Papers

The stated overarching goal of the highly active field of quantum simulation of high-energy physics (HEP) is to achieve the capability to study ab-initio real-time microscopic dynamics of $3+1$D quantum chromodynamics (QCD). However, existing experimental realizations and theoretical proposals for future ones have remained restricted to one or two spatial dimensions. Here, we take a big step towards this goal by proposing a concrete experimentally feasible scalable cold-atom quantum simulator of a U$(1)$ quantum link model of quantum electrodynamics (QED) in three spatial dimensions, employing linear gauge protection to stabilize gauge invariance. Using tree tensor network simulations, we benchmark the performance of this quantum simulator through near- and far-from-equilibrium observables, showing excellent agreement with the ideal gauge theory. Additionally, we introduce a method for analog quantum error mitigation that accounts for unwanted first-order tunneling processes, vastly improving agreement between quantum-simulator and ideal-gauge-theory results. Our findings pave the way towards realistic quantum simulators of $3+1$D lattice gauge theories that can probe regimes well beyond classical simulability.

A description of the Kibble-Zurek mechanism with linear response theory has been done previously, but ad hoc hypotheses were used, like the use of the rate-dependent impulse window via the Zurek equation in the context of no driving in the relaxation time. In this work, I present a new framework where such hypotheses are unnecessary, preserving all the characteristics of the phenomenon. The Kibble-Zurek scaling obtained for the excess work is close to 2/5, a result that holds for open and thermally isolated systems whose relaxation time diverges at the critical point and the first zero of the relaxation function is finite. I exemplify the results using four different but significant types of scaling functions.

It is known that, for a range of chemical potentials, the infrared behavior of the complex Sachdev-Ye-Kitaev (cSYK) model is governed by a 1D Nearly Conformal Field Theory (NCFT$_{1}$), thereby realizing a continuous line of NCFTs. A finite chemical potential $\mu$ introduces an asymmetry parameter $\mathscr{E}$ into the cSYK fermion two-point function in the conformal limit. In this work, we compute the cSYK four-point function in the conformal limit for an arbitrary value of $\mathscr{E}$ at leading order in $1/N$. We show that the result is fully consistent with the NCFT$_{1}$ structure of the cSYK model and use it to extract the structure constants for correlation functions of two complex fermions with bilinear operators.

We explore the connection between evolution and large-deviation theory. To do so, we study evolutionary dynamics in which individuals experience mutations, reproduction, and selection using variants of the Moran model. We show that, in the large population size limit, the impact of reproduction and selection amounts to realizing a large-deviation dynamics for the non-interacting random walk in which individuals simply explore the genome landscape due to mutations. This mapping, which holds at all times, allows us to recast transitions in the population genome distribution as dynamical phase transitions, which can then be studied using the toolbox of large-deviation theory. Finally, we show that the mapping extends beyond the class of Moran models.

Framing anomaly is a key property of $(2+1)d$ chiral topological orders, for it reveals that the chirality is an intrinsic bulk property of the system, rather than a property of the boundary between two systems. Understanding framing anomaly in lattice models is particularly interesting, as concrete, solvable lattice models of chiral topological orders are rare. In a previous work, we defined and solved the $U(1)$ Chern-Simons-Maxwell theory on spacetime lattice, showing its chiral edge mode and the associated gravitational anomaly on boundary. In this work, we show its framing anomaly in the absence of boundary, by computing the expectation of a lattice version of the modular $T$ operator in the ground subspace on a spatial torus, from which we extract that $\langle T \rangle$ has a universal phase of $-2\pi/12$ as expected: $-2\pi/8$ from the Gauss-Milgram sum of the topological spins of the ground states, and $2\pi/24$ from the framing anomaly; we can also extract the $2\pi/24$ framing anomaly phase alone from the full spectrum of $T$ in the ground subspace by computing $\langle T^m \rangle$. This pins down the last and most crucial property required for a valid lattice definition of $U(1)$ Chern-Simons theory.

We consider the intrinsic fluctuation conductivity in metals with multiply sheeted Fermi surfaces approaching a superconducting critical point. Restricting our attention to extreme type-II multicomponent superconductors motivates focusing on the ultraclean limit. Using functional-integral techniques, we derive the Gaussian fluctuation action from which we obtain the gauge-invariant electromagnetic linear response kernel. This allows us to compute the optical conductivity tensor. We identify essential conditions required for a nonzero dissipative part of the longitudinal conductivity in a disorder-free and translationally invariant system. Specifically, this derives indirectly from the multicomponent character of the incipient superconducting order and the parent metallic state. Under these conditions, the enhancement of the DC conductivity due to fluctuations close to the critical point follows the same critical behavior as in the diffusive limit.

