Papers

The quasiparticle effective mass $m^*$ of the three-dimensional uniform electron gas (UEG) is a fundamental Fermi-liquid parameter whose value and density dependence have remained controversial for decades. Using renormalized perturbation theory with explicit counterterms, we determine $m^*$ in the metallic regime ($r_s \le 6$) from first principles by two complementary routes – the self-energy and the forward-scattering four-point vertex via the $p$-wave spin-symmetric Landau parameter $F_1^s$ – that agree within uncertainties at each density through sixth renormalized order. The resulting $m^*/m$ remains close to unity throughout the metallic regime, with a shallow non-monotonic density dependence – a minimum near $r_s\approx 1$ followed by a gentle upturn – reflecting the interplay of exchange and dynamical screening in the self-energy, and disfavoring strong monotonic suppression. This finding supports a physical picture for the metallic UEG in which dominant charge correlations are concentrated in nearly forward scattering and generate only a weak $F_1^s$ component.

We introduce a composition-weighted symbolic regression framework for interpretable prediction of materials properties directly from chemical composition. The method jointly learns analytical functional forms and task-dependent elemental weightings without predefined descriptors. By incorporating max/min operators, it naturally enforces constraints such as non-negative band gaps and bounded classification probabilities, unifying regression and classification tasks. Efficient search is achieved through a hybrid Monte Carlo tree search–genetic programming algorithm with gradient-based refinement and parallel computation. Benchmarks on MatBench tasks show competitive accuracy relative to state-of-the-art black-box models while yielding explicit analytical expressions. Applied to III–V semiconductor alloys, the model produces smooth composition-dependent trends and learned elemental weights with chemically meaningful periodic behavior. This framework provides a scalable and interpretable route for materials discovery and property screening.

In far-field thermal radiation, electromagnetic waves emitted by an object propagate to infinity, requiring the far region to be modeled as an effective thermal bath. This bath was proposed as infinitesimal environmental "dust", but explicit calculations with such distributed dust involve integrals over infinite space that are difficult to evaluate. In this work, we map this environmental dust to a photonic bath at infinity within the nonequilibrium photonic Green's function formalism. By explicitly evaluating the spatial integral over the dust, we show that its contribution reduces to a simple local self-energy, for which we derive analytical expressions for both three-dimensional objects and planar systems. We further demonstrate that the bath behaves as a black body and clarify its role in far-field thermal radiation. An alternative derivation based on the surface Green's function framework is also provided, demonstrating the theoretical consistency of the results without invoking the dust model. The photonic bath at infinity provides a convenient framework for both analytical and numerical calculations in far-field thermal radiation.

Low-order hybridization expansion methods such as the non-crossing approximation (NCA) and the one-crossing approximation (OCA) are widely used impurity solvers in the study of strongly correlated systems, yet their accuracy in genuine multi-orbital settings remains poorly understood. Using the decoupled orbital limit as a controlled reference point, we derive analytic results connecting multi-orbital restricted propagators and Green's functions to their single-orbital counterparts, identify the diagrammatic mechanisms responsible for the breakdown of low-order methods in multi-orbital settings, and determine their regimes of applicability. Our central finding is that the accuracy of these methods is governed by the least correlated orbital: i.e., the orbital with the most rapidly decaying retarded Green's function. That orbital's properties are transferred to all other orbitals through a spurious coupling generated by the truncated expansion, thereby suppressing correlation-induced features such as the Kondo resonance. This occurs even in orbitals that are themselves strongly correlated within single-orbital calculations using the same approximation scheme. We confirm this numerically across representative two-orbital model systems in the steady-state, systematically identifying the parameter regimes in which low-order methods succeed or fail. Our results provide a practical guide for assessing when insights from single-orbital calculations carry over to multi-orbital settings, and serve as a benchmark for the development and validation of higher-order multi-orbital impurity solvers.

