Papers

In-space servicing has been receiving great attention to extend the operation of spacecraft with defective components. This requires rendezvous and proximity operations for a chaser to provide service to a target. This work constructs a fuzzy inference system-based controller for the chaser to reach the cooperative target on a circular orbit in the final approach phase while minimizing the energy consumption of the chaser. The offline training process performed by a genetic algorithm deals with multiple initial relative positions of the chaser, and the trained controller is validated using a testing environment with disturbances, which differs from the training scenarios.

Magnetic levitation offer passive levitation of massive objects for use in advanced inertia sensors, for the generation of non-classical macroscopic motional states, and towards the table-top testing of low energy gravity with quantum mechanics. Magnons, a quanta of spin wave, couple to many physical quantities and strongly to electromagnetic fields, even at room temperature. In this work we demonstrate the stable trapping of a small YIG sphere using a magnetic Paul trap. We present a classical stability analysis of a magnetic Paul trap and show the stability diagram for all mechanical degrees of freedom. We show that coupling between librational and translational modes changes the stability region. We experimentally levitate the soft magnet yttrium iron garnet at room temperature obtaining Q-factors of $\sim25$ and secular frequencies $15.8$ Hz and $17.2$ Hz. We provide numerical estimates of the achievable enhanced coupling between the center-of-mass motion and excited magnon modes, with a cooperativity above unity despite strong mechanical damping, indicating potential applications in quantum information processing, quantum interconnects and quantum memories.

Precise measurements of the metastable helium (1s)(2s)$\,^3S_1$ ionization energy have revealed a 9$\sigma$ discrepancy with QED theory that persists in isotopic measurements, suggesting a leptophilic bosonic interaction as a possible explanation. A subsequent investigation of such interactions has concluded that only a scalar boson interaction is consistent with the He observations. Taking this as a starting point, we derive the response of positronium energy levels to the corresponding finite-range Yukawa potential, using exact hydrogenic matrix elements and a numerical helium calculation. Across the viable mediator-mass range of 0-800 eV, the He anomaly interpreted in this way implies a positronium 1$^3$S$_1 \rightarrow 2^3$S$_1$ shift ranging from 0.250-0.850 MHz, and a 2S-ionization shift of 0.14-0.21 MHz. We discuss the feasibility of observing these shifts experimentally.

The $\Omega^0_c$ baryon is unique among charmed sextet baryons because it decays through the weak interaction. In this work, we investigate the topological amplitudes of $\Omega_c^0$ decays in the $SU(3)_F$ limit. The complete set of tree- and penguin-induced diagrams contributing to $\Omega_c^0$ decays into decuplet and octet baryons is presented. The linear relations between the topological amplitudes and the $SU(3)$ irreducible amplitudes are derived through tensor analysis. Several isospin relations are obtained, and additional relations are derived to test the Körner-Pati-Woo theorem.

In this work, we take a first step to a stochastic real-time description of the vacuum phase transitions in a radiation-dominated FLRW universe from the Schwinger-Keldysh formalism. By splitting the phase transition field $\Phi$ into the long-wavelength mode $\phi$ and the short-wavelength mode $\sigma$ and tracing over the latter as the environment, we obtain a classical Langevin-type equation-of-motion for the long-wavelength field $\phi$, where the quantum effects are encoded in a non-Markov memory kernel and a non-Gaussian noise. As a phenomenological example, we start from a polynomial potential and a thermalized initial state, and study the structure of the memory kernel as well as the correlation functions of the noise term. Further extensions remain possible to describe the whole dynamics of cosmological first-order phase transitions via numerical simulations.

