra towards regions of high gas column density in the Galactic plane. One extended component associated with the natal cloud of Kes 41 is statistically preferred over the point source previously reported towards the supernova remnant shell. The other two extended components overlap with neutral gas within ~100 pc from the edge of the Westerlund 1 superbubble. The extended emission may be explained either by mismodeled gas in the interstellar background model or by the local injection of particles. Under the latter hypothesis, explaining the component associated with Kes 41 requires converting $\lesssim 5\%$ of the supernova remnant energy into accelerated particles, while accounting for the two components near Westerlund 1 requires converting $10^{-4}$ of the cluster wind mechanical power into gamma rays. Nevertheless, our results strengthen the evidence for gamma-ray emission structures arising at intermediate spatial scales between isolated objects and the large-scale diffuse emission from the interstellar medium. This could explain a part of the soft unassociated Galactic sources detected by the Fermi LAT. (Abridged)

Constraint-satisfying initial data for binary black holes require the repeated solution of a nonlinear elliptic boundary-value problem throughout the physical parameter space. We present a para\-metric, differentiable initial-data model that combines sparse-grid spectral interpolation with Newton refinement over a family of binary configurations. Interpolation is used only to provide warm starts for the underlying elliptic solver, rather than to replace it. A small number of Newton iterations refines each interpolated solution to a discrete, row-equilibrated constraint residual $\|R\|_\infty\le10^{-10}$, independent of the interpolation error, so that every returned initial-data set satisfies the discretized constraint to that tolerance. Our JAX implementation provides analytic derivatives with respect to the physical parameters, enabling gradient-based parameter targeting, optimization, and sensitivity analysis. We demonstrate the method for quasi-circular binary-black-hole initial data using conformally flat Bowen–York punctures by constructing four-dimensional aligned-spin and eight-dimensional general-spin models. The resulting initial data are validated against TwoPunctures, and the method is applied to certified targeting of the physical Arnowitt–Deser–Misner mass and angular momentum and to effective-potential eccentricity reduction using a dedicated separation–tangential-momentum model.

We present a pedagogical showcase of BRST quantization for restoring symmetries in nuclear many-body systems as a reformulation and potential alternative to conventional projection methods. The formalism is illustrated using translational invariance for a simple system of two interacting masses in one dimension, but with an eye toward generalizing to more particles, higher dimensions, and other symmetries. We explain the considerations underlying particular choices within the BRST construction, and develop both Hamiltonian and path integral formulations to provide guidance for the variety of many-body and effective field theory contexts where gauge fixing for symmetry restoration might be useful. For the demonstration system we show how to diagonalize within the extended BRST phase space, how variation after projection is recovered for product reference states, how the corresponding gauge-fixed functional integral is constructed, and how collective zero modes are isolated and controlled. Throughout, we keep in mind extensions of BRST symmetry to various approximation schemes as a guide for consistent symmetry restoration.

We develop a thermodynamically consistent diffuse-interface model for multicomponent membranes. The proposed model is derived from a coupled free energy functional that incorporates protein-dependent bending elasticity, diffuse surface tension, a volume penalty, and a membrane-associated Ohta–Kawasaki energy. Applying the Onsager variational principle, we derive a coupled $L^2$ gradient flow system and its energy dissipation law. We then construct a stabilized alternating ETD1 scheme and a stabilized alternating ETDRK2 scheme with Strang-type composition (alternating Strang-ETDRK2). To the best of our knowledge, the proposed alternating Strang-ETDRK2 scheme has not previously been developed and analyzed for coupled phase field systems. We further prove the discrete energy dissipation for both schemes under some regularity assumptions on the numerical solutions. Numerical experiments in two and three dimensions validate the discrete energy dissipation law, and present the protein segregation and membrane deformation produced by the proposed model.

