We derive general trade-off relations among the power, efficiency, and constancy for two-terminal thermoelectric systems in the linear response regime. Constancy, which quantifies the steadiness of the heat engine, is measured by its fluctuations. The bounds of the efficiency, power and fluctuations are valid even when time-reversal symmetry is broken, revealing how such a symmetry breaking alters the fundamental constraints on steady-state energy conversion. Our results extend and refine previously established universal trade-offs, offering deeper insight into the performance limits in nonequilibrium thermodynamics. Guided by this bound, heat engines with broken time-reversal symmetry can be operated at near-Carnot efficiency while maintaining finite power output and fluctuations, enabling them to outperform their traditional counterparts.

We postulate that the excesses of di-dijet events observed at the LHC are attributed to the production of four fourth-generation quarks $b'$ with a mass $m_{b'}\approx 2$ TeV at few-TeV scales. The di-dijet signals around the four-jet invariant mass $m_{4j}\approx 8$ TeV arise from a resonant $b'b'\bar b'\bar b'$ tetraquark production, where the dijet resonances of masses about 2 TeV correspond to $b'\bar b'$ first excited states (color-octet scalars with the principal quantum number $n=2$) in a Yukawa potential created by Higgs boson exchanges. Those around $m_{4j}\approx 3.6$ TeV originate from a non-resonant $b'b'\bar b'\bar b'$ production, where the dijet resonances of masses 0.95 TeV correspond to $b'\bar b'$ ground states (color-octet vectors with $n=1$). It is shown that a $b'\bar b'$ system with $m_{b'}\approx 2$ TeV in the Yukawa potential does generate the aforementioned bound state spectrum. We then illustrate that the observed excesses can be accommodated in our setup by translating the fourth-generation model to the effective theories containing color-octet scalars and vectors available in the literature. The di-dijet events at $m_{4j}= 6.6$ TeV and 5.8 TeV with dijet masses about 2 TeV can also be interpreted in the same framework. Simply speaking, our scenario can be viewed as a TeV-scale version of the search for a fully charmed tetraquark via the four-muon channels $X(6900)\to (c\bar c)(c\bar c)\to 4μ$ at a GeV scale.

We report MINERvA's first measurement of inclusive charged-current $\barν_μ$ cross sections on carbon, hydrocarbon, iron, and lead, and their ratios to the cross section on hydrocarbon, as functions of the antimuon transverse momentum, $p_{\mathrm{T}}$. Using a wide-band $\barν_μ$ beam with mean energy $\sim 6~\text{GeV}$, these measurements probe all interaction modes, including the transition from resonance production to deep-inelastic scattering. The total uncertainties are typically $5-10\%$ for the absolute cross sections and $2-5\%$ for the ratios. Comparisons with multiple neutrino interaction models reveal significant discrepancies in the $p_{\mathrm{T}}$ dependence, particularly for heavier nuclei. The disagreements are most pronounced at low $p_{\mathrm{T}}$ but extend across the full $p_{\mathrm{T}}$ range, indicating missing or mis-modelled nuclear effects.

In this study, energy backflow in the Poynting vector, as well as its orbital and spin current density components, has been examined for a 2-dimensional causal unidirectional vector-valued monochromatic electromagnetic wave. Linear transverse electric (TE), transverse magnetic (TM), and circular polarization cases are considered and studied in detail, including both electric and magnetic contributions to the current density components. Spin current backflow has been found to be unexpectedly strong. A study of the energy backflow is also presented in the scalar version of the 2-dimensional monochromatic wave. A detailed study has been carried out of the correlation of the positions of energy backflows with local wavenumbers and their signs, the zeros of appropriate intensities and the presence of vortices.

