Papers

We study interacting finite-color urn schemes on directed acyclic graphs, allowing the graph to be infinite. Each urn evolves through reinforcements driven by colors drawn from its in-neighboring urns via edge-dependent reinforcement matrices. Assuming that every vertex has only finitely many ancestors, we prove almost sure convergence of urn proportions and show that the limiting configuration is determined by vertices with no ancestors or self-loops. Under additional balance and irreducibility assumptions on reinforcement matrices, we also obtain second-order asymptotic results in all regimes of appropriately defined parameters.

Context. R Coronae Borealis (RCB) stars are hydrogen-deficient and carbon-rich (HdC) supergiants that likely originate from a merger of two white dwarfs. As such they are not expected to be members of close binary systems, in agreement with current observations. Aims. We test the above hypothesis and search for eclipses of RCB stars that could be due to a companion. Methods. We exploited old archival photometric data from Harvard photographic plates (DASCH) as well as modern-era photometric surveys such as Gaia, ASAS-SN, and ZTF to search for eclipses, and conducted follow-up spectroscopic observations. Results. We found one RCB star (WISE J005128.08+645651.7) that features two 3.5 yr long dimming events. We argue that these may be eclipses separated by an orbital period of 66 yr and that the star is an eclipsing binary candidate. The next eclipse is predicted for 2080. If confirmed, this would be the first RCB star in a binary system, the second-longest orbital period of any known eclipsing binary, and the longest duration of an eclipse. Light curve simulations support the idea that the eclipses could be caused by a dusty disk around the companion. The star shows unusually large pulsations. Our follow-up spectroscopy indicates a stellar temperature of about 11000 K, the presence of sharp emission lines (including forbidden lines) during the normal brightness, and extremely strong diffuse interstellar bands. The star is likely surrounded by a hotter chromosphere and an extended low-density nebula. We calculated atmosphere models of the star. Models feature a density inversion and the derived chemical composition is compatible with some cool extreme He stars (EHe). The star constitutes a bridge between the classical RCB, hot RCB, and EHe stars. Conclusions. Future research is encouraged to confirm or refute the binary nature of the star and search for other RCB binaries.

Radio pulsars can power their coherent radio emission through intermittent plasma discharges in magnetospheric gaps. The nonlinear coupling between particle acceleration, quantum electrodynamic (QED) processes, and electric field screening remains difficult to model self-consistently. We present an analytical concurrency model and first-principles particle-in-cell (PIC) simulations of polar cap discharges. The model predicts limit-cycle behavior where the electric field and plasma density oscillate with a frequency set by the local plasma frequency, modified by the plasma inertia. One-dimensional simulations with exact QED rates and realistic plasma parameters validate these predictions. The discharges generate pair multiplicities up to $M_\pm \sim 10^4$ and excite electric field oscillations with spectra consistent with pulsar radio microstructure. These results provide a theoretical framework connecting microphysical gap dynamics to macroscopic observables.

The fermionic Tonks-Girardeau gas is an exactly solvable model realizing a conventional macroscopic condensate of p-wave Cooper pairs. Here we demonstrate that, when confined by a trapping potential, it also hosts unconventional odd-frequency pairing, i.e., pair correlations with s-wave symmetry that are only present with a finite time delay t between fermions forming a pair. Quantitative results for fixed particle number are obtained using a generalization of Yang's theory of off-diagonal long-range order to define a t-dependent order parameter that is antisymmetric under combined t inversion and exchange of fermion-pair indices. Odd-frequency pairing in the fermionic Tonks-Girardeau gas is found to be a mesoscopic effect, localized at the system's boundary and therefore nonextensive thermodynamically. Our results show that this elusive hidden order is accessible in systems having fixed particle number, suggesting new avenues towards its experimental realization and further detailed study.

We consider a reduced Lorenz-like model that describes two walking droplets interacting through their mutual wave field, and investigate the emergence of strong bipartite correlations in this classical wave-particle system. The coupled nonlinear dynamics admit two invariant synchronization manifolds associated with correlated and anticorrelated states, within which the droplets display synchronized chaotic intermittency. Employing measurement protocols inspired by Bell experiments, we compute position correlations from the long-time dynamics and identify parameter regimes for which the CHSH-Bell parameter $S$ exceeds 2, corresponding to violations of Bell's Inequality. We further introduce a procedure for isolating the two subsystems, thereby ensuring the absence of wave-mediated signaling between them. Changing measurement settings following this isolation allows us to execute dynamic Bell tests in which violations persist. Our results demonstrate that nonlinear deterministic dynamics can produce Bell violations through wave-mediated synchronization mechanisms; moreover, these violations may be rationalized on the grounds that the wave form is influenced by the measurement settings. We thus provide a consistent dynamical framework for the appearance of classical entanglement in pilot-wave systems.

