Papers

Current geophysical exploration methods face challenges in accurately determining gas saturation levels and elastic constants with adequate spatial resolution. Seismic wave velocity is a critical physical property in these techniques, but it introduces uncertainties because of its composite nature involving density and two elastic constants (e.g. bulk and shear modulus), which exhibit a trade off relationship. We propose a novel approach that integrates cosmic ray muon detection with seismic exploration to independently resolve P and S wave velocities into their constituent elastic constants and densities. First, we utilized a fluid substitution approach based on Gassmann s model to illustrate the benefits of incorporating density information in predicting gas saturation levels in pores. This supports the advantage of decomposing seismic wave velocity into density and two elastic constants. Second, to validate the applicability and performance of the proposed method, which involves separating seismic wave velocity into density and two types of elastic constants, muon and ultrasonic data were collected in laboratory experiments on two different targets: an acrylic block and an aluminium block. Upon muon observation, a relationship is established to convert muon flux into density length, considering the characteristics of the building housing the laboratory and the direction of muon arrival at specific positions within the building. Although there is potential for enhancing the accuracy of the derived physical properties such as density, bulk modulus, and shear modulus, the feasibility of this method has been successfully demonstrated at the laboratory scale.

Asymptotic symmetries at null boundaries provide a powerful window into the soft sector of field theories, revealing conserved charges and infinite-dimensional symmetry algebras beyond the standard bulk dynamics. While these structures are usually associated with residual gauge transformations, null boundaries also exhibit a characteristic global zero-mode ambiguity, whose physical consequences are less explored. We discuss how this zero mode modifies the canonical structure of field theories at null boundaries. In particular, we show that it gives rise to a new quasilocal edge observable, with consequences to the charge algebra. It can arise on any kind of null boundaries, both at the null infinity and the finite distance such as a black hole horizon.

We develop a hybrid qubit–qumode algorithm for nonlinear ordinary differential equations of the form $\dot{\mathbf{x}}=\mathbf{f}(\mathbf{x})$ with drift of polynomial degree~$L$. Following the Fokker–Planck route of Tennie and Magri, the algorithm propagates the state density and returns the deterministic trajectory as the peak of that density in the small-noise limit. The discretised generator is carried into a parametrised family of Schrödinger equations by the warped-phase transformation of Jin, Liu, and Yu, and the Fourier-mode parameter of that family is placed on a single continuous-variable qumode. Our central structural result is that the Hermitian parts $H_{1}$ and $H_{2}$ of the discretised generator admit a bipartite Pauli decomposition that sorts the non-zero Pauli strings into $\mathcal{O}(\log N)$ mutually commuting families and factorises each family into a diagonal of degree at most $L$ tensored with a fixed rank-two bond operator. The factorisation renders each family exponential an exact product of $\mathcal{O}(n^{L})$ monomial-controlled momentum displacements, with no intra-family Trotter error. On a $d$-dimensional grid of $N=2^{n}$ points per axis the circuit costs $\mathcal{O}(d^{L+1}n^{L+2})$ gates per Trotter step. No sparse-access oracle and no block encoding is invoked: every gate is fixed in closed form by the polynomial coefficients of the drift. We also prove a bound on the numerical abscissa $\lambda_{\max}(H_{1})$ that fixes the recovery domain of the warped-phase transform and the post-selection cost. A classical simulation on two nonlinear benchmarks confirms the structural theorems, the shifted recovery, and the accuracy-per-resource advantage of the continuous-variable coupling over a discretised mode register.

We search for generic gravitational-wave transients associated with high-energy neutrinos detected by the IceCube Neutrino Observatory during the third Observing Run (O3) of Advanced LIGO, Advanced Virgo, and KAGRA. We perform an unmodeled, targeted search, which is sensitive to gravitational-wave signals weaker than those reported in real time or in the gravitional-wave transient catalog, and can thus uncover coincidences missed by typical neutrino follow-up searches. We find no statistically significant gravitational-wave signal and set lower bounds on the distance of possible gravitational-wave sources for different emission models.

