Papers

Geometric analysis of electronic Bloch states offers a universal framework for understanding electronic properties, yet its role in the transport of orbital angular momentum remains unexplored. In this work, we establish an analytic connection between orbital angular momentum transport and the geometric properties of Bloch wave functions in electronic systems. Focusing on the intrinsic orbital Hall effect in the dc limit under a spatially nonuniform electric field, we show that its conductivity can be expressed in terms of universal geometric quantities, such as the orbital Berry curvature and quantum metric. This formulation provides a term-by-term correspondence with the geometric description of intrinsic charge Hall transport established in previous studies. Using a tight-binding model, we further illustrate that the higher-order orbital Hall response can exhibit enhanced sensitivity to the orientation of an anisotropic sample. Our work deepens the understanding of diverse intrinsic transverse transport phenomena and the role of quantum geometry in electronic systems.

The Hamiltonian-Adaptive Resolution Simulation (H-AdResS) method allows to combine atomistic and particle-based coarse-grained models in a single simulation box, which makes it very attractive to model systems containing interfaces or reactive regions surrounded by an interacting environment. In our previous work [J. Chem. Inf. Model. (2026) 66 (15): 9215-9225], we implemented H-AdResS in LAMMPS (2 Aug 2023 version) and extended its use to interfaces, focusing on MOF/CO$_2$ interfaces as an example. We found that, despite its advantages, using this method properly for this kind of systems is not trivial. In this work, an in-depth analysis of the impact of the choice of thermostatting schemes and long-range electrostatics models is presented. Even though its Hamiltonian formulation enables performing H-AdResS simulations within constant temperatures ensembles, not every thermostat is appropriate. We demonstrate that Langevin thermostat is a reliable choice for this method, while Nosé-Hoover results in artifacts. In addition, we show that using short-range models such as the Damped Shifted Force method for electrostatics, a popular choice for H-AdResS simulations, can lead to non-physical results when modeling interfaces. The need of capping strategies to deal with discontinuities in forces and energies arising from abrupt changes in resolution is also discussed. Finally, the impossibility of changing the definition of the H-AdResS Hamiltonian to include a gradual interpolation of the bonded degrees of freedom is discussed. We hope that this contribution helps the reader to appropriately set up H-AdResS simulations and to assess if this method can be used to accurately model their system of interest.

Here we describe the quantum gas analysis and inference (Q-GAIN) Python package, which enables rapid deployment of machine learning (ML) and physics-informed analysis techniques for cold-atom experiments. Out of the box, Q-GAIN implements classification, object detection, and physics-informed metrics for feature detection in images of atomic Bose-Einstein condensates (BECs). Q-GAIN encourages a natural, module-based workflow: starting with data loading and preprocessing, followed by ML-based feature identification, and ending with conventional analysis techniques. We demonstrate this modularity by configuring Q-GAIN for three ML tasks. First, we demonstrate the basic workflow of the Q-GAIN framework by implementing the standard task of classifying handwritten digits from the MNIST dataset. Then, we re-implement our earlier soliton detection (SolDet) package in the Q-GAIN framework, enabling the detection and analysis of solitonic excitations in time-of-flight data. Finally, we develop an object-detection tool that identifies quantized vortices in images of ring-shaped BECs.

Helical spin textures represent the minimal realization of $p$-wave magnetism which is characterized by momentum-odd spin polarization. Independently, structurally chiral crystals exhibit momentum-odd orbital polarization arising from broken inversion symmetry. Here, we demonstrate that spin-orbit coupling couples these two independent microscopic chirality degrees of freedom, allowing the orbital polarization of a chiral crystal to generate an additional contribution to the $p$-wave spin splitting. The resulting spin-orbital state is naturally classified by the relative chirality $\eta=\chi_{\mathrm c}\chi_{\mathrm m}$, giving rise to two symmetry-distinct $p$-wave phases corresponding to homochiral and heterochiral configurations which can be directly probed by the longitudinal conductivity. These phases exhibit distinct transport signatures, establishing a unified framework linking orbitronics and unconventional magnetism through coupled spin-orbital $p$-wave order.

