Papers

Solid-state single organic molecules, such as dibenzoterrylene (DBT) in organic matrices, are prominent deterministic single-photon sources, usually modeled as effective two-level systems (TLS). We show that single DBT molecules in anthracene nanocrystals, under strong continuous-wave driving, depart from this picture: instead of the expected saturation, fluorescence is strongly suppressed at high resonant pump power, while the linewidth broadens beyond the TLS prediction – an anomalous saturation regime. Comparing coherent and incoherent excitation and independently calibrating temperature via phonon-induced dephasing rules out laser-induced heating and intersystem crossing. Instead, a model of intensity-dependent excited-state absorption (ESA) toward a short-lived dark state quantitatively reproduces both the fluorescence suppression and the linewidth broadening. We further show that matrix quality mitigates this quenching, and that pulsed excitation schemes are strategic toward full population inversion, with direct implications for quantum nanophotonics and molecular optomechanics.

In stream finishing, the wear experienced by a workpiece depends strongly on its orientation within the rotating abrasive media. Determining suitable orientations to achieve uniform wear requires evaluating the wear-rate field over all feasible orientations. Although the discrete element method (DEM) accurately resolves particle interactions, simulating hundreds of feasible orientations for a new geometry is computationally expensive. We present an uncertainty-guided surrogate framework that predicts, directly from geometry, the three fields governing erosion: per-triangle normal impact velocity, tangential impact velocity, and particle impact flux. These fields are combined through the Finnie wear model to reconstruct the wear-rate distribution. The surrogate employs a deep ensemble whose disagreement estimates epistemic uncertainty, enabling an active-learning strategy that selectively performs DEM simulations for the most uncertain orientations. Trained using only $13\%$ of the $696$ feasible orientations, the surrogate achieves Spearman rank correlations of $0.93$, $0.89$, and $0.93$ for the normal impact velocity, tangential impact velocity, and particle impact flux, respectively. Moreover, the predicted uncertainty is well calibrated, reliably anticipating prediction error and the fidelity of the reconstructed wear field, which matches DEM with a Spearman rank correlation of up to $0.97$ for low-uncertainty orientations and degrades in a controlled manner as uncertainty increases.

We propose a novel UV-IR mechanism in quantum gravity in which black hole instabilities act as a bridge to the most ultraviolet sector of the theory. Specifically, we argue that when black holes reach a critical temperature associated with a light tower of states, they undergo a phase transition that sources particles near the species scale, a threshold beyond which any effective field theory of gravity fails. Using the existing numerical results, we show that production of such particles through Hawking radiation is always subdominant. We also extend our investigation to a large family of dyonic and dilatonic black holes and show how the conclusion depends on the origin of the gauge symmetry, its dilatonic coupling, and the charge under that gauge symmetry.

Exploring axion-like particle (ALP) signatures from neutron stars (NSs) in the Fermi-LAT energy range remains largely unexplored. Neutron stars with exceptionally strong magnetic fields, such as magnetars and pulsars with magnetar-like magnetic fields, provide particularly promising environments for ALP–photon conversion. Magnetars are characterized by surface magnetic fields as large as $B_0\sim(10^{14}$–$10^{15})\,\mathrm{G}$; however, despite their extreme magnetic fields, no steady magnetar emission has been firmly detected in the Fermi-LAT energy range, with high-energy activity generally associated with rare flaring episodes. In this work, we investigate ALP production in the interiors of different classes of NSs and the subsequent conversion of ALPs into photons in their magnetospheres. The ALP emissivity is determined by the stellar density and temperature $T$, while the conversion probability is enhanced by the strong magnetic fields surrounding the star. We further account for photon propagation through the Galactic magnetic field, which can provide an additional contribution to the observable photon flux. We investigate the resulting gamma-ray signatures and assess whether ALP-induced emission from NS magnetospheres could be detectable at energies $E\gtrsim100,\mathrm{MeV}$ in the Fermi-LAT band. In addition, we consider if the reprocessing of the magnetospheric photons through inverse Compton scattering can shift part of the emission to higher energies and provide an additional observational signature. We use the resulting fluxes to derive constraints from existing gamma-ray observations and to estimate the sensitivity of future MeV–GeV observations, taking COSI as a representative example.