Nearly three decades after the first SOHO/EIT observations, reported EUV-wave speeds still range from a few tens to more than 1000 km/s. This Perspective asks what those numbers actually trace. A measured image speed depends on passband and line-of-sight weighting, cadence, difference imaging, the selected crest or leading edge, propagation sector, fitted interval, and projection geometry. Same-event comparisons quantify this observation-operator effect. In events common to the Nitta and Muhr analyses, early or fastest-sector measurements were typically higher; five of six directly shared events differed by about 30%. For 19 May 2007, the 171 Angstrom peak speed was 475 +/- 47 km/s, compared with 238 +/- 20 km/s in 304 Angstrom, while the 171 Angstrom cadence was four times faster than the 195 Angstrom cadence. A sampling audit of the 1 April 2017 SWAP event shows that a repeated speed near 834 km/s is almost exactly one 91.6-Mm radial ring per 110-s image interval. In a reconstructed 3 April sector, AIA 171 Angstrom gives about 405 km/s, compared with the published SWAP mean of 484 km/s; an independently selected AIA 193 Angstrom ridge gives about 250 km/s under strongly shortened exposures. Such differences are not automatic evidence for different MHD modes. A same-event energy pilot separates compact-source heating, dimming/ejecta, and one weak-compression front segment. The current data do not justify a universal power law, but define a falsifiable question: is the fraction of released energy carried by the front scale invariant from compact quiet-Sun events to global waves and shocks? Establishing this dependence would show which eruption scales can contribute materially to coronal heating.

A direct, analytical, non-iterative ghost-cell reconstruction framework is developed for Cartesian-grid embedded-boundary methods. Analytical expressions impose Dirichlet and Neumann boundary conditions directly at the embedded boundary, eliminating intermediate image-point reconstruction, matrix inversion, and precomputation or storage of geometry-dependent reconstruction weights. For the Cartesian stencil considered, dependencies among neighboring ghost cells form a directed acyclic graph. A topological ordering partitions ghost cells into dependency levels, permitting level-by-level reconstruction without iterative updates. The formulation is combined with hybrid ghost cells (HGC), whose centers may lie on either side of the embedded boundary. This placement satisfies the linear reconstruction-stability criterion previously derived for scalar advection while retaining a compact nearest-neighbour Cartesian stencil. An extended-stencil classical ghost-cell formulation (CGC_ES) serves as a stability-preserving reference, distinguishing the effects of reconstruction stability and stencil compactness. The same analytical relations provide solution values and spatial gradients directly on the embedded boundary, enabling evaluation of pressure forces, wall stresses, drag, and lift without separate surface reconstruction or filtering. Simulations of flow past a circular cylinder and an airfoil show that the linear criterion remains a useful indicator of reconstruction stability for the nonlinear incompressible Navier-Stokes cases considered. Classical ghost-cell reconstruction develops spurious oscillations when the criterion is violated, whereas CGC_ES and HGC remain stable. HGC additionally satisfies the stability requirement with a compact nearest-neighbour stencil.

A physically correct description of ground state conical intersections is essential for simulating non-adiabatic dynamics of radiationless decay to the electronic ground state. Coupled cluster theory offers a particularly balanced treatment of static and dynamic correlation in excited states. However, coupled cluster methods and other single-reference approaches fail to describe ground state intersection regions, and several workarounds have been proposed to address this shortcoming. Here we present convex similarity constrained coupled cluster theory (CVX-SCC), a framework that resolves the ground state intersection problem by construction. We have applied this theory to two different coupled cluster methods, and tested the resulting models on ethylene, uracil, PSB3, and HeH$_2$, showing that both variants produce physically correct ground state conical intersections. With future development of nuclear gradients and non-adiabatic coupling vectors, this approach will provide single-reference electronic structures suitable for non-adiabatic dynamics simulations all the way to the ground state.

We investigate a generalized inhomogeneous two-dimensional Ising model on the kagomé lattice with two alternating couplings $J_i$ and $J'_i$, $i=1,2,3$, along the three lattice directions. The local Boltzmann weights are mapped onto a non-symmetric eight-vertex $R$-matrix satisfying the free-fermion condition for arbitrary values of the six couplings. We analyze the Yang–Baxter structure for the cases $J'_i=J_i$ and $J'_i=-J_i$ and derive the corresponding one-dimensional quantum spin chains in the anisotropic limit. The first case yields a transverse-field Ising-type Hamiltonian, while the second leads to a modified chain with a graded permutation structure and shifted partition-function zeros. For a partially anisotropic model, we also obtain the free energy and specific heat.