We study the nonequilibrium dynamics following a quantum quench in spin chains that can be solved via a mapping to free fermions in disguise. These models feature an exponential degeneracy of all energy eigenvalues, raising the question of the validity of the established framework describing the properties of integrable systems out of equilibrium. We present two main results. First, we develop an analytic method to compute the quasi-momentum distribution function characterizing the generalized Gibbs ensemble, and derive an analytic formula to compute the corresponding expectation values for special observables. Second, we adapt the standard formula for the entanglement growth based on the quasi-particle picture, discussing how our constructions do not explicitly make use of the zero-energy auxiliary free fermions responsible of the exponential degeneracies. We test our theoretical predictions against numerical tensor-network computations for different initial states and Hamiltonian parameters. For the local observables, we find excellent agreement. For the entanglement dynamics, we find small deviations suggesting that the standard quasi-particle picture is only approximately correct for the initial state considered. Our results represent a first step towards the extension of the established framework of integrable systems out of equilibrium to models hosting free fermions in disguise.

I revisit the Galam Majority Model (GMM) with contrarian agents from a statistical-mechanics perspective, revealing three fundamental features. First, in addition to the GMM simultaneous-update of small discussion groups, I construct a related single-agent stochastic dynamics, providing a Markovian microscopic representation, which is found to yield the same evolution equation. Second, I show that, contrary to what is often stated in the literature, the GMM closed evolution equation for the opinion density is not the result of a mean-field approximation. Indeed, I derive the conventional mean-field dynamics associated with majority-rule interactions and show that it yields a distinct, probabilistic evolution equation contrary the deterministic GMM equation. I therefore identify the GMM as an iterated mean-field dynamics. Third, I investigate the thermodynamic nature of the dynamics obtained from both single-agent and simultaneous updates. Both are shown to violate detailed balance. However, while Kolmogorov's cycle condition is satisfied for single-agent updates, it is violated for simultaneous updates, making the departure from equilibrium stronger in the latter case. I then compute the probability flux in the stationary state and show that it is non-vanishing, confirming the absence of an effective Hamiltonian and establishing that the stationary state is a genuine nonequilibrium steady state.These results clarify the statistical-mechanical foundations of the GMM and establish contrarian majority dynamics as an intrinsically non-equilibrium process with distinct regimes of irreversibility. Contrarians are not thermal noise.

We study mesoscopic linear spectral statistics for two ensembles of random quantum graphs. These are defined by a discrete graph $G$ and a unitary-matrix-valued function $U(k)$ indexed by directed edges of $G$. The matrix function $U(k)$ is constructed from unitary matrices $U^{(v)}$ indexed by the neighbours of each vertex $v$. The first ensemble is obtained by sampling the underlying discrete graph uniformly from the set of $d$-regular graphs. The second ensemble is obtained by sampling $U^{(v)}$ uniformly from the Haar measure, independently for each vertex. We prove that the variance of a linear spectral statistic in the large graph limit on polynomial mesoscopic scales coincides with that of the Gaussian Orthogonal/Unitary Ensemble.