We bridge two sides of singular perturbation theory: the classical theory of slow-fast systems and the semi-classical approach to quantum mechanical systems. For a specific but physically important class of dynamical systems, we show that purely classical and exotic objects, so-called canard solutions, are shadows of instantons in the corresponding quantum system. We demonstrate that canard solutions exist in a domain of parameter space whose boundaries are determined by an instanton action. We illustrate our statements analytically for the relevant example, the overdamped Josephson junction, and confirm them numerically. For the Josephson junction, the canard window is the exponentially narrow gap between consecutive Shapiro steps.

A new semi-implicit, two-phase, double-point formulation of the Material Point Method (MPM) for soil-water interaction with seepage and free-surface flows under large deformation is presented in this paper. The approach advances the water phase implicitly while keeping the soil phase explicit, enabling stable, efficient time integration in problems that involve rapid seepage and strong free-surface motion. The proposed framework models high-Reynolds-number interphase drag through a non-linear Darcy's law implemented for the first time within an incremental fractional step MPM formulation without enlarging the implicit solve. This methodology also enhances the numerical stability for fast flows and wave breaking via a hyperelastic constitutive treatment of slightly compressible viscous water, and mitigates spurious oscillations through a new stabilisation approach for the velocity. Robustness of soil-water interface is achieved by combining nodal-based, free-surface detection, suited for higher-order spline functions with smooth porosity-permeability transitions that avoid constitutive divergence at sharp material boundaries. Validation against laboratory benchmark cases reported in the literature, including pure-water dam break, dam-break seepage through a porous barrier, two granular-collapse tsunami experiments, and a dam-break wave over a movable granular bed, shows accurate and stable free-surface evolution, pressure time histories, seepage fronts, and wave-gauge records. Using an advanced critical-state soil model (NorSand) further improves the reproduction of granular flow kinematics. The results demonstrate that the proposed formulation is a reliable and computationally efficient tool for geotechnical hazards involving intense soil-water coupling, seepage, sediment transport and free water.

We study two types of mechanisms of state transitions for vector Kuznetsov-Ma breathers (KMBs) in the coupled Fokas-Lenells framework on unequal backgrounds. The amplitude imbalance breaks spectral reflection symmetry and generates richer breather morphologies. In the degenerate sector, KMBs approaching a non-self-conjugate degeneration curve from opposite sides yield different limiting solitons, revealing a discontinuous KMB-to-soliton transition. In the nondegenerate sector, the background plane waves become frequency matched at a special wavenumber, converting the KMB into a single- or two-soliton state. We determine the exact transition threshold and characterize how nearby solutions vary with the parameter. We further investigate special limiting mechanisms arising on the self-conjugate degeneration curve and on the real spectrum at the state-transition wavenumber. Numerical excitation provides further evidence for these results.

We investigate the pion-photon transition form factor within the framework of analytic QCD. A comparison is performed between experimental data and perturbative QCD based on conventional and analytic versions of perturbation theory with the “massive” form of the twist-four contribution. We show that conventional perturbation theory fails to reproduce the data, while the analytic version demonstrates good agreement with experiment.

Electronic-structure and embedding workflows terminate in effective many-body Hamiltonians, whereas quantum eigensolver studies often start from hand-built qubit models. We present the Adaptive Clifford-Algebra Subspace Eigensolver (A-CASE), a single-reference, operator-generated Rayleigh–Ritz method. Overlap, Hamiltonian, observable, and response matrices are reconstructed from one shared Pauli-expectation bank, while adaptive growth scores overlap-aware local pencils and rejects symmetry leakage or near-linear dependence. A strict FCIDUMP adapter supplies the active-space boundary. For linear H$_4$ in STO-3G with CAS(4e,4o), the mapped sector agrees with independent determinant FCI to $3.1\times10^{-15}$ Ha. At a nine-vector budget A-CASE has a $3.019$ mHa error; replacing the determinant reference by a two-operator ADAPT-VQE state reduces it to $0.342$ mHa, without implying a matched total-cost advantage. Under a matched contract, the fixed-reference route uses one state preparation versus ADAPT-VQE's ninety but measures roughly an order of magnitude more Pauli words. Exact fixed-angle ADAPT-GCIM gives $13.364$ mHa at the nearest size match and $10.674$ mHa at the iteration match, with its transition-pair burden reported separately. Across a broader benchmark ladder, fixed Krylov bases are generally more accurate and often narrower but substantially less well conditioned. A grouped bootstrap propagates finite-shot variability through thresholding, diagonalization, root matching, spectral weights, susceptibility, and broadening; its bands are explicitly heuristic and conditional, not finite-sample confidence certificates. The work establishes an executable path from an interchange Hamiltonian to energies, correlations, and response, without claiming materials accuracy, favorable scaling, or quantum advantage.

