Papers

We analyze the spectrum of collective modes in a superconductor in which pairing is mediated by long-range nematic fluctuations. Previous experimental and theoretical studies have found that the superconducting gap in such a system is highly anisotropic and, at any finite $T<T_c$, vanishes on four arcs of the Fermi surface, even when the pairing symmetry is $s$ wave ($s^{+-}$ between hole and electron pockets). We derive the expression for the pair susceptibility $\chi(\mathbf{q},\Omega)$ at finite momentum $\mathbf{q}$ and frequency $\Omega$ deep in the superconducting phase. We analyze the spectral function, $\operatorname{Im}\chi(\mathbf{q},\Omega)$, and its pole structure in the transverse (phase) and longitudinal (amplitude) channels, and compare the results with those of a conventional $s$-wave superconductor. We find that the analytic structure of the pair susceptibility in both channels is qualitatively distinct from that in a BCS superconductor. This gives rise to a highly unconventional dispersion of phase and amplitude collective modes.

In a free Fermi gas at temperature $T$ much higher than the Fermi temperature one expects that the fluctuations of the number of particles in a given region has Poissonian/classical statistics. On the other hand at low temperature the Pauli exclusion principle leads to non trivial counting statistics. It is of great interest from a theoretical and experimental point of view to characterize the crossover between these two limits. Here we focus on the hole probability $P(R,T)$, i.e. the probability that a region of size $R$ is devoid of particles, in dimension $d$, and on the case of a spherical region of large radius $R$. We show that at low temperature it takes the scaling form $P(R,T)\sim \exp\big[-(k_F R)^{d+1}\Phi_d(u=2R\,T/k_F)\big],$ where $k_F$ is the Fermi momentum. By mapping the problem to an effective Coulomb gas, we compute exactly the scaling function $\Phi_d(u)$ in any dimension. Remarkably, it exhibits a transition of order $\tfrac{3}{2}(d+1)$ at the universal critical value $u_c=2/\pi$, signaling a sharp change in the mechanism of rare fluctuations, associated with the emergence of a macroscopic gap in the optimal density of the associated Coulomb gas. Our analytical predictions are supported by precise numerical evaluations of the corresponding Fredholm determinants.

Kappa distributions are widely used in space plasma physics to model velocity distribution functions with heavy tails. Parameter estimation in these distributions is, however, complicated by the fact that the kappa distribution does not belong to the exponential family, so it admits no sufficient statistics and direct maximum likelihood requires numerical optimization without analytically closed-form update equations. Working within the Beck-Cohen superstatistics framework, where a gamma-distributed inverse temperature \(\beta\) generates the kappa distribution upon marginalization, we treat \(\beta\) as a latent variable. This hierarchical description restores the exponential family structure that the marginal kappa distribution lacks, and yields an analytically tractable implementation of the expectation-maximization (EM) algorithm whose E-step and M-step admit closed-form expressions in terms of sufficient statistics. Applied to synthetic data drawn from the model, the algorithm converges monotonically to a stationary point of the marginal kappa log-likelihood and recovers the generating parameters consistently across the explored range of \(\kappa\). EM thus offers a tractable and transparent route to inference in superstatistical systems with local temperature fluctuations.

Band theory provides the foundation for understanding electronic structure in crystalline materials, but its reliance on exact translational symmetry limits its applicability to systems with defects, disorder, incommensurate modulations, or large unit cells. Here, we introduce a band unfolding framework that directly generalizes traditional band theory to systems where exact periodicity is absent, and which remains well-defined for both aperiodic and finite systems. To do so, we employ a pseudospectral approach to identify approximate joint eigenvectors of a system's Hamiltonian and translation operators, thereby yielding an unfolded band structure whose features are directly connected to the manifestation of approximate extended states simultaneously localized in energy and crystalline momentum. To reveal bulk-only spectral phenomena in finite systems, we further show that this pseudospectral framework naturally accommodates additional operators that suppress contributions from boundary-localized states, enabling the systematic isolation of intrinsic bulk behavior. We benchmark the scheme on several representative systems in one and two dimensions, including a Fibonacci chain, where our approach is able to both reveal a dispersive envelope while preserving the underlying hierarchy of spectral gaps. Looking forward, this pseudospectral approach may yield a broad framework for predicting momentum-resolved material responses in aperiodic, disordered, and finite systems where conventional band-theoretic methods are not applicable.