The Holevo limit bounds the channel capacity of a communication channel in which information is encoded in quantum states in a Hilbert space at the transmitter and decoded using quantum measurements at the receiver. Saturating the Holevo limit requires quantum-limited transceivers that either generate quantum states of light or employ quantum-limited measurements. Here, we demonstrate an integrated photonic-electronic quantum-limited coherent receiver (QRX) achieving 14.0 dB shot noise clearance (SNC), 520 $μ$W knee power, 2.57 GHz 3-dB bandwidth, 3.50 GHz shot-noise-limited bandwidth, and 90.2 dB common-mode rejection ratio ($\mathrm{CMRR}$). We scale this design to a 32-channel QRX array with median 26.6 dB $\mathrm{SNC}$, and automatic $\mathrm{CMRR}$ correction yielding a median 76.8 dB $\mathrm{CMRR}$ at minimum. Using the integrated QRX and fiber-optic transmitter, we measure $0.15\pm0.01$ dB of squeezing below the shot noise limit, limited by off-chip losses. We propose a squeezed light communication scheme that can surpass the Shannon limit, with a path toward the Holevo limit.

Horizontal stirred bed reactors (HSBRs) are used in gas--phase polyolefin production, where efficient solids mixing and controlled residence time distributions are essential for product quality and stability. Despite their industrial relevance, the influence of operating conditions on granular flow and mixing in HSBRs is not well understood. Discrete Element Method (DEM) simulations are used to study the effects of rotation speed and fill level on particle motion, mixing, and axial transport in a lab--scale HSBR. An industrial--grade polypropylene powder is modelled using calibrated contact parameters. Mixing is quantified using the Lacey index in axial (z) and cross--sectional (xy) directions. Particle circulation is characterised via cycle--time analysis and a coarse--grained angular velocity field. Axial dispersion coefficients are obtained from particle trajectories using both Einstein--type and cycle--based approaches, and validated with a diffusion model predicting the axial Lacey index. Results show that axial mixing depends strongly on rotation speed and fill level: higher rotation speeds accelerate homogenization, while higher fill levels slow mixing. Cross--sectional mixing is mainly sensitive to rotation speed, with fill--level effects diminishing at higher speeds. Cycle time decreases with increasing rotation speed and fill level, indicating enhanced circulation. Axial dispersion increases with rotation speed but decreases with fill level, with consistent results across methods. These findings reveal trade--offs between axial mixing, circulation, and dispersion, highlighting the need to balance operating conditions and demonstrating the capability of DEM to support HSBR optimisation.

Machines are designed, assembled, and programmed to convert power into predetermined dynamics and functions. In contrast, living systems such as interacting cells and animal groups self-organize, synchronize, and perform complex tasks without predefined patterns. Inspired by these decentralized architectures, experiments have shown that small assemblies of elastically coupled self-propelled robots can achieve two fundamental functionalities observed in nature: collective motion and oscillatory deformations. However, biological inspiration has steered research toward translational self-propulsion, while active rotation remains an underexplored route to designing broader animate materials. Here, we study the self-organization of microscopic metamachines composed of thousands of 3D-printed rotary motors. We first demonstrate and explain how motors precessing in unspecified directions collectively arrange their dynamics into a pristine antiferromagnetic phase. Next, we elucidate the emergence of spatiotemporal order in the form of phase coherence in the rotors' precession. Finally, we show how quenched disorder initiates the free propagation of phase waves across self-organized regions with mismatched rotation speeds. Our results suggest that spinner-based metamachines could illuminate metachronal-wave formation in living systems, and signal propagation in synthetic animate materials.

The study of stronger-than-quantum phenomena (i.e., postquantum) has enabled a deeper understanding of the scope of quantum theory. Much is known about the case of correlations in Bell scenarios, where the device-independent framework allowed us to explore its possibilities independently of the formalism of quantum theory. However, less is known about the phenomenon of Einstein-Podolsky-Rosen steering. Here, the `characterised parties' are assumed to describe their systems locally through the quantum formalism, which inconveniences a theory-independent description. In addition, a theorem by Gisin and Hughston, Josza and Wootters further hindered the discovery of the phenomenon. The study of postquantum steering, initiated about a decade ago, has been quite fruitful, including: the development of mathematical formalisms that frame the effect, resource theories that quantify it as a resource, and activation protocols that relate it to Bell correlations. However, all these results have a limitation in common: they apply to scenarios with only one quantum party. Here we articulate the concept of postquantum steering for scenarios with multiple quantum parties, bringing in the missing piece to the puzzle. We provide an algorithm to certify postquantumness, which in some cases also certifies quantumness. We also define a hierarchy of semidefinite programs that bounds the set of quantum assemblages from the outside. Moreover, we show that the study of postquantum steering is fundamentally relevant since it is not just a mere mathematical curiosity allowed by the no-signalling principle, but it may arise within compositional theories beyond quantum theory. Our work further discovers a peculiarity of steering: its theory-independent description fundamentally prevents a direct connection with Bell nonlocality -- e.g., nonclassical Bell correlations do not imply nonclassical steering.