The recent discovery of the 3D quantum Hall effect in $\mathrm{HfTe_5}$ has also revealed puzzling signatures of possible 3D fractionalization. Beyond the first plateau associated with the lowest Landau band, Hall conductivity exhibits a second plateau with a value of about $3/5$ of the first, accompanied by a suppressed longitudinal resistivity. Here, we attribute this second plateau to an insulating ground state arising from spin-density-wave order. We show that a magnetic-field-driven Lifshitz transition causes the spin-down holelike zeroth Landau band to cross the Fermi energy and that the resulting nesting between the lowest spin-up and spin-down Landau bands induces a spin-density wave. We calculate the Hall and longitudinal resistivity and reproduce the experimental behaviors. Our renormalization-group analysis further supports this insulating ground state. Our work reveals that the tunability of Landau bands along the magnetic-field direction endows the 3D quantum Hall effect with a broader phenomenology than its 2D counterpart and merits further exploration.

Wilson loops provide the central gauge-invariant probe of confinement in lattice gauge theory. This survey reviews the statistical-mechanical formulation of lattice gauge ensembles, the strong-coupling and duality mechanisms behind area laws, finite-temperature and continuum scaling diagnostics, and the mathematical status of Wilson-loop confinement.

We obtain exact closed-form moments for a harmonically trapped self-propelled particle with anisotropic translational mobility in two dimensions. At high persistence, the mean and MSD develop a quasi-steady plateau with vanishing fluctuations, after which the MSD relaxes in a second step. The steady excess kurtosis is negative and nonmonotonic in the mechanical-to-rotational timescale ratio, and the particle is pushed beyond the activity-confinement ring. The non-monotonic kurtosis is specific to strong mobility anisotropy - as in wheeled or gliding particles, not bulk hydrodynamic rods - whereas the two-step MSD remains visible whenever transverse relaxation is slow compared with rotational diffusion.

The pursuit of dissipationless spin supercurrents is a central theme in superconducting spintronics. We propose a field-free Josephson junction using an inhomogeneous altermagnetic interlayer with in-plane Néel vectors. We show that the current-phase relation and the critical Josephson current are highly sensitive to the misorientation angle between the altermagnetic layers' Néel vectors. Specifically, at a $\pi$ misorientation with equal layer thicknesses the spatial oscillations of the superconducting pair amplitude, governed by the center-of-mass momentum, undergo mutual cancellation. This compensation suppresses individual layer pair-breaking, significantly enhancing the critical current and eliminating $0$-$\pi$ transitions. Furthermore, the non-collinear alignment of the Néel vectors facilitates the emergence of a net spin-polarized Josephson current. This spin current serves as a distinct signature of spin-triplet pair correlations, generated by the spin-dependent momentum shifts inherent to the altermagnetic exchange field. Our results establish a highly tunable, field-free platform for the realization of dissipationless spintronic devices.

Magnetic topological insulators provide a unique platform to explore the interplay between magnetism and topology. MnBi$_2$Te$_4$, known for its A-type antiferromagnetic (AFM) ground state, undergoes a striking transformation when single crystals are grown in an applied magnetic field. Despite retaining the same crystal structure, field-grown MnBi$_2$Te$_4$ exhibits a ferromagnetic (FM) ground state with a Curie temperature of $\sim$ 12.5 K, confirmed by magnetization, magnetic torque, electrical resistivity, and specific heat measurements. First-principles calculations support these findings, revealing that magnetic-field-assisted synthesis can effectively reconfigure the ground-state spin order and thereby modify the material's electronic properties, as reflected in the de Haas-van Alphen oscillation seen in the magnetic torque.