Quadratic response tensors arise naturally in quantum kinetic descriptions, such as the quantum linear Boltzmann equation (QLBE), where they encode the coupled structure of drift and fluctuations beyond simple positive-definite forms. Motivated by this class of systems, we investigate how such response structures are modified under monitoring-induced coarse graining. Within the Gorini–Kossakowski–Sudarshan–Lindblad (GKSL) framework and under time-scale separation, Zeno elimination of fast degrees of freedom generates a subtractive renormalization with Schur-complement structure. As a result, positive definiteness of the response tensor is not preserved: coupling between slow and rapidly damped sectors can induce negative directions even when the microscopic tensor is strictly positive. We formulate a minimal effective flow capturing this mechanism and show that the competition between Schur-induced compression and anisotropic perturbations organizes the dynamics into distinct signature sectors. The resulting structure appears to be robust within the class of models considered and, in appropriate regimes, may be experimentally accessible. Our results establish a general framework for how quadratic response structures, as encountered in QLBE-type dynamics, are dynamically reorganized under Zeno-induced coarse graining.

Moire superlattices formed by stacking atomically thin two-dimensional materials with a relative twist angle have emerged as a versatile platform for engineering quantum electronic, optical, and ferroic properties. Computational modelling of such systems with periodic boundary conditions requires the identification of commensurate supercells in which the moire periodicity is reproduced exactly, or within a prescribed tolerance. While several codes exist for bilayer systems, extension to three or more layers with independently chosen twist angles remains a significant challenge. Here we present MLM (Multi-Layer Moire), an open-source Python package that constructs periodic, PBC-compatible moire supercells for an arbitrary number of twisted layers with any Bravais lattice type. The package employs a solve-and-round algorithm that reduces the coincidence-site search to an $O(N^2)$ linear-algebra problem per twist angle, compared to the O(N^4) brute-force enumeration required by conventional approaches. We demonstrate the package on bilayer graphene, bilayer and trilayer MoS$_2$, bilayer SrTiO$_3$, and a PbTiO$_3$/SrTiO$_3$ oxide heterostructure, producing simulation-ready structure files for both VASP and LAMMPS. The fractional-coordinate atom-selection algorithm scales to supercells containing millions of atoms and is robust across all twist angles including very small angles below 1 degree.

We introduce the Frustrated Distance Matrix (FDM) model, a dynamic extension of the static distance-matrix ensemble on S^2 analyzed by Bogomolny, Bohigas, and Schmit (BBS). Its entries are pairwise geodesic distances between N Brownian particles on the sphere evolving under quenched random pairwise couplings linear in those distances. Where the static BBS theory recovers geometric information about the underlying manifold from spectra of distance matrices on i.i.d.\ samples, the time-resolved FDM spectrum carries information about structural changes of the underlying point process. The particle dynamics realize one such change: a fast collapse from a uniform configuration onto a one-dimensional ring, followed by slow rotational drift of the ring orientation; the particle-level picture provides the ground truth against which spectral diagnostics are calibrated. We find that the static BBS template is preserved at every time, with the dynamics entering as a redistribution of spectral mass within that template, sharp enough to flag ring formation. We propose self-averaging of the bulk density as the mechanism behind this preservation, verified by an i.i.d.-resample comparison, and extract a small set of spectral diagnostics of the structural change computable from the distance matrix alone. We suggest that our diagnostics can be applied in other similar inverse-problem settings: financial correlation matrices, graph and network adjacency spectra, similarity matrices in molecular dynamics, and dynamics on parameter manifolds.