This work numerically validates the application of bio-inspired concepts on CMOS derived from bacterial photosynthetic light harvesters. We investigate a modification of symmetric inverted pyramid array CMOS image sensors into an asymmetrically shaped texture to explore the structural boundary of passive non-reciprocity. Diverging from traditional macroscopic continuum assumptions, we analyze whether structural asymmetry at sub-wavelength scales can induce non-reciprocal scattering under passive, linear, and time-invariant conditions. A theoretical framework based on perturbation theory is developed, estimating a potential efficiency enhancement of 5% to 15%. Numerical simulations performed via the MEEP finite-difference time-domain (FDTD) platform reveal that the linear response is highly localized, showing a subtle 0.02% change. This suggests that macroscopic Lorentz reciprocity remains robust at the investigated scale due to apex field concentration, defining a clear geometric threshold for microscopic non-reciprocity.

We develop the first rigorous topological framework for an auxiliary boundary-integral model motivated by physical scaling identities for wave scattering from self-similar or fractal media. The model is periodic in logarithmic scale, and a multiplicative Bloch-Floquet-Zak transform fiberizes its interscale coupling. For sufficiently small, well-separated components, equilibrium densities define a computable finite-dimensional projected matrix, while Riesz projections select the corresponding invariant spectral subspaces of the full boundary symbol. Under suitable spectral-isolation and point-gap conditions, and after recentering the two families at their respective same-scale reference values, we prove that the determinant winding of the exact Riesz-reduced family agrees with that of the projected matrix family. For regular-simplex configurations, we derive explicit nonzero winding formulas and track the resulting local winding data across finite prefractal levels and along a geometric sequence of wavenumbers. We also formulate conditional winding data for multiple dilation centers and show that the Zak phase of the chiral Hermitianization equals $\pi$ times the point-gap winding modulo $2\pi$. Thus, the scale-periodic boundary model admits a rigorous topological reduction.

We construct rank-zero irregular vertex operators for the Neveu–Schwarz algebra as linear maps between irregular Verma modules of the same rank satisfying the usual superconformal commutation relations and an irregular asymptotic condition. Under the nondegeneracy assumption $\Lambda_{2p}\neq0$, we prove their existence and uniqueness. We then extend the decomposition theorem for the Neveu–Schwarz algebra to the irregular setting: the tensor product of the free-fermion Fock module with a rank-$p$ Neveu–Schwarz irregular Verma module decomposes into an infinite direct sum of tensor products of two Virasoro irregular Verma modules. We also prove a compatible decomposition of the irregular vertex operators into tensor products of Virasoro irregular vertex operators. Using suitable pairings and mode insertions, we derive bilinear differential equations for weighted sums of products of Virasoro irregular conformal blocks of types $(0,0,1)$ and $(0,2)$. After explicit parameter identifications and a gauge transformation in the Painlevé V case, the resulting bilinear differential operators agree with those appearing in the quantum Painlevé V and IV tau-function equations.

We propose a differential full counting statistics protocol for mesoscopic transport. Additionally, we compare terminal Fano factors and noise cumulants between gate configurations at matched k1, instead of inferring a bulk divergence sensor from a single absolute F. it is illustrated analytically for a two channel factorization via a zero temperature geometry scan. Secondary benchmarks show that a two dimensional lattice non equilibrium Greens function calculation yields sub Poissonian Fano factors, whereas Kumars low temperature quantum point contact calibration validates the numerical implementation.

The g-factor is a key parameter governing the behavior of semiconductor spin qubits, as it directly determines the qubit frequency and its sensitivity to electrical and magnetic noise. Recent experiments in germanium quantum dots have revealed large g-factor variations under small gate voltage changes, indicating a strong coupling between electrostatics and spin properties. Here, we present a quantitative explanation based on strain-induced g-tensor modulation. By combining finite-element simulations of inhomogeneous strain with quantum calculations of hole wavefunctions, we show that device-induced strain produces spatially varying g-tensors. Gate voltages shift the quantum dot within this landscape, leading to substantial changes in the effective g-factor. Our results may account for the experimentally observed tunability and highlight the importance of in-plane g-tensor variations. This work establishes a direct link between strain, electrostatic control, and qubit performance in germanium spin qubits.