The solid electrolyte interphase SEI critically dictates the cyclability and Coulombic efficiency of sodium-metal batteries, yet its dynamic formation mechanisms and atomic-scale evolution during electrochemical cycling remain elusive due to the spatiotemporal limitations of existing techniques. Here, an "Interface Reactor" sampling strategy is proposed to construct a charge-aware neuroevolution potential (qNEP). This approach overcomes the instability bottlenecks of conventional machine learning potentials, enabling stable, first-principles-accurate molecular dynamics simulations of complex electrode-electrolyte interfaces on the hundred-nanosecond scale. Fundamentally distinct SEI formation mechanisms are revealed during the early stage: carbonate-based electrolytes form heterogeneous organic-inorganic matrices via "mixed co-formation," whereas ether-based electrolytes generate dense, self-limiting inorganic barriers through "surface-energy-controlled" NaF crystallization. Metadynamics simulations further elucidate that these compositional disparities govern sodium-ion storage dynamics: NaF-rich SEIs facilitate efficient metallic deposition, while carbonate-dominated interphases induce irreversible sodium trapping and continuous electrolyte decomposition. These findings establish a comprehensive atomic-scale framework linking solvation structure, interfacial reaction networks, and electrochemical performance, providing mechanistic guidelines for rational SEI engineering in next-generation alkali-metal batteries. Crucially, a general and robust computational framework is established for simulating complex interfacial reactions in electrochemical systems.

We present a JWST/NIRSpec-IFU study of metallicity gradients in seven low-metallicity systems at $z=7.2-9.5$. The main sample spans stellar masses of $\rm \log(M_*/M_{\odot}) \sim 7.8-9.5$, star formation rates (SFRs) of $\rm \log(\text{SFR} / M_{\odot} \text{yr}^{-1}) \sim 0.5-2.5$, and gas-phase metallicities of $4\%-15 \%~Z_\odot$. Within our sample, we also identify three low-metallicity satellite galaxies associated with two of our sources, providing a rare view of early-epoch interactions. The three satellites exhibit even more primordial properties, with metallicity $3\% -4\% ~Z_\odot$ and low star-formation activity ($\rm \log(\text{SFR} / M_{\odot} \text{yr}^{-1}) \sim -0.5$ to $-0.9$). We find that our galaxies, and especially the satellites, are significantly offset from the local Fundamental Metallicity Relation (FMR), with deviations reaching $Δ\text{FMR} \approx -0.9$ dex. This indicates that these galaxies are likely experiencing strong accretion of pristine gas. Overall, we observe a large scatter in radial metallicity gradients, ranging from positive to negative with an average metallicity gradient of $\rm -0.02 \pm 0.04 \ dex \ kpc^{-1}$. Flat gradients are found in systems with confirmed satellites, suggesting that tidal interactions and mergers drive the radial mixing necessary to homogenise the interstellar medium. The (tentative) presence of an AGN in two of our sources suggests that strong feedback may also be responsible for the observed flat gradients. Conversely, the detection of a positive gradient in one source points toward a direct funnelling of metal-poor gas inflow into the central region of the galaxy. These results show that galaxies in the first billion years grow through diverse, episodic processes, suggesting that early evolution is characterised by structural variety rather than a single, predictable path.