We develop a statistical field theory that describes the large-N limit of a system of Brownian particles with quenched random pairwise interactions on a compact two-dimensional Riemannian manifold. The resulting Frustrated Fields (F2) model is a non-linear field theory for a smooth self-interacting density field $\rho$ on the manifold, with local and non-local (in space and time) self-interactions characteristic of spin-glass dynamics. Particle simulations show adiabatic dimension reduction: on $S^2$, the density concentrates on a slowly precessing great-circle ring whose orientation is a director ($\hat{\mathbf{n}} \sim -\hat{\mathbf{n}}$, even profile). Conditioned on this simulation-supported ring saddle and on a Born-Oppenheimer separation between the slow orientation and the gapped density fluctuations, symmetry fixes the low-energy dynamics to be the nonlinear sigma model (NLSM) on the real projective plane $S^2/\mathbb{Z}_2 = \mathbb{RP}^2$ (the $\mathbb{RP}^2$ NLSM on the projective rotor space) in $(0+1)$ dimensions, governed by a single low-energy constant, the rotational diffusion coefficient $D_{\text{rot}}$. With $D_{\text{rot}}$ and the static ring profile $f_0$ measured from particle simulations, the resulting effective theory reproduces multiple independent orientation- and density-sector diagnostics with no further adjustable parameters.

The current work has investigated the effect of co-doping 3Y-Zirconia (3YSZ) with Sc, Mg and Y by wet infiltration. Pre-sintered discs of 3YSZ were immersed in diluted nitric acid solutions containing Sc, Mg or Y, and combinations of the three, trapping liquid within the porosities of the samples. Upon drying, the cations are maintained inside the pellet, making the basis for the co-doping. After sintering, mass increase confirms the co-doping effect and X-ray diffraction analysis show clear variations in atomic structure depending on the doping element. Rietveld refinements show that the wet-infiltrated samples contain the tetragonal t, t double prime and cubic c-phase in various fractions depending on the doping elements. Sc-infiltrated samples show a tendency to higher tetragonality, while the Mg-infiltrated sample obtained a single cubic phase. The multi-phase wet-infiltrated samples have a similar phase separation after sintering as 5Y-Zirconia (5YSZ), as calculated by the tetragonality deviation parameter. 3YSZ and 5YSZ sintered for 0 hours and 2 hours at 1500 degrees C show the effect of sintering time on the phase segregation. To evaluate the material properties in an application-based perspective, the Knoop hardness, translucency and grain size was measured. We conclude that liquid infiltration is a viable route to perform co-doping of Zirconia with various co-doping elements.

Understanding the atomic-scale structure and dynamics of amorphous oxide surfaces is essential for interpreting their chemical reactivity, mechanical stability, and interfacial behavior, yet direct experimental characterization remains challenging. We employ Deep Potential (DP) molecular dynamics to generate large-scale, ab initio-quality models of amorphous Al$_2$O$_3$ bulk glasses and melt-quenched free surfaces, enabling a quantitative analysis of both structure and relaxation dynamics with statistical confidence inaccessible to direct ab initio simulation. The trained DP model reproduces experimental liquid and glass structure, captures the cooling-rate dependence of the bulk glass transition, and corrects systematic biases in the polyhedral populations predicted by widely used classical force fields. At the free surface, mass density recovers to bulk values over ~10 $\unicode{x212B}$, while local coordination requires a slightly wider subsurface region to fully converge. The outermost layer is oxygen-enriched, exhibits altered polyhedral connectivity with contracted Al-O bonds, and hosts a broad population of under-coordinated motifs (notably AlO$_3$ and OAl$_2$) whose abundances are governed by glass stability. These reactive Lewis acid and Br$\unicode{x00F8}$nsted base sites are locally paired in a manner consistent with bond-valence compensation, yet remain spatially dispersed rather than aggregating into extended clusters. Despite this pronounced structural heterogeneity, the surface relaxes on the same timescale as the bulk and exhibits a comparable glass transition temperature, suggesting that the disordered surface is kinetically stable once formed. Together, these results establish a molecular-level picture of amorphous alumina surfaces and demonstrate the capability of machine-learned potentials to resolve structure-property relationships in disordered oxide interfaces.