False vacuum decay, which is understood to happen through bubble nucleation, is a prominent phenomenon relevant to elementary particle physics and early-universe cosmology. Understanding its microscopic dynamics in higher spatial dimensions is currently a major challenge and research thrust. Recent advances in numerical techniques allow for the extraction of related signatures in tractable systems in two spatial dimensions over intermediate timescales. Here, we focus on the $2+1$D quantum Ising model, where a longitudinal field is used to energetically separate the two $\mathbb{Z}_2$ symmetry-broken ferromagnetic ground states, turning them into a “true” and “false” vacuum. Using tree tensor networks, we simulate the microscopic dynamics of a spin-down domain in a spin-up background after a homogeneous quench, with parameters chosen so that the domain corresponds to a bubble of the true vacuum in a false-vacuum background. Our study identifies how the ultimate fate of the bubble – indefinite expansion or collapse – depends on its geometrical features and on the microscopic parameters of the Ising Hamiltonian. We further provide a realistic quantum-simulation scheme, aimed at probing bubble dynamics on atomic Rydberg arrays.

We propose a Hamiltonian framework for constructing chiral gauge theories on the lattice based on symmetry disentanglers: constant-depth circuits of local unitaries that transform not-on-site symmetries into on-site ones. When chiral symmetry can be realized not-on-site and such a disentangler exists, the symmetry can be implemented in a strictly local Hamiltonian and gauged by standard lattice methods. Using lattice rotor models, we realize this idea in 1+1 and 3+1 spacetime dimensions for $U(1)$ symmetries with mixed 't Hooft anomalies, and show that symmetry disentanglers can be constructed when anomalies cancel. As an example, we present an exactly solvable Hamiltonian lattice model of the (1+1)-dimensional "3450" chiral gauge theory, and we argue that a related construction applies to the $U(1)$ hypercharge symmetry of the Standard Model fermions in 3+1 dimensions. Our results open a new route toward fully local, nonperturbative formulations of chiral gauge theories.

FeF$_2$ is a prototypical rutile antiferromagnet recently proposed as an altermagnet, with a magnetic symmetry that permits spin-split electronic bands and chiral magnons. Using very-high-resolution inelastic neutron scattering on a single crystal of FeF$_2$, we show that the dominant source of magnon splitting is in fact the long-range dipolar interaction rather than altermagnetic exchange terms. At momenta where the dipolar splitting vanishes, we observe additional broadening due to altermagnetic chiral splitting and estimate this splitting to be $\sim$35 $\mu$eV. Polarized measurements further reveal that, where dipolar splitting is present, the chiral magnon modes become mixed and the resulting modes are predominantly linearly polarized, with at most a small chiral component. These findings highlight the significant effect of dipolar interactions on magnon chirality, particularly when altermagnetic interactions are weak.

This work presents a pedagogical derivation of the thermodynamics of a van der Waals fluid by explicitly incorporating pairwise molecular interactions and the finite size of particles into the statistical-mechanical description. Starting from the Lennard-Jones potential, we evaluate the second virial coefficient to infer the virial expansion of the equation of state and recover the van der Waals equation using only its leading correction. The corresponding partition function allows us to obtain all thermodynamic potentials for both monoatomic and diatomic fluids in a transparent and instructive manner. Building on this framework, we formulate and solve analytically the Clausius-Clapeyron equation in the vicinity of the critical point, obtaining the liquid-vapor coexistence curve in closed form. This approach not only clarifies the microscopic origin of van der Waals thermodynamics but also complements-and in several aspects improves upon-traditional treatments that rely heavily on numerical methods or heuristic arguments. In addition, because the van der Waals equation naturally predicts the liquid-vapor equilibrium, the existence of critical points, and the functional form of the saturation curve of the pressure as a function of temperature, it provides an analytically tractable framework for studying a 150-year-old problem that has historically been addressed using graphical constructions or numerical solutions. As such, the formulation developed here offers a coherent, accessible, and conceptually unified route for students and instructors to understand phase coexistence in simple fluids from first principles.

To facilitate rational molecular and materials design, this research proposes an integrated computational framework that combines stochastic simulation, ab initio quantum chemistry, and molecular docking. The suggested workflow allows systematic investigation of structural stability, binding affinity, and electronic properties across biological and materials science domains by utilizing complementary tools like Avogadro for molecular construction and visualization, AutoDock for docking and interaction analysis, and ORCA for high-level electronic structure computations. Uncertainty, configurational sampling, and optimization in high-dimensional chemical spaces are addressed by combining Monte Carlo-based and annealing-inspired techniques. The work shows how materials science ideas such as polymer design, thin films, crystalline lattices, and bioelectronic systems can be applied to drug development. On-device, open-source computational methods are viable, scalable, and economical, as demonstrated by comparative platform analysis. All things considered, the findings highlight the need of an integrated, repeatable computational pipeline for speeding up de novo molecule assembly and materials architecture while lowering experimental risk and expense.