In detector-based spectroscopy and high-energy physics, the observed lineshape of a narrow resonance is distorted by the finite resolution of the detector. While the Gaussian is the standard first approximation, realistic resolution functions deviate from it in nontrivial ways. We present a unified Fourier-space framework in which a resolution function that can be written as a Gaussian convolved with a kernel, $f=G*h$, is expanded into a series of Gaussian derivatives. The Voigtian distribution serves as the prototype, and the mechanism extends to arbitrary kernels whose Fourier transforms are analytic at the origin and of exponential type. We establish an admissibility criterion, and then examine several kernels used in practice— smeared Hypatia, Cruijff, the Laplacian distribution, and the generalised hyperbolic core—classifying each as directly, perturbatively, or asymptotically admissible. The framework thus provides a common language for comparing and constructing non-Gaussian resolution parametrisations around the Gaussian.

We present a multi-sector $TESS$ photometric and spectral energy distribution analysis of the eclipsing binary CPD–82~291 (RX~J0853.1–8244). Eight $TESS$ sectors reveal well-defined eclipses and substantial, changing out-of-eclipse modulation. The asymmetries are reproduced by different surface-brightness configurations at different epochs, consistent with strong and evolving stellar activity, although the fitted circular regions are not unique maps of individual starspots. A detached-binary light-curve model yields an orbital inclination of $i\simeq82.1^\circ$ and a photometric mass ratio of $q_{\rm phot}\simeq0.464$. Without a spectroscopic radial-velocity orbit, the mass ratio and absolute parameters are model-dependent rather than dynamical measurements. Combining the light-curve geometry with the SED radius scale and Gaia distance gives $R_1\simeq1.25\,R_\odot$ and $R_2\simeq3.70\,R_\odot$; the corresponding model-inferred masses remain substantially less secure than the dimensionless light-curve parameters. The stellar photospheres reproduce the observed SED from the optical region through WISE W4, with no statistically significant mid-infrared excess. The only positive long-wavelength deviation is a low-significance $60\,\mu$m measurement, while the $90\,\mu$m result is an upper limit. A cool circumbinary-dust model can reproduce this tentative signal, but such a component is not required by the photometry, and its inferred mass and radial extent are non-unique and strongly model dependent. Evolutionary tracks place the primary close to the zero-age main sequence and the secondary well above the main-sequence locus. However, the absence of radial velocities and spectroscopic youth indicators, together with $Gaia$ astrometry inconsistent with Chamaeleon~I membership, prevents a secure pre-main-sequence classification.

We present a route-resolved comparative assessment of Rigetti's Cepheus-1-108Q and IBM Heron-r2 processors using the established do-nothing state-transfer protocol. Rather than proposing a new protocol, we use this deterministic, low-complexity task as a high-resolution spatial probe. For each evaluated initial qubit, we report two complementary quantities: the largest tested radius within which every evaluated shortest route satisfies the operational success rule, and the longest successful route identified within the evaluated route family. To address the question "How far can you do-nothing on a quantum computer?", we prepare a quantum state, route it outward using SWAP gates, apply the inverse preparation at the destination, and route it back for measurement. We compare the measured probability of returning $0$ with the empirical cutoff $2/3$. For this circuit ordering, that comparison does not certify above-classical unknown-state transfer. While this trivial state-transfer protocol serves as the most intuitive baseline, actively preserving a quantum state across a physical lattice proves to be a non-trivial task that exposes the information to cumulative relaxation, dephasing, and environmental cross-talk. In the highlighted IBM QPU case, we identify an isotropic radius of 10 and a successful path of swap distance 27, whereas the highlighted Rigetti Cepheus case exhibits an isotropic radius of 1 but selected above-threshold routes reaching swap distance 8. These results reveal a sharp distinction between uniform spatial reliability and best-route performance. The presented quantities are empirical and conditional on the evaluated route families, finite-shot decision rule, calibration state, and execution time; they are not architecture-wide constants.