Ultrafast birefringence oscillations observed in superfluid helium provide evidence for anisotropic quantum squeezing of quasiparticle pairs. The measured response is a superposition of contributions from all vibrational modes, with dominant contributions from rotons, maxons, and Pitaevskii's plateau. The nonzero initial phase follows naturally from multimode interference.

Spin splitting underpins a vast range of spin-dependent phenomena. Traditionally, two primary mechanisms generate such splitting: relativistic spin-orbit coupling (SOC) and nonrelativistic magnetic exchange coupling (MEC). Governed by distinct symmetry constraints, they produce splittings of opposite parity – odd for SOC and even for MEC – a dichotomy that underpins the distinct spin physics of nonmagnetic and magnetic systems. In this work, we break this dichotomy by demonstrating the dynamic generation of even-parity spin splitting in centrosymmetric, nonmagnetic systems driven by circularly polarized light. We show that the symmetry of the induced splitting is controlled by the angular character of the underlying orbitals, enabling the realization of s-wave, d-wave, and g-wave spin-split band structures identical to those of ferromagnets and altermagnets. Furthermore, we find that these spin-split bands can naturally host a Chern insulator phase. We also discuss the associated spin and orbital magnetization. Our results establish a direct and previously unrecognized conceptual link between the two fundamental mechanisms of spin splitting.

We study the crystalline phase of the $O(2N)$ Gross–Neveu model with a chemical potential for $a \leq N-2$ of the fermions. We analyze the problem in three independent ways: using perturbative QFT methods, a semiclassical large $N$ analysis, and integrability techniques (both at finite and large $N$). The resulting picture is consistent across all three approaches: at sufficiently large chemical potential $h$, an inhomogeneous phase emerges in which $a$-particle bound states condense and which, at large $N$, corresponds to a periodically oscillating chiral condensate. In this phase, the usual dynamically generated scale $\Lambda$ is replaced by two new dynamically generated scales $\Lambda_{\rm n}$ and $\Lambda_{\rm c}$. These two scales govern the multiple nonperturbative effects in the theory, corresponding in particular to the mass gaps of neutral and charged excitations on top of the inhomogeneous vacuum, respectively. They also control the nonperturbative corrections to observables such as the free energy and provide the parameters characterizing the oscillatory profile of the mean field at large $N$. In this paper, we provide the necessary details of each of the three methods, thereby complementing the results announced in a previous, shorter publication.

Measurement-induced phase transitions are nonequilibrium transitions between phases characterized by distinct entanglement scaling behaviors, driven by the competition between unitary dynamics and measurements. Despite recent numerical efforts, how quenched disorder affects these transitions remains unclear. In this work, we study a $d$-dimensional noninteracting fermionic system subject to both quenched disorder and continuous monitoring of the local particle density, and derive an effective field theory describing its long-time universal behaviors. We find that the system is governed by the same nonlinear sigma model as in the case of clean monitored fermions, with disorder entering only through a modification of model parameters. This result suggests that the presence or absence of a measurement-induced phase transition is unaffected by the introduction of disorder. In spatial dimension $d=1$, the system exhibits only an area law phase and no transition, whereas in $d>1$, a transition persists between an area$\times$log law phase and an area law phase, with the critical measurement rate suppressed by disorder. Numerical simulation confirms the absence of MIPT in $d=1$, and the linear shift of the critical measurement rate by disorder scattering rate in higher dimensions predicted by analytical theory.

Conventional approaches to simulating quantum many-body dynamics produce a single trajectory: if the Hamiltonian or the initial state is changed, the computation must be re-performed. Recent efforts toward foundation models have begun to address this limitation, yet existing methods transfer across either Hamiltonians or initial states, but not both. In this work, we introduce the Universal Neural Propagator (UNP), a single, unified model that learns the functional mapping from driving protocols to time-evolution propagators. Trained in an entirely self-supervised way, a single UNP model predicts dynamics across a function space of driving protocols and an exponentially large Hilbert space of initial states simultaneously. We benchmark on a two-dimensional driven Ising model and demonstrate the UNP's accuracy and transferability across product and entangled initial states, as well as for both in- and out-of-distribution driving protocols. The UNP remains accurate at system sizes beyond exact diagonalization, and can be efficiently fine-tuned across all initial states using observable data. By shifting the object of learning from quantum states to operators, this work opens a route toward transferable simulation of driven quantum matter.