This study introduces an innovative Isotropic Elastic Lattice Spring Model (IELSM) that addresses the fundamental limitation of classical lattice spring models: the constraint of fixed Poisson's ratio. By amending the total strain energy within the Lattice Spring Model (LSM), IELSM provides a self-consistent formulation for simulating isotropic elastic materials with arbitrary Poisson's ratios. The model's core innovation lies in augmenting classical axial spring frameworks with additional volumetric constraints, establishing a direct and exact mapping between IELSM's parameters and macroscopic elastic constants. This enables simulation across the full admissible Poisson's ratio: -1 < {\nu} < 1 under plane stress and -1 < {\nu}< 0.5 under plane strain conditions. Eigenvalue analysis indicates that the IELSM has better numerical stability compared to the standard bilinear quadrilateral element and the constant strain triangular element. The characteristic of the numerical implementation lies in directly decomposing the additional volumetric constraints into an equivalent combination of standard mechanical components (axial, shear and rotational springs), laying the foundation for the realization of fracture simulation based on discrete methods. Comprehensive validation through uniaxial tension, pure shear, stress concentration around a circular hole, and stress singularity analyses for central and crucifix-shaped cracks demonstrates IELSM's exceptional accuracy, convergence and computational robustness. The model exhibits excellent performance in stress intensity factor calculations at crack tips, validating its effectiveness for singular stress field analysis. This work bridges the gap between LSM and continuum mechanics, establishing an analog framework that maintains theoretical consistency while offering computational accuracy for the solution of elastic boundary value problems.

A central challenge in computational catalysis is the identification of low-energy and chemically plausible adsorption configurations, as these directly affect adsorption energies, reaction pathways, and catalytic performance. Existing approaches generally rely on enumerating candidate adsorption sites followed by iterative refinement through density functional theory calculations or machine-learning-based relaxations. However, such workflows remain computationally expensive and are difficult to scale to complex surfaces or multi-adsorbate systems. Here, we introduce Meta-LegNet, a graph learning framework that combines SE(3)-equivariant atom-level message passing with voxel-based multiscale aggregation and cross-domain meta-learning to learn transferable representations of local adsorption environments across diverse catalyst–adsorbate systems. Rather than following a conventional regression-only paradigm, Meta-LegNet encodes local chemical environments using invariant radial features and equivariant directional information, and further incorporates broader structural context through coordinate-frame voxel pooling, assignment-based upsampling, and gated feature fusion. The resulting local-global decomposition produces atom-resolved attribution maps, which are processed to identify adsorption-relevant local environments in an interpretable manner. Based on the learned representations, we further construct an adsorption-environment database and develop a template-matching strategy to propose likely adsorption sites on previously unexplored surfaces without exhaustive site enumeration. Overall, our results suggest that learning transferable adsorption environments provides an accurate, interpretable, and practical route for accelerating catalyst screening.

We introduce a finite-size gradient-transport framework for real language-model training, based on five observables $(D,z,\beta,\delta,v_{\mathrm{rel}})$ that separate cascade size, duration, absolute transport, and intensive transport efficiency. We analyze direct raw-gradient measurements from Pico-LM across four scales and 125 aligned steps, together with a five-scale Pythia companion dataset built from 153 aligned checkpoint-difference update fields. The same algebraic closure holds in both families, and both share a near-unity cascade-size backbone, but they occupy distinct transport regimes: Pico-LM shows positive duration scaling and negative intensive-efficiency scaling, whereas Pythia remains near the $D=1$ baseline with only weak positive efficiency scale dependence. Randomized-field controls give nearly matched null floors in the intensive and duration channels, indicating that the contrast reflects different real departures from a shared null skeleton rather than different null calibrations. The families also differ in stepwise power-law compressibility: Pico-LM retains clean duration and efficiency power laws, whereas Pythia preserves the size backbone but shows weaker one-slope compressibility in those channels. External performance associations are correspondingly channel-level, carried mainly by $v_{\mathrm{rel}}$ and normalized cascade duration, while $D(t)$ acts as a shared size backbone without a significant exponent-level performance association. These results support a reusable transport measurement framework without claiming a universal fixed point or a first-principles derivation of neural scaling laws.