We investigate predissociation in homonuclear ($^{87}$Rb$^*$$^{87}$Rb$^+$) and heteronuclear ($^{87}$Rb$^*$$^{7}$Li$^+$) long-range Rydberg atom-ion molecules. Owing to their micron-scale bond lengths, these dissociate on time scales far removed from those of more tightly bound diatomic molecules. We employ the eigenchannel $R$-matrix method to compute predissociation rates for a broad range of principal quantum numbers $n$. The rates depend strongly on the mass, but more remarkably display a rapid and periodic variation as a function of $n$ as well as within a single vibrational ladder. A semiclassical Landau-Zener-Stückelberg analysis reveals that Stückelberg interference governs the decay process and produces the observed variation in the molecular lifetime. Although the heavy mass of the homonuclear Rb molecule constrains its predissociation rates to a sub-kHz level, the lighter molecule $^{87}$Rb$^*$$^{7}$Li$^+$ dissociates on time scales competitive with radiative and collisional decay. This can enable in situ study of non-adiabatic decay via ion microscopy.

Fixed quantum feature maps are increasingly inserted into diffusion denoisers, but standard image benchmarks do not reveal which structural constraint limits them. We introduce CoupledPhaseTexture, a torus-diffusion benchmark with analytic heat-kernel noising that separates parity, within-sector approximation, and sample-complexity limitations. For the depth-1 RY+CNOT+Pauli-Z family we prove a containment-free parity floor: all reachable features are even functions of the encoded angles while the sine components of the Bayes denoiser are odd, so the excess risk splits exactly into an inaccessible odd part and a within-sector residual. The first term is an irreducible, noise-scale-resolved lower bound holding for every even feature class, with no containment, linearity, or closedness assumption on the feature class. The obstruction is a property of the noise-conditioned denoising target rather than static representability: the floor is re-derived at each noise scale because the target's parity content changes with noise. The measured excess is dominated by the parity proxy on two distinct priors. Higher-order Z readouts improve the even sector, but entanglement does not lower the floor and re-uploading does not reliably close it. Classical controls confirm the deficit is parity rather than quantumness: a cosine-only bank is floored similarly, while adding the sine sector matches the reference. Among tested constructions, odd readouts and a noise-coupled encoder do not match the sine-carrying classical bank. These results motivate nonclassical data access or feature classes without efficient classical surrogates; they do not establish either as sufficient for quantum advantage.

Growing integration of distributed energy resources increases power-system variability and uncertainty. During disturbances, these effects can intensify generation-load imbalances and cascading failures. Controlled islanding limits their propagation by partitioning a compromised grid into connected, electrically sustainable islands. However, classical methods face rapidly growing computational costs as network size and island count increase. Quantum optimization offers an alternative for exploring this combinatorial partition space. Yet monolithic quantum formulations encode all assignment decisions in one circuit, causing qubit demand and circuit complexity to scale with network size. In this study, a qubit-bounded sequential distributed quantum approximate optimization algorithm (QAOA) framework is proposed to tackle coherent controlled islanding under limited quantum resources. It formulates the optimization as boundary-conditioned regional quadratic unconstrained binary optimization (QUBO) subproblems that are solved sequentially within a fixed qubit budget. Thus, circuit width remains independent of network size, with aggregate quantum workload scaling linearly on bounded-degree networks. Evaluation covers eleven IEEE systems from 9 to 300 buses using IBM quantum computing resources, with Gurobi and monolithic QAOA as references. Across all systems, the framework recovers feasible Gurobi-optimal partitions under noise, confirming the resilience of its solution quality. The results further show that the proposed method substantially reduces quantum-resource demand and circuit complexity relative to monolithic QAOA, allowing large islanding problems to be addressed within current hardware limits. The proposed framework provides a feasible and scalable pathway for quantum optimization in large-scale power systems.