Certifying a quantum bound can require more information than realizing the correlations that attain it. We show that this distinction becomes unbounded when a proof must condition on one party's measurement question. A fixed Bell scenario attained by one entangled qubit pair has a standard degree-two sum-of-squares certificate, yet the minimum degree in either conditioning direction grows as the inverse square root of the distance to a local endpoint. Choosing the better party does not remove this cost. The obstruction also survives approximate certification: bounding the quantum maximum to any fixed fractional accuracy relative to its Bell advantage requires the same diverging level. Thus a short standard proof cannot be transferred to a uniformly bounded conditioned level, even after relaxing exactness and optimising the direction. Mixing directions within a proof removes this family's obstruction, while a separate finite separation establishes its limits. Contact geometry explains the cost and connects it to a sharp precision law for randomness certification.

We propose a quantum version of the Barankin bound as an alternative to the quantum Cramér-Rao bound for quantum parameter estimation. The quantum Barankin bound provides a lower bound on the mean squared error of estimators satisfying arbitrarily chosen bias constraints at arbitrarily chosen parameter points. In particular, unbiasedness over the entire parameter space can be imposed, yielding precision limits for globally unbiased quantum parameter estimation. In contrast to the recently derived quantum Barankin bound, which is based on a symmetric division superoperator, our bound is based on a nonsymmetric right-division superoperator. This formulation enables us to find analytic expressions for the Barankin matrix for Gaussian states, which allows for an efficient calculation of the bound. We demonstrate the usefulness of our results by applying them to various examples that exhibit the threshold effect in the few-shot regime, which is invisible to the standard quantum Cramér-Rao bound approach.

Context: the recent discovery of filamentary stellar structures in the Milky Way disk raises the question of their formation in the context of the Galaxy evolution. Aims: in this work, we aim to kinematically and chemically characterize several filamentary stellar structures by looking for clues about their origin and formation mechanism. Methods: recent works using machine-learning techniques and $Gaia$ data have identified many previously unknown Galactic strings. We cross-matched such data with the kinematics derived from the most recent Gaia DR3 catalog as well as chemical data provided by the Galactic Archaeology with HERMES (GALAH) survey. Results: we found that most strings contain one or more open clusters and are kinematically hotter than open clusters (with internal velocity dispersions in the 1–7 km/s range) but cooler than field stars. 18 objects appear chemically homogeneous ($\sigma_{[Fe/H]}$ <= 0.1 dex), while two strings have a broad [Fe/H] distribution similar to the field stars but exhibit a different mean metallicity, which may identify them as migrating stellar structures. For seven objects the GALAH observations focus on the embedded open clusters; therefore, the chemical abundances are not representative of the whole structure. An object shows clues of chemical gradients along its extension in Galactic longitude. Conclusions: these objects may be evaporating or disrupted open clusters in which the chemical homogeneity is preserved in an unbound and expanding cloud of stars or co-moving stars belonging to a former and now disrupting star formation hub. In a few cases they appear to be moving groups with no chemical homogeneity, likely formed by the dynamical action of the Galactic bar or spiral arms. More data are needed to confirm such hypotheses.

Microwave Kinetic Inductance Detectors are superconducting resonators capable of single-photon counting with energy resolving capability at visible and near-infrared wavelengths. Their zero read noise, extremely low dark counts, and compatibility with frequency-division multiplexing make them well suited for large imaging arrays. The detector yield of these arrays is often limited by the fabrication-induced frequency scatter leading to resonator collisions. We find that the tight packing of the pixels can add significant frequency scatter as well. We developed a post-fabrication correction method that is suitable for tightly packed arrays with a pixel pitch of $150\ \mathrm{\mu m}$. We demonstrate this method on a 1024-pixel array multiplexed on a single octave of readout bandwidth and show a reduction in frequency scatter from $1.1\times 10^{-2}$ to $3.5\times 10^{-4}$ and an increase in yield from $76\%$ to $94\%$.