Autonomous-research agents have demonstrated end-to-end LLM automation in machine-learning sandboxes where execution provides calibration. Frontier physical science differs categorically: physical reasoning underlies every methodology choice, toolchains are often underdocumented, and calibration must come from external literature anchors - which unscaffolded agents cite but do not confront, hallucinating plausible, unverifiable results from internal priors. We present a pipeline that runs end-to-end from a corpus of 11,083 recent condensed-matter physics arXiv papers to a publication-grade manuscript with three substantive physics findings (here on altermagnetic piezomagnetism): the agent autonomously conceives a research direction by mapping the corpus, calibrates methodology by reproducing published references, conducts novel first-principles computations, and writes the manuscript - grounded in literature throughout, across 47 fresh-context sessions in six phases sharing only on-disk state, with 2,162 literature-consultation events. Fault tolerance emerges from redundancy: fresh-context isolation, distributed grounding, and adversarial review catch what any single session misses; pre- and post-pilot stages are fully autonomous, and pilot requires bounded human intervention only at reproduction failures - operational knowledge curation, not scientific direction. Two paired failure modes - a pre-architecture baseline and a no-pilot ablation - isolate structurally enforced numerical confrontation at calibration checkpoints as the operative grounding mechanism. The primitives, characterized failure modes, and quantified intervention pattern lay a foundation for autonomous research in high-stakes scientific domains beyond computational physics.

We show that topological invariants constructed from single-particle Green's functions (GFs) cannot reliably diagnose the topology of interacting many-body states. Using coupled interacting SSH chains as a minimal example, we demonstrate that a spin-spin interaction can trivialize the many-body ground state without affecting the GF topological invariant. This breakdown originates from the GF's inability to probe electronic excitations in the Fock sectors responsible for the topological degeneracy. Consequently, GF zeroes are not associated with physical topological quasiparticles and cannot generally characterize interacting topological phases.

Universality is one of the central organising principles of modern physics, explaining why systems with vastly different microscopic constituents can exhibit identical large-scale behaviour. While the classification of equilibrium critical phenomena through hydrodynamics and the renormalization group (RG) is now well established, our understanding of universality far from equilibrium remains far less developed. In recent years, however, rapid progress - driven in large part by developments in active and living matter - has uncovered a growing range of genuinely nonequilibrium universality classes (UCs) with no equilibrium counterparts. In this review, we present a pedagogical and unified introduction to hydrodynamic and RG approaches to nonequilibrium many-body systems. We first show how hydrodynamic theories can be systematically constructed from symmetry and conservation laws alone. We then introduce perturbative dynamic RG methods and demonstrate how hydrodynamic theories are organised into distinct UCs according to their scaling behaviour. Building on these foundations, we review the diverse nonequilibrium UCs uncovered since 2015, while emphasizing the conceptual connections and unifying physical principles underlying their emergence. We conclude by discussing open theoretical and experimental challenges for the field.

Electrochemical impedance spectroscopy (EIS) is a widely used technique to understand time-dependent response and relaxation under applied voltage. While these spectra contain a wealth of information, major gaps in our understanding can hinder our ability to interpret EIS spectra in terms of microscopic chemical mechanisms. We propose an alternative approach to common empirical fitting procedures for describing the contribution of the bulk electrolyte to the EIS spectrum. This new approach is rooted in determining the moments of the frequency-dependent conductivity, with molecular interpretability provided by a generalized Langevin equation description of an effective single particle dynamics; the `itinerant oscillator' (IO) model. In contrast to a Debye–Falkenhagen description, the IO model makes no assumptions regarding the concentration of the electrolyte, a fact we demonstrate by analysing molecular dynamics simulations of a room-temperature ionic liquid. By analysing the memory function from simulation within the framework provided by the IO model, we reveal the importance of capturing the separation of timescales within the memory function for describing the temperature dependent $\beta$-relaxation process. We go on to show how our impedance model directly reports on this distribution of timescales while retaining the simplicity of commonly employed workflows.

We study Poiseuille flow of a one-component fluid between adiabatic plates in liquid-gas coexistence with a stationary interface. Using only bulk transport laws and particle and energy conservation, we identify small dimensionless parameters $A^\mathrm{L}$ and $A^\mathrm{G}$ governed by squared microscopic-to-macroscopic length ratios. In weak driving with macroscopic bulk regions and a regular interfacial temperature response, the pressure drop is concentrated across the interface, strongly suppressing the particle current. For equal-temperature reservoirs, the residual current produces interfacial cooling. Experimental feasibility is also discussed.