We present Atacama Large Millimetre/submillimetre Array (ALMA) observations targeting the [OIII]$88\,\mu$m line for six $z\sim10$ galaxy candidates selected with the Hubble Space Telescope and the Spitzer Space Telescope. We detect a line ($4.5\sigma$) and dust continuum emission ($30\sigma$) in UDS_18697, while detecting neither robust line nor continuum emission in the remaining five objects. The detected line in UDS_18697 is identified as CO($J=9-8$), because follow-up James Webb Space Telescope (JWST) NIRSpec observations have confirmed the redshift as $z=2.54$. UDS_18697 is classified as an ultra luminous infrared galaxy (ULIRG) with far-infrared (FIR) luminosity of $L_\mathrm{FIR}\approx1.1\times10^{12}\,L_\odot$, assuming a dust temperature of $T_\mathrm{d}\approx42\,$K, estimated using a physically-motivated method. We find that UDS_18697 follows the $L_\mathrm{FIR}-L'_\mathrm{CO}$ relation for local and $z>2$ galaxies, albeit being slightly brighter in CO($J=9-8$). Also, based on the follow-up NIRSpec observations and spectral energy distribution fitting using JWST/NIRCam photometry, we found that most of our targets are suggested to be low-$z$ interlopers. Motivated by these redshift misclassifications, we investigate colour–colour selection criteria for high-$z$ galaxies using JWST spectroscopic survey catalogues. We find that elevating a colour threshold tracing the Lyman break is crucial for constructing a robust high-$z$ sample, particularly for wide field surveys such as Euclid Deep Fields and Roman High-Latitude Wide-Area Survey.

We investigate scalar induced gravitational waves (SIGWs) as probes of a dark QCD crossover. Motivated by twin Higgs and asymmetric twin baryon dark matter scenarios, we consider a dark QCD sector with a confinement scale approximately 5.5 times the Standard Model (SM) QCD scale. We construct the effective energy and entropy degrees of freedom for the SM supplemented by dark QCD sectors containing either three light dark quark flavors or all six dark quark flavors. The resulting equation of state parameter and sound speed are then used to solve the first-order scalar perturbations and the second-order SIGWs through the SM and dark QCD crossover epochs. For a monochromatic primordial curvature power spectrum, we first demonstrate that the realistic SM thermal history modifies the SIGW spectrum relative to the idealized radiation-dominated case. We then show that a dark QCD crossover generates an additional frequency-shifted distortion when the enhanced scalar mode reenters the horizon near the dark confinement scale. This distinctive feature can therefore serve as a characteristic signature of the dark QCD sector. Our results demonstrate that SIGWs provide a complementary cosmological probe of hidden confining sectors, with characteristic spectral features shifted to higher frequencies relative to the SM QCD imprint. The analysis developed in this work can also be extended to other well-motivated theories containing different dark confining sectors.

We present ultra-deep JWST spectroscopy of GN-z11 ($z=10.6$) obtained through the SPURS Cycle 4 Large Program, providing the deepest rest-UV view yet obtained of a galaxy at $z>10$. GN-z11 was previously found to be nitrogen-enhanced with detectable Ly$\alpha$. The SPURS spectrum reveals P-Cygni stellar wind features and broad He II emission that are jointly reproduced by stellar population models incorporating very massive stars (VMS; $>100\,M_\odot$) at low metallicity and young ages ($\lesssim3$ Myr). We also detect a broad ($\rm FWHM=1670$ km s$^{-1}$) component to N IV] $\lambda1486$, now seen in several nitrogen emitters, potentially arising from dense WN-like winds or LBV-like outbursts associated with a population of VMS in a dense environment, though an AGN-driven wind cannot be excluded. In either scenario, this broad component may trace the gas producing GN-z11's nitrogen enhancement. Rest-UV absorption lines reveal a fast ($\sim500$~km~s$^{-1}$), highly ionized outflow and a negligible neutral gas covering fraction. We resolve the weak Ly$\alpha$ emission (EW=5.6 Å, $f_{\rm esc,Ly\alpha}=2.7$%), finding a broad red wing (44% of flux at $>500$ km s$^{-1}$) that should experience reduced IGM damping wing suppression and help explain Ly$\alpha$ visibility at $z>10$. Fine-structure O I* $\lambda1304$ emission indicates dense neutral gas near a subset of the ionizing sources, which may also scatter Ly$\alpha$ to the large observed velocities. The weak low-ionization absorption favors a picture in which this dense neutral gas is confined to a compact nuclear region. Together, these results are consistent with a rapid burst of star formation building up the dense nuclear regions and surrounding clusters in GN-z11.