Spontaneous scalarization provides a dynamical mechanism to evade the no-hair paradigm, but it has been argued to generically eliminate the Cauchy horizon in charged black holes. We show that this obstruction is not universal, but instead follows from the sign-definite structure of the Einstein-Maxwell source term. Within the $P$-dual formulation of nonlinear electrodynamics, we derive a general condition under which the effective scalar source changes sign between the horizons, allowing the integral constraint to be satisfied without destroying the Cauchy horizon. This establishes that the fate of the Cauchy horizon depends on the electromagnetic coupling and identifies candidate theories where scalarized horizons may persist. The resulting framework opens the possibility of studying scalarization in the interhorizon region and its interplay with mass inflation.

The mass spectrum of tetraquark states is examined using the spinless Salpeter equation alongside the Cornell potential. Analytical wave functions are derived through a variational approach, resulting in a specific mass formula for the bound states. This study investigates the mass spectra of heavy tetraquark states within a constituent diquark-antidiquark model. We employ a spinless Salpeter equation framework, incorporating the Cornell potential to describe the interaction between the diquark and antidiquark constituents. To account for relativistic effects, we utilize first-order perturbation theory to include the leading-order kinetic energy corrections arising from the expansion of the relativistic kinetic energy operator. A variational approach is adopted to determine the ground state masses, where the optimal variational parameter ${\beta}$ is found by minimizing the system's energy and then for higher states. We systematically calculate the masses of several experimentally observed and predicted tetraquark candidates, across a range of strong coupling constant values. Our results demonstrate a sensitivity of the calculated tetraquark masses to, and the model provides theoretical mass predictions that are in reasonable agreement with experimental observations for these exotic hadronic states. This work contributes to a deeper understanding of the internal structure and dynamics of heavy tetraquarks.

As photons propagate through curved spacetime, gravitational effects become unavoidable. In particular, gravitational redshift can induce significant distortion in photon wave packets, making it es?sential to investigate parameter estimation within this context. While previous research has focused on single-parameter estimation using the quantum Cramer-Rao bound, the multiparameter scenario remains largely unexplored. In this work, we investigate multiparameter quantum estimation for a photon system subject to gravitational redshift under both amplitude-damping and Ohmic-like dephasing channels. Our analysis reveals that the quantum Cramer-Rao bound fails to provide a tight error bound for the two-parameter estimation involving the initial phase and weight parameters inboth types of noisy channels. To overcome this limitation, we numerically compute two tighter error bounds, i.e., the Holevo Cramer-Rao bound and the Nagaoka bound, when utilizing a semidefinite program. We demonstrate that the Nagaoka bound yields the tightest error bound among all considered bounds, consistent with the general hierarchy of multiparameter quantum estimation. Furthermore, for the three-parameter estimation, including the initial weight parameter, the phase parameter, and the strength of gravitational redshift, we observe significantly enhanced estimation precision in the strong-coupling regime compared to the weak-coupling regime under the amplitude-damping channel. Similarly, in the Ohmic-like dephasing channel, the sub-Ohmic regime consistently affords higher precision than the Ohmic and super-Ohmic regimes.