Most modern bridge-diffusion methods achieve finite-time transport by specifying an interpolation, Schrodinger-bridge, or stochastic-control objective and then learning the associated score or drift field with a neural network. In contrast, we identify a restricted but sufficiently broad analytically solvable class in which, for a deterministic source and a Gaussian-mixture target, the score and all intermediate marginals are explicit and protocol objectives of the type used in this paper can be differentiated without inner stochastic simulation loops. We recast the classical linear–quadratic–Gaussian stochastic-control structure as a transport problem of the Path Integral Diffusion type. Linear dynamics, Gaussian noise, and quadratic running costs reduce the bridge calculation to a matrix Riccati cascade, while the terminal state cost is replaced by a prescribed Gaussian-Mixture terminal probability density. Linear Quadratic – Gaussian Mixture – Path Integral Diffusion (LQ-GM-PID) thereby turns bridge diffusion from terminal target matching alone into an analytically controlled laboratory for path shaping. We demonstrate this on a 2D corridor task, a 2D multi-entrance task, and a high-dimensional study reaching d=32 and M=16 terminal modes in separate scaling sweeps. We position LQ-GM-PID as an analytically solvable reference model in which score approximations, path-shaping objectives, and protocol-learning procedures can be tested against explicit quantities.

In this study we analyze the topological invariants and edge states of transverse magnetic wave propagation in continuum photonic systems at a finite-width interface between two gyrotropic materials with different magnetic biases. Where previous studies have almost exclusively considered sharp transitions between two different electromagnetic media, we consider the more general geometry where the magnetic field bias is allowed to vary arbitrarily in a finite-width interface between two bulk regions. We find that when the magnetic field bias varies continuously between the two bulk regions, the Bulk Edge Correspondence (BEC) holds robustly with respect to well-defined Chern invariants. However, discontinuities in the magnetic field bias introduce new edge modes and anomalous high-wavenumber spectral effects which alter the BEC. We analyze these spectral alterations and define a new anomalous BEC in continuum photonic systems which includes contributions from topological invariants and discontinuities in magnetic field bias.

We show that multi-invariants provide necessary and sufficient criteria for full separability in finite-dimensional multipartite systems. For tripartite three-qubit states, the third-order negativity gives an exact criterion for full separability for both pure and mixed states. We then extend the framework to four-qubit pure states, whose full characterization requires eighteen independent real parameters. We identify eighteen independent entanglement measures, consisting of six bipartite, eight tripartite, and four quadripartite measures, with the third-order negativity serving as a key separability criterion. Finally, we generalize the construction to multipartite qudit systems and discuss an application to conformal field theory.

We uncover hierarchy of topological phases within the synthetic Brillouin zone of a three-terminal Josephson junction's (3-TJJ's) Bogoliubov-de Gennes spectrum. We demonstrate that the above-gap continuum realizes a Chern insulator phase with quantized monopole charges (\pm 1), while the subgap Andreev bound states (ABS) are characterized by a quantized dipolar invariant. By breaking time-reversal symmetry at the junction, we induce synthetic flat bands that suppress DC Josephson currents across the entire phase-bias space. Furthermore, under voltage bias, the junction exhibits a robust quantization of the time-averaged transconductance that is reminiscent of a quantized Hall conductance plateau owing to the flat band limit and its dipole phase. As a byproduct, the flat band produces a global "sweet plateau" of phase insensitivity, surpassing localized sweet spots of conventional superconducting qubits and enabling a robust architecture for symmetry-protected Andreev qubits.