In low-field, lightweight, pole-pieceless permanent-magnet MRI systems built with sintered Nd-Fe-B or Sm-Co magnets, the rapid switching of gradient fields readily induces eddy currents in the sintered magnets, leading to image artifacts. To address this, we report for the first time a Sm-Fe-N permanent-magnet MRI system based on anisotropic Sm-Fe-N bonded magnets, whose high electrical resistivity reduces the eddy currents in the X, Y and Z directions to 0.093%, 0.172% and 2.38%, respectively, while a magnetic field inhomogeneity below 150 ppm is achieved at the boundary of a 220 mm diameter of spherical volume (DSV). Compared with sintered Nd-Fe-B and Sm-Co magnets, using Sm-Fe-N bonded magnets as the source of the static magnetic field not only suppresses eddy currents but also makes a closely tiled, densely packed magnetic-circuit layout feasible, providing a more uniform static magnetic field for the MRI system. Imaging results free of obvious geometric distortion and banding artifacts further indicate that the Sm-Fe-N magnet system delivers low eddy currents and high static magnetic field homogeneity.

We develop a quantum circuit synthesis method for preparing a class of tensor network states. The scheme applies to states tractable with belief propagation (BP), a tensor network gauging scheme which recently allowed for classical simulations at large scales. The problem is reduced to independent, strictly local, classical variational optimizations: each nearest-neighbor two-qubit "disentangler" gate minimizes the entropy defined on an edge. Disentanglers drive the state to a product state and their Hermitian conjugate prepares the target. Each disentangling layer has depth at most $z+1$ (with $z$ the maximal number of nearest neighbors per site), the optimization has no barren plateaus, and the bond dimension stays bounded. As a demonstration, with only $3$-$5$ disentangling layers we prepare a $102$-qubit tree tensor network encoding a $17$-dimensional normal distribution and the transverse-field Ising model ground states on a $64$- to $127$-qubit heavy-hex lattice with fidelities of order $0.9-0.999$. The method opens new possibilities for quantum applications by transferring classical tensor network states onto hardware.

We present a unified calculation of bound and resonant states in purely leptonic Coulomb systems: $e^-e^-e^+$ ($\mathrm{Ps}^-$), $\mu^+e^-e^-$ ($\mathrm{Mu}^-$), $\mu^+\mu^+e^-$ ($\mathrm{Mu}_2^+$), $e^+e^+e^-e^-$ ($\mathrm{Ps}_2$), and $\mu^+\mu^+e^-e^-$ ($\mathrm{Mu}_2$). Using an extended stochastic variational method combined with the complex scaling method, we resolve the natural-parity $S$- and $P$-wave spectra. Near their respective $n=2$ thresholds, all three trilepton systems exhibit Gailitis–Damburg sequences generated by $2S$ and $2P$ Stark mixing and the resulting inverse-square attraction. Although microscopically distinct from the Efimov effect, this mechanism produces the same inverse-square asymptotics and geometric scaling. The $\mathrm{Ps}^-$ and $\mathrm{Mu}^-$ systems exhibit resonance sequences of comparable density, whereas the $\mathrm{Mu}_2^+$ produces a much denser spectrum, with 20 resolved members in the $^3P^o$ channel. In $\mathrm{Mu}_2^+$, the deeper states follow molecular Born–Oppenheimer configurations, while the near-threshold spectrum is governed by the atomic $\mathrm{Mu}(2)+\mu^+$ structure. In $\mathrm{Ps}_2$, coupling between threshold-degenerate configurations is essential for a near-threshold bound state. In $\mathrm{Mu}_2$, the Born–Oppenheimer organization of the resonance spectrum is channel dependent.

We develop a semiclassical Boltzmann framework for second-order extrinsic spin transport in the presence of skew scattering. The conventional relaxation-time approximation reduces the full collision integral to a single phenomenological timescale and thereby neglects the angular structure of impurity scattering. While the transport relaxation time primarily characterizes the leading angular harmonic of the nonequilibrium distribution, nonlinear response is sensitive to its higher angular harmonics, which are governed by distinct components of the collision operator. We therefore retain the angular and band dependence of the scattering kernel and decompose both the collision integral and the distribution function into Fourier harmonics. The resulting coupled algebraic equations allow the symmetric and skew-scattering corrections to the distribution function to be obtained recursively order by order in the electric field. We apply this formalism to the gapped surface states of a topological insulator with spin-dependent impurity scattering and evaluate the corresponding second-order extrinsic spin-current response. Our results show that higher angular harmonics of the nonequilibrium distribution and scattering between distinct constant-energy contours play an essential role in extrinsic nonlinear spin transport beyond the single-relaxation-time approximation.