The jets of blazar active galactic nuclei (AGN) are promising sites of hadron acceleration and subsequent neutrino production, owing to their extreme intrinsic power and high radiation density. Potential associations of IceCube neutrinos with blazars displaying delayed radio flares, such as TXS~0506+056 and PKS~1424+240, may support this scenario. However, the mechanisms and location of particle acceleration in the jet remain unclear. The 2017 IceCube event associated with TXS 0506+056 was concurrent with the initial peak of a flare in gamma rays, followed by a longer flare at radio frequencies peaking three years later. State-of-the-art single-zone radiative source models focus on the compact high-energy-emitting region, and thus fail to describe this subsequent radio enhancement. In this work, we model the time-domain multi-frequency evolution of TXS 0506+056 by considering electron emission along the physically extended jet. We couple a numerical particle interaction framework with a dynamic description of the temporal and spatial jet evolution down to the parsec scale. We fit the model to multi-wavelength data, including multi-frequency radio light curves. The results suggest that the parsec-scale jet meets a population of older, cooled electrons near the edge of the observable radio core, establishing a causal relation between the initial high-energy emission and trailing radio activity. This spatially and temporally resolved modeling approach can offer new insights into the physical conditions along the jet of flaring neutrino candidate blazars.

This paper is associated with a poster winner of a 2025 American Physical Society's Division of Fluid Dynamics (DFD) Milton van Dyke Award for work presented at the DFD Gallery of Fluid Motion. The original poster is available online at the Gallery of Fluid Motion, at https://doi.org/10.1103/APS.DFD.2025.GFM.P012

In this paper, 65 nm n-type Metal-Oxide-Semiconductor Field-Effect-Transistors (nMOSFETs) are taped out and measured at 292 K to 4.5 K. Technology Computer-Aided-Design (TCAD) model parameters are then calibrated to fit the simulation curves to experimental electrical curves. Transmission electron microscopy (TEM) is used to unveil the dimensions of the transistors to ensure accurate modeling. The experimental and simulation capacitance-voltage (CV) curves, drain current - gate voltage (IDVG) curves, and drain current - drain voltage (IDVD) curves are fitted well using the calibrated parameters. The major models calibrated are the Lucent model, which is comprised of an extended PhuMob model, Lombardi model for surface mobility, and the Hänsch high field mobility model. A band-tail model with adjusted band width is applied to fit the sub-threshold swings at all temperatures. The calibrated parameters are expected to be applicable to other technologies because TCAD models are not technology-specific. It is also found that, except for saturation velocity, no new temperature-dependent model is needed. The calibration process and fitting strategies are detailed and are expected to be applicable to calibrate other transistor types.

Accurate solvation free energies from molecular dynamics simulations require efficient sampling of coupled slow variables, including solvent coordinates, solute conformational modes, and the alchemical coordinate $\lambda$. Here, we develop a $\lambda$-dynamics framework that combines mass scaling, on-the-fly probability enhanced sampling (OPES), and driven adiabatic free energy dynamics (d-AFED) to address these sampling challenges within a unified protocol. For rigid organic solutes, Hamiltonian replica exchange with mass scaling is first used to quantify the effect of octanol solvent relaxation. Reducing all octanol atomic masses by a factor of ten accelerates convergence by more than fivefold while preserving equilibrium solvation free energies. These calculations then provide reference benchmarks for $\lambda$-OPES, a dual-bias $\lambda$-dynamics strategy that combines the "standard" and "explore" variants of OPES to promote transitions along the alchemical coordinate. This approach reaches convergence on timescales comparable to replica exchange, but without predefined $\lambda$ windows or multiple parallel simulations. For flexible $N$-acetyl amino-acid amide solutes, $\lambda$-OPES is coupled with d-AFED on selected backbone and side-chain dihedrals to enable simultaneous alchemical and conformational enhanced sampling. This combined strategy improves agreement with experimental octanol-water partition coefficients and reduces the mean absolute error from 0.75 log units with $\lambda$-OPES alone to 0.30 log units with $\lambda$-OPES-d-AFED. Overall, this work establishes an integrated enhanced sampling protocol for solvation free energy calculations across rigid organic solutes and flexible peptide-like solutes, and provides a foundation for the application of alchemical free energy methods to larger and more conformationally complex systems.