How many past requests are needed to decide which qubits should share entanglement? We show that the answer depends on the allocation choices created by the queries: a larger memory can require no more data. The memory stores a classical bit and answers requests through a fixed detector that preserves coherence within each measured sector. For independent commuting $X$- and $Z$-type Pauli queries, we characterize the full attainable prediction-contrast region and construct encodings that preserve the bit at every nonzero vertex. With sharp reports, a $d$-qubit path and groups of at most $k$ qubits have minimax excess error after $m$ requests proportional to $k^{-1}\min\{1,\sqrt{d\log(k+1)/m}\}$, uniformly for $2\leq k<d$. Connected biclique regions can grow without increasing sample demand when depth, region count and connections per region stay bounded. Preparation noise introduces a separate calibration requirement. We derive an exact tradeoff with extra fresh detector calls and transfer the learning law to structured transaction co-location. Population-risk experiments test the statistical predictions. We also compare encodings on a native 15-qubit device and learned partitions on public purchase baskets. The full chain wins on the device; frequency grouping outperforms basket search in the largest-capacity retail setting.

We constrain a damped harmonic oscillator (DHO) dark-energy equation of state using the full cosmic microwave background (CMB) likelihoods in combination with DESI BAO and three distinct Type Ia supernova compilations: Pantheon+, DES-Dovekie, and Union3. The equation of state obeys a second-order damped oscillator equation in number of $e$-folds, so that its frequency $f$, damping rate $b$, and equilibrium value $w_{\rm m}$ fully specify the late-time dynamics. The model exhibits oscillatory behavior only at low redshifts, around the equilibrium value $w=-1$, with distinct characteristics for the different supernova compilations: an underdamped solution for DES-Dovekie and Union3, and an overdamped solution for Pantheon+. At higher redshifts, the model closely mimics $\Lambda$CDM and deviates significantly only at $z<0.6$, with the magnitude of the deviation depending on the supernova compilation. We further identify a region of the $(f,b)$ parameter space, corresponding to rapid variation of the equation of state at low redshift, in which the perturbation equations become numerically stiff and cannot be integrated with a canonical dark-energy sound speed i.e., $c_s^2 =1$. We show that reducing the rest-frame sound speed removes this obstruction while leaving the observables unchanged at the $10^{-3}$ level, and therefore treat it as a numerical prescription rather than a physical modification of the model. The model yields $H_0 = 67.53^{+1.22}_{-1.18}$ km/s/Mpc for Pantheon+, $H_0 = 69.08^{+1.23}_{-1.16}$ km/s/Mpc for DES-Dovekie, and $H_0 = 70.67^{+1.89}_{-1.87}$ km/s/Mpc for Union3. The present-day equation-of-state parameter is constrained to $w_0 = -0.521^{+0.891}_{-0.414}$, $-3.01^{+1.14}_{-1.21}$, and $-3.16^{+1.11}_{-1.16}$ for Pantheon+, DES-Dovekie, and Union3, respectively.

In the late 1990s, Suzuki and Yasuta proposed a compact formula that extracts the decay rate per unit volume of a false vacuum in the $D$-dimensional $O(N)$ $\lambda(\phi^2)^2$ theory with an unbounded potential from conventional perturbative coefficients of the vacuum energy density, i.e.\ vacuum bubble diagrams. The idea was to identify the imaginary part arising from the Borel integral along the discontinuity of the Borel transform with that of the vacuum energy density. While the formula works quite well for~$D=1$, i.e.\ quantum mechanics, its validity remained unclear for~$D\geq2$ because only the first three perturbative coefficients for~$D=2$ were available and the result showed no sign of convergence. In the present paper, we reexamine this approach using the first seven nontrivial perturbative coefficients (up to nine loops) for~$D=2$ and~$N=1$ obtained by Serone, Spada, and~Villadoro. Introducing two tunable parameters in the finite-order truncated Borel transform following these authors, we find that the imaginary part converges as the perturbative order increases, with the last few orders agreeing to within a few percent. In the intermediate range of the coupling constant, $3\lesssim\widetilde{g}\lesssim8$, this approach yields an imaginary part rather close to the leading-order semiclassical approximation with the one-loop determinant; it is $10$–$20\%$ larger than the semiclassical result with the two-loop correction computed by Malatesta, Parisi, and~Rizzo. Our result is consistent, within errors, with the continuum extrapolation of the Padé-resummed linked-cluster expansion in a quantum $\phi^4$ chain.