The divergence of Feynman graph integrals is one of the central issues in the study of perturbative quantum field theories. A rigorous formulation of these integrals usually requires renormalization. In this paper, we prove that the Feynman graph integrals arising from holomorphic field theories on closed real-analytic Kähler manifolds are convergent with respect to heat-kernel renormalization, Cauchy principal value renormalization, and zeta-function renormalization. Moreover, these three renormalization procedures produce the same value. Our proof is based on the theory of wonderful compactifications in algebraic geometry, which provides a geometric understanding of these integrals. As a consequence, we establish a gauge anomaly formula for these graph integrals.

The Mahabharata and the Ramayana constitute the two major Sanskrit epics of ancient India. Previous network analysis revealed substantial structural similarities between their character networks, alongside differences consistent with their contrasting forms of narrative organisation. Building upon these findings, we investigate the representation and structural positions of male and female characters within the two texts. In particular, we examine whether the genders differ systematically in their connectivity, prominence, community participation, and contribution to network cohesion, while accounting for the considerable imbalance between the numbers of male and female characters. We employ methods designed to identify characters who connect otherwise distinct regions of the networks and to assess the structural consequences of character removal. Through these analyses, we ask whether gendered patterns are consistent across the two epics or instead reflect the different narrative structures previously identified. In so doing, we find that male characters are considerably more prevalent among highly central and structurally consequential nodes in both epics, and targeted removal of central male characters produces substantially greater network disruption. However, once baseline structural position is taken into account, we find little residual difference in deletion effects between male and female characters. Furthermore, under selected Girvan-Newman partitions, we find that female characters in the Mahabharata exhibit greater cross-community participation than female characters in the Ramayana.

Integration and sampling in high dimensions are among central challenges in modern science and technology, underlying applications ranging from quantum many-body physics to Bayesian inference and artificial intelligence. Although conventional Monte Carlo methods are formally scalable, their efficiency deteriorates rapidly in the presence of strong correlations or sharp features in high-dimensional configuration space. Here we introduce a new framework, termed the Schr"odinger Generator, for integration and sampling based on the explicit optimization of coordinate transformations. The method decomposes the total Jacobian into two complementary components, including an adaptive map that minimizes estimator variance by learning the marginal structure in each dimension, and a normalizing-flow-based transformation that captures non-factorizable correlations in the target distribution. A final resampling step guarantees unbiased sampling even when the learned transformation is imperfect. We demonstrate stable and scalable performance for nuclear quantum many-body states in dimensions exceeding 600. Short-range correlations among nucleons in finite nucleus are faithfully reproduced. The framework offers a physically transparent approach to high-dimensional stochastic integration and sampling, opening new possibilities for simulations of complex quantum systems.

Recent studies have revealed that a confined bismuth layer at the graphene/SiC interface can be reversibly switched between a topologically trivial precursor phase and the quantum spin Hall insulator bismuthene. Here, we present a detailed spin- and angle-resolved photoelectron spectroscopy study of both structures, resolving the spin texture of their low-energy electronic states. Owing to the strong intrinsic spin-orbit coupling of bismuth and the asymmetric confinement potential at the interface, the valence bands of both structures are Rashba-split. We demonstrate the expected spin-momentum locking for both phases and Kramers' doublets through the investigation of the valence bands' spin polarization at multiple positions in reciprocal space.

Cooperative platooning can reduce the energy use of Connected and Autonomous Vehicle (CAV) fleets, but the routing problem becomes difficult when vehicles must meet on the same road segments at compatible times while moving through unstable urban traffic. This paper develops an edge-assisted, closed-loop evaluation pipeline for platooning-aware vehicle routing. Roadside Units estimate local traffic kinematics from video, classify segment-level flow stability, and activate platooning rewards only on road segments where close-gap coordination is physically appropriate. The resulting multi-vehicle routing problem is written directly as a Quadratic Unconstrained Binary Optimization (QUBO) model, so pairwise platooning interactions are represented as native quadratic Ising terms instead of requiring auxiliary MILP linearization variables. We evaluate the framework using a 24-hour microscopic SUMO simulation of Troy, NY, together with localized IBM Quantum hardware benchmarks. The SUMO study shows an $18.5\%$ reduction in fleet tractive-energy demand relative to a non-cooperative baseline. On 25-active-qubit benchmark instances executed on $\texttt{ibm_boston}$, Linear-Chain QAOA reduces two-qubit CNOT depth by $66.7\%$ compared with dense QAOA and samples the exact classical ground state with $P_{\text{feas}} = 38.6\%$ and $P_{\text{opt}} = 14.2\%$ at $p=2$. These results suggest that edge perception and shallow quantum optimization can work together as a useful component of closed-loop CAV platoon dispatching.