Stellar activity cycles on magnetically active stars can be estimated by molecular absorption bands. We have previously introduced a molecular index which compares absorptional line strength of the TiO567nm with its nearby continuum has previously been introduced. In this work we use this indicator to evaluation long-term activity variations for Proxima Centauri star, using spectroscopic data from HARPS. The results indicate periodicity with an activity period of 2873(+47.4-53.9) days, which is similar to the previous measurements from other indicators.

An “Attention Residual U-Net” method is described for probabilistic quantitative precipitation forecasting (PQPF) that predicts the hourly probability of no precipitation plus the distribution of positive precipitation from a weighted mixture of two Gamma distributions. The neural network is trained on patches of numerical weather prediction (NWP) hourly precipitation from The Weather Company's convection-permitting GRAF (Global high-Resolution Atmospheric Forecasting) model along with terrain information and column-average relative humidity from the National Oceanic and Atmospheric Administration's (NOAA's) Global Forecast System (GFS). The target data are NOAA's Multi-Radar, Multi-Sensor (MRMS) gauge-corrected, quality controlled radar data sampled to the same grid as the GRAF data. The network outputs distributional parameters for each model grid point. Training uses negative log-likelihood as a proper scoring rule, with climatological initialization for stable convergence. Inference is performed as a single forward pass over the contiguous United States (CONUS) domain, with edge-replication padding to satisfy the network's spatial-divisibility requirement. The subsequent forecasts are spatially detailed, highly reliable, and skillful with respect to climatology and a simpler reference forecast method. The method is particularly useful for estimating probabilities in regions with large terrain variation.

Low-dimensional reductions provide a useful framework for studying high-dimensional dynamics on complex networks, but most existing approaches are restricted to pairwise interactions. Here, we develop a one-dimensional reduction for dynamical systems on networks with purely higher-order interactions. The reduction is formulated through an effective higher-order interaction strength ($\beta_{\Delta}$), associated with the triangular interactions of the underlying network and the dynamical system's effective state. We present a theoretical framework for the dimension-reduction approach and validate it across three dynamical models with exclusively higher-order interactions. We find that the reduction accuracy is mainly determined by the homogeneity of node states, i.e., the deviations in state values become very small. Numerical results on synthetic and real networks show that the reduced model captures the effective steady states and transitions of the full system with good accuracy.

The lumbar cartilage endplate (CEP) is a short-$T_2^*$ structure whose composition has been linked to disc health. Ultrashort-echo-time (UTE) MRI enables direct CEP visualization, but acceleration and reconstruction may alter quantitative $T_2^*$ even when image quality improves. We evaluated how radial undersampling and reconstruction strategy affect CEP $T_2^*$ fidelity in a fully synthetic setting. A 96 x 96 sagittal lumbar phantom with five CEP levels (ground-truth $T_2^*$: 24, 22, 20, 18, and 16 ms) was simulated with six UTE echoes, eight receive coils, and radial sampling. Acceleration factors $R=1,2,4,6,8$ used 302, 151, 76, 50, and 38 spokes, respectively. Reconstructions were CG-SENSE, joint multi-echo FISTA, and direct model-based estimation from k-space. Twenty independent complex-noise realizations were evaluated per acceleration. Direct model-map RMSE increased from 0.172 ms at $R=1$ to 0.800 ms at $R=4$, 1.472 ms at $R=6$, and 2.256 ms at $R=8$. At $R=4$, joint-FISTA had lower image NRMSE than the direct model (0.132 vs. 0.203), while the direct map had lower level-wise $T_2^*$ RMSE than CG-SENSE and joint-FISTA ROI fits (0.800 vs. 1.448 and 1.288 ms; estimators differed). At $R=8$, CG-SENSE ROI fitting had the lowest $T_2^*$ RMSE (1.501 ms), whereas the direct model showed systematic underestimation (bias, -2.136 ms; CCC, 0.723). Image fidelity and quantitative biomarker fidelity therefore diverged under radial acceleration. In this synthetic framework, $R=4$ was a promising operating point for direct CEP $T_2^*$ mapping, whereas $R=8$ produced substantial bias and spatial instability. Scanner, phantom, and in vivo validation are required before clinical translation.