Recent hints of dynamical dark energy, including a possible crossing of the phantom divide, have motivated the search for viable theoretical explanations. Scalar fields non-minimally coupled to gravity with a coupling of the form $F(\varphi)=1+\alpha\varphi^2$ have emerged as promising candidates, providing an improved fit to the data compared to $\Lambda$CDM and even the $w_0w_a$CDM parametrization. However, in the absence of a screening mechanism, the regions of parameter space examined exhaustively so far (with $\alpha<0$) violate stringent local constraints on the strength and time variation of gravity and enhance the matter growth rate at low redshifts, thereby compromising the viability of these solutions. In this work, we investigate a largely unexplored region of parameter space (with $\alpha>0$) that realizes the crossing while remaining consistent with local constraints. This setup, which is subject to some fine-tuning, respects the BBN constraints and leads only to deviations of the effective gravitational coupling from Newton's constant below $0.3%$ in the past. We review the background and linear perturbation dynamics of the model, deriving analytical results that provide physical insight into its behavior, and update the constraints on the model using the latest cosmological data, including the DES-Dovekie supernova sample. We perform for the first time a full-fledged Monte Carlo analysis with $\alpha>0$, studying the impact of the variation of $G$ on the supernovae absolute luminosity, and compare the results with those obtained for $\alpha<0$, using in both cases a linear potential. In the context of the model with non-minimal coupling and $\alpha<0$, the standard model is excluded at the $2.50\sigma$ CL, whereas for $\alpha>0$, the exclusion significance decreases to $\sim 2\sigma$ CL, indicating a moderate preference for these models over $\Lambda$CDM. [abridged]

Spin Hall nano-oscillators (SHNOs) are nanoscale microwave sources for wireless communication, neuromorphic computing and oscillator-based Ising machines, but conventional devices require a global magnetic bias. Here we replace this bias through crystallographic anisotropy in epitaxial Co/Pt. Growth of hcp Co with its c-axis in the film plane produces an anisotropy field of about 0.36 T and enables field-free auto-oscillations above 10 GHz in nanoconstriction SHNOs. The active current polarity is selected by the remanent magnetization, providing nonvolatile reconfiguration of the oscillation state. Micro-focused Brillouin light scattering confirms that the nonlinear response is confined to the nanoconstriction region. Lithographic control of the angle between the current and anisotropy axes tunes the excitation threshold and drives two spectral branches from separated modes to a dominant single branch, consistent with mutual synchronization. These results establish epitaxial crystallographic anisotropy as a route to reconfigurable field-free spintronic oscillators and oscillator networks.

The stabilization of the electroweak scale strongly motivates the search for new heavy resonances and top-partner states. We investigate the discovery potential of exotic resonances mediating the production of vector-like quarks at the High-Luminosity LHC ($\sqrt{s} = 13.6$ TeV), focusing on the $pp \to X \to t \bar{t}_p$ cascade decay. Using a model-independent Effective Field Theory approach, we classify the intermediate mediator $X$ by its spin (0 and 1) and color (singlet and octet) representations. Parton-level kinematics demonstrate that the normalized differential cross-section with respect to the transverse momentum provides a robust observable for spin discrimination. To address the experimental challenges of highly boosted, semi-resolved hadronic decays, we introduce a cut-flow strategy based on an inclusive four-jet invariant mass reconstruction, $M(4j)$. Because this standard approach remains sensitive to systematic uncertainties, we implement a Generalized BSM Tagger based on Deep Neural Networks (DNNs). By exploiting non-linear multi-jet correlations, the DNN achieves robust background rejection factors ranging from $\mathcal{O}(600)$ to $\mathcal{O}(1000)$ while preserving the underlying partonic signatures. Projecting to an integrated luminosity of $3000\text{ fb}^{-1}$, this combined strategy yields a projected statistical significance of $3.74\sigma$ for the dominant color-octet vector channel, establishing strong evidence potential and offering a robust phenomenological baseline for future HL-LHC searches.