Neural quantum states (NQS) provide a flexible and scalable framework for approximating quantum many-body wavefunctions. Among NQS parameterizations, autoregressive models are especially attractive because they enable exact, independent sampling from the Born distribution, avoiding the autocorrelation and mixing issues of Markov chain methods. Yet their optimization remains comparatively underexplored: Adam is a scalable method but ignores function space geometry, while stochastic reconfiguration is principled but costly and numerically fragile in large models. To address this gap, we show that variational energy minimization can be viewed as an advantage policy-gradient problem over the Born distribution, motivating trust-region optimization for NQS training. We introduce Proximal Wavefunction Optimization (PWO), a principled trust-region algorithm that clips probability-ratio changes in the amplitude channel and phase increments in the phase channel. PWO avoids explicit matrix inversion, reuses samples across multiple updates, and combines the scalability of first-order optimization with theoretical guarantees. Across Ising and frustrated $J_1$-$J_2$ one- and two-dimensional spin systems, PWO improves stability and wall-clock convergence over Adam, minSR, and SPRING. Finally, we fine-tune a $1.5$B-parameter RWKV-7 model, demonstrating NQS optimization at a scale over three orders of magnitude beyond prior work.

We derive a general relation between the velocity and force autocorrelation tensors (VACT and FACT) for a Brownian particle subject to an external magnetic field. Using time-symmetry arguments, we show that, for the full Langevin dynamics, the VACT depends only on the FACT, independently of the details of the interaction potential. Under the hypothesis of timescale separation between thermalization and interaction-driven motion, this relation simplifies considerably in the overdamped (Brownian) limit. A central feature of the overdamped result is that, unlike in the field-free case, the part of the VACT that controls the self-diffusion of the particle couples to the antisymmetric part of the FACT, with a coupling strength set by the ratio of the cyclotron frequency to the thermalization rate. We validate and illustrate the formalism on an exactly solvable model: a dimer of charged particles bound by a harmonic potential. Depending on the relative sign of the particle charges, the magnetic field is found to produce either a transient suppression of mobility and diffusion that is fully recovered at long times, or a persistent oscillatory force autocorrelation, regions of negative mobility, and a long-time suppression of self-diffusion.

Braiding phenomena, from the charge-flux Aharonov-Bohm effect to anyonic statistics in fractional quantum Hall systems, are paradigmatic manifestations of topology in quantum physics. Ordinary mutual braiding between $p$- and $q$-dimensional excitations occurs in $d=p+q+2$ spatial dimensions. In this work, we introduce a universal construction of mutual statistics in the adjacent dimension $d=p+q+1$, applicable to excitations obeying $\mathbb Z_N$ fusion for arbitrary $N$ and all excitation dimensions $p$ and $q$. The corresponding invariant is the Berry phase accumulated in a simple $4N$-step microscopic unitary process built from local excitation operators on lattices. This process measures the linking of one excitation with the $N$-fold fusion junction of the other, encompassing particle-particle statistics in one dimension, particle-loop statistics in two dimensions, and loop-loop or particle-membrane statistics in three dimensions. We establish the quantization and bilinearity of the invariant and show that its field-theory response is governed by the Bockstein homomorphism, motivating the name Bockstein braiding statistics. Interpreting the excitation operators as open symmetry operators turns the same invariant into a direct microscopic diagnostic of mixed anomalies between symmetries. We demonstrate this diagnostic in a (1+1)D spin chain, where the nontrivial Bockstein braiding phase proves the mixed anomaly between the spin-flip symmetry $\prod X$ and the nearest-neighbor controlled-$Z$ symmetry $\prod CZ$. We construct explicit (2+1)D and (3+1)D lattice analogs, yielding new anomalous symmetry pairs, and apply the framework to strongly coupled (3+1)D continuum gauge theories. Nontrivial Bockstein braiding rules out a fully symmetric gapped phase, obstructs simultaneous condensation of the two excitations, and implies fractionalization of higher-form symmetries.