Classical PET glycolysis struggles with industrial scale-up due to a research paradigm defect: uncoupled reaction optimization that ignores system-level engineering entropy. By establishing a governing reference frame, Scientific Reasoning Units (SRUs) and human-AI collaborative discovery in this article, we present a Three-Step Synergistic Reinforcement Paradigm addressing the triple failure modes of traditional systems-mass-transfer collapse, viscosity deadlock, and side-reaction accumulation. By integrating twin-screw controlled shearing, solid-state micro-homogenization, and deep depolymerization (2:1 EG/Oligomer ratio), we achieve an ultrafast kinetic regime. BHET yields surge to 80% to 95% within 10 minutes, eliminating multi-hour thermal bottlenecks and delivering an economically viable framework for closed-loop polyester recycling.

Gridded-dataset suitability varies by support, season, variable, and application. This study evaluated E-OBS, AgERA5, MARS-STAT/JRC Agri4Cast, ERA5, and ERA5-Land against observations from 624 European Climate Assessment & Dataset (ECA&D) and Hellenic National Meteorological Service (HNMS/EMY) stations, using 18.18 million source-station-day records containing minimum (TN) and maximum (TX) temperatures. Derived variables included mean temperature (Tmean), diurnal temperature range (DTR), and growing degree days (GDD). Identical-support rankings and station bootstraps assessed daily and GDD performance; Fisher's z transformation summarized seasonal correlations; temporal and network tests screened trends. E-OBS minimized daily and monthly-climatology-removed anomaly root mean square error (RMSE) for TN, TX, Tmean, and DTR in all 16 country-variable comparisons. With at least 10 matched years, E-OBS led 42 of 64 seasonal RMSE comparisons and 59 of 64 correlation comparisons; MARS-STAT/JRC Agri4Cast led the remaining 22 and five, respectively. E-OBS minimized GDD RMSE in Spain and Italy, whereas MARS-STAT/JRC Agri4Cast led in Greece and narrowly led in France. GDD RMSE equaled 3.3-7.2% of observed mean GDD. Robustness tests supported increases in Spanish annual DTR, French annual TX, and French growing-season GDD. The lapse-rate correction improved 22 of 40 comparisons but usually worsened TN. Dataset choice should reflect support, variable, season, terrain, and application.

Despite the remarkable observational success of the $\Lambda$CDM model, the physical origin of dark energy and the cosmological constant remain unresolved, motivating the exploration of dynamical vacuum scenarios within modified theories of gravity. Inspired by the quantum field theoretical description of running vacuum energy, we investigate a running vacuum cosmology in the framework of linear $f(R,T)=R+\lambda T$ gravity. Unlike recent studies that establish an effective correspondence between running vacuum energy and modified gravity, our approach directly incorporates a quantum field theory motivated running vacuum scenario into the $f(R,T)$ framework and examines its cosmological implications. Exact analytical solutions of the modified field equations are obtained in a spatially flat Friedmann–Lemaître–Robertson–Walker spacetime, yielding an analytical expression for the Hubble parameter. The free model parameters are constrained using the latest Pantheon+SH0ES compilation, DESI baryon acoustic oscillation measurements, and their joint dataset through Markov Chain Monte Carlo analysis. The observationally constrained model successfully reproduces the observed expansion history, remains consistent with independent Cosmic Chronometer measurements, predicts an age of the universe within current observational bounds, and yields an effective equation of state compatible with current observations. Furthermore, the statefinder and $Om$ diagnostics indicate close agreement with the $\Lambda$CDM scenario at late times, while the generalized second law of thermodynamics remains valid throughout cosmic evolution. These results demonstrate that the proposed framework provides an observationally viable and thermodynamically consistent realization of running vacuum cosmology in $f(R,T)$ gravity, offering a theoretically motivated alternative for describing the present accelerated universe.