Pollux is a high-resolution spectrograph and spectropolarimeter (R from 65000 to 100000) covering a spectral range from 100 nm to 1750 nm, proposed by a European consortium to equip NASA s Habitable Worlds Observatory (HWO). This instrument aims to revolutionize the study of stellar and (exo)planetary systems, as well as cosmic ecosystems, by combining high spectral resolution, broad and simultaneous spectral coverage, temporal stability, and unique UV spectropolarimetric capabilities, thus opening a new parameter space for astrophysics.

Deterministic multiscale gas flow simulations have long suffered from the curse of dimensionality: the number of discrete velocities increases dramatically with the velocity space dimension and the Mach number, exhausting available memory and computational resources. To address this issue, this paper proposes a memory-efficient deterministic method based on an ensemble-of-subproblems strategy using stochastic discrete velocities. This strategy transforms the originally computationally expensive problem into a series of independently and efficiently solvable subproblems. To be concrete, the proposed method replaces the conventional large deterministic velocity set with multiple small random velocity sets. Each random set defines a subproblem, which is solved by a deterministic multiscale numerical scheme that computes macroscopic moments via Monte Carlo integration. The final flow field is obtained by arithmetic averaging over all sub-problems. In this work, we employ the discrete unified gas kinetic scheme (DUGKS) for spatial discretization and term the resulting method SDV-DUGKS. To validate the proposed method, several numerical test cases are conducted, including (a) the one-dimensional shock structure, (b) the two-dimensional cavity flow, and (c) supersonic flow around a square cylinder. The results of the one-dimensional shock structure confirm the feasibility of the proposed method. The two-dimensional cases demonstrate that, compared to its deterministic counterpart, the proposed method saves more than 80% of memory usage while maintaining comparable accuracy. These results indicate that the proposed method markedly reduces memory demand for multiscale flow simulations and exhibits strong potential to alleviate the curse of dimensionality that currently hinders deterministic multiscale numerical schemes from being applied to engineering problems.

High-resolution spectroscopy, typically operating at resolving powers R greater or equal to 25,000, has matured into one of the primary techniques for characterising the atmospheres of extrasolar planets. The ability of HRS to resolve individual rotational-vibrational lines of molecular bands, combined with the large Doppler shifts experienced by close-in planets during their orbits, allows planetary signals to be separated from quasi-stationary telluric and stellar contamination. Since the pioneering detection of carbon monoxide in the transmission spectrum of HD 209458b, HRS has enabled the identification of more than a dozen chemical species, including H2O, CH4, HCN, TiO, VO, Na, K, Li, H-alpha, He I, Mg, Ca, V, Cr, Mn, Fe, Co, Ni, and Ti, in a wide variety of transiting, non-transiting and directly imaged exoplanets . In addition to chemical abundances, HRS constrains the vertical temperature structure through the pressure dependence of line depths, and reveals atmospheric dynamics through Doppler shifts and asymmetries imprinted on the planetary cross-correlation function. This review synthesises observational and methodological progress from the past fifteen years with a focus on how current and forthcoming high-resolution facilities HARPS, ESPRESSO, NIRPS, CARMENES, CRIRES+, SPIRou, GIANO, and ultimately the ANDES, METIS and HARMONI instruments on the Extremely Large Telescope are reshaping our empirical view of exoplanet atmospheres.