Quantum many-body scars in Rydberg atom arrays have thus far only been observed on bipartite lattices, leaving open the question of whether and how they survive frustration, and what the appropriate initial states are that lead to nonthermal dynamics. We introduce a graph-theoretic framework to find suitable candidates for scarring on arbitrary lattices. Our framework predicts two distinct mechanisms: type-I scars generalize the bipartite case by using locally entangled states to overcome mild frustration, while type-II scars exploit strong frustration to pin part of the lattice, leaving the remainder to oscillate freely. We numerically demonstrate both mechanisms and uncover an exponential family of scarred trajectories on the hexagonal lattice that can encode information protected from thermalization. Our results establish scarring as a generic feature of Rydberg systems beyond one dimension and provide an experimentally accessible route to systematically probing non-thermal dynamics in quantum simulators.

Quantum many-body scars enable persistent non-ergodic dynamics in otherwise thermalizing systems, yet their stabilization typically relies on fine-tuned initial states or engineered Hamiltonian perturbations. Here we show that lattice geometry alone can serve as a powerful and experimentally accessible control knob for inducing and enhancing scarring. By transforming a one-dimensional chain into a quasi-one-dimensional triangle-decorated lattice, we find that the fully polarized state – normally thermalizing in the PXP model – exhibits pronounced fidelity revivals, slow entanglement growth, and strong overlap with a tower of weakly entangled eigenstates. We trace this behavior to a geometry-induced restructuring of the constrained Hilbert space, whereby the adjacency graph decomposes into hypercube subgraphs that enforce coherent population transfer and stabilize an emergent approximate $\mathrm{su}(2)$ algebra. We propose a direct implementation in programmable arrays of tweezer-trapped Rydberg atoms, where the triangle-decorated geometry can be realized using spatial light modulators and the resulting scarring dynamics probed via time-resolved measurements of excitation density. Our results establish lattice connectivity as a design principle for engineering non-ergodic dynamics in constrained quantum systems.

Deep neural networks owe their expressive power to nonlinear activation functions. The effective field theory of signal propagation at initialization reveals a few distinct universality classes of activations that exhibit different depth scaling. Tuning across these, especially with analytical control, is an open problem. We show that a statistical mixture of activations, where each neuron independently and randomly draws its activation from a two-component distribution with mixing fraction $p$, provides a new mechanism for a continuous phase transition. Applied to a mixture of Tanh and Swish, the transition is sharp in the depth scaling of the preactivation variance, separating a variance-collapsing from a variance-inflating phase; at $p_c$, the network acquires statistical scale invariance, with depth-independent variance, without sacrificing smoothness. This resolves a longstanding tension, where scale-invariant propagation has previously required the non-smooth ReLU family, rendering such networks ill-suited to curvature-based optimizers, physics-informed architectures, and neural-network quantum states. We corroborate the transition through variance propagation, parallel and perpendicular susceptibilities, and Lyapunov exponents. Training multilayer perceptrons on real datasets reveals non-monotonic test performance as a function of $p$, with an optimum near the theoretically predicted $p_c$, confirming that the initialization-level transition has direct consequences for learned representations. The quenched activation disorder acts as a structural regularizer, suppressing memorization of corrupted labels while preserving generalization. Our framework establishes statistical activation mixtures as a controlled tool for navigating the phase diagram of deep network universality classes.