Negative Gaussian curvature provides an unusual route for designing electronic structure in extended sp2 carbon networks. Here I report ab initio density-functional calculations on the D-type carbon schwarzite C136, focusing on the response of the ideal high-symmetry framework to spin polarization and fixed-cell ionic distortion. A partial spin-polarized fixed-cell relaxation lowers the total energy by approximately 0.213 eV per 136-atom cell over six completed ionic steps. The distortion remains moderate: the RMS atomic displacement is approximately 0.098 Angstrom, the maximum atomic displacement is approximately 0.200 Angstrom, the RMS C-C bond-length change for the 170 reference bonds shorter than 1.80 Angstrom is only approximately 0.0107 Angstrom, and no unphysically short C-C contacts below 1.20 Angstrom are found. A separate clean from-scratch spin-polarized SCF calculation on the last saved distorted geometry converges successfully to a magnetic state with total energy -2490.35442340 Ry, total magnetization 10.63 muB/cell, and absolute magnetization 12.94 muB/cell. Spin-resolved DOS calculations further show that the distorted geometry retains a high density of states near the Fermi level. A 3x3x3 diagnostic DOS gives N(EF) approximately 42.84 states/eV/cell, while a 4x4x4 validation DOS gives N(EF) approximately 42.85 states/eV/cell, demonstrating that the high-DOS character is robust with respect to this k-point refinement. These results support the interpretation of C136 as a negative-curvature carbon parent phase near coupled spin-lattice and high-DOS electronic instabilities. Superconductivity is not established here; rather, the results motivate a search for stabilized, distorted, doped, or intercalated descendants of D-type carbon schwarzites.

Variational quantum algorithms are promising for near-term quantum computing, but are severely limited by hardware noise and the substantial circuit overhead required for error mitigation methods such as Zero-Noise Extrapolation (ZNE). We propose a Physics-Informed Denoising Network (PIDN) that reduces the cost of ZNE by learning a surrogate model of its optimization dynamics. By viewing the variational update as a trajectory in the parameter space, PIDN is trained to reproduce ZNE-mitigated expectation values and gradient directions while incorporating a physics-informed loss that preserves the gradient descent dynamics. Once trained, PIDN replaces repeated multi-noise evaluations with denoised expectation and gradient estimation directly from the current noisy observation and the historical trajectory, significantly reducing circuit executions. We benchmark the approach on the quantum approximate optimization algorithm for 3-regular graphs, Sherrington-Kirkpatrick, and transverse-field Ising models, as well as the variational quantum eigensolver for LiH, BeH$_2$ and H$_2$O. Across all tasks, PIDN attains performance comparable to ZNE, while reducing the number of circuit executions by a factor of approximately 4 to 6. Gradient cosine similarity with ZNE remains above 0.95 throughout training. Robustness analysis shows that PIDN fails only when ZNE itself becomes unreliable, and ablation studies confirm the necessity of the physics-informed loss for maintaining directional consistency. We further find that PIDN tracks optimization dynamics most accurately when the effective loss landscape retains strong low-frequency structure. These results establish PIDN as a scalable, resource-efficient strategy for noise-resilient variational optimization in the noisy intermediate-scale quantum regime.

Cobalt ferrite (CoFe$_2$O$_4$) is a prototypical ferrimagnetic spinel oxide whose exceptional magnetic anisotropy, magnetoelastic coupling, and thermal stability underpin applications in spintronics, magnetic hyperthermia, energy harvesting, and catalysis. This chapter presents a comprehensive computational framework that integrates electronic$-$structure calculations with atomistic spin modeling, statistical mechanics, and continuum micromagnetics to predict magnetic functionality across length and time scales. Starting from density functional theory with Hubbard corrections (DFT$+$U), we derive exchange constants J$_{ij}$, magnetocrystalline anisotropy K$_1$, and magnetoelastic coefficients B$_1$, accounting for cation inversion, strain, and correlation effects. These parameters feed into generalized Heisenberg Hamiltonians, enabling Monte Carlo and Landau-Lifshitz-Gilbert simulations of finite-size effects, hysteresis, coercivity, and hyperthermia response in nanoparticles and thin films. Coarse-graining strategies bridge to micromagnetic modeling, ensuring consistent parameter flow without empirical fitting. Computational case studies demonstrate size-dependent anisotropy enhancement, surface spin disorder, strain-tunable switching, and doping trends, revealing design principles inaccessible to experiment alone. Validation against benchmarks, e.g. Curie temperature, anisotropy constants, coercivity, magnetostriction, confirms predictive accuracy. Current challenges, e.g., U$-$parameter sensitivity, realistic surface chemistry, spin-lattice coupling, and large-scale integration are discussed alongside emerging directions including DFT$+$DMFT, coupled dynamics, and machine-learned potentials.