We establish a sufficient one-minimum criterion for the off-shell Kerr family $\Delta(r) = r^2 - 2rm(r) + a^2$ with a positive, nondecreasing mass profile $m(r)$, showing that $1 - 2m'(r) - rm''(r) > 0$ ensures strict convexity and determines root counts for $\Delta$. Using a fuzzy-dark-matter-inspired benchmark satisfying this bound, we derive first-order responses for the outer horizon, extremal branch, photon sphere, and shadow functional under general deformations $m/M_{\text{ADM}} = 1 + \varepsilon h$. We demonstrate that static horizon and photon responses are profile-controlled, spin-odd shadow displacements are completion-dependent, and scale-consistent weak-field limits render local profile-gradient effects negligible ($\ll 10^{-20}$), confirming the strong-field box as a formal radial-profile benchmark rather than a self-consistent rotating scalar-field solution.

To accurately determine phase boundaries and phase transitions, thermodynamic models that describe phase free energies often have to be optimized based on experimentally observed phase equilibria. While different approaches exist for thermodynamic optimization, they are often implemented in ways that are not compatible with machine learning workflows requiring differentiable calculation of the loss function. In this work, we derive a phase-equilibrium loss function based on thermodynamic potentials that can be efficiently evaluated and enables gradient-based optimization by auto-differentiation in the PyTorch package. By minimizing this loss function, general thermodynamic model parameters can be optimized with respect to experimental phase-equilibria data. Using thermodynamic models in the CALculation of PHAse Diagram (CALPHAD) framework, we illustrate successful and efficient optimization in different systems, including ternary systems with more than 100 parameters. As the loss function is defined independently of the details of the thermodynamic models, it can be used to optimize machine learning thermodynamic models in general. In particular, we demonstrate top-down optimization of an atomistic potential from target phase equilibria.

In this work, a ensemble-of-subproblems strategy with stochastic discrete velocities is extended to deterministic methods for mitigating ray effects in rarefied flow simulations. The strategy involves performing multiple independent subproblems, each using a small set of randomly sampled velocity points, and then averaging their solutions to obtain the final result. The core idea is to ensure that the distribution function at any velocity can contribute to the final result, approximating highly refined velocity-space resolution without increasing the memory requirement in any single subproblem. We incorporate this strategy within the DUGKS framework, and the resulting method is denoted as SDV-DUGKS. To evaluate the performance of the proposed method, we compare SDV-DUGKS with the original DUGKS on several test cases: (a) the Sod shock tube problem, (b) the one-dimensional Riemann problem, (c) the two-dimensional lid-driven cavity flow, and (d) the two-dimensional Riemann problem. The results show that, in the collisionless limit $\mathrm{Kn} \to \infty$: (1) for one-dimensional compressible flows, SDV-DUGKS reduces memory usage by approximately 2/3 compared with that of the original DUGKS while achieving good agreement; (2) for two-dimensional compressible flows, SDV-DUGKS requires one to two orders of magnitude less memory than the original DUGKS while achieving good agreement. Based on these results, it can be concluded that the proposed method serves as a reliable and effective tool for mitigating ray effects in rarefied flow simulations.

In Non-Intrusive Load Monitoring (NILM), adaptive segmentation of electricity consumption time series is critical for appliance recognition. However, prevailing methods face challenges including heuristic parameter tuning, boundary sensitivity, and metric saturation. This paper proposes BayesSeg, a unified framework integrating time-series segmentation, multidimensional evaluation, and automatic parameter optimization. The segmentation layer employs a dual steady-state criterion based on the tail value and mean of preceding subsequences, combined with a sequential extraction and complement-set parsing strategy, to achieve precise unsupervised partitioning of steady-state and transition-state segments. The evaluation layer maps segmentation results to binary state sequences and formulates a composite metric integrating an event-level F1 score (event_F1) with Normalized Mutual Information (NMI). The event_F1 quantifies switching-event precision and recall via tolerance matching, while NMI captures global structural consistency, jointly overcoming the boundary sensitivity and limited discriminability of point-wise metrics. In the optimization layer, the composite score serves as the objective function for Bayesian optimization, which constructs a TPE surrogate model for efficient global parameter-space exploration. Experiments on the SustDataED2 dataset demonstrate that Bayesian optimization requires only ~100 objective evaluations to locate a parameter region within 0.35% deviation of the exhaustive grid-search optimum. The framework achieves a weighted composite score of 0.7149 and an event_F1 of 0.9340 while reducing optimization latency from ~5300 seconds to under 1 second, a speedup exceeding 5700x. BayesSeg automates segmentation configuration and provides a scalable, efficient solution for time-series analysis in NILM and related domains.

