Papers

Stack pressure is commonly treated as a means of maintaining physical contact in all-solid-state lithium-metal batteries, but it can also alter the chemistry of reactive solid-solid interfaces. Here, using pressure-aware, charge-resolved machine-learning molecular dynamics validated against DFT, we determine how pressure magnitude and loading geometry regulate interphase formation at Li||Li6PS5Cl interfaces. The response is nonmonotonic: compression at 1 kbar accelerates PS4 decomposition and Li2S-like ordering, whereas 10-100 kbar compression restricts structural rearrangement and long-range crystallization. Charge-resolved dynamics further identify sulfur-centered, lithium-rich early-interphase environments associated with subsequent Li2S-like ordering. Uniaxial loading accelerates interfacial reaction relative to isostatic loading at the same nominal pressure. Pressure also changes void closure and dead-lithium spreading in a defect-location-dependent manner. These results establish applied pressure as a mechanochemical process variable coupling interphase chemistry, ion transport and defect evolution, providing a mechanistic framework for interpreting pressure effects in sulfide solid-state batteries.

We present a hybrid, physics-based analytical pencil-beam (PB) dose engine, augmented by two small frozen neural physics priors, followed by a 3-D convolutional residual-correction network (U-Net). We address the DoseRAD2026 (https://doserad2026.grand-challenge.org/) photon dose-prediction task with PyDoseRT Photon, a GPU PB engine implemented in PyTorch and corrected toward Monte Carlo (MC) accuracy in three learned stages of decreasing physical specificity. The engine reproduces the challenge's head-less MC source exactly where it can and models the patient with a beam-quality-indexed pencil kernel evaluated at the field's fluence-weighted radiological depth, and TERMA source scaling at the interaction site. Two tiny neural priors are trained through the frozen engine and then frozen themselves: a 39k-parameter 2-D fluence correction and a 48-parameter lateral heterogeneity correction mixing mass-conserving Gaussian redistribution operators. A compact 3-D U-Net (1.36M parameters) with a sequential refinement branch then predicts, per control point (CP) in the beam's-eye-view (BEV) frame, a bounded multiplicative gain and additive residual from seven channels. All learned stages are zero-initialized, so training starts from the analytical solution. For MRI, an nnU-Net regression model synthesizes a CT that enters the identical pipeline, with consecutively, the same trained corrector as the CT track. Design choices were driven by the challenge ranking, in which runtime carries double weight. The submitted method evaluated on our local CT and MR validation dataset achieved CP MAE 0.0086 and 0.0098, IDD distance 0.0011 and 0.0013, plan MAE 0.0024 and 0.0047, gamma pass rate (1%/1mm) 99.12% and 96.95%, with runtimes of 46s and 49s, respectively.

The jet may compress an interstellar medium and soft X ray outside the jet may be absorbed by a compressed interstellar medium and thermal emission heated by a shock is expected inside the jet. Thermal emission was found for HST-1 and knot A of M87 in X ray energy spectra analysis by Chandra (Osone, 2017). The X ray image of the surrounding of the jet of M87 was studied by Chandra (Osone 2024). I find a soft X ray dip in a south region outside knot A. Therefore, by taking only a north region outside knot A as a background, where there is no soft X ray dip, I analyze X ray energy spectra for knot A by Chandra and confirm thermal emission with a high significance.

AlGaN/GaN heterostructures are critical for high-power electronic devices but suffer from electron trapping at defects, limiting reliability. We investigate how ultrasonic vibrations affect electron transport in MOCVD-grown AlGaN/GaN heterostructures by combining temperature-dependent Hall effect and high-resolution X-ray diffraction measurements. Here we demonstrate that ultrasonic loading induces persistent acoustoconductivity and lattice parameter changes, attributed to acoustically driven rearrangement of metastable DX centers. This leads to increased carrier concentration and decreased mobility, reflecting defect state modulation by acoustic strain. These findings provide new insights into trap dynamics under dynamic deformation and suggest ultrasonic treatment as a potential approach to mitigate trapping effects, thereby enhancing the performance and reliability of GaN-based devices.