We theoretically investigate supercurrents of ultracold atoms in angularly ac-shaken ring lattices subjected to external rotation. Our results demonstrate how these supercurrents can be harnessed for the development of high-precision atomtronic angular accelerometers. Using both analytical and numerical approaches within the Bose-Hubbard model framework, we demonstrate that a significant net atomic current arises when the lattice driving frequency is tuned to an integer fraction of the Bloch frequency, while the current averages to nearly zero away from such a resonance. In the single-particle regime, the resonance width scales inversely with the averaging time, thereby setting a fundamental Fourier-limited bound on the measurement's sensitivity. Strikingly, our numerical simulations demonstrate that this Fourier limit - a fundamental barrier in the non-interacting system - can be surpassed by introducing weak interactions between atoms. In the interacting regime, the sensitivity surpasses the Fourier-limited scaling with the averaging time, achieving an improvement of at least two orders of magnitude over the single-particle scenario, and exceeding the performance of previously proposed ultracold-atom-based angular accelerometers. These findings pave the way for developing new atomic-current-based inertial sensors with interaction-enhanced sensitivity.

In this work, we explore a microscopic realization of three types of anyonic symmetries in a $\mathbb{Z}_2\times\mathbb{Z}_2$ topological order, corresponding to a double toric code. These symmetries act as nontrivial permutations on the anyon labels of the parent state. We consider a setup consisting of two decoupled Wen plaquette models stacked on top of each other and introduce dislocations that modify the Hamiltonian, giving rise to localized twist defects, eventually inducing interactions between the layers. In this context, branch cuts act as sources of anyon permutations when they cross it. We characterize the defects by calculating their quantum dimensions, and we also consider double loop operators around them that allow us to determine the non-Abelian fusion rules between the defects, including when they carry different anyon permutations.

High-throughput characterization of architected materials across a wide range of length scales enables rapid screening of topologies for engineering applications. Scaled-down specimens manufactured and evaluated in laboratory environments enable this iteration, but application scenarios may involve differing length scales and loading conditions that complicate direct comparisons. Here, we use a spinodal architected morphology to determine the interplay among the constituent material's strain-rate sensitivity, the topological length scale, and the imposed deformation rates. We report characterization spanning strain rates from $10^{-3}$ s$^{-1}$ to $10^{4}$ s$^{-1}$ on spinodal architected specimens with length scales of 100 $\mu$m (microscale) and 30 mm (macroscale). The experiments show that while microscale specimens exhibit moderate increase in strength at high strain rates, macroscale specimens exhibit a nearly tenfold increase in strength at equivalent strain rates. Finite element calculations reveal that this increase is linked to a transition from a response governed by constituent material strain-rate sensitivity to inertia-dominated behavior in macroscale specimens, a transition not observed in microscale specimens at the strain rates investigated here. Using extensive finite element calculations, we develop maps to establish the parameters governing the regimes of behavior, illustrating that the transition from behavior governed by constituent material rate sensitivity to inertia-dominated behavior has analogies to fluids in that it depends on a structural length scale. Our findings provide insights into the physical parameters that govern responses across length and time scales, towards the development and design of new laboratory experiments that extract relevant dynamic properties for structural applications.