The interplay between disorder, gauge fields, and internal degrees of freedom fundamentally affects localization and topological properties of quantum many-body systems. Motivated by recent experimental realizations of synthetic non-Abelian gauge fields for SU(3) colored fermions, we investigate their localization and topological properties in 1D bichromatic optical lattices consisting of strong and weak laser beams. Describing the non-Abelian gauge field via color-orbit coupling and color-flip (Rabi) fields, we obtain a tight-binding description of trapped SU(3) colored fermions corresponding to a generalized three-color Aubry-André model. We show that these fields explicitly break the conventional self-duality of a simple three-color Aubry-André system. This duality breaking generates mobility regions across the energy spectrum, demonstrating that non-Abelian fields can either enhance or hinder color localization. Using exact diagonalization, density-of-states evaluations, and finite-size scaling of the inverse participation ratio, we obtain phase diagrams that identify regions of extended or localized bulk states. Furthermore, the color-orbit and Rabi fields induce edge states with topological properties. We develop an exact mapping from our 1D disorder model into a 2D color Harper model with a fictitious magnetic flux ratio and dimension controlled by the weak laser beam's phase. Using this mapping, we evaluate topological invariants, such as the charge-charge Chern number, for edge states emerging in energy gaps, revealing the topological insulating nature of several gapped phases. Lastly, we identify that these topological color-insulator phases can energetically neighbor three configurations: two extended, two localized, or one of each. This sharply contrasts with conventional topological insulators, which always neighbor two extended phases.

If a generalized Langevin equation contains a potential of mean force, it cannot at the same time contain a linear memory kernel and a fluctuating force that obeys a second fluctuation dissipation theorem in the sense of Kubo, and be exact. As modelers often prefer to use generalized Langevin equations that have the first three properties, one needs to ask how close the model dynamics is to the dynamics of the underlying microscopic system. To test this, we analyze a simple model system in which the potential of mean force can be well approximated by a polynomial of low order. The exact generalized Langevin equation of this model contains memory terms in addition to the linear one. We show that these additional terms, at least for the model system regarded in this article, are important for the dynamics and cannot be neglected if one intends to model core aspects of the underlying system correctly.

Correlated phases of matter are typically investigated in crystalline systems, where disorder is considered to be detrimental. However, intriguing exceptions exist, such as superconductivity being enhanced in amorphous realizations of Al and Bi. Here, we demonstrate that superconductivity can even emerge entirely from disorder, using monolayer graphene as an example. In the clean limit, the semi-metallic nature of graphene requires prohibitively strong electronic interactions to achieve superconductivity. Despite the inherently random nature of disorder, we show that introducing low concentrations of vacancies or hydrogenation in graphene provides a large density of low-energy states that easily induce superconductivity. For conventional $s$-wave pairing, disorder induces a finite superconducting order parameter for arbitrarily weak attractive interactions. Rather than forming isolated superconducting puddles, global phase coherence is established through a finite superfluid weight of purely geometrical origin. Away from the chiral limit of vacancies, hydrogenation similarly yields a finite transition temperature and nonzero superfluid weight for weak interactions. For unconventional nearest-neighbor pairing, typically more disrupted by disorder, superconductivity exhibits quantum-critical-like behavior, yet phase coherence persists at low interaction strengths, with mixed $d$-wave symmetries. Our work demonstrates the robust emergence of macroscopic superconducting phase coherence engineered entirely from microscopic disorder.

We analyze particle and spin currents in networks of coupled spinor exciton-polariton condensates arranged as plaquettes and regular polygonal rings. In closed geometries, spin-conserving and TE-TM-induced spin-flip tunnelling combine to generate circulating particle currents, hidden spin counterflows, and bond-dependent spin-current patterns. For the minimal geometries - an equilateral triangle, and a square plaquette - we derive analytical expressions for edge-resolved currents from stationary configurations obtained by energy minimization. We then show how particle, in-plane spin, and out-of-plane spin currents partition the parameter plane and provide direct signatures of the equilibrium phases. Finally, we apply the same current-resolved diagnostics to larger rings, where winding numbers and a branch-invariant common-phase coherence metric organize the resulting phase structure.