This paper presents a computational study of language competition dynamics on Erdős–Rényi random networks, extending the foundational Abrams–Strogatz model through two novel contributions: (i) a dynamic edge-weighting mechanism that reinforces social ties between co-minority speakers by an additive increment $\Delta$, and (ii) a probabilistic agent-based framework governing language switching via a weighted majority rule. Phase boundaries separating the dominance and coexistence regimes are identified across a two-dimensional parameter space $(p, \Delta)$, where $p$ denotes the network connectivity probability. We further characterise anomalous persistence zones within predicted dominance regions, attributing them to the formation of isolated minority speaker clusters. Scaling study across network sizes $N \in \{50, 100, 250, 500, 1000\}$ reveal that average cluster size decreases with $N$ and that phase boundaries diffuse with increasing stochastic noise. Finally, we discuss extensions to a tripartite bilingual model and heterogeneous prestige/volatility to more faithfully capture real sociolinguistic contact scenarios.

Crystal generators can now propose periodic structures, but their control interfaces remain poorly matched to the mixed descriptors used in materials design. Text provides a compact way to combine composition, symmetry, prototype and property cues, yet it has not been clear whether such information can steer flow-based crystal generation. Here we introduce TFMat, a text-conditioned flow-matching framework that uses structured materials language as a semantic prior for a CrystalFlow generator. Across Perov-5, Carbon-24 and MP-20 crystal structure prediction benchmarks, TFMat improves one-candidate match rates over CrystalFlow and reaches a 92.04% MP-20 match rate with 20 candidates; in de novo generation, it improves element-count and density distribution alignment while retaining coarse property consistency in composition-selected outputs. These results position structured text as an inspectable control layer for translating human-readable materials intent into candidate crystals for downstream simulation and validation.

Antiferromagnets combine terahertz spin dynamics with insensitivity to stray fields, and how quickly their order can be manipulated sets the speed limit on device operation. Femtosecond optical pulses demagnetize antiferromagnetic insulators on timescales that span picoseconds to nanoseconds across compounds, and no material parameter is known that accounts for the spread or predicts where a new compound will fall. In a compensated antiferromagnet, no angular momentum needs to leave the spin system, so the rate is set by energy flow from the lattice into the spins. Time-resolved second-harmonic generation experiments show that Cr2O3 demagnetizes within 2 ps once the lattice is driven above the Neel temperature, two orders of magnitude faster than the structurally similar FeBO3. First-principles calculations trace the disparity to exchange striction: short Cr-Cr contacts make the exchange coupling tenfold more sensitive to atomic displacements and widen the phase space for phonon decay into magnon pairs. Spin-lattice simulations with ab initio parameters reproduce the order of magnitude of the measured ratio. The derivative of the exchange coupling with respect to the ionic displacement thus emerges as a computable parameter that predicts how fast an insulating antiferromagnet can be demagnetized. The results advance our understanding of ultrafast control in insulating antiferromagnets, and suggest a practical pathway to screen candidate materials for thermally assisted antiferromagnetic memory before synthesis.

We establish the general form of the evolution equation and study scattering and tunneling in real quantum mechanics. We prove an analogue of Stone's theorem for a real Kahler space and derive the corresponding general evolution equation, whose evolution operator is both orthogonal and symplectic. We formulate scattering theory in terms of real wave operators and the associated S-matrix. For the class of potentials considered, we show that the differential scattering cross section is equivalent to that obtained in standard complex quantum mechanics. We also show that the tunneling probability in real quantum mechanics is identical to that in complex quantum mechanics.