Electronic circular dichroism (ECD) is a key experimental probe for assigning the absolute configuration of chiral molecules, but interpreting measured spectra often requires costly time-dependent density functional theory (TDDFT) calculations. The few existing machine learning methods for ECD prediction are faster, but their accuracy still falls well short of that required for experimental applications. Here we introduce PhysECD, a parity-aware E(3)-equivariant framework that builds the spectrum from its underlying quantum-chemical quantities, ensuring correct chiroptical symmetry by construction. To improve generalization and support experimental applications, we construct SCECD, a conformer-resolved dataset of 578,104 computed spectra spanning diverse natural products with one to five stereocentres. PhysECD predicts ECD spectra from conformer geometries in milliseconds, achieving state-of-the-art accuracy on the CMCDS benchmark and SCECD. Validation against 77 experimental spectra further demonstrates that PhysECD can serve as a fast alternative to TDDFT for assigning the absolute configuration of complex chiral molecules.

Optical computing is emerging as a promising paradigm for next-generation information processing. Diffractive optical processors rely on spatially distributed trainable degrees of freedom, leading to extended architectures. Here, we propose a compact neuromorphic optical-computing approach where the entire trainable transformation is implemented by a single Mie scatterer. By formulating computation in vector spherical harmonics basis, trainable modal couplings can be concentrated within a finite object through its T-matrix. Since available T-matrix parameters scale as the fourth power of maximal multipole order, this architecture can overcome trainable-parameter-density limitations of conventional spatially distributed diffractive processors. We demonstrate classification of phase-encoded MNIST images using scattered-field intensity. At a particle size parameter of $ka = 15$, the trained T-matrix reaches approximately 90% test accuracy, comparable to a single-layer artificial neural network. Similar performance can be achieved using near-fields, enabling on-chip integration. We show how reciprocity, passivity, and particle symmetry constrain performance: passivity reduces the accessible operator space while improving robustness, whereas symmetry reduces the number of independent parameters. Finally, we inverse-design a non-absorbing dielectric scatterer that realizes the classification task with 84% accuracy. These results demonstrate that nontrivial neuromorphic transformations can be encoded within the multipolar response of a single compact scatterer.

Fourier ptychographic tomography (FPT) is an implementation of intensity diffraction tomography that reconstructs three-dimensional (3D) refractive-index (RI) distributions from angle-varied intensity measurements. The distinctive advantage of FPT emerges when incorporating dark-field illumination, which extends the space-bandwidth product toward gigavoxel-scale volumetric imaging, yet dark-field measurements are highly sensitive to system imperfections and often have low signal-to-noise ratios. Here, we propose feature-domain FPT (FD-FPT), which evaluates data fidelity after feature extraction and is optimized using automatic differentiation. In numerical and experimental tests, FD-FPT resolves structures near the synthetic-aperture cutoff far more reliably than the spatial-domain baseline (SD-FPT). Notably, in a whole-mount Oedogonium specimen, the reticulate chloroplast network and transverse septa were resolved only by FD-FPT. We further demonstrate a 1.81-gigavoxel RI reconstruction of a mouse adrenal gland section across a 1.66 by 1.40 square millimeter field of view, establishing FD-FPT as a practical route to label-free volumetric imaging that combines millimeter-scale coverage with cellular-scale structural contrast.