Metallic magnets exhibit complex spin dynamics governed by electronically generated interactions. Predictive simulations of such dynamics typically require repeated solutions of an underlying electronic problem throughout the time evolution, creating a major computational bottleneck. Here we introduce a graph neural network (GNN) magnetic force-field framework that learns the effective magnetic energy functional governing itinerant spin dynamics directly from electronic calculations. Conceptually analogous to machine-learned interatomic potentials, the proposed framework enables efficient evaluation of spin torques while capturing the nonlinear and spatially extended interactions generated by itinerant electrons. We benchmark the method on representative metallic magnetic systems exhibiting collinear, noncollinear, and noncoplanar magnetic order. The learned force fields accurately reproduce electronically generated spin torques and yield nonequilibrium spin dynamics in excellent agreement with direct electronic simulations. Our results establish graph neural networks as a powerful framework for machine-learned magnetic force fields, providing a pathway toward predictive large-scale simulations of nonequilibrium magnetism across multiple length and time scales.

At high temperature, quantum Gibbs states retain several classical features of the maximally mixed state: the absence of entanglement, the absence of magic, analyticity of the partition function, correlation decay, and algorithmic tractability. We prove new and sharp bounds showing that these features persist down to finite temperatures independent of system size, but fail at distinct inverse-temperature scales, forming a hierarchy of classical-to-quantum transitions. Our results hold for long-range Pauli interactions with bounded strength at every site. Despite such all-to-all interactions, we show that the death of entanglement occurs at constant temperature, resolving an open question of Rouze, Franca and Alhambra (STOC'25). We give a polynomial-time classical algorithm that prepares Gibbs states up to the death of entanglement transition. Notably, this is asymptotically colder than temperatures at which quantum Gibbs samplers are known to mix quickly, as well as the original separability temperature of Bakshi et al. (FOCS'24), which we improve to be tight up to constants. At asymptotically even colder temperatures, we show that the Gibbs state remains in the thermodynamic infinite-temperature phase. We give polynomial-time classical algorithms for estimating thermal expectations up to the phase transition (despite both entanglement and magic), and as a corollary resolve a correlation decay conjecture of Harrow, Mehraban and Soleimanifar (STOC'20).

Neural networks that map seismic data directly to velocity models tend to memorize the acquisition geometry they were trained on, and their uncertainty estimates are rarely trustworthy once the data drift away from the training distribution. We describe a laptop-scale pipeline that addresses both problems. The network never sees shot gathers. Instead, variable acquisition geometries are mapped into a fixed model-space representation computed by classical physics operators: the starting model, a regularized classical inversion, two misfit-gradient images, and six illumination and wavenumber-coverage maps from fast-marching traveltimes. The learned component is not a replacement for FWI; it is a calibrated residual corrector applied to this physics-derived prior. A six-member heterogeneous ensemble with per-pixel variance heads is calibrated by physics-conditioned conformal prediction, giving finite-sample pixel-wise marginal coverage on the calibration distribution. Beyond that distribution, a held-out-shot physics audit simulates shots the inversion never used through samples of the predictive distribution and rescales interval width where their data-space coverage peaks; no ground truth is involved. On a corpus of 1000 synthetic models spanning six acquisition families, the ensemble reduces error by 38% relative to its classical prior and transfers to never-seen geometries without measurable degradation. Applied zero-shot to the full 17 km Marmousi-2 line, it lowers the error from 354 to 304 m/s while raw coverage collapses to 0.42; the audit restores coverage to 0.89-0.91 across eleven corruption conditions covering noise, wavelet error, and shot decimation, and its peak height cleanly separates physics mismatch from benign corruptions. Budget-matched gather-based baselines underperform substantially off their training acquisition. Code and checkpoints will be archived on Zenodo.