We present two methods to estimate bottom topography in a shallow water flow using only surface deformation measurements. One is based on Physics-Informed Neural Networks (PINNs) and the other on the Adjoint State Method. We test both methods using synthetic data in 1D and 2D cases. Both are able to successfully reconstruct not only the bottom topography but also the surface velocity. Both also show robustness against noise and data sparsity up to reasonable levels.

We demonstrate complete coherent control of a single spin qubit confined in a self-assembled InAs negatively charged quantum dot subjected to an Oblique magnetic field, and directly compare this regime with the conventional Voigt geometry. In the Oblique-field configuration, the groundstate spin eigenstates are found to be unequal superpositions of the bare electron spin, with their composition tunable via the orientation of the applied field. This tunable spin mixing provides an additional degree of freedom to engineer the spin basis and associated optical couplings in the charged quantum dot system. Although this geometry has a distinct structure with important implications, it provides a regime in which we can fully and coherently control the tailored spin qubit. We observe Rabi oscillations and Ramsey fringes, and demonstrate arbitrary single-qubit rotations, enabling a direct comparison with the Voigt case. Our results establish that spin-qubit control does not necessarily require a pure Voigt geometry and can instead be achieved under Oblique magnetic fields. This relaxes constraints on device and field alignment and offers a versatile route to design and optimize quantum information processing architectures in semiconductor quantum dots.

Debris disks are created and sculpted by planetary bodies in the orbital space they share. The properties of these disks, including mass, orbital extent, and morphology, can be indicators of their planetary shepherds. Recently, T. Pearce and collaborators placed limits on the masses and orbits of hypothetical planets around 178 stars with resolved debris disks. We consider 176 of these stars, all the objects that have astrometric data in the Gaia Data Release 3 archive, to assess planet detection from astrometry. Our analysis begins with a set of stellar hosts of known exoplanets, selected to roughly match the parallax, apparent magnitude, and color of the 176 debris disk systems. We confirm that Gaia's ruwe parameter, a measure of the quality of astrometric fitting to a linear drift model, is sensitive to the presence of massive companions, even planetary ones. Guided by ruwe and a metric derived from a machine-learning algorithm trained on Gaia parameters from the exoplanetary host data set, we identify promising stars with debris disks that may host as-yet-undiscovered planets. These stars will be compelling subjects for time-series analyses with Gaia Data Release 4.

Topological defects (TDs) are crucial for understanding important physical properties of crystalline materials including mechanical failure, ion transport, and two-dimensional melting. This concept has not translated to disordered materials like glasses because these solids have no obvious reference structure that can be used to define TDs. As a result, key properties related to those listed above have typically been modeled using purely phenomenological approaches. Recent studies have demonstrated that certain observables commonly associated with TDs can also be identified in disordered solids indicating that topological concepts may be as crucial in amorphous solids as in crystals. This hints that TDs may offer a first-principles framework for understanding their mechanical response and complex spatiotemporal dynamics. In this Perspective, we review recent theoretical, numerical, and experimental studies that have exploited topological concepts to rationalize mechanical properties of amorphous solids. We also highlight pressing open questions and some promising directions for future research in the field.

Based on experimental results, this work proposes the influence of the Oxygen order present in the Ortho-II superstructure of YBa$_2$Cu$_3$O$_{7-δ}$ (YBCO), on the final ordering of Oxygens in its Orthorhombic phase for $δ$ $\approx$ 0. Isothermal oxygenation (oxyg) of YBCO powder material is performed, starting from non-oxygenated material ($δ$ $=$ 1) and evolving until saturation in an oxygen atmosphere. The oxyg process is carried out within a temperature range from 300 $^o$C to 800 $^o$C (300 $^o$C $<$ T$_O$ $<$ 800 $^o$C). During the oxyg process, and using a thermogravimetric balance, the evolution of mass (m) and the differential thermal analysis (DTA) of the material are monitored with respect to an inert reference material subjected to the same conditions as the YBCO powder. These results allow observation of the Tetragonal-Orthorhombic (T-O) transition occurring in the YBCO material. From these results, oxygenated YBCO material is obtained by working at different temperatures and under two different conditions: through a direct T-O transition into the Ortho-I superstructure, and by passing through the Ortho-II superstructure along the transition. The material obtained under these two conditions is studied by X-Ray diffraction, revealing differences in the resulting diffractograms. Furthermore, we propose that, for low values of T$_O$ (T$_O$ $<$ 400 $^o$C), the T-O transition proceeds through the region of the phase diagram where the Ortho-II superstructure is present, leading to progressive ordering of the Oxygen atoms within the material. This ordering leaves a fingerprint in the final configuration reached by the YBCO material, even beyond the region where the Ortho-II superstructure is stable. Finally, we suggest that this mechanism is responsible for the differences observed between the diffractograms obtained under both conditions.