Quantum networks require qubits that combine efficient optical access, coherent control, and long-lived quantum memory, but realizing all three in one scalable platform remains a central bottleneck. Diamond color centers are leading candidates, yet widely studied defects retain tradeoffs among these capabilities. Here, we show that transition-metal defects in diamond provide a distinct route beyond these platforms by combining spin-orbit protected ground-state coherence, all-optical control, and near-infrared emission. Using a single nickel-vacancy (NiV$^-$), we demonstrate an all-optically controlled diamond spin qubit with coherence exceeding one millisecond at 1.65 K, compatible with compact closed-cycle cryogenics. We implement Raman Rabi oscillations and Ramsey interferometry and use all-optical dynamical decoupling to extend coherence from $T_2^*$ = 371 ns to $T_2^{CPMG-4}$ = 1.27 ms, establishing NiV$^-$ as a deployable diamond spin-photon interface.

We report an experimental investigation of the depth-dependent domain wall formation in L1$_0$-FePd thin films with high perpendicular magnetic anisotropy. Using circular dichroism X-ray resonant magnetic scattering (CD-XRMS) as a function of the incident X-ray angle, we explore the depth evolution of chiral spin textures in two samples with different strengths of magnetocrystalline anisotropy. Combined with CD-STXM, CD-ptychography, and macroscopic characterization of the structural order, magnetic properties, and surface morphology, we relate these observations to differences in the long-range order of the L1$_0$ phase of FePd. One FePd thin film with very high magnetocrystalline anisotropy, characterized by $Q_{PMA}=1.8$, exhibits an unexpectedly large Néel contribution. Angular-dependent CD-XRMS directly reveals a smooth transition from a hybrid Bloch-Néel chirality within the upper FePd layer towards a purely Néel-type structure at the lower FePd interface. In the second FePd sample, despite a still relatively large $Q_{PMA}=1.45$, the domain walls were found to be purely Néel type. These results indicate a crucial role of the long-range structural order in determining the formation of the magnetic structure.

Single-molecule (SM) rotational dynamics of fluorescent probes in polystyrene near the glass transition temperature ($T_g$) are investigated over long times to reconstruct susceptibility spectra. The loss spectrum, commonly recorded using external field-driven (frequency-domain) spectroscopy, such as dielectric spectroscopy, is reconstructed from purely thermal SM rotational fluctuations. The results reproduce time-temperature superposition typically seen in dielectric spectroscopy for materials near $T_g$ and show that the ensemble spectrum is comprised of individual molecular responses to distinct environments.

Fermionic non-Gaussianity, or fermionic magic, is a key resource underlying the computational complexity of fermionic quantum systems, yet tractable and operationally meaningful ways to quantify it remain limited. We address this challenge by developing a convex resource theory of fermionic non-Gaussianity and introducing two families of computable quantities for pure fermionic states, both derived from the Williamson normal form of the covariance matrix. The first family, occupation number entropies, is defined as the Tsallis-$\alpha$ entropy of the occupation numbers. We prove that one member of this family is monotonic under Gaussian protocols, establishing it as a computable convex resource monotone. It consequently lower bounds the number of non-Gaussian gates needed for state preparation. The second family, natural-orbital participation entropies, is given by the Rényi-$\alpha$ entropy of the squared amplitudes of the state in the natural-orbital basis, defined by the eigenvectors of the covariance matrix. They quantify state compressibility in this basis and thus upper bound the classical simulation cost in an orthonormal Gaussian basis. We analyze both families for stabilizer and translation-invariant states, where they simplify and reveal additional structure. We further study representative examples, including random SWAP-doped matchgate circuits and the bond-modulated XXZ model, highlighting the role of non-Gaussianity in many-body phenomena. Our work establishes a resource-theoretic framework for computable fermionic non-Gaussianity that unifies notions arising across quantum information, condensed-matter physics, and quantum chemistry, opening new directions for studying the complexity of quantum many-body systems and providing practical tools to assess the classical simulability of fermionic states relevant for quantum advantage.