We investigate whether cosmogenic gamma rays and neutrinos from ultra-high-energy cosmic rays (UHECRs) produced in hadronically active blazars can significantly contribute to the observed spectral energy distribution (SED), and examine the potential of the Cherenkov Telescope Array Observatory (CTAO) to detect and discriminate this component. For four nearest neutrino bright blazars modeled by Rodrigues (2024), specifically AP Librae, TXS 1700+685, PKS 2326$-$502, and PKS 2345$-$16, we constrain the UHECR luminosity by requiring that the total emission does not overshoot available multi-wavelength data, assuming acceleration in the optically thin large scale jet, propagate UHECRs through realistic Galactic and extragalactic magnetic fields, and forecast CTAO performance. We find that cosmogenic gamma rays contribute up to about 7.5% of the total gamma-ray emission at the highest energies ($10^{20}$ eV), and thus remain subdominant in the SED. In contrast, the associated neutrino emission, at approximately $10^{44}$ to $10^{46}$ erg s$^{-1}$, offers a robust propagation signature of hadronic acceleration. Our simulations of 50 hour CTAO exposures show that the observatory can accurately reconstruct the intrinsic gamma ray spectrum, enabling strong constraints on the hadronic origin and propagation of UHECRs. These results demonstrate the power of combining CTAO gamma-ray measurements with neutrino observations to probe blazar hadronic processes.

The evolution of High Energy Physics (HEP) toward future collider experiments with High Luminosity (HL), such as the HL-LHC, requires the development of scintillating materials that combine high density, excellent radiation hardness and an ultrafast response. While Cerium-doped Gadolinium Aluminum Gallium Garnet (GAGG:Ce) offers a very high light yield and resilience to irradiation, its typical decay time of approximately 50-60 ns may lead to pile-up effects in high-rate environments. In this paper, we report on the development and multi-stage characterization of various accelerated GAGG compositions optimized for timing performance and grown by Crytur. By taking advantage of divalent co-doping to engineer the scintillation kinetics, we achieved an effective decay time (tau_d,eff) down to 5.5 ns while maintaining a competitive light yield of several thousand photons per MeV. Laboratory characterization demonstrates that the time resolution under gamma-ray excitation is comparable to commercial GAGG, while the time resolution measured with 120 GeV pions reaches performance levels comparable to state-of-the-art LYSO:Ce,Ca. After a 1 MGy proton irradiation campaign the material retains most of its optical transmission. The results confirm that this ultrafast GAGG composition is a viable candidate for the next generation of HEP calorimetry and timing detectors.

Entanglement-assisted optical interferometry promises diffraction-limited imaging over baselines where light cannot be physically combined, but existing theory treats only a single visibility on one two-station baseline. This work formulates the multiparameter estimation problem for an M-station array imaging an extended scene. A reduction lemma shows that the multimode quantum Fisher information (QFI) equals the mean photon number times the QFI of a single delocalized photon, collapsing the problem to a finite-dimensional one. The local photon-number superselection rule (SSR) erases all phase information from the bare state, while shared entanglement restores a fraction f(r)=r/(1+r) of the QFI on a baseline supplied with r pairs – a factor shown to be achievable, since the reduced two-mode state of any pair is exactly the two-station weak-thermal state. The QFI matrix and its mean Uhlmann curvature reveal numerically that a point source is measurement-compatible, whereas for every extended-source model examined it is incompatible, the Holevo bound exceeding the symmetric-logarithmic-derivative (SLD) bound by up to ~74%. An explicit collective receiver – a global mode-sorting (quantum Fourier transform) measurement – then attains a weighted variance within ~7% of the SLD bound and roughly an order of magnitude below an explicit pairwise receiver, and a noisy-resource advantage threshold gives the break-even baseline (~20 km for near-term parameters) beyond which repeater-distributed entanglement beats direct transmission. Finally, the optimal allocation of a finite entanglement budget is a convex program with a closed-form proportional (square-root-law) solution favoring low-visibility baselines. These results recast quantum aperture synthesis as collective multiparameter estimation and give concrete design targets, illustrated on the CHARA array.

The next generation of telescopes such as the Square Kilometre Array and the Vera C. Rubin Observatory will produce enormous quantities of data, too large for traditional analysis techniques. Machine learning has proven invaluable in handling massive data volumes and automating tasks traditionally done by human scientists. The question is, can machine learning also automate scientific discovery? Recent advances in the field have made this feasible but only when combined with expert human input through active learning. Astronomaly is a publicly available framework for active anomaly detection in astronomy. It learns to make recommendations of interesting sources to a user, allowing scientists to quickly uncover rare and new classes of objects in large datasets. In this paper, we review some of the discoveries made using Astronomaly, discuss the latest deep learning-based approaches and explore the critical role of the cyber-human interface in unveiling cosmic mysteries hidden in massive astronomical datasets.