The space-time correlation of a passive scalar advected by a Gaussian colored-noise velocity with wavenumber-dependent correlation times and power-law spatial spectra is investigated in the present paper. Within the inertial-convective subrange, we derive an analytical solution for the space-time correlation. This solution validates the elliptic approximation (EA) model [He and Zhang, Phys. Rev. E 73, 055303(R) (2006)], demonstrating that the iso-correlation contours are self-similar in the co-moving space-time frame $(r-Uτ, Vτ)$, with a universal spatial-to-temporal intercept ratio of 1.55. Unlike the classic Kraichnan white-noise model, our formulation simultaneously recovers the Obukhov--Corrsin scaling for spatial correlations (when the velocity obeys Kolmogorov scaling) and reproduces the random-sweeping mechanism, yielding Gaussian (rather than exponential) temporal decorrelation of scalar Fourier modes. Our results clarify the underlying decorrelation mechanism of passive scalars: mean-flow advection and large-scale sweeping dominate temporal decorrelation, and small-scale distortion dominates spatial decorrelation.

In a recent paper [M. Gül et al., Phys. Rev. E, 110 (6), 064115] we showed that test particle sum rules, which address the excess chemical potential and isothermal compressibility, could be used to develop new and accurate classical density functionals for hard-sphere (HS) fluids. Here we extend our approach to the construction of HS functionals building upon the state of art White-Bear (WB) and White-Bear mark II functionals. Employing the same test-particle sum rules we determine the two free parameters in the Lutsko [James F. Lutsko, Phys. Rev. E, 102, 062137] formulation of fundamental measure theory (FMT) by minimizing the relative errors between different routes to the two thermodynamic quantities. The resulting optimized Lutsko WB functionals, especially Lutsko WB mark II, are generally more accurate and consistent than those obtained in earlier treatments.

In this paper, we study the internal structure of light pseudoscalar mesons using spin improved power-law wave functions. We choose the pion and the kaon for our work. We use the standard quark-quark correlation functions to calculate the distribution amplitudes (DAs), parton distribution functions (PDFs), transverse momentum dependent parton distribution functions (TMDs), and generalized parton distribution functions (GPDs) at zero skewness and form factors. We present all the above distribution functions through the overlap of light-front wave functions (LFWFs). We use leading-order Efremov-Radyushkin-Brodsky-Lepage (ERBL) equations for DAs and next-to-leading-order (NLO) Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) equations for PDFs to evolve them to higher scales. We find that only 41\% of the longitudinal momentum fraction is carried by the quark and antiquark of both pion and kaon at 16~GeV$^2$. The vector form factors for both the pion and the kaon are found to be in good agreement with experimental data. Similarly, the electromagnetic charge radii are found to be 0.668~fm and 0.704~fm for the pion and kaon, respectively.