We develop a microscopic theory of charged excitations in an SU(2) Chern ferromagnet and obtain closed-form wavefunctions for a hierarchy of charge-$e$ spin polaron states binding an arbitrary number of spin flips. In an ideal Chern-$1$ band with a normal-ordered contact interaction, we show that these polarons are exact eigenstates of the Hamiltonian with the same energy as single-hole excitations. Away from this ideal limit, we promote these states to a variational family by introducing a single size parameter and a geometry-informed single-particle dressing. Our momentum-space wavefunctions admit two equivalent representations: a ratio of Jastrow factors of Weierstrass functions of relative momenta or an antisymmetrized geminal product of particle-hole wavefunctions. The latter enables efficient evaluation of overlaps and expectation values for large system sizes and many spin flips. Benchmarking in the lowest Landau level, the single-spin-flip ansatz achieves $\gtrsim 99\%$ overlap with exact diagonalization and accurately captures binding energies, while the multi-spin-flip energies interpolate smoothly toward the large-texture (skyrmion) regime. For Chern bands with tunable quantum geometry, we find that interaction-generated single particle dispersion quickly destabilizes the spin polarons once quantum geometry becomes sufficiently non-uniform. When such dispersion is suppressed, however, the bound states persist deeper into the non-uniform regime, with the binding energy slowly decreasing and the bound state becoming larger as the quantum geometry becomes more concentrated. Our results provide a microscopic foundation for analyzing doped Chern ferromagnets in moiré platforms and lay the groundwork for variational wavefunctions of multi-polaron excitations and phases.

Strong-to-weak spontaneous symmetry breaking (SWSSB) is diagnosed by nonlinear correlators, but its direct static implication for conserved charge fluctuations is not automatic. We show that, for continuous symmetries, long-range Rényi-1 correlator, together with a sufficiently rapid approach to its nonzero asymptotic value, forces subsystem charge indefiniteness: the block-charge variance has an extensive lower bound; equivalently, the truncated symmetry expectation has extensive curvature. This gives a precise static fluctuation footprint of charge scrambling. We construct examples to show that the implication is conditional and non-reversible: dephased superfluids retain Rényi-1 SWSSB with subextensive charge variance when the Rényi-1 tail is too slow, while sparse fixed-charge projectors have extensive charge variance but no local charge-transfer Rényi-1 order or long-range conditional mutual information. Finally, we introduce a twist overlap correlator, which serves as an analogue of charge variance applicable to both discrete and continuous symmetries. This naturally decomposes local block-charge fluctuations into strong- and weak-symmetry channels. We found that the weak-symmetry channel isolates coherent charge fluctuations and is directly related to the Wigner–Yanase skew information. Taken together, these results give a unified understanding for distinguishing nonlinear SWSSB order, local charge indefiniteness, and coherent charge fluctuations.

We introduce PhenixCraft, a fully automated pipeline for building atomic models from cryo-EM density maps. By integrating AlphaFold predictions, we enhance the map-segmentation step in Phenix during model building, addressing challenges posed by noise and artifacts that traditionally hinder this step. Our results demonstrate PhenixCraft's superior performance in TM-scores and sequence accuracy, significantly improving upon the limitations and inefficiencies of traditional model building using Phenix.

Altermagnetism has so far mainly been understood in its even- and odd-parity forms. We show that collinear antiferromagnets with zero net magnetization can also host mixed-parity spin splitting, namely neither purely even nor purely odd in momentum. We identify the symmetry conditions for such mixed-parity altermagnetism and show that, in two dimensions, it can arise in spin-orbital magnets when the two antiparallel spin sectors are related by a single mirror symmetry. Using a two-sublattice two-orbital model, we demonstrate that circularly polarized light induces mixed-parity altermagnetism at finite staggered potential and odd-parity spin-orbital altermagnetism at zero staggered potential. Mixed-parity altermagnetism thereby emerges as the intermediate spin-split regime between even- and odd-parity altermagnetism when spin splitting and zero net magnetization are maintained. Spin-resolved orbital Edelstein effects provide a complementary electrical probe of the underlying spin-orbital order.