Scale-free turbulent motions, gravitational collapse and galactic dynamics govern galactic-scale, hierarchical organization of star formation (SF) within galaxies. Past studies suggest that properties of SF hierarchies depend upon host galaxy properties and interstellar medium (ISM) conditions. To characterize SF hierarchies, we performed two-point correlation function analysis on ~25000 UV-selected star-forming clumps (SFCs) identified in a morphologically diverse sample of 8 classic spirals, 6 flocculent spirals and 3 dwarf irregulars. We found that SF hierarchies in galaxies exhibit a maximum spatial scale – the correlation length ($l_{\rm corr}$) – largest scale up to which SF is spatially correlated, presumably owing to ISM turbulence. The $l_{\rm corr}$ values range from ~100 pc to 3.4 kpc and exhibit strong dependence on the galaxy's stellar mass, morphology and nature of spiral arms. This suggests that a galaxy's gravitational potential and spiral structure place an upper limit on the sizes of the largest, hierarchically structured SF complexes. Connecting $l_{\rm corr}$ with turbulence injection sources suggests that stellar feedback in dwarf irregulars, whereas disk instabilities and spiral structure in classic/flocculent spirals dominate towards sustaining their SF hierarchies up to the $l_{\rm corr}$ scale. These hierarchies disperse to near-random distributions on timescales ($T_{\rm dis}$) ranging from 20-160 Myr. The broad range of derived $l_{\rm corr}$, projected fractal dimension ($D_2$ $\in$ 0.71$-$1.73), and $T_{\rm dis}$ indicates a non-universal, galaxy-specific nature of SF hierarchies. In this work, full coverage of each galaxy's star-forming extent with the AstroSat-UltraViolet Imaging Telescope uniquely enabled us to connect global parameters of SF hierarchies with large-scale galaxy properties.

Stress-tensor fluctuations carry information that is absent from the mean semiclassical Einstein equation, but their observable effect depends as much on the response of the geometry as on the noise itself. We formulate an effective, quasistationary spherical model organized by the response–noise structure of a quantum Langevin equation. A prescribed mean dressing and a horizon-localized colored source are varied independently. For every source realization we reconstruct the lapse, locate its outer trapping horizon, and evaluate the adiabatic Hayward–Kodama temperature from the slope at that same root. As the mean lapse approaches an inner–outer root merger, its inverse slope acts as a geometric susceptibility: a fixed source covariance produces enhanced horizon fluctuations, horizon–temperature covariance, and a positively skewed, greybody-filtered luminosity. The specific advance is a single-realization map from colored metric noise to correlated geometric, thermal, and radiative statistics, together with an explicit separation of reservoir strength from near-critical amplification. The model is a stochastic-semiclassical testbed, not a microscopic evaluation of Unruh-state response and noise kernels.

High-frequency gravitational waves in the MHz–GHz range require detection strategies beyond conventional interferometers. We study the response of a SQUID-terminated superconducting microwave cavity as a narrowband parametric transducer. The cavity boundary conditions and the flux dependence of the Josephson inductance are used to derive the quarter-wave mode spectrum and the first-order eigenfrequency response to changes in the physical line length, phase velocity, and SQUID inductive length. By projecting the perturbed dynamics onto the static cavity modes, we show that the resonance-frequency response and the photon-pair-production response are generally distinct. We therefore introduce two independent kernels, $R_n^{\omega}$ and $R_n^{\rm pair}$, which coincide only when changes in mode normalization and spatial profiles can be neglected. Near $\Omega_{\rm GW}\simeq 2\omega_n$, the isolated-mode dynamics reduce to a Mathieu-type parametric amplifier, allowing the photon number, quadrature variances, gain, and instability threshold to be obtained in the presence of dissipation. Spontaneous photon production scales quadratically with the gravitational-wave strain and is extremely small for representative parameters, whereas phase-sensitive responses with a coherent probe can scale linearly with strain. The framework therefore provides a theoretical description of narrowband gravitational-wave transduction, while a quantitative sensitivity estimate requires device-specific calibration of the mechanical–electromagnetic response, verification of mode isolation, and a complete treatment of loss and noise.