Photon upconverters are anti Stokes emitters capable of generating photons with higher energy than those absorbed. This behavior can be achieved through different mechanisms, which are extensively studied for applications in imaging, anticounterfeiting, information encryption and most importantly, solar energy technologies. Among these mechanisms, photon upconversion based on sensitized triplet-triplet annihilation (sTTA-UC) is particularly attractive because it operates under low intensity, incoherent light. In sTTA UC, two optically dark triplet states of a conjugated annihilator fuse upon collision to populate a higher energy fluorescent singlet, with the triplets initially generated via energy transfer from a lower energy sensitizer. Here we introduce a general molecular design strategy to maximize singlet generation through TTA. By selective substitution, we engineered a naphthalene derived annihilator with an excited state energy landscape that strongly favors singlet formation, achieving yields up to 0.83. When combined with an appropriate triplet sensitizer, the system delivers stable UV/visible upconversion peaking at 390 nm, with an absolute upconversion yield about 0.19 and an activation excitation intensity threshold lower than 0.1 suns under non-coherent broadband excitation fully compatible with the requirements of solar powered technologies.

We analytically study the time evolution of the expectation values of observables in periodically kicked many-body quantum systems. Starting from an initial state, we compute both the transient and the long-time properties of the observables. Our derivation explains the criteria and the mechanism that lead to the infinite-temperature statistical average of observables at long times, irrespective of the initial state. When the criteria are violated, the observables oscillate with time. These oscillations are subharmonic and robust to small perturbations, suggesting the emergence of a discrete time crystal phase. We demonstrate these features explicitly in periodically kicked nonintegrable spin chains. For a spin chain with two kicks per cycle, we show that the kicked chain can exhibit an ergodic or a discrete-time crystal phase for the same kicking strengths, depending on the initial state preparation. We complement our time-evolution study of observables with the spectral form factor of these kicked models.

Mid-infrared photo-induced force microscopy (IR-PiFM/PiF-IR) enables high-resolution chemical imaging of surfaces with lateral resolution less than 5 nm. Here are some answers to questions about the physical background, practical handling and potential applications of PiF-IR including its use in the context of studying antimicrobial interaction. Such questions had been addressed to me during the Faraday Discussions on Vibrations at Interfaces which took place in April 2026 in Manchester/UK. The discussion was part of the theme "What is the question, what is the technique?" in the context of which I presented our recent work [James et al., Faraday Discussions, 2026, doi: 10.1039/d6fd00003g]. A modified version of this manuscript will be published in the themed collection "Vibrations at Interfaces" in Faraday Discussions.

We present a first principles study of the ferrochiral phase transition in chiral BaTiOCu$_4$(PO$_4$)$_4$, which has been shown using X-ray diffraction to proceed via the antiferroaxial rotation of antipolar structural units. We analyze the atomic-site electric and magnetic multipole moments to identify connections between these multipoles and chirality and corroborate the previous experimental interpretation. We show that antiferroically ordered atomic-site electric toroidal dipole moments act as an order parameter for the antiferroaxial rotations, and that the overall chiral order is parameterized by the composite order of the antipolar electric dipole and electric toroidal dipole moments. Finally, we evaluate the suitability of various proposed order parameters for chirality, show that some can be excluded and suggest the most promising directions for future exploration.

Recent work has demonstrated microscale compressive plasticity in pulse laser deposited (PLD) amorphous alumina (a-Al2O3). This work explores microscale bending plasticity and fracture behavior of a-Al2O3 films deposited using three different methods-PLD, atomic layer deposition (ALD) and sputter deposition (SD). The three deposition routes produced amorphous films with similar stoichiometric compositions. We demonstrate, for the first time, bending plasticity in PLD and ALD a-Al2O3 films at microscale using in situ microcantilever bending experiments at room temperature. All tested PLD a-Al2O3 microcantilevers showed substantial ductile behavior in bending by accommodating total strains >10% without fracture. Half of the tested ALD a-Al2O3 cantilevers exhibited elastic brittle fracture while the other half showed bending plasticity, indicating that the observed deformation behavior is strongly influenced by the presence and distribution of defects within the tested volume. All SD a-Al2O3 microcantilevers showed elastic brittle failure attributed to their columnar growth microstructure. The microscale bending response was found to be highly dependent on the film deposition method highlighting the role of defects in suppressing plasticity mechanisms. Notched microcantilever bending tests on all three films showed brittle failure with similar fracture toughness value of 3.1 +/- 0.2 MPa.m0.5, effectively ruling out any localized crack tip plasticity. These findings underscore the importance of minimizing defects during fabrication in order to develop damage tolerant amorphous oxides. Nonetheless, the observation of bending plasticity in both PLD and ALD microcantilevers, which include a tensile stress component as well, suggests that the plastic deformation mechanisms in amorphous alumina are more general and are not exclusively governed by the deposition method.