Rhombohedral graphene exhibits an exceptionally diverse array of correlated phases that depend sensitively on the displacement field. Compiling reported phases into a unified phase diagram reveals a pronounced field-dependent electron-hole asymmetry: correlated states on the hole-doped side emerge at small displacement fields, whereas the fractional quantum anomalous Hall effect (FQAHE) is observed exclusively on the electron-doped side under large displacement fields. This stark asymmetry highlights the need to understand how flat bands evolve with displacement fields. Here, we directly visualize the field-induced electron-hole asymmetric band flattening in rhombohedral pentalayer graphene (R5G) using nanospot angle-resolved photoemission spectroscopy with electrostatic gating. Beyond gap opening and spectral weight redistribution indicative of layer polarization, the gating field drives a strongly asymmetric modification of the flat bands: the flat valence band (FVB) evolves into an M-shaped dispersion at high field, whereas the flat conduction band (FCB) progressively flattens with increasing field. Comparison with calculations identifies critical parameters governing the band curvature of R5G, from which the resulting finite Berry curvature and near-ideal quantum geometry support the emergence of topological phases under electron doping at large fields. These results establish a direct link between the asymmetric phase diagram, band structure evolution, and quantum geometry, providing a microscopic framework for understanding correlated and topological phases in rhombohedral graphene.

Spin-orbital generalization of Kitaev model provides a robust extension to the original Kitaev model. However, real materials often exhibit competing interactions that break exact solvability which can give rise to new phases. Motivated by recent microscopic proposals of coexisting Yao-Lee and Kitaev couplings, we investigate the fate of the ground state when two independent exactly solvable spin liquid Hamiltonians each originally formulated on different lattice geometries are combined on a common lattice environment. We first focus on the hybrid Kitaev's honeycomb and square-lattice model. Using self-consistent mean-field analysis and perturbative calculation, we show that the strong-Kitaev regime yields magnetic order in the spin sector, while the orbital sector retains its topological order. We further analyze the hybridization of the Yao-Lee and square-lattice models and find that the model exhibits a rich evolution of Majorana Dirac bands and Lifshitz transitions. Remarkably, when the Yao-Lee and square-lattice couplings are equal and opposite, the model restores its exact solvability with a single itinerant Majorana flavor. These results demonstrate that hybrid spin liquid platforms may host various emergent phases beyond conventional exactly solvable limits.

Hopf bifurcations are a universal route to self-sustained oscillations in driven systems. Despite the absence of any singular stationary state, we show that time-averaged observables generically exhibit singularities at the onset of oscillations. The origin of this behavior is geometric: phase averaging over the emergent periodic attractor eliminates odd powers of the oscillation amplitude, while the squared amplitude varies smoothly with the distance from the bifurcation. Consequently, the excess of a time-averaged observable admits an integer-power expansion; observables remain finite but display discontinuities in finite-order derivatives. This yields an Ehrenfest-like hierarchy of Hopf singularities, in which the first nonanalytic derivative is determined by the lowest-order coupling between the observable and the limit-cycle waveform that survives phase averaging. The time averages of generic observables therefore exhibit kink singularities, while symmetry or geometric cancellations can suppress lower-order couplings and shift nonanalyticity to higher derivatives. We demonstrate this mechanism in chemical, electronic, and climate oscillators. Our results identify supercritical Hopf bifurcations as a universal mechanism for nonanalytic observable behavior, where singular yet non-diverging features emerge without any underlying singular stationary state.

By far the most common way to estimate an expected loss in machine learning is to draw samples, compute the loss on each one, and take the empirical average. However, sampling is not necessarily optimal. Given an MLP at initialization, we show how to estimate its expected output over Gaussian inputs without running samples through the network at all. Instead, we produce approximate representations of the distributions of activations at each layer, leveraging tools such as cumulants and Hermite expansions. We show both theoretically and empirically that for sufficiently wide networks, our estimator achieves a target mean squared error using substantially fewer FLOPs than Monte Carlo sampling. We find moreover that our methods perform particularly well at estimating the probabilities of rare events, and additionally demonstrate how they can be used for model training. Together, these findings suggest a path to producing models with a greatly reduced probability of catastrophic tail risks.