External magnetic fields can qualitatively reshape the electronic structure of crystals, underpinning quantum Hall physics, Landau-level spectra and field-induced topological phases. Their first-principles treatment at laboratory-scale fields is, however, hindered by magnetic-flux quantization, which requires magnetic unit cells with areas inversely proportional to the applied field. Such cells contain a large number of chemical unit cells, rendering real-space and plane-wave calculations prohibitively expensive. Here we, for the first time, construct a magnetic Bloch basis built from linear combinations of gauge-including Gaussian-type atomic orbitals, which incorporate the magnetic-field phase factors required by magnetic translation symmetry. The framework requires far fewer basis functions than real-space or plane-wave representations of the same magnetic supercell and retains the sparsity of an atom-centred basis, together substantially reducing computational cost. We validate the framework by reproducing Landau-level spectrum of graphene from first principles. This approach provides a practical route to simulations of crystalline materials under experimentally accessible magnetic fields.

Wide-field optical transient surveys collectively discover $\sim$50 new transients per night, making rapid, multi-filter and/or spectroscopic follow-up of all but the most exceptional events unfeasible. Consequently, the (early) light-curve properties of most supernovae (SNe), particularly sub-luminous events, are often poorly characterised. Here, we showcase recovery of key parameters by combining publicly available data from multiple, contemporaneous surveys. We built a catalogue of $125$ SNe by cross-matching the MeerLICHT (ML) transient survey with the Transient Name Server list of spectroscopically classified SNe detected between August 2017 and October 2022. For a subset of $14$ SNe with good multi-survey photometric coverage, we combined ML-$q$, ZTF-$g,r$, and ATLAS-$c,o$ data to construct composite early-time light curves. We then applied an expanding fireball ($t^2$) model to constrain their explosion dates and rest-frame rise times. We find that this simple model provides a reliable description for the early emission of most SNe in our sample and successfully constrains their rise time, a key parameter for characterising SN categories and probing progenitor origins. This multi-survey approach, only using standard survey products, provides a powerful method to characterise large numbers of SNe that would otherwise be lost, a technique that will be essential for maximising the scientific return from current and future surveys such as GOTO, BlackGEM, the Vera C. Rubin Observatory's LSST, and Global Open Transient Telescope Array (GOTTA).

This paper introduces QXymb, a general framework for constructing observational declarative twins of quantum circuits, and develops QILP-0, its first complete order-0 specialization. QILP-0 constructs a finite multi-valued propositional logic program from observed circuit behaviour within a declared observational scope. The pipeline traverses a declared family of quantum observables incrementally according to a reproducible structural grading and a declared observational reference horizon. Progress is quantified through reference-relative coverage against a fixed target-independent reference. Observable responses are organized through target-independent geometry, while retained latent structure is mapped deterministically back to original observable columns before symbolic processing, preserving observational semantics and provenance. Selected observable profiles are converted into a finite relation through admissible target-independent discretization. The target is used only afterwards to audit twin-admissibility and induce the declarative theory. A theory is certified as an exact observational declarative twin when it completely and correctly reconstructs the resulting finite task-conditioned discrete relation. Logical exactness is therefore separated from numerical, backend, provider, and discretization uncertainty, which is retained as audit metadata. Validation uses two complementary QML settings. Exhaustive Bars & Stripes experiments compare product and grid-CZ embeddings from 16 to 100 qubits and exercise the native-discrete branch. Low-Depth MNIST analyses all 14,708 digit-0/1 instances before and after a trained variational quantum transformation and exercises continuous discretization. In every reported relation, the induced QILP-0 theory achieves complete, conflict-free reconstruction with strict accuracy equal to one.

We investigate asymptotically Weyl-invariant gravity (AWIG) in the Palatini formulation, defined by an exponent n that interpolates between an Einstein-like infrared regime, where n goes to one, and a Weyl-invariant ultraviolet regime, where n goes to two. In four dimensions, we show that exact Weyl invariance within the minimal scalar Palatini f(R) sector uniquely selects the R^2 action as the ultraviolet endpoint. Interpreting the exponent as an effective curvature-dependent quantity, we constrain a phenomenological class of smooth autonomous flows compatible with the required infrared and ultraviolet endpoints. We then analyse the strict ultraviolet theory. On the regular branch R not equal to zero, and within a restricted torsionless, parity-even sector constructed purely from curvature, all admissible divergent on-shell counterterms reduce at arbitrary loop order to the original \sqrt{-g}R^2 term plus a topological Euler density. Although this conditional result does not establish full off-shell perturbative renormalizability, it provides nontrivial evidence for improved ultraviolet behaviour relative to Einstein gravity and identifies a concrete target for a future first-principles renormalization-group calculation.