We explore on-site interaction energies $U$ for pairs of shielded ultracold molecules on the same lattice site. We use 2-dimensional effective potentials appropriate for microwave shielding, which have dipole-dipole character at long range but feature a very large repulsive core when the two molecules come close together. This causes very strong correlation between the motions of two molecules on the same site. We find behavior very different from that for ultracold atoms: in particular, there are states for which $U$ is negative for weak lattices but crosses zero to positive values as the lattice strength increases. This behavior is found for both unbound pairs and 2-body bound states. The latter will give access to previously unexplored types of strongly dipolar Hubbard physics with multiple site occupancy.

How much energy does the quiet corona require? Its radiation shows that energy must be supplied. Electrons also carry heat into or out of it. We ask whether temperature observations justify the heat-flow estimate used to judge a heating mechanism's energy supply. Two radio methods give temperatures near 0.62 and 1.5 million kelvin. A population with extra fast electrons can give both readings. Unresolved structure and delayed ion formation also leave Maxwellian explanations open. Neither temperature interpretation alone determines the heat flow. The tested local conduction formula diverges for the idealized fast-electron model with an unbroken tail. Applying X-ray limits to the model still leaves about 5–6% of the electrons holding 28–33% of its kinetic energy. The heat they carry depends on the balance between directions and on conditions along their paths. Source and collision calculations test whether the population could be sustained. The observations examined here do not establish whether the conductive estimate is accurate enough for the heating comparison. We cannot judge whether a mechanism supplies enough energy against a heat loss we have not established. Measuring, reliably calculating, or sufficiently bounding that loss would settle this part of the budget.

We give a quantum signal processing (QSP) algorithm for the overlap fermion Hamiltonian which preserves the Ginsparg-Wilson relation up to a controllable error $\epsilon_e$. Quantum simulations of Dirac fermions with exact chiral symmetry are thus nearly free: applying the overlap Hamiltonian costs only a factor logarithmic in $\epsilon_e$ more than the Wilson-Dirac Hamiltonian. Comparing to domain-wall fermions, a mild overhead is found in circuit complexity while reducing qubit costs. We show how QSP effectively constructs an extra dimension when simulating the overlap operator, illustrating that the scaling of quantum algorithms reflects the deeper physics of overlap fermions arising at the boundary of domain-wall fermions.

We prove that every ironed two-qubit gadget whose KAK-derived parameter satisfies $a=5/9$ has, on the complete graph $K_n$ with $n\geqslant 5$, the same second-moment spectral gap as the iSWAP gadget. The central step is a representation-theoretic localisation theorem: the largest strictly negative eigenvalue of the associated $\mathfrak S_n$-invariant operator always occurs in the highest-spin $\mathrm{SU}(2)$ summand. A local positive-semidefinite decomposition separates every spin sector except the two highest. This settles a conjecture of Kong, Li, and Liu.

Observable properties of core-collapse supernovae (CCSNe) depend sensitively on the circumstellar material (CSM) formed by pre-explosion mass loss from the progenitor star. Since a large fraction of CCSN progenitors reside in binaries, both the progenitor structure and surrounding CSM can be significantly impacted by binary interaction. Yet, its impact on the observed CCSN landscape remains poorly constrained. In this work, we investigate CCSNe from binary systems undergoing stable Roche lobe overflow. We construct a suite of binary evolution models in MESA with a fixed initial primary mass ($16M_{\odot}$), exploring secondary masses in the range $12-15M_{\odot}$ and initial orbital periods $>500$ days. We generate three-dimensional (3D) CSM structures from the resulting mass-loss histories and orbital dynamics, extract angle-dependent density profiles along three lines of sight, and compute multi-band light curves with the radiation-hydrodynamics code Stella. We find that binary-driven CSM develops highly aspherical morphologies, governed by the orbital period and the mass ratio. Interaction between SN ejecta and this structured medium produces pronounced viewing-angle dependence in the light curves, with peak luminosities differing by factors of $\sim5$ and late-time $B-V$ colors varying by $\sim1.5$ mag depending on observer orientation. We further show that interpreting such events with one-dimensional frameworks assuming isolated progenitors and spherical winds can introduce biases up to $50\%$ for inferred explosion properties and $>200\%$ for inferred mass-loss rates. Our results are consistent with a substantial fraction of interacting Type II SN diversity arising from binary-shaped asymmetric CSM and viewing-angle effects, motivating multidimensional approaches to interpreting these transients.