Long-range (LR) quantum spin systems offer promising advantages for quantum information processing and sensing. Here, we investigate parameter estimation in an long-range XX spin model coupled to a reservoir, which gives rise to an effective long-range RT-symmetric non-Hermitian iXY Hamiltonian. The interactions extend up to a tunable coordination range and decay algebraically with distance, enabling a direct comparison between long-range and short-range (SR) regimes. Focusing on the estimation of the transverse magnetic field and anisotropy parameter, we initialize the system in a fully polarized state and analyze the resulting dynamical quantum Fisher information (QFI). We show that, with suitable tuning of the system parameters, both the time and system-size scaling of the QFI are enhanced in the LR regime relative to their SR counterparts. Moreover, the non-Hermitian LR model can exhibit superior dynamical QFI compared with the corresponding Hermitian model, demonstrating a genuine metrological advantage induced by the interplay of long-range interactions and non-Hermitian effects. In contrast, we establish a no-go result at the critical magnetic field: when the probe is prepared in the lowest-energy eigenstate, the QFI scaling remains identical for the Hermitian and non-Hermitian cases.

Boron nitride nanotubes (BNNTs) provide wide-bandgap, optically transparent one-dimensional hosts for molecular dyes, limiting direct electronic participation of the host. Whether dye@BNNT systems produce bright, well-defined J- or H-aggregates or instead heterogeneous emissive ensembles whose character depends on chain length and local packing remains only partly resolved. We address this question using ensemble extinction, photoluminescence, quantum-yield measurements, and TCSPC-derived radiative and non-radiative rates, together with polarization-resolved single-nanotube microscopy on encapsulated quaterthiophene, sexithiophene, octithiophene, and Nile Red, selected from a ten-dye screening. In the oligothiophene series, confinement modifies spectra and excited-state dynamics in a length-dependent manner, with all three oligothiophenes forming weakly emissive ensembles with suppressed effective radiative rates and 6T showing the strongest redistribution between effective radiative and non-radiative decay. The absence of radiative-rate enhancement or fluorescence-lifetime shortening across the series disfavors bright J-aggregate assignments. Polarization-resolved single-nanotube microscopy reveals strongly polarized emission, but with tube-to-tube and intratube variations, identifying oligothiophene@BNNTs as ordered yet structurally heterogeneous confined ensembles. Nile Red provides a complementary case in which the dominant response is dielectric tuning of a solvatochromic charge-transfer state rather than oligothiophene-like aggregate formation. These findings establish dye-filled BNNTs as optically quiet nanoconfined systems in which molecular ordering, dielectric confinement, and guest-guest coupling can be distinguished through combined ensemble and single-nanotube spectroscopy.

The non-equilibrium behavior of particle systems driven by reservoirs has been extensively studied in recent years. In one dimension, various regimes have been explored depending on the coupling strength to the reservoirs. In this paper, we investigate the role of the dimension and of the geometry of the contacts with the reservoirs. For the symmetric simple exclusion process with point contact reservoirs, we show that in dimension 2, as in one dimension, three different regimes occur depending on the coupling strength. On the other hand in dimensions 3 and higher, there exists only a weak coupling regime which is very sensitive to the microscopic structure of the contacts. We then argue that for reservoirs with mesoscopic size contacts the macroscopic fluctuation theory remains in force and we propose an extension of the additivity principle for multiple mesoscopic reservoirs.