We study dynamical spin correlations in a dissipative XXZ spin chain subject to uniform local spin-loss and pumping. Starting from a mixed steady state that is featureless albeit possessing finite magnetization, rich dynamics emerges in time-dependent two-point correlators evaluated on top of it. For unitary evolution in which the reservoir is absent, the longitudinal correlators reproduce the established hierarchy of spin-transport universality classes - ballistic, Kardar-Parisi-Zhang (KPZ) superdiffusive, and diffusive - across the phase diagram. However, for finite magnetization, additional ballistic light cone propagation gets superimposed on the previous universality classes, arising from magnon propagation.The transverse correlator displays very fast, exponential decay of correlations without wavefront propagation in the easy-plane case. At the isotropic point, it follows KPZ scaling due to $SU(2)$ symmetry, while in the easy-axis regime, it is characterized by ballistic spreading of correlations. Under full Lindbladian dynamics, the universality classes are preserved at early times, while the correlations acquire an overall exponential damping in the long-time limit. In terms of methods, we have used vectorized TEBD for numerical simulations and exact analytical results obtained via a Pfaffian representation and the third-quantization framework for the noninteracting XX case.

Engineering the dispersion relation is one of the key ingredients enabling the application of spin waves in computational elements. One way to engineer the spin-wave band structure is to create an artificial magnonic crystal, which can be used to design specific band gaps or dispersion branches. However, creating a two-dimensional magnonic crystal usually requires removing material, which dramatically decreases the decay lengths of spin waves. Here, we present a method to manipulate the demagnetizing field landscape by utilizing large-area curvilinear nanotemplates consisting of three-dimensional nanopyramids arranged in a square lattice with a period of 400 nm. In a 50-nm-thick Permalloy film grown on these curvilinear templates, we experimentally observe a complete in-plane band gap together with flat-band modes that exhibit strong real-space localization of the spin waves in the pyramid valleys. Micro-focused Brillouin light scattering measurements corroborate the numerically predicted dispersion and reveal the possibility of opening and closing this gap by varying the external magnetic field. Our results establish three-dimensional-templated continuous films as a versatile platform for two-dimensional signal processing and magnonic computing elements.

We prove several rigorous results about the asymptotic behaviour of the numbers of tadpoles (or lassos) embedded in a lattice, including cases where the head is subject to a constraint like being unknotted, or where the tail pierces the surface spanned by the head. Similar results can be proved for other homeomorphism types such as dumbbells, twin tailed tadpoles and two tailed tadpoles.

In this work we study driven $SU(2)$ Gross-Neveu (GN) model whose time-dependent interaction strength is constrained by quantum integrability within the recently developed generalized Bethe ansatz framework. Integrability requires the coupling strengths to evolve according to the same equation as the renormalization-group (RG) flow of the corresponding static theory, where time `$t$' of the time-dependent model is identified with the logarithm of the cutoff `$\ln \Lambda$' of the static model. We reformulate the exact quantum Knizhnik-Zamolodchikov (qKZ) solution in terms of a Yang-Yang functional, whose saddle-point equations determine the long-time dynamics of the system. In the scaling regime, this analysis reveals the emergence of a characteristic time scale $t_0$. In the case of coupling strength decreasing with time, we show that in the adiabatic regime, which corresponds to $t\sim t_0$ for drive rate $\alpha_0=1$, the system exhibits a dynamically generated time-dependent mass gap, which at time $t=t_0+\Delta t$ is given by $m(t)=m_0 e^{-\pi\alpha_0\Delta t}$, where $m_0=\Lambda e^{-\pi \alpha_0 t_0}$, which possesses the same functional dependence as the non-perturbatively generated mass scale of the static GN model. We thereby establish a time-dependent analogue of dynamical dimensional transmutation and identify the adiabatic regime of the driven system with the scaling regime of the static theory. In the case of very large time scales $t\gg t_0$ for drive rate $\alpha_0$ or for very fast drive rates $\alpha$ such that $\alpha t \gg \alpha_0t_0$, for any $t<L$, we argue that the system is asymptotically free and approaches the $SU(2)_1$ WZNW model, which corresponds to the UV fixed point of the $SU(2)$ GN model.