We prove the redundancy of a family (the so-called melonic family) of large-$N$ moments in arbitrary tensor models. This reduces the number of independent entries in the positive semidefinite matrices that build the core of the tensor bootstrap (for tensor models there are already several generalizations of the positive semidefinite Toeplitz and Hankel matrices of lattice gauge theory and random matrix bootstrap, respectively). More concretely, we prove that any melonic operator $C$ at large-$N$ has an expectation value that depends on $C$ exclusively through its degree. A similar statement is shown here to hold for the Schwinger-Dyson equations of melonic moments. The strength of our result is also its scope, which is not limited to melonic tensor models.

Cold, collisionless dark matter successfully explains a wide range of observations, including the formation of large-scale structure. Nevertheless, tensions remain on small, galactic scales, most notably the cusp-core, or inner-mass-deficit, problem and the diversity of inner rotation-curve shapes and central densities at fixed halo mass. These observations suggest that additional dark-sector physics may affect the inner structure of halos, although no generally accepted explanation has yet emerged. Here, making use of a toy but representative model, we show that interacting dark-matter Q-balls – non-topological solitons stabilized by a conserved charge – can provide a natural mechanism for halo cusp flattening and may contribute to observed diversity of inner halo profiles. Produced in the early Universe in the dark sector, these Q-balls grow in the dense central regions of halos, while their interaction cross section decreases as the soliton mass increases. This process operates preferentially in halo centers, converting part of the rest-mass energy stored in massive Q-balls into relativistic dark-sector particles and thereby modifying the inner mass-density profile. The resulting density-dependent, self-regulating energy loss provides a dynamical mechanism for flattening halo cusps while leaving the outer halo largely unaffected.

350 years from the 1676 announcement of the Roemer's discovery that light propagates with finite speed, we present our observations using eyes with telescopes having similar resolution compared to those in the late 17th century. We confirmed that Roemer's method is valid and gives reasonable values for the speed of light c, within about 10 per cent of the modern value for our measurements, even with the simplest modelling technique, using uniform circular motions. We found that increasing the complexity of the model, e.g., by taking into account the elliptical orbit of Jupiter, does not necessarily bring the results closer to the value of c due to the influence of other perturbations. Using modern ephemerides yields a noticeably accurate result of c=(298200+-1900) km/s. This experience can have great didactic value by showing the interconnections between formulation of hypotheses and the consequent predictions, making observations, reducing data, and searching for alternative explanations for the same phenomenon. Lastly, we also found, in the correspondence between Roemer and Huygens, that Roemer in 1677 searched for an independent confirmation of what he found during previous years observing Io's eclipses by making observations and reducing the data of the meridian transits of the Great Red Spot on Jupiter.

The classification of Tidal Disruption Events in large-scale photometric surveys is challenging because deterministic machine learning models produce overconfident misclassifications under varying data quality and low signal-to-noise conditions. Existing lightcurve-based approaches fail to incorporate measurement uncertainties, consequently generating brittle outputs. We present a host-agnostic, uncertainty-aware classification framework using a Probabilistic Random Forest (PRF). Our pipeline extracts 11 characteristic features from nuclear transients in the ZTF alert stream, including rise and decay timescales, blackbody temperature evolution, and pre-transient variability metrics. Relying exclusively on photometric data without host galaxy information ensures effectiveness for the faint transient population expected from the Rubin Observatory. The PRF, which treats feature measurements as distributions, was evaluated against XGBoost through Leave-One-Out Cross-Validation. It yields higher stability and robustness for ambiguous candidates than XGBoost. The two classifiers occupy complementary regimes. XGBoost achieves higher recall in balanced and high-precision scenarios, where its rigid decision boundaries efficiently isolate TDE-like sources, while PRF rejects more false positives by penalizing sources with large feature uncertainties. Applying this framework to archival data identified 11 new candidate TDEs from the unclassified population and 3 potential photometric TDEs within existing training labels previously misclassified as supernovae or active galactic nuclei. This work demonstrates that TDEs can be reliably identified using photometric lightcurve features, providing a host-independent framework. Uncertainty-aware, probabilistic classifiers are essential for the Rubin era to prevent the overconfident misclassifications inherent in deterministic models at low signal-to-noise.