Polymer gelation involves the emergence of a system-spanning network from growing polymer-rich domains, yet conventional percolation models typically prescribe particle size independently of material consumption. We formulate gelation as a locally mass-conserving growth-percolation process in which Voronoi capture zones define finite material reservoirs for individual nuclei. Local depletion determines the evolving supersaturation and limiting particle size, while particle contacts generate a dynamic network whose first spanning cluster defines the gel point. Three mechanisms, namely, interface-, diffusion-, and polymer-blob-controlled growth produce distinct gelation kinetics while sharing the same accessible final state. Spatial fluctuations in nucleation further generate a distribution of gelation times. The framework separates gelation from saturation and naturally captures post-gel aging as continued growth and topological maturation.

Mobile phone mobility data have transformed the study of human behavior, but demographic and behavioral biases can compromise their representativeness and distort population-level inference. Existing calibration approaches primarily address demographic and geographic representativeness, leaving behavioral discrepancies largely uncorrected. Here we introduce the Behavioral Population (BePop) framework, which jointly calibrates mobility data to representative demographic and behavioral distributions using census data and time-use surveys. BePop embeds mobility sequences into behavioral profiles and estimates person-level weights that align both population composition and daily activity patterns. Across three U.S. metropolitan areas, the framework consistently improves agreement between GPS-derived mobility and representative behavioral distributions, including time allocation, activity transitions, and mobility motifs. Calibration also substantially alters downstream mobility indicators, demonstrating that behavioral biases can propagate into commonly used mobility measures. Our results establish behavioral representativeness as a critical complement to demographic calibration and provide a general framework for population-representative mobility inference.

An interesting feature of quantum corrections to the Bekenstein–Hawking entropy is the appearance of logarithmic area terms, whose coefficients are governed by the spectrum of massless fields. For near-extremal black holes, the entropy also receives a logarithmic temperature correction, whose coefficient is determined by the zero modes of the corresponding extremal black holes. In this paper, we study near-extremal rotating black holes in three, four, and five dimensions with an important focus on rotational zero modes. For three-dimensional BTZ black holes, our results are in agreement with the microscopic description. Furthermore, by treating the cosmological constant scale \(\ell\) as an independent parameter, we find an additional \(\log \ell\) correction to the entropy at extremality. For the five-dimensional BMPV black hole, we explicitly construct all the extremal zero modes and use them to evaluate the log temperature corrections to the entropy.

Quantum compilers typically follow the circuit model, representing programs as fixed sequences of gates. This static view breaks down in hybrid quantum-classical applications, where gate choices depend on runtime data or measurement results. We introduce a new Intermediate Representation (IR) that elevates gates to first-class values, enabling their dynamic creation, composition, and control. This unified representation allows classical computation to steer quantum behaviour, capturing phenomena including stochastic gate selection, adaptive error correction, and measurement-driven computation within a single framework. Case studies in noise modelling, randomised compilation, error correction, and measurement-based quantum computing show that our IR expresses these programs compactly and supports optimisations that were not possible in the circuit model. Evaluation on a benchmark suite of hybrid quantum-classical programs indicates that our IR represents programs compactly and facilitates compiler analysis and transformation.