We present a multi-wavelength study of the quasar SDSS J141945.50$+$524648.0 ($z=1.1599$), a member of the newly identified population of quasar-associated $2175\,\mathring{\mathrm{A}}$ dust absorbers. Utilizing JWST/NIRCam observations from the SAPPHIRES survey and archival data, we analyze the prominent $2175\,\mathring{\mathrm{A}}$ extinction bump detected in this object. The bump parameters are highly consistent with the Milky Way extinction curve, implying similar dust properties. Spectral analysis reveals a $\mathrm{Mg\,II}$ absorption doublet near the systemic velocity. Joint fitting of the $\mathrm{Mg\,II}$ and $\mathrm{Fe\,II}$ absorption lines favors a partial-covering model, yielding $C_{f,\rm BEL}=0.11^{+0.12}_{-0.07}$. Together with the small velocity offset ($\Delta v\approx96~{\rm km\,s^{-1}}$), these results favor an intrinsic absorber rather than an intervening system. Infrared SED modeling and double-peaked $\mathrm{Pa\,\alpha}$ emission indicate consistent orientations of the dusty torus ($\theta\approx60^{+7}_{-8}$ deg) and accretion disk ($i=63.7^{+10.9}_{-7.8}$ deg), suggesting a rim-penetrating line of sight through the torus. This configuration naturally explains the infrared emission, continuum extinction, and associated $2175\,\mathring{\mathrm{A}}$ bump, although a contribution from the host-galaxy ISM cannot be excluded. If associated with the torus, the carbonaceous carriers of the $2175\,\mathring{\mathrm{A}}$ feature may survive the intense AGN radiation field through localized shielding in optically thick dusty clumps. These results highlight the role of viewing geometry and dust distribution in regulating dust survival in quasar environments.

Simulating the trajectory of surface drifters in the ocean matters for search and rescue, pollution tracking, oil and chemical spill response, and marine risk analysis. Accurate prediction remains difficult, as widely acknowledged in the literature, and also illustrated by the “Forecasting Floats in Turbulence” challenge issued by the US Defense Advanced Research Projects Agency (DARPA) in 2021, and which ultimately led to this paper. The main source of error usually comes from uncertain ocean currents, while errors in wind forcing and object drift properties are often smaller [Dagestad and Röhrs, 2019]. Here, we use an open one-year dataset of Sofar Spotter trajectories together with several ocean and atmospheric hindcast products to test data-driven drift models at scale. We compare three approaches: i) a standard (baseline) drifter trajectory simulation based on one ocean model and one atmospheric model, ii) linear regression (LR) models that fuse all available predictors, and iii) neural networks (NN) using similar inputs. A simple LR model that combines all predictors performs equally well as the NN. Because LR is simpler, cheaper, and more robust, we retain it as the preferred approach. In 2-day trajectory prediction, this improves the Liu-Weisberg skill score by around 40% relative to the baseline. These findings apply to hindcast mode; applying this methodology for forecast mode remains for future work.

We investigate the dynamics of bound pairs in an extended Hubbard model at resonance. We show that a single fermion and a singlet bound pair possess identical dispersion relations and scatter off each other. In contrast, a neighboring doublon pair is dynamically pinned in the strong-interaction regime. Remarkably, a single fermion and a singlet bound pair exhibit fundamentally different scattering behaviors when encountering a pinned doublon pair acting as a scattering center. While the singlet bound pair undergoes perfect transmission, the single fermion is completely reflected. These results demonstrate that a neighboring doublon pair functions as an efficient filter that separates bound pairs from single particles. Numerical simulations fully support the analytical predictions. Our findings provide a dynamical mechanism for generating and manipulating bound-pair states.

We formulate a data-completeness test for extracting low-energy characteristic-cone running from flat-space on-shell renormalization-group residues. In four-dimensional, parity-even Einstein–scalar–Maxwell effective field theory through four derivatives and four external fields, Wilson directions are first placed on the physical EFT quotient and background propagation is represented by a traceless response on the full massless root sector. The response is identifiable from chosen amplitude coordinates precisely when the amplitude kernel lies in the response kernel. For the published opposite-helicity vector–scalar residue we find $\beta_\mu C_{\gamma\phi}^{(2)}=-55/(96\pi^2)$ and, after an order-reduced frame translation, the contribution $\beta_\mu(r_T-r_\gamma)=-55/(48\pi^2M_{\rm P}^4)$. A finite operator registry gives explicit rank-two incompleteness tests: independent $F^4$ directions split photon polarizations on a magnetic background, while $\mathcal CFF$ produces an analytic splitting along a principal Weyl axis on a Petrov-I Einstein–scalar background. For the isolated scalar–photon contact, direct Schur reduction finds nonzero raw mixing but no first-order physical off-diagonal entry, by the Maxwell Ward identity. Thus the residue fixes one diagonal cone contribution but does not determine the term-complete characteristic response over the declared admissible coefficient domain.