The $\vartheta$-MGGA class of density functionals is formally reformulated as Hessian-level meta-generalized gradient approximations (HL-MGGAs). In contrast to standard meta-GGAs that rely on the orbital-dependent kinetic-energy density or the density Laplacian, HL-MGGAs utilize the full density Hessian. We introduce a simplified, non-empirical functional, $\vartheta$-PBE, and present a roadmap for its self-consistent implementation within the projector augmented-wave (PAW) method. By utilizing the complete set of spatial second-order density derivatives, the functional's underlying descriptor successfully distinguishes between distinct one-electron density limits, such as single-center atomic densities and two-center bonds, that standard iso-orbital indicators often conflate. Benchmarks across molecular and solid-state datasets reveal that while $\vartheta$-PBE delivers accurate chemisorption energies and molecular properties, challenges remain in predicting bulk lattice constants. Ultimately, this work demonstrates the physical utility and feasibility of designing orbital-independent, Hessian-based exchange-correlation functionals.

The relic abundance of vector dark matter originating from an inherited axion-$SU(2)$ condensate is typically determined by implementing an adiabatic matching procedure across the symmetry-breaking transition. We demonstrate that this outcome does not arise in the generic case. The post-inflationary crossover can instead be formulated as a dynamical quantum quench problem, in which the residual coherent component of the field is characterized by a survival factor that induces an $\mathcal{O}(1)$ renormalization of the standard abundance relation. Expressed in conformal time, the spatially homogeneous condensate dynamics reduce to those of a canonical oscillator with quartic and quadratic self-interactions. This representation enables an analytic determination of the matching conditions across the symmetry-breaking transition, the derivation of the corresponding quench work and excess energy relations, and a quantitative validation of the coherent sector description via numerical simulations in both Minkowski and Friedmann--Robertson--Walker backgrounds. We also formulate the homogeneous fluctuation theory via the diagonal-$SO(3)$ $1 \oplus 3 \oplus 5$ decomposition and isolate a soft traceless-symmetric quintet with a $k=0$ vacuum obstruction, a regulated ultraviolet adiabatic bound, and a positive quartic stabilization term. Collectively, these results refine the theoretical description of inherited non-Abelian dark matter production and establish the necessary infrared framework for subsequent investigations of finite-$k$ gauge--Higgs transfer dynamics.

Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally dense, overlapping detector signatures. In this regime, event interpretation becomes impractical for conventional reconstruction approaches, particularly when labelled data are scarce and the analysis spans diverse downstream objectives. We present a sparse ViT framework for learning reusable representations from heterogeneous detector data. Self-supervised pre-training combines masked autoencoder reconstruction with relational voxel-level objectives for hierarchy, ghost and particle identification, and the resulting shared encoder is then jointly fine-tuned across classification and regression tasks. Evaluated on simulated events from the proposed FASERCal concept at the LHC, we find that pre-training consistently improves neutrino flavour and charm-quark identification, momentum regression, and vertex reconstruction over training from scratch, with the addition of relational objectives yielding further gains in the most topologically complex channels. Interpretability analyses further show that pre-training yields a more structured latent space, while detector-subsystem ablations recover physically plausible channel-dependent roles for the heterogeneous inputs. A data-efficiency study shows that, with roughly $10^3$ labelled events, the pre-trained encoder already matches the flavour-classification performance of a randomly initialised model trained on an order of magnitude more data. The learned representations also transfer effectively to publicly available benchmarks spanning different detector technologies and energy scales, matching or exceeding published baselines. These results support self-supervised pre-training on multimodal detector data as a scalable route towards reusable representations for neutrino and particle-detector analysis.

We construct a causal and covariantly stable kinetic model whose spectrum at real wavenumbers $k$ reproduces any rest-frame stable dissipative dispersion relation $ω(k)$ via suitable initialization of the microscopic degrees of freedom. Macroscopic observables can therefore obey arbitrary linear evolution equations (including forms that would be acausal if taken as fundamental), while the underlying dynamics remains causal, and all apparent propagation is encoded in the initial data. This provides an explicit counterexample to the idea that microscopic causality alone constrains the analytic form of dispersion relations at real $k$. In particular, bounds on transport coefficients based solely on the analytic structure of $ω(k)$, such as the hydrohedron bounds, require additional assumptions about the region in the complex $k$-plane where $ω(k)$ corresponds to physical modes.