Large-scale spectroscopic surveys will need suitable benchmark stars that can be used to verify the performance of automatic pipelines. A promising type of object for this purpose is the detached eclipsing binary (DEB) containing an FG-star and a low temperature companion. For flux ratios $\lesssim1$~per~cent, the spectra obtained for the binary will be almost identical to a single star. As the methods for obtaining accurate parameters for binaries are well established, they would be excellent benchmark candidates. We analyse a group of DEBs with M-dwarf companions using TESS light curves and high resolution spectroscopy from NIRPS and HARPS on the ESO 3.6-m telescope. We obtain accurate fundamental parameters for the stellar components. The secondary component is visible with cross-correlation, allowing them to be characterised as well. With the stellar parameters obtained from the analysis, we can measure precise effective temperatures from Gaia parallaxes and archival magnitude data. Chemical compositions of the primary stars are also extracted from the stellar spectra. In this analysis, the secondary components have minimal impact on determined spectroscopic parameters. Our radii and masses are characterised to within sub per~cent precision as well as our primary effective temperatures. Beyond a new set of stellar benchmarks, the secondary components analysed in this work represent a well characterised sample of M-dwarf stars which will be useful to improve our understanding of low mass structure and evolution.

The Dirac quantum walk (a 1+1 dimensional space-time discretization of the Dirac equation) has a $2\mu$ mass gap both at the center and at the corner of the quasi-energy-momentum Brillouin zone. Gupta and Short recently noted [Quantum 9, 1845 (2025)] that the Dirac vacuum can create a particle-hole pair at the zone corner with the release of an energy $2\mu$ to the environment. They removed this vacuum instability at the expense of fermion doubling, the appearance of a second low-energy Dirac cone. Here we show that an alternative discretization scheme, with a tangent rather than a sine dispersion relation, offers stability while retaining a single Dirac cone. The key step is the Cayley transformation from the unit circle of Floquet eigenvalues $e^{-i\varepsilon}$ to the real line of unbounded energies $E=2\tan(\varepsilon/2)$. We compute the Schwinger effect (particle-hole pair creation in a uniform electric field) for tangent fermions and show that the pair-production rate agrees with the continuum result for a single Dirac cone. The zone corner is exactly decoupled if the scalar potential is coupled through the Hermitian generator of the quantum map. If it is coupled as a split operator, in order to preserve exact gauge invariance on the lattice, the corner does contribute - with a weight that vanishes quadratically with the lattice constants, in contrast to the Dirac quantum walk where the zone-corner instability survives the continuum limit.

Density Functional Theory (DFT) is indispensable for materials science and drug discovery, yet the exchange–correlation (XC) evaluation remains a major bottleneck due to its cubic scaling. Although linear-scaling methods exploit electronic nearsightedness to reduce asymptotic complexity, they produce irregular sparse workloads that hide implicit sparsity and prevent efficient use of modern AI accelerators. We present MakoXC, a modular matrix-aligned XC evaluation engine that rearchitects nearsightedness-induced sparsity into regular, accelerator-friendly computations. MakoXC co-designs three key techniques: (1) Matrix-Aligned Cells reorganize nearsightedness-induced interactions into dense, accelerator-aligned data clusters; (2) Sparsity-Guided Activation translates deeper implicit sparsity into numerically correct structured execution for practical linear scaling; and (3) Kernel-Fused Pipeline consolidates fragmented workloads into a unified, compute-intensive execution path that fully unleashes accelerator throughput. Extensive evaluations show that MakoXC achieves average speedups of 67.8$\times$ speedup over standard XC evaluation and 4.7$\times$ over state-of-the-art linear-scaling methods. When integrated into a production-grade commercial DFT package, MakoXC scales XC evaluation to ubiquitin (1,231 atoms, def2-SVP) on 64 GPUs, enabling the end-to-end DFT calculation to complete in under five minutes. By restructuring XC evaluation into a unified, structured computation, MakoXC demonstrates how scientific workloads can achieve genuine low complexity while maximizing parallel efficiency on AI accelerators.