Coronal mass ejections (CMEs) are inherently three-dimensional (3D), but traditional white-light coronagraphs provide only two-dimensional (2D) projections. While the Polarization Ratio Technique (PRT) utilizes Thomson scattering to infer proxy 3D plasma locations, its results are typically limited to 2D topographical maps, hindering geometric interpretation. To address this, we introduce PRICM3 (Polarization Ratio Integrated CME Mapper in 3D), a framework that converts PRT-derived maps into explicit 3D point-cloud reconstructions. This tool enables intuitive visualization, multi-viewpoint comparison, and direct validation against geometric models such as the Graduated Cylindrical Shell (GCS). As a proof-of-concept, we analyzed a limb CME observed on 28 October 2021 using data from Solar Orbiter/Metis, SOHO/LASCO, and STEREO-A/COR2. The independent reconstructions converged into a consistent 3D volume that aligned remarkably well with the corresponding GCS geometry. These results prove that the 3D information embedded in PRT topographical maps can be successfully recovered through spatial reconstruction. PRICM3 offers a powerful, intuitive method for interpreting polarimetric coronagraph observations, providing a vital tool for current and future solar missions such as Proba-3/ASPIICS and PUNCH.

Fault-tolerant quantum computing requires system-level coordination of logical primitives. Here, we establish a logical compilation framework for the color code, grounded in its topological structure and supporting universal logical operations. Based on its anyon-condensation and domain-wall structure, we introduce a spacetime block-diagram representation capturing logical patches and operations and derive the rules governing block assembly. A correspondence with ZX diagrams further identifies the logical semantics of this representation and enables transformations that preserve the represented computation. Moreover, we develop a code-derived compilation strategy that converts ZX representations of logical computations into valid color-code spacetime layouts. In this strategy, edge-decorated ZX diagrams tailor the logical representation to the color code under the block-assembly constraints, and fusion-region-aware routing exploits semantic equivalence during geometric embedding. We automate the complete logical compilation process and demonstrate successful compilation across a broad range of algorithms. Our work advances color-code architecture from individual primitives to the automated synthesis of logical computations, marking a significant step toward its full-stack quantum computing.

Recent small-scale CMB data show a preference for larger scalar spectral index, $n_s$, when combined with DESI data. Monomial $\alpha$-attractor T-models can be reconciled with the new observations if the power of the hyperbolic tangent function is $p\geq 6$, where $p$ is even. The supergravity construction of monomial T-models with $p>2$ relies on the assumption that lower powers remain negligible over the whole field range explored during inflation and reheating. What would be the consequences of going beyond the monomial formulation? As a first step in this direction, we consider the case of a binomial potential, given by the sum of quadratic and quartic terms. When the quartic coefficient, $c$, is $0< c+1/2 \ll 1$, we find that the new model displays non-universal behavior for $n_s$, leading to values as large as $0.965$ and with an $\alpha$-dependence that is qualitatively different from that of monomial potentials. By solving the background dynamics during the first few e-folds of perturbative reheating we show that the quartic term might dominate before the quadratic one eventually takes over as the inflaton oscillations decrease in amplitude. This leads to a time-dependent equation of state, with $\bar w\sim 1/3$ initially before ultimately $\bar w\to 0$. Obtaining a quartic-dominated reheating stage lasting $\sim4$ e-folds requires a substantial hierarchy between the quartic and quadratic terms, $c\sim 10^5$ for $\alpha\gtrsim 0.1$. Our study highlights that models beyond the monomial form can lead to non-trivial deviations of $n_s$ from the predictions of monomial potentials. Furthermore our results for $\bar w$ during reheating call into question the use of monomial models with large $p$; assuming that $\bar w$ is uniquely determined by the $p$-th power relies on substantial fine-tuning of the underlying supergravity potential.