Bicycle node networks are regional bicycle networks equipped with a wayfinding system of numbered nodes to ease recreational cycling. They spur sustainable bicycle tourism, economic spending, and local culture. Due to their country-wide scale, implementing bicycle node networks is a considerable effort and investment. Despite this investment, planning is a manual ad-hoc process that follows general design principles, but without clear performance metrics that account for the human cycling experience. Here we analyze a 28,215 km long bicycle node network spanning Denmark, developing and studying such metrics. First, a spatial analysis of geometric and topological properties reveals high heterogeneity and local clusters of node density, face loop lengths, gradients, and feature-rich areas. Next, taking the perspective of a recreational cyclist starting at any node on the network, we create a loop census that lists all loops in the network up to day-trip length. The loop census identifies the feasible points on the network from which to take a day trip and quantifies the number of round trip choices, unveiling different levels of choice depending on the considered demographic group. While long-range cyclists can access most of the country with often overabundant choices, cyclists with stronger length and gradient limitations like families with small children can not - which could be overcome by e-bikes. Our open-source analysis methods provide data-driven decision support for bicycle node network planning with the potential to boost the development of rural cycling and cycling tourism.

Dust torus plays the key role in determining active galactic nuclei (AGN) observational appearance. Here, the scenario of accretion regulated central dust torus is tested for the first time in the individual changing-look AGN (CLAGN) SDSS J1011+5442. Through the dependence of broad H$α$ luminosity on continuum luminosity, the scenario of moving dust clouds can be ruled out in SDSS J1011+5442. Meanwhile, virial BH mass in the bright state is consistent with the M-sigma relation determined mass, indicating the virialization assumptions efficient in central BLRs. However, the virial BH mass determined in the dim state is 60 times smaller than the M-sigma relation determined value. The contrary properties of broad H$α$ in different states can be naturally explained by the scenario of accretion regulated dust torus. Below a critical Eddington ratio, opening angle of dust torus declines with increasing accretion rate, leading to only outer part of central BLRs for broad H$α$ with smaller line widths detected in the dim state but all the BLRs detected in the bright state. The results in this manuscript not only indicate properties of central dust torus having apparent effects on variability properties of CLAGN, but also indicate that studying CLAGN could provide further clues to check dynamical evolving models for dust torus in AGN.

We take causality and uniqueness of events observation as our driving forces. They are built in in the way we define distinct observers, which then require a finite time to communicate between each other. This unavoidably leads to the existence of maximal transfer-information velocity between arbitrary (not necessarily inertial) reference frames. Inertial reference frames are defined by fixing the geometrical properties of (spatial) distance without any reference to relativity, electromagnetism, or laws of physics in general. For these inertial reference frames, the causality condition fixes the causal group to be the orthochronous inhomogeneous Lorentz group times dilatations. The mathematics we will use are quite basic.

Designing quantum neural networks (QNNs) that are both accurate and deployable on NISQ hardware is challenging. Handcrafted ansatze must balance expressivity, trainability, and resource use, while limited qubits often necessitate circuit cutting. Existing quantum architecture search methods primarily optimize accuracy while only heuristically controlling quantum and mostly ignore the exponential overhead of circuit cutting. We introduce QNAS, a neural architecture search framework that unifies hardware aware evaluation, multi objective optimization, and cutting overhead awareness for hybrid quantum classical neural networks (HQNNs). QNAS trains a shared parameter SuperCircuit and uses NSGA-II to optimize three objectives jointly: (i) validation error, (ii) a runtime cost proxy measuring wall clock evaluation time, and (iii) the estimated number of subcircuits under a target qubit budget. QNAS evaluates candidate HQNNs under a few epochs of training and discovers clear Pareto fronts that reveal tradeoffs between accuracy, efficiency, and cutting overhead. Across MNIST, Fashion-MNIST, and Iris benchmarks, we observe that embedding type and CNOT mode selection significantly impact both accuracy and efficiency, with angle-y embedding and sparse entangling patterns outperforming other configurations on image datasets, and amplitude embedding excelling on tabular data (Iris). On MNIST, the best architecture achieves 97.16% test accuracy with a compact 8 qubit, 2 layer circuit; on the more challenging Fashion-MNIST, 87.38% with a 5 qubit, 2 layer circuit; and on Iris, 100% validation accuracy with a 4 qubit, 2 layer circuit. QNAS surfaces these design insights automatically during search, guiding practitioners toward architectures that balance accuracy, resource efficiency, and practical deployability on current hardware.