Neutron stars contain several forms of quantum condensed matter whose microscopic properties control macroscopic rotational dynamics and magnetic behavior of these fascinating objects. This review surveys superfluidity and superconductivity in compact stars, with emphasis on phenomena associated with quantized vorticity and magnetic-flux structures, and the possible connections to observed phenomena. We first summarize the microphysics of nucleonic pairing, including spin-singlet $^1S_0$ neutron pairing in the inner crust, proton superconductivity in the outer core, and spin-triplet $^3P_2$–$^3F_2$ neutron pairing at higher densities, together with the principal many-body uncertainties affecting the corresponding pairing gaps. We then discuss the dynamics of neutron vortices, including pinning, vortex creep, and dissipative motion, and the role of vortex dynamics in angular-momentum exchange between the superfluid and the observable crustal component. We give special attention to proton flux tubes in type-II superconducting cores, the possible realization of type-I superconductivity, and vortex–flux-tube interactions. We also review collective rotational phenomena, including Tkachenko oscillations of the vortex lattice and free precession, and their possible relation to long-term variability in pulsar timing. Finally, we discuss the possible deconfinement of hadronic matter into quark matter, the formation of color-superconducting phases, and the topological defects associated with these phases, together with their possible observational consequences. Throughout the review, we identify key open questions connecting microscopic pairing, mesoscopic defect dynamics, and observable neutron-star phenomena.

Photonic fusion operations are a central primitive in photonic quantum information processing and are commonly characterized by their success probability and resource cost. Here, we identify an additional way in which different implementations of fusion operations differ, namely in how they transform partial distinguishability. We consider distinguishability originating both from imperfect entangled resource states and from imperfect single photons. We find that different successful fusion events can induce markedly different distinguishability transformations depending on the fusion protocol, heralding outcome, and error model. Under a collective resource-state error model, we identify a modification to an existing fusion protocol that improves the fidelity of the remaining state on average. Generally, however, these transformations adversely affect distinguishability, and many successful fusion outcomes are accompanied by distinguishability degradation. Our results show that partial distinguishability is dynamically shaped by interference and measurements and should be considered alongside overall fusion success probability when evaluating photonic fusion protocols.

Architecture category. Hybrid method: a physics-based analytical pencil-beam (PB) dose engine followed by a 3-D convolutional residual-correction network (RepVGG-U-Net). We addressed the DoseRAD2026 proton dose-prediction task with PyDoseRT Proton, a GPU-accelerated engine implemented in PyTorch and augmented by a learned residual toward Monte Carlo (MC) accuracy. A double-Gaussian PB kernel was calibrated to GATE/Geant4 integrated depth doses in water in two stages: a classical per-energy curve fit, then a gradient-based fit of the full 3-D dose through the PyTorch physics engine as it retains a differentiable execution path for gradient-based optimization of dose-dependent objectives. The engine computes each beamlet on a beam's-eye-view (BEV) lattice with variance-preserving Gaussian splitting, an analytic nuclear halo, and a Fermi-Eyges heterogeneity term, then rotates the result into the patient frame. Additionally, a compact residual U-Net predicts an additive correction in BEV space. It is conditioned on voxelwise material-label embeddings, a discrete energy embedding and spot size. The same model was used for all anatomical sites (thoracic and abdominal). It was trained with a patient-space L1 objective emphasizing the scored high-dose region and multi-scale BEV deep supervision. The submitted CT configuration obtained preliminary-test beamlet MAE 0.0066, image-z IDD distance 0.0025, plan MAE 0.0049, 98.30% gamma pass rate (1%/1 mm), and DVH error 0.460.

Wavefront shaping is a key technique for mitigating scattering in complex media, enabling advanced imaging and optical communication. Yet existing approaches are inherently local, requiring active correction elements - such as spatial light modulators or deformable mirrors - to lie directly in the optical path of the scattered light, which limits their integration into compact imaging systems. Here, we experimentally demonstrate nonlocal wavefront shaping using spatially entangled photon pairs. By applying a phase correction to a photon that never interacts with the scattering medium, we compensate for the distortions experienced by its entangled partner and restore their initial spatial correlations. Our approach physically decouples the wavefront correction from the scattering medium, paving the way for imaging through complex media in compact and otherwise inaccessible systems.