X-ray computed tomography (CT) is an essential imaging technology in clinical diagnosis. However, scattered photons can reduce image contrast and introduce CT value bias, which severely degrades image quality. Recently, scatter correction methods based on the Boltzmann transport equation (BTE) have attracted increasing attention due to their high physical accuracy and flexibility. Nevertheless, existing BTE-based methods usually employ single-material models, which cannot accurately describe the nonlinear energy dependence of photon interaction cross-sections in different materials. In this work, a scatter correction method based on the wavelet adaptive material-dependent BTE (WAM-BTE) is proposed. The conventional single-material model is extended to a multi-material model by introducing material-dependent scattering distributions. Furthermore, an adaptive multi-scale framework is established through wavelet decomposition. The low-frequency wavelet coefficients are used for coarse-scale scatter estimation to reduce computational complexity, while the high-frequency wavelet energy of high attenuation materials is utilized for adaptive local refinement. Theoretical analysis demonstrates that, when using the Haar basis function, the low-frequency wavelet coefficients at the $w$-th level are mathematically equivalent to block-average downsampling with a scale factor of $2^w$, except for a deterministic normalization factor. Experimental results show that the proposed WAM-BTE method achieves comparable accuracy to the Monte Carlo method while preserving the computational efficiency of coarse-scale estimation. The scatter calculation time for a single projection view is reduced to the millisecond level.

Computing boson star families traditionally requires repeated solution of nonlinear eigenvalue boundary-value problems and careful numerical continuation through turning points. We develop a physics-informed neural network (PINN) that learns the map from the physical parameters and radial coordinate directly to the scalar and metric fields over an equilibrium solution manifold. Regularity and asymptotic boundary conditions are incorporated into the network output, while the training objective combines pointwise supervision, Einstein-Klein-Gordon residuals, and curve-level constraints on the Arnowitt-Deser-Misner mass and Noether charge. A trained model generates a complete configuration in a single forward pass. Across representative one-, two-, and three-branch families, the method reconstructs the mass-frequency spirals and conserved quantities, including configurations on inner branches that require delicate continuation in conventional solvers. These results establish physics-informed surrogate learning as a practical route to amortized exploration of nonlinear self-gravitating solution families.

A large suite of N-body/hydrodynamical simulations is used to demonstrate that the physical properties of the merging cluster El Gordo are well reproduced within a two-state self-interacting dark matter scenario. Our findings show that, in addition to elastic scattering, the presence of an inelastic, endothermic, up-scattering channel is essential to satisfy observational constraints derived from the measured weak lensing profiles of the two colliding clusters. We find that the observational properties of El Gordo are adequately matched by our self-interacting dark matter model within the following interval of parameters: an elastic cross-section in the range of ~ 4 -5 cm^2/gr, and an up-scattering channel bounded by an inelastic cross-section of approximately ~ 2 -4 cm^2/gr with a threshold velocity of ~1200 - 1600 kms, respectively. We argue that our conclusions depend critically on current uncertainties in the primary mass and the projected separation d_{DM}. In fact, our findings suggest that if error estimates in weak lensing measurements were significantly reduced - with future observations showing evidence of a low primary mass (<~ 10^{15} M_sun ) and a larger projected separation d_{DM} >~ 740 kpc - it would then be difficult for the proposed self-interacting scenario to be reconciled with observational constraints. We further suggest that future lensing surveys of massive, high-velocity merging clusters could be decisive in testing the proposed dark matter scenario.

Quantum error correction (QEC) codes have emerged as a powerful tool to protect quantum-enhanced metrology against noise. However, the ability to correct errors alone does not guarantee high metrological sensitivity, as the encoded states may become insensitive to the parameter of interest. Here we show that this limitation can be overcome by exploiting an intrinsic freedom of QEC codes: for a fixed set of correctable errors, the Knill-Laflamme conditions admit an equivalence class of encodings. When the correctable noise possesses unitary symmetries, these symmetries generate continuous transformations within this class, allowing systematic optimization of the encoding to increase the quantum Fisher information while preserving the correctable set of noise. Based on this observation, we develop a symmetry-based optimization approach and derive criteria identifying when such optimization can enhance metrological sensitivity. In particular, for stabilizer-sum Hamiltonians, symmetry optimization can convert a code with vanishing QFI into one achieving the standard quantum limit in general or even Heisenberg scaling in specific cases, illustrating the power of symmetry optimization for QEC-assisted quantum metrology.