Tantalum (Ta) is a promising material for reaching long coherence times in superconducting qubits. A detailed understanding of the underlying structure-property relationship remains elusive though. In the present study, we sputter-deposited 200 nm thick Ta films on high-resistivity silicon (100) substrates at temperatures ranging from T = 20{\deg}C to 600{\deg}C, as well as on different seed layers (Nb, TiN and TaN). Alpha-Ta thin films were readily obtained at temperatures above 500{\deg}C and on all seed layers. The films were characterized in terms of surface morphology, residual-resistance ratio, crystal phase composition and superconducting transition temperature, as well as RF-performance using coplanar waveguide resonators. Internal quality factors of up to 1.5 million were measured at 100 mK in the single-photon regime. Despite similar bulk material properties, alpha-Ta films on different seed layers exhibit markedly different RF-performance, which we attribute to dissimilar strain and structural defects at the substrate-metal interfaces. Williamson-Hall analysis of XRD data reveals a clear correlation between decreasing microstrain and increasing quality factor. Cross-sectional HR-TEM further supports this interpretation by directly resolving interfacial disorder. Our results highlight the critical role of interface engineering in optimizing superconducting thin films for low-loss quantum computing circuitry.

The time auto-correlation of auxiliary wave functions (TACAW) method enables efficient simulations of ultra-low-loss electron energy loss spectra (EELS) arising from vibrational and magnon excitations. In practical applications to realistic materials systems, however, TACAW calculations become challenging due to the large system sizes required for models containing defects, interfaces, impurities, or grain boundaries, as well as the substantial computational cost and data throughput associated with molecular dynamics and multislice calculations. Here we discuss a practical methodology for large-scale TACAW simulations and present torched-TACAW, a freely available implementation of the TACAW part of the described workflow for efficient STEM-EELS simulations. The overall approach combines molecular dynamics based on foundational machine-learned interatomic potentials, partitioning of elongated supercells, and on-the-fly processing of multislice outputs in order to enable near ab initio quality simulations with tractable memory use and data flow. Using rutile TiO2 as a model system, we analyze important numerical aspects of the method, including windowing and supercell partitioning, and demonstrate atomic-resolution STEM-EELS simulations for thick samples.

For ultrafast magnetization switching devices, critical slowing down in conventional ferromagnets near their Curie temperature constitutes a key challenge that must be overcome. In contrast to this typical behavior, we observe an anomalous acceleration of demagnetization in CaRuO$_{3}$/SrTiO$_{3}$ superlattices, a moderately correlated weak itinerant ferromagnet. The demagnetization rate increases with rising temperature, pump fluence, and applied magnetic field. To explain these anomalous phenomena, we develop a phenomenological model integrating the three-temperature model with self-consistent renormalization theory. Because the intrinsic gradient magnetism of the superlattice suppresses the typical divergence of specific heat, the conventional thermodynamic bottleneck is bypassed. Our model reveals that this decoupling enables the ultrafast dynamics to be predominantly governed by the spin-fluctuation-driven enhancement of the electron-spin scattering vertex. Our work demonstrates how spatial inhomogeneity can decouple macroscopic thermodynamic singularities from microscopic scattering processes, offering a new paradigm for manipulating ultrafast spin dynamics in correlated quantum materials. The pronounced sensitivity of the demagnetization rate to external parameters further suggests the potential for designing highly tunable ultrafast spintronic devices that leverage enhanced fluctuations near the magnetic instability.