The concept of freely falling frames suggests that gravity exhibits a local Lorentz gauge symmetry and requires a background Minkowski reference frame. The gauge vector fields of a Yang-Mills-type theory can be constructed from the transformations to these local freely falling frames, thereby leading to a composite theory of gravity. We propose coordinate conditions under which an exact black-hole solution can be obtained. Our analysis of planar gravitational waves reveals that, despite the large symmetry group, composite gravity possesses only four physical degrees of freedom. We elaborate a Hamiltonian formulation of composite gravity, derive the full set of constraints for the nonlinear theory, and outline the pathway toward its quantization.

The first measurement of inclusive J/psi polarization at mid-rapidity (|y^{J/psi}| < 0.8) in 200 GeV Ru+Ru and Zr+Zr collisions at sqrt(s_NN) = 200 GeV with the STAR experiment at RHIC is presented. J/psi mesons are reconstructed through their di-electron (e+e-) decay channel. The polarization parameters (lambda_theta, lambda_phi) are measured as a function of the J/psi transverse momentum (p_T) and collision centrality in both the helicity and the Collins-Soper frames. These polarization parameters are found to be consistent with zero across the measured J/psi p_T range of 0.2 < p_T < 10 GeV/c and across collision centralities within 0-80 percent in both frames. These results are consistent with corresponding measurements p+p collisions at the same collision energy and with transport-model calculations.

We design and experimentally characterize a balanced homodyne detector optimized for high-repetition-rate (100 MHz) pulsed optical sources. Unlike conventional transimpedance-amplifier architectures, which suffer from nonlinearities and dynamic instabilities with ultrashort pulses, our approach allows to directly amplify the photocurrent extracted at the common photodiode node without feedback loops. A theoretical model describing the detector response, noise, and pulse-to-pulse correlations is developed, providing quantitative predictions for the signal variance, signal-to-noise ratio (SNR), and inter-pulse correlations. Implemented with two matched InGaAs photodiodes illuminated by a 1030 nm mode-locked laser at 100 MHz, the detector exhibits excellent linearity and shot-noise-limited scaling of the signal variance with optical power. Optimizing the temporal integration window yields a maximum SNR of about 14 dB, while correlation measurements confirm negligible inter-pulse correlations. These results demonstrate that the proposed architecture offers a robust and simple solution for high-speed pulsed homodyne detection, suitable for quantum optics and continuous-variable quantum information applications.

Cost-effective wireless electrocardiograms (ECGs) enable long-term and scalable monitoring of cardiac patients in their home and work environments. Because they offer greater freedom of movement, they are also suitable for investigating the relationship between cardiac workload and underlying physical exertion. However, this requires that the quality of the generated data meets the standards of clinical devices. The aim of this study is to examine this closely. We therefore analyze data from 54 healthy subjects who performed five physical activities using wireless ECGs outside of clinical settings and without medical supervision. The results are compared with clinically collected data from standard 12-lead ECGs (2493 subjects) and Holter ECGs (29 subjects), with particular attention to the RR interval time series (tachogram) and heart rate variability (HRV). Our study shows significant statistical agreement between the different datasets. We calculated the 95% confidence intervals for the mean RR interval and HRV assuming that (1) the statistics of the 12-lead ECGs could serve as reliable reference, and (2) the statistics of the 12-lead ECGs cannot be taken as reliable reference. The p-values for both conditions (for the RR interval: 0.23 and 0.26 respectively; for HRV: 0.10 and 0.11 respectively) suggest that there is insufficient evidence to reject the hypothesis that significant statistical agreement exists between the different datasets.