The physics, geometry, and kinematics of the gas and dust surrounding the central engine of active galactic nuclei (AGN) are not well understood. In some sources, this material obscures the coronal X-ray emission, allowing its line-of-sight column density ($N_H$) to be measured. Many sources display $N_H$ variability across multiple epochs. Studying this variability can provide information about the distribution and dynamics of the obscuring material. Particularly, previous works have shown that the probability of observing $N_H$ variability increases with the number of observations available. Additionally, the observed magnitudes of the $N_H$ variability depend on the timescale between observations. In this work, we present the $N_H$ variability analysis of NGC 1142, which has a total of nine X-ray observations over $\sim20$ years, including five from a NuSTAR+XMM-Newton monitoring campaign performed in 2024-2025 and reported here for the first time. We use the physically-motivated torus models UXCLUMPY, XSKIRTor, and RXTorusD to model the spectra. Our results confirm the previously observed trends, and we compare these trends to simulated obscuration curves assuming different locations and distributions of obscuring clouds.

Wave equations provide a natural testbed for near-term quantum simulation of partial differential equations, but hardware demonstrations have remained limited in spatial dimension, equation class, system size, and physically meaningful output. We develop and benchmark structure-preserving, Fourier-based quantum circuits for the one- and two dimensional acoustic wave equations and Dirac dynamics with variable mass on the Quantinuum H2-2 trapped-ion processor. The experiments include one-dimensional grids with up to \(1024\) points and \(32\times32\) two-dimensional grids, corresponding to an encoded state-space dimension of up to \(4096\). Rather than reconstructing the full fields, we estimate subdomain kinetic energies directly from measurement samples. Across all tested acoustic and Dirac dynamics problems, the H2-2 results track the classical kinetic-energy dynamics with mean absolute errors between \(5.9\times10^{-3}\) and \(2.4\times10^{-2}\). At fixed retained bandwidth, the compiled gate counts grow approximately quadratically with the number of grid qubits; the acoustic circuit sizes are essentially independent of evolution time, whereas the cost also grows with the number of product-formula steps. These results provide hardware-level evidence that accurate observable dynamics can remain resolvable for structured wave problems with thousands of encoded degrees of freedom on a present-day trapped-ion processor.

Predicting the patterns of human movement is important to applications from urban design to disease control and emergency response. In this work, we leverage machine learning (ML) to study the predictability of movements to different types of locations (e.g., movements to grocery stores, to schools, or to hospitals). Our approach relies on developing multilayer mobility networks encoding movements between census tracts with network layers associated with different industry sectors. We study the predictability of node degrees across layers, studying which industries are easier/harder to predict. Rather than treat prediction as an end in itself, we propose ML predictability as an exploratory tool to understand multilayer network organization. Our results suggest that node's out-degrees are easy to predict, since they are driven by census tract populations; whereas in-degrees are harder to predict, since persons can be drawn to diverse type of locations in a census tract. We also find that movements to certain industry types (e.g., restaurants) are easier to predict than others, and the different industrie's predictability are positively correlated with the number of movements to those types of locations. These findings provide a practical step toward using ML for multilayer mobility modeling and the many downstream application.

Broadband squeezed light functioning as a Markovian reservoir can exponentially enhance light-matter interactions, benefiting quantum technologies. However, conventional single-cavity sources face a trade-off between squeezing depth and spectral bandwidth. We propose a scalable scheme for generating broadband squeezed vacuum using a cascade of parametric microring resonators coupled to a common bus waveguide. By analyzing the output, we identify the specific conditions that yield a broad, flat-topped squeezing spectrum, even under realistic intracavity pump attenuation. We demonstrate that this architecture is robust against fabrication imperfections, including inhomogeneous resonator frequencies and component failures. We show that the flat-topped spectrum converges to the Markovian limit significantly faster than a single-cavity Lorentzian profile. An array of as few as $N=5$ coupled resonators with an intrinsic loss ratio of $\kappa_I/\kappa = 0.1$ reduces the required bandwidth to a quarter of that needed by a single cavity to achieve same squeezing. This rapid convergence relaxes the low-$Q$ and high-gain constraints of single broadband cavities, distributing the squeezing process across moderately pumped resonators to provide a practical route for engineering squeezed reservoirs on mature integrated photonic platforms.