Remarkably common statistical laws characterize the diversity scaling and its fluctuations across a wide range of complex "component systems". These regularities are often interpreted as signatures of an underlying innovation mechanism driving the growth of component diversity, but the basic ingredients necessary for their emergence remain poorly understood. In particular, from language and technological artifacts to genomes and gene expression patterns, the number of distinct components grows sublinearly with system size, while its variance scales approximately as the square of its mean. This behavior is consistent across diverse systems, raising the question of whether general constraints or emergent principles underlying diversity and innovation define the architectures of realizations with different numbers of components. To address this question, we derive analytical conditions for the joint emergence of these two diversity laws within a broad class of growth models, showing that they require a specific asymptotic dependence of the innovation probability on diversity and system size. We then demonstrate that the same macroscopic laws arise in a different class of models with latent heterogeneity, where quadratic fluctuation scaling always emerges asymptotically as a consequence of general statistical principles, essentially the law of total variance, without explicitly assuming an innovation mechanism or any specific rule for system assembly. We compare these predictions with empirical data from language, genomes, LEGO constructions, and texts generated by large language models. Our results show that empirical diversity scaling laws strongly constrain generative models but do not uniquely identify the mechanisms generating diversity, revealing a close correspondence between innovation-driven growth models and latent-variable descriptions.

Short-range order (SRO) governs the mechanical response of multi-principal-element alloys, but designing an alloy for a target property usually means solving two disconnected problems: building a structure matching a desired SRO pattern, then separately checking its property, with no shared optimization. This work replaces the standard random-swap search (reverse Monte Carlo) with a gradient-based approach: atom occupancy is treated as continuous rather than fixed, so the whole process can be tuned using gradient descent, the same method used to train neural networks. This builder matches random-swap accuracy on small systems, but is six times faster and eight times more accurate on large 4000-atom systems, and scales smoothly to alloys with many elements without extra bookkeeping. A physics-based correction term, adapted from prior two-element work and extended here to many elements, keeps designed structures thermodynamically realistic rather than just numerically matching the target SRO pattern. A small neural network then predicts mechanical properties directly from composition and SRO statistics, closing the loop from target property back to structure. Tested on nine face-centered-cubic and body-centered-cubic alloys, the pipeline captured SRO-driven stiffness changes from -20% to +57%, and cell-size checks showed at least 864 atoms are needed to get the direction and size of these changes right, since the commonly used 108-atom cells can mislead. Against real simulations for a cobalt-chromium-nickel alloy, the method matched three of four target stiffness values within 6%. The method is released as an open-source Python package, anisro, offering a practical route to gradient-based, property-driven alloy design.

It has been known for several decades that the third moment of the multifractal spectrum of the harmonic measure for diffusion-limited aggregates is linked to the underlying fractal dimension of the cluster. We demonstrate, using an argument based on the Hastings-Levitov formulation of diffusion-limited aggregation (DLA) in two dimensions, an even stronger link, connecting the universal amplitude of the third moment to the cluster fractal dimension. This argument can be used for both the standard circular DLA as well as DLA in a cylinder (i.e., with periodic boundary conditions); in the latter case the relationship of the amplitude to the fractal dimension is weaker, and must be extracted via a scaling analysis.

Non-Abelian anyons emerging in fractional quantum Hall states carry a characteristic entropy, $\Delta S = k_B \log d$, where $d$ is the anyon's quantum dimension. This $\mathcal{O}(1)$ entropy can, in principle, be extracted from charge measurements of an antidot via Maxwell relations. However, equilibrium charge measurements in fractional antidots have proven to be challenging with conventional charge detectors. Here, we propose a scheme based on an antidot embedded in an interferometer, in which the charge can be inferred from the recently observed time-dependent switching of the interference phase. Performing such non-local charge measurements at equilibrium, the characteristic $\mathcal{O}(1)$ entropy of non-Abelian anyons (e.g., $d = \sqrt{2}$ for the $\nu = 5/2$ state) can be extracted for intermediate temperatures, which exceed the level spacing of the interferometer edge, but are much smaller than the level spacing of the antidot.