Infinite-layer nickelates have recently emerged as a new family of potential unconventional high critical temperature ($T_c$) superconductors. However, fundamental questions such as their superconducting (SC) pairing mechanism and gap symmetry remain under intense debate. Here we present a fully ab initio theoretical study on the SC properties of optimally doped nickelates $Re$$_{0.8}$Sr$_{0.2}$NiO$_2$ ($Re=$ La, Pr, Nd), based on the density functional theory for superconductors calculations with electron-phonon coupling (EPC), screened Coulomb repulsion and spin fluctuation (SF) interaction treated on an equal footing. We find that $Re_{0.8}$Sr$_{0.2}$NiO$_2$ are two-band superconductors with sign reversal $d_{x^2-y^2}(\pm)$-wave gap functions on the different Fermi surface (FS) pockets. Interestingly, when the SF interaction is turned off, $T_c$ becomes negligibly small ($\sim$0.01 K), thus demonstrating that the superconductivity in $Re_{0.8}$Sr$_{0.2}$NiO$_2$ is driven by SF interaction. Moreover, our ab initio calculations reveal that the SF interaction is an order of magnitude stronger than both EPC and Coulomb repulsion on the large quasi-two-dimensional FS pocket around the Brillouin zone (BZ) center, thus leading to the SF-mediated pairing mechanism, although the EPC dominates on the small three-dimensional electron FS pockets at the BZ corners. The emergence of nodal $d_{x^2-y^2}(\pm)$-wave gap structure is traced to the pronounced peaks in the Lindhard response function at the BZ corners. Our calculated FS, SC critical temperature, nodal gap structure and SC quasiparticle density of states are consistent with most available experiments. Furthermore, predicted unconventional SC properties such as scanning tunneling spectra of La$_{0.8}$Sr$_{0.2}$NiO$_2$ and Pr$_{0.8}$Sr$_{0.2}$NiO$_2$ are ready for immediate experimental verifications.

In this paper we find that the scattering matrix for dipole-dipole interaction in the saturation region has the form: ${\cal S}^d_d \xrightarrow{z \,\gg\,1} \exp\Lb - C^d_d z^2\Rb \propto \Lb {\cal S}_{BK}\Rb^4 = \exp\Lb - 4\,C_{BK} z^2\Rb$, where $z = \bas \kappa Y\,+\,\ln\Lb \frac{r^2}{r'^2}\Rb$ for interaction of a dipole $r$ at rapidity $Y$ with dipole $r'$ at rest. $S_{BK}$ is the S-matrix for the Balitsky-Kovchegov amplitude. All constants are determined in the text. The proof is given in the same theoretical framework for both cases (${\cal S}^d_d$ and ${\cal S}_{BK}$): the Pomeron interaction which takes into account the Pomeron vertices in the leading $1/N_c$ approximation ($N_c$ is the number of colours). This result is in striking contradiction with 'rare' fluctuation approach as well as with summing the large Pomeron loops. These lead to ${\cal S}^d_d \propto \sqrt{{\cal S}_{BK}}$ at large $z$. In the paper we collect arguments supporting the idea that the sum of large Pomeron loops can be trusted in a wide region of energy: $Y \leq 1/\as^4$. In addition we discuss the influence of the structure of the Hamiltonian on the asymptotic behaviour of the scattering amplitudes using the exactly solvable one dimensional model as our theoretical ground.