We investigate analytically and numerically a one-dimensional periodically driven free-fermionic system subjected to monitoring of the local particle density. Based on the analytical approach that describes the long-wavelength physics of the time-dependent Hamiltonian in the field-theoretical language using the nonlinear sigma-model (NLSM), we reveal that driving does not alter the universality class of the problem. As a consequence, the system retains the area-law behavior in the thermodynamic limit, with an intermediate diffusive regime giving rise to logarithmic growth of entanglement entropy for a small monitoring rate. At the same time, driving leads to a renormalization of the bare coupling constant of the NLSM, which controls the space-time “conductivity” in the diffusive regime. We derive the analytic form of this renormalization, which becomes particularly strong in the case of a “maximally symmetric” drive and sufficiently short driving period. In addition, we employ the Wiener-Hopf method to investigate the ballistic-diffusive crossover. These analytical predictions are corroborated by numerical simulations of the von-Neumann entanglement entropy and the density correlation function. Our numerical results clearly demonstrate that, with an increase in the system size, there are successive crossovers from ballistic to diffusive behavior and ultimately to localization. Furthermore, in the diffusive regime, we observe weak-localization corrections that are in agreement with the analytical predictions of the NLSM. Overall, our results provide a unified analytical and numerical framework for understanding the effects of monitoring in time-modulated fermionic systems, paving a way for broader investigations of driven quantum matter.

We study how discrete self-similarity (DSS) in the critical behavior of scalar-field collapse is imprinted on primordial-black-hole (PBH) mass functions. Using the DSS-modulated critical scaling law found in cosmological simulations, we propagate the near-threshold mass map into normalized PBH mass functions during a {kination} era. We compare Gaussian window function, $k$-space top-hat window function, and real-space top-hat window function, together with a real-space top-hat window function multiplied by a kination transfer function. We find that critical behavior in gravitational collapse produces an irreducible minimum width even for an infinitesimally narrow primordial spectrum. DSS then modulates this critical-scaling profile, generating approximately log-periodic features in mass. At fixed horizon mass, successive equal-phase points of the DSS-modulated critical mass map satisfy $\Delta\ln M_{\rm PBH}=\gamma P_{\rm ln}$. Consequently, in the narrow-spectrum limit, the corresponding structures in the final mass function are expected to satisfy $\Delta\ln m\simeq\gamma P_{\rm ln}$, or $m_{n+1}/m_n\simeq5.6$, for the fiducial Choptuik DSS parameters $\gamma$ and $P_{\rm ln}$. For broad primordial spectra, the convolution over horizon masses dephases the DSS pattern and progressively washes out the critical substructure. We normalize the mass functions so that we may primarily study the profile shape and the survival of DSS substructure, rather than the absolute PBH abundance. These results provide a bridge between cosmological DSS collapse simulations and PBH phenomenology including population observables.

Low-energy $\bar K N$ scattering provides direct access to strange-baryon spectroscopy, but conventional charged-kaon reactions mix the $I=0$ and $I=1$ amplitudes. Motivated by the isospin-selective nature of the $K_Lp$ reactions, we present, to our knowledge, the first simultaneous analysis of the pure-$I=1$ reactions $K_Lp\to\pi^+\Sigma^0$ and $K_Lp\to\pi^+\Lambda$ in which a common set of resonance parameters and a fixed relative-phase convention are imposed on both final states. Within an effective-Lagrangian model, a joint fit of available differential cross sections and recoil polarizations yields $\chi^2/\mathrm{d.o.f.}=1.604$. We find clear channel complementarity: the $t$-channel $K^*$ exchange is more important in $K_L p\to \pi^+\Lambda$, especially at forward angles, whereas $K_L p\to \pi^+\Sigma^0$ is more sensitive to the contribution of $\Sigma(1620)\,1/2^-$. At the same time, $\Sigma(1660)\,1/2^+$ remains important through interference effects in both channels. These results demonstrate the importance of multichannel, phase-constrained analyses for establishing the $I=1$ hyperon spectrum and provide timely phenomenological input for future high-precision measurements by the KLF program at JLab. Once the pure $I=1$ amplitudes are reliably determined, they will also enable the separation of the $I=0$ component in the much more abundant $K^- p\to \pi^\pm\Sigma^\mp$ data, opening a path toward a more quantitative study of the $\Lambda^*$ spectrum.