Conventional X-ray fluorescence (XRF) and X-ray diffraction (XRD) analysis applied to the investigation of ancient metal salts used as pigments and/or therapeutics provide bulk average compositions in two stand-alone data sets; however, major elements aside, these two sets cannot inform on the spatial distribution of one with respect to the other. To address this issue, we present here a multimodal approach incorporating spatially resolved XRF, XRD and nanoscale X-ray imaging applied to the analysis of archaeological and experimental samples of synthetic lead carbonate (PbCO3 - Greek psimythion); psimythion was used in antiquity as a cosmetic and/or a therapeutic for external applications. The experimental sample was produced according to a well-documented recipe dated to the 4th century BCE. In this paper we demonstrate that by using a multimodal approach we can confidently assign trace elements to individual crystalline or to infer the existence of non-crystalline phases. Although the assignment of an element to a phase (i.e. the location) is now possible, the origin underlying it (i.e. the mechanism) is not always clear. Trace elements do not 'control' chemical/mineralogical composition, but they can influence it. Our approach is particularly suited to following changes in the artefact's chemical/mineralogical profile, from its manufacture, to use and burial, to excavation and conservation.

The ideal quantum geometry (IQG) condition for the trace of quantum metric ($TrG(k)$) being equal to the magnitude of Berry curvature (|$\Omega(k)$|) as in $|\Omega|$/Tr$G$=1 has been associated with realizing fractional Chern insulators for the flat bands in a few layers of rhombohedral graphene (RG). More recently the IQG condition has also been proposed for superconductivity in the flat bands of thick RG layers. Using density functional theory and Wannier functions, we study the symmetry-protected topology of bulk RG, drumhead surface states (DSS) of semi-infinite RG surface and slabs, and the IQG condition for thin and thick RG slabs. We find that bulk RG is a weak topological insulator with spin-orbit coupling (SOC), besides being effectively a chiral semimetal with chiral nodal lines without SOC. We also find that the DSS flat bands of thick RG slabs have a sizable convex curvature with dispersion depth agreeing with the recent angle-resolved photoemission spectroscopy experiment. The calculated IQG also shows a convex shape with the K point at the center having a minimum with approximately $|\Omega|$/Tr$G$$\approx$1. But the inner rim of the DSS region approaches the IQG condition of $|\Omega|$/Tr$G$=1. These results on thick RG slabs from first-principles calculations provide useful information for the pristine DSS at the single-particle level for future studies to consider when enhanced electron correlation and many-body interaction will be included.

In the original Hayden–Preskill recovery, the post-injection scrambler and initial state are not related. We extend this setup in two ways: by using a SWAP gate so that the scrambler and initial state are related, and by considering recovery at finite temperature. For this modified protocol, we show that the information is successfully recovered in the sense that the postselection probability is non-negligible and the conditional fidelity is large. We find that both the postselection probability and the conditional fidelity are proportional to temperature, reflecting the reduced entanglement of the initial state at lower temperatures. We also derive their late-time analytic estimates under the assumption of uniform operator spreading and show that they agree well with the numerical results. This demonstrates that strong scrambling is important for successful information recovery. Implementing the protocol on an IBM superconducting processor using a binary sparse SYK Hamiltonian with $N = 8$ Majoranas, we observe that the data retain the qualitative recovery dynamics and that a SWAP-based error-mitigation scheme improves both the postselection probability and the conditional fidelity.