The Nelson-Barr mechanism solves the strong CP problem through spontaneous CP violation, but the resulting CP-conjugate vacua generically lead to stable domain walls. We propose that the Nelson-Barr scalar itself drives hilltop inflation. A CP-symmetric double-well potential for its imaginary component forms two CP-breaking valleys, with inflation proceeding along one of them. Since the lowest CP-invariant ridge is generically much higher than the energy available after inflation, transitions between the two branches are energetically inaccessible, and the domain walls cannot be regenerated after inflation. A small CP-preserving linear deformation raises the scalar spectral index of quartic hilltop inflation and yields CMB-compatible parameter regions. The Nelson-Barr sector necessarily provides a portal to visible-sector reheating. When coupled to right-handed neutrinos, it can also transmit the spontaneous CP phase to the lepton sector and, in an extension that allows a higher CP-breaking scale, even realize nonthermal leptogenesis. This establishes a unified cosmological realization of the Nelson–Barr mechanism in which the same CP-breaking dynamics solves the strong CP problem, can generate quark and lepton CP violation, drives inflation and reheating, and enables baryogenesis, while simultaneously eliminating the associated domain-wall problem.

Light incident on an insulator is generally not expected to turn it into a metal without invoking intense ultrafast excitation that leads to transient structural transitions. Here we show that magic-angle twisted bilayer graphene tuned to half filling of the moiré band provides a notable exception to this expectation. We find that weak beam of long-wavelength photons, with energies comparable to the flat-band width, selectively heat the low-heat-capacity electronic subsystem, thereby suppressing the correlated gap. This produces a giant resistance change governed not by a persistent photocarrier population, but by the extreme sensitivity of a many-body correlated gap to weak electronic heating. The resulting photon-driven insulator-to-metal transition produces a broadband low-noise photoresponse with voltage responsivity exceeding millivolts per nW of absorbed power. The mechanism is dual to superconducting hot-electron response: radiation-heated electrons suppress a many-body order, but in reverse the correlated insulator melts into a metal, providing robustness to magnetic fields of several tesla and a sharp insulator-to-metal resistive contrast. Our results establish correlated flat-band systems as a platform for ultra-sensitive detection of faint long-wavelength radiation.

All-sky surveys in the soft X-ray band are essential for detecting transient objects such as high-redshift gamma-ray bursts (GRBs), which provide key insights into the early universe. HiZ-GUNDAM is a future satellite mission designed to detect and localize high-redshift GRBs. Its wide-field X-ray monitor, EAGLE, combines Lobster Eye Optics with a pnCCD imaging detector operating in the 0.4-4 keV band. Because of limited satellite telemetry, full-frame pnCCD images cannot be downlinked, requiring onboard event selection. Charged particles in the space environment produce background events that can be misidentified as X-ray photons, degrading detection sensitivity and potentially triggering false alerts. In this study, we developed a pnCCD readout system and evaluated charged-particle rejection using conventional grade methods and a convolutional neural network (CNN). Performance was evaluated using X-ray events from an Fe-55 source and electron events from a Sr-90 beta source. The CNN reduced the misclassification rate from 10.2-11.9% for conventional grade methods to 3.1% while maintaining a high acceptance rate for X-ray events. The improvement is particularly pronounced at higher deposited energies, reflecting the CNN's ability to distinguish track-like particle events from X-ray events by capturing detailed spatial features of charge distributions. Comparison with a thin-depletion-layer CMOS sensor further indicates that the thicker depletion layer of the pnCCD enhances discrimination performance. These results demonstrate that CNN-based event classification can substantially reduce charged-particle contamination while maintaining high X-ray acceptance, making it a promising approach for onboard event selection in future pnCCD-based wide-field X-ray missions.

Ultralight axions from string compactifications carry non-canonical kinetic terms whose normalization is set by a coupling function that depends on an accompanying modulus field. As dark matter, such an axion forms a cold condensate whose quantum pressure resists gravitational collapse below a Jeans scale fixed by that coupling. One might hope that backreaction from the condensate's oscillations could shrink this Jeans length and thereby enhance structure growth. We show that it cannot. For any smooth, positive coupling function, the oscillation-averaged backreaction always drives the coupling to larger values, strengthening the quantum pressure and growing the Jeans length with time. We establish this no-go result analytically through an adiabatic- invariant analysis and confirm it by direct numerical integration. Kinetically coupled dark matter therefore cannot self-generate the conditions for enhanced gravitational collapse or the seeding of structure on sub-Jeans scales.