Compressive sensing emerges as a paradigm shift to realize real-time volumetric ultrasound imaging using a single element transducer equipped with an aberrative mask. Such a coded aperture encodes each scatterer in the FoV as a specific echo signal, compressing each volumetric into a time sequence that are reconstructed into image via computational methods. Compressive imaging (CI) can greatly reduce the data rate and simplify the electronics. Despite this potential, the practical performance of single-snapshot CI remains unclear, especially how it is influenced by mask design, imaging task complexity, and reconstruction strategy. For this, we separate the information budget provided by the mask from the algorithm-dependent extraction of the encoded information. First, the spatial impulse responses of random masks with different pixel sizes and time-delay ranges were calibrated, and the entropy-based effective rank of their similarity matrix was used to quantify the available encoding capacity. Masks with pixel size of approx. half wavelength and a time-delay range of two carrier periods provided higher encoding capacities, reaching up to 1.1% of the total sampled voxels. Algorithm-dependent information extraction was further evaluated for both ULM-motivated particle localization and B-mode imaging. For particle localization, L1-norm regularized least-squares method reconstructed particles corresponding to approx. 10% of the available encoding capacity, outperforming the matched filter. A transition from successful to failed reconstruction was observed when the number of particles exceeded this value, revealing the upper limit of the present CI systems using random masks. For B-mode imaging, LSQR achieved the highest SSIM among the evaluated methods, of up to 0.12, although the encoding capacity of the current random masks remained insufficient for high-fidelity reconstruction.

High spatiotemporal fidelity precipitation products that accurately capture storm spatial organization, propagation, and lifecycle evolution, are essential for advancing hydrometeorological research and operations at regional and global scales. Satellite products offer the only near-global precipitation observations, but they still fall short of reproducing the spatiotemporal structure of ground-based references, due largely to dynamic distortions from the inhomogeneity, intermittency, and indirectness of satellite retrievals. Here we propose a video-diffusion framework for satellite-based High-Dynamical-Fidelity Precipitation (HiDFiP) field generation beyond the space-time coverage of ground-radar, using radar-rich CONUS as a testbed. The framework performs explicit spatiotemporal modeling with IMERG as the primary source and leverages four-dimensional storm-environment information from about 40 ERA5/ERA5-Land atmospheric/land fields to compensate for the temporal information deficit inherent to satellite retrievals. We introduce an extensive metric suite to assess HiDFiP dynamical fidelity in temporal-reconstruction and spatial-transfer settings against MRMS ground-radar precipitation over CONUS. Relative to IMERG and image-wise diffusion baselines, HiDFiP accurately reproduces the storm space-time spectral characteristics; storm timing, location, and directional propagation; precipitation-event episodicity and temporal structure; precipitation-system morphology and spatial organization; and storm-track kinematics and lifecycle evolution. Transferability experiments indicate that HiDFiP generalizes reasonably well to an unseen region. This work advances a video-diffusion paradigm for satellite-based high-spatiotemporal-fidelity precipitation generation and provides an algorithmic and diagnostic foundation for long-term global radar-grade precipitation records.

Indirect photothermal infrared spectroscopy of dense materials typically relies on photoacoustic cells for detecting acoustic waves generated by light-induced heating. This detection approach can be challenging to implement as it is highly sensitive to the sealing quality of the interface between the cavity and the sample, as well as to the properties of the gas within the cavity. Here, we present a simplified and more robust method. This approach relies on direct photothermal temperature measurement using an optimized platinum microsensor fabricated on a thin silicon substrate that acts as a thermally transparent interface with the sample. The sensor design, fabrication in a 200 mm CMOS pilot line, assembly on a readout PCB, and experimental characterization are reported. The component achieves a signal-to-noise ratio close to 1000 making it well-suited for miniaturized and embedded infrared spectroscopic applications.

We classify the differential operators \(T=z^j\partial_z^j+z^m\partial_z^\ell\), where \(0\le m<\ell\) and \(1\le j<\ell\), whose monic eigenpolynomials satisfy a finite-term recurrence relation. Writing \(k=\ell-m\), such a recurrence exists if and only if \(j=1\) and \(k\mid\ell\). In that case we determine all recurrence coefficients in closed form and prove that the associated difference operator has order \(\ell\). We also give an explicit factorization showing that every admissible operator is of Type~(2) in Conjecture~1.10 of Horozov–Shapiro–Tater; the equality of the differential and difference orders is the conclusion predicted by their Conjecture~1.9.