The field of exoplanetary research is rapidly evolving, thanks to TESS and Kepler/K2. With the latest data release, Gaia DR3, Gaia has transformed the study of star clusters. By combining the known properties of exoplanets and those of star clusters, in which they are found, it is possible to study the planets in greater detail and test theories of planetary evolution. We aim to create a catalogue of Gaia IDs for known exoplanets and use it to link the planets to a catalogue of star clusters. We utilised the NASA Exoplanet Archive and the Extrasolar Planets Encyclopaedia to compile a catalogue of known exoplanets. We then cross-matched the data with Gaia DR3 sources to obtain the Gaia IDs of the exoplanets. Using this information, we inferred the potential association of these exoplanets with star clusters. We described the statistical properties of these exoplanets. We compiled a catalogue of Gaia IDs for known exoplanets and identified those associated with star clusters. This resource facilitates detailed studies of exoplanet properties and their evolutionary contexts within stellar clusters.

We explore the construction of higher-dimensional Einstein-Maxwell(-Chern-Simons) solutions from vacuum seeds by means of a generalized Kerr-Schild transformation along a geodesic null vector field $\mathbf{k}$. Assuming the vector potential $\mathbf{A}$ to be aligned with $\mathbf{k}$, and $\mathbf{k}$ to be a Weyl aligned null direction satisfying the “optical constraint”, we arrive at three distinct branches of solutions. If $\mathbf{k}$ is expanding and twisting, then its shear must vanish – this branch includes certain charged Taub-NUT metrics. If $\mathbf{k}$ is expanding and twistfree, one finds two subfamilies: Robinson-Trautman electrovac solutions with a non-null Maxwell field if the shear is zero, or shearing solutions with a null field. Finally, the case when $\mathbf{k}$ is non-expanding reduces to a subset of the known Kundt solutions. In all cases, the Chern-Simons term turns out to be identically zero on-shell. In passing, by relaxing the alignment assumption on $\mathbf{A}$, we also obtain a six-dimensional extension of a charged Taub-NUT metric for which the magnetic part of the field strength is a linear combination of two distinct Kähler 2-forms, as opposed to the previously known examples in more than four dimensions.

We analyzed photometric and spectroscopic data for 11 candidates for non-pulsating stars located in the Cepheid instability strip (IS) of the Large Magellanic Cloud (LMC) in order to investigate the reasons for the lack of pulsations. We used available temperature calibrations based on photometric colors to estimate the effective temperatures of the candidates, which served as initial parameters for the spectroscopic analysis. We also applied surface brightness-color relations calibrated for Cepheid variables, giants, and supergiants to estimate stellar radii. The spectral analysis was performed using the spectral synthesis method to determine the atmospheric parameters; namely, the effective temperature, metallicity, surface gravity, microturbulent velocity, projected rotational velocity, and chemical abundances for up to ~30 elements. For most objects, only a single spectrum was available. However, no significant variations in radial velocities were detected among the stars with repeat observations; therefore, all stars were treated as single object in the analysis. Two stars exhibit broad spectral lines, which may indicate high rotational velocities or possible binarity; however, additional spectra are required to confirm this interpretation. One of these objects also shows asymmetric line profiles, which might be related to the presence of non-radial pulsation modes causing line-shape variations. A common feature among all analyzed candidates is an enhancement of barium-peak s-process elements compared to solar values. This may indicate past mass transfer from a companion during its post-asymptotic giant branch phase. This study provides an insight into the physical parameters of candidates for non-pulsating stars residing within the Cepheid IS in the LMC, although the lack of pulsations remains a mystery and challenges pulsation theory.

Gaussian boson sampling requires control of how closely finite optical matrices follow Gaussian reference laws. We prove an explicit total variation bound of order $N^2/M$ between a rescaled Haar transpose Gram block and its Gaussian transpose Gram counterpart, where $N$ is the detected photon count and $M$ is the number of optical modes. The bound establishes quantitative product hiding uniformly over every number of squeezed inputs. The proof combines Stiefel recursion, centered circular orthogonal ensemble scores, and a rectangular entropy estimate. Applications combine hiding with local hafnian bounds to obtain relative probability guarantees and connect them to sampler error through exact photon-sector normalization.