Single T centers in silicon have emerged as promising optically active spins for quantum networking applications. One of the major obstacles to advancing the system is their broad optical linewidth due to spectral diffusion, which is two orders of magnitude larger than their cavity-enhanced radiative linewidth. We tackle this issue by utilizing above-band optical excitation delivered via a laser scanning microscope to device-coupled single T centers, achieving up to 70% optical linewidth reduction. We attribute the linewidth narrowing effect to the filling of nearby charge traps by photo-generated free carriers. We analyze charge stabilization dynamics by exploiting pulsed above-band excitation and develop a rate equation model to describe the dynamics and to explain the observed linewidth narrowing and center shift. This work provides an effective pathway to control and reduce the optical linewidth for single T centers, clearing one of the major roadblocks to advance the single T center spin platform for quantum information and networking applications.

A search for a Lorentz-boosted pseudoscalar resonance $a$ in the mass range between 20 GeV and 85 GeV, produced in association with a top-antitop quark pair and decaying into a $\tau$-lepton pair, is presented. Both $\tau$-leptons are reconstructed in the hadronic decay mode. The boosted production of $a$ results in a small angular separation between its decay products, requiring the use of dedicated boosted di-$\tau$ objects with custom reconstruction, energy calibration, and identification procedures. The analysis uses proton-proton collision data at a centre-of-mass-energy of $\sqrt{s}=13$ TeV collected with the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of 140 fb$^{-1}$. No significant deviation is observed over the expected Standard Model background, and a model independent upper limit of 0.19 fb is placed at the 95% confidence level on the visible cross-section. Limits on $\sigma(t\bar{t}a) \times BR(a \to \tau\tau)$ are also obtained for a Two-Higgs-Doublet Model signal scenario, ranging from 0.4 pb at $m_a=20$ GeV to 0.05 pb at $m_a=85$ GeV.

High-resolution wide-field imaging is essential for applications requiring simultaneous global coverage and local detail, yet conventional approaches face a fundamental trade-off: wide-FOV cameras sacrifice spatial sampling density by distributing finite detector pixels over a broad angular range, while telephoto systems resolve fine features at the cost of scene coverage. Beam-steering devices can mitigate this trade-off but are currently limited in achieving simultaneously all-solid-state, large aperture, and high-speed operation. Here, we report an all-solid-state large-aperture cascaded liquid-crystal beam-steering (CaLiBS) imaging system that extends the effective angular range of a high-resolution narrow-FOV camera by electrically steering sub-FOVs. The CaLiBS module comprises cascaded liquid crystal waveplates and liquid crystal Pancharatnam-Berry phase gratings; a theoretical voltage-prediction model with a hierarchical search algorithm enables efficient calibration under oblique incidence and 10 times faster calibration speed compared with conventional methods. The calibrated system addresses sub-FOVs across 30.3{\deg} * 30.3{\deg} at 2{\deg} intervals with diffraction efficiency above 60%. Sequential sub-FOV acquisition reconstructs a 34.7 * 34.7 composite image, an 8.6-fold enhancement in spatial-bandwidth product over a single-shot wide-FOV camera using the same detector. Combined with object tracking methods, sub-FOV switching further enables high-resolution tracking of moving vehicles within the wide-area scene. This cascaded LC architecture offers a scalable pathway toward compact, vibration-free, and high-resolution wide-field observation.

Liquids confined to nanometer-scale geometries exhibit behavior that departs markedly from their bulk counterparts, yet studying their dynamics under controlled conditions remains experimentally challenging. Here, we use nitrogen-vacancy (NV) center nuclear magnetic resonance (NMR) spectroscopy to probe water confined in 5.6 nm channels as a function of temperature. The system remains liquid throughout the investigated temperature range and exhibits strongly suppressed diffusivity, enabling direct detection of its 1H NMR spectrum. Occasionally, the proton resonance transforms into a doublet with a splitting of several tens of kilohertz, which we tentatively attribute to hyperfine interactions mediated by long-lived paramagnetic charge complexes, in turn seeded by solvated electrons optically injected during laser illumination. The intermittent appearance of this feature suggests a metastable state comprising a correlated population of charge-hydration complexes extending throughout the confined liquid.