We present CosmoFit, a desktop graphical interface for Bayesian parameter inference in background cosmology. The application is designed to simplify cosmological analyses by reducing the need to manually program each step, while maintaining the transparency and reproducibility of the results. Users can define an expansion history H(z), specify fixed and sampled parameters, assign prior ranges and proposal scales, select the available observational likelihoods, and run Markov chain Monte Carlo analyses from a unified graphical interface. CosmoFit uses Cobaya for Bayesian sampling and GetDist for posterior analysis and visualization. The current version supports cosmic-chronometer data and the official Pantheon+, Pantheon+SH0ES, and Union3 supernova likelihoods available through Cobaya. For each run, the application stores the configuration files, metadata, execution logs, chains, and numerical summaries required to inspect and reproduce the analysis. The performance of CosmoFit was evaluated through unit tests, a parameter-recovery test using synthetic data, and an independent comparison with an analysis performed directly in Cobaya. The posterior mean values obtained with both procedures agree to within less than one percent. In addition, the synthetic-data test recovers the fiducial parameters within the expected credible regions. As an illustrative example, we perform a spatially flat wCDM analysis using Pantheon+SH0ES and obtain marginalized constraints and triangle plots directly from the interface. Within its current scope, CosmoFit provides an accessible, transparent, and reproducible tool for research and academic applications involving explicit models of the background cosmological expansion.

There is a longstanding dogma in the physics of ultracold neutrons (UCN): The optimal temperature of ortho-deuterium based UCN-sources must not exceed $5\,\mathrm{K}$. This value has been established by the pioneering work of Golub et al. decades ago, utilizing previously established cross sections for solid ortho-deuterium. But recently, an improved calculation of the crucial 1-phonon up-scattering cross section - using the so-called corrected Incoherent Approximation - leads to a new upper limit for the optimal operation temperature of ortho-deuterium based UCN sources. After a discussion of the relevant cross sections of the \(\mathrm{D}_2\)-molecule we conclude that the optimal temperature lies between $10\,\mathrm{K}$ and $12\,\mathrm{K}$, a factor 2 higher than estimated earlier. This offers significantly relaxed cryogenic conditions for UCN experiments with solid ortho-deuterium and especially for the operation of ortho-deuterium based ultracold neutron sources.

Building a quantum machine learning (QML) model competitive with a classical baseline currently requires a practitioner to separately choose a circuit architecture, a data-encoding scheme, a model paradigm (kernel versus variational), and a set of training hyperparameters, then verify after the fact that the chosen circuit is even trainable. Existing QML libraries provide the primitives for this but not the search, and existing classical AutoML libraries provide the search but not the quantum-specific search space or diagnostics. We present qkabrine-automl, a Python package that treats architecture, encoding, model type, and hyperparameters as a single, jointly searchable configuration space, evaluated through one consistent harness regardless of which of five search strategies proposed the candidate. The package integrates trainability diagnostics, a Data Quantum Fisher Information Metric (DQFIM) estimate and a gradientmagnitude barren-plateau monitor, directly into the evaluation loop as an optional prescreening step, alongside expressibility and entangling-capability characterization, a post-search circuitsurgery pass for NISQ deployment, and OpenQASM export. We position this contribution against recent AutoQML frameworks that already automate parts of the QML pipeline, and report a small, fully reproducible illustrative run rather than a benchmark claim.