We develop a new approach to compress cyclic tensor networks called stochastic path compression (SPC) that uses an iterative importance sampling procedure to target edges with large bond-dimensions. Closed random walks in SPC form compression pathways that spatially localize large bond-dimensions in the tensor network. Analogous to the phase separation of two immiscible liquids, SPC separates the graph of bond-dimensions into spatially distinct high and low density regions. When combined with our integral decimation algorithm, SPC facilitates the accurate compression of cyclic tensor networks with continuous degrees of freedom. To benchmark and illustrate the methods, we compute the absolute thermodynamics of $q$-state clock models on two-dimensional square lattices and an XY model on a Watts-Strogatz graph, which is a small-world network with random connectivity between spins.

Motivated by the analogy between many-body localization (MBL) and single-particle Anderson localization on hierarchical graphs, we study localization on the Husimi tree, a generalization of the Bethe lattice with a finite density of local loops of arbitrary but finite length. The exact solution of the model provides a transparent and quantitative framework to systematically inspect the effect of loops on localization. Our analysis indicates that local loops enhance resonant processes, thereby reducing the critical disorder with increasing their number and size. At the same time, loops promote local hybridization, leading to an increase in the spatial extent of localized eigenstates. These effects reconcile key discrepancies between MBL phenomenology and its single-particle Anderson analog. These results show that local loops are a crucial structural ingredient for realistic single-particle analogies to many-body Hilbert spaces.

Latch-mediated Spring Actuation (LaMSA) is a mechanism found in nature, employed by organisms that generate the highest levels of power density through repeatable, rapid energy release. While LaMSA has been used in engineered systems like archery bows, catapults, and jumping robots, most such technologies require external power for self-repeating motion. Recent advances in soft actuators have demonstrated that engineered gels swollen with a volatile solvent are capable of self-repeating, high specific-power generation by taking advantage of balances between environmental interaction (evaporation) and elasticity. These systems rely upon snap-through instabilities. Due to the complex coupling between material properties and geometry, both of which evolve as self-repeating motion continues, an understanding of how polymer properties and boundary conditions control the lifetime, count, and magnitude of power generating events for a given amount of solvent remains unrealized. We overcome the challenges in characterizing the performance of evaporation-driven, power-generating gels by measuring accumulating force response from evaporation in parallel with the profile deformation of the structure. By optimizing the balance between swelling properties and elasticity, the lifetime of snapping is increased by 445% from previous literature, snapping at a maximum power density of about 87 W/kg. This power is achieved with swollen beams 50 mm in length after 53 mg of solvent had evaporated and is comparable to the power output of adult jumping mantises at 68 W/kg at a similar size scale.1 We develop scaling relationships that balance Flory-Rehner swelling theory with buckling mechanics to generate insight into optimizing lifetime and power of autonomous power-generating systems.

We investigate a driven particle system, a multilane asymmetric exclusion process, where the particle number in every lane is conserved, and stationary state is fully uncorrelated. The phase space has, starting from three lanes and more, an umbilic manifold where characteristic velocities of all the modes but one coincide, thus allowing us to study a weakly hyperbolic system with arbitrarily large degeneracy. We then study space-time fluctuations in the steady state, at the umbilic manifold, which are expected to exhibit universal scaling features. We formulate an effective mode-coupling theory (MCT) for the multilane model within the umbilic subspace and test its predictions. Unlike in the bidirectional two-lane model with an umbilic point studied earlier, here we find a robust $z=3/2$ dynamical exponent for the umbilic mode. The umbilic scaling function, obtained from Monte-Carlo simulations appears to have a universal shape for a range of interaction parameters and depends only on umbilic mode degeneracy. Remarkably, the shape and dynamic exponent of the non-degenerate mode can be analytically predicted on the base of effective MCT, up to non-universal scaling factor. Our findings suggest the existence of novel universality classes with dynamical exponent $3/2$, appearing in long-lived hydrodynamic modes with equal characteristic velocities.

We develop point-group equivariant neural networks for learning local mappings used in dynamical simulations of lattice systems. The same network acts on a finite neighborhood around each site, respecting lattice translations through shared parameters. The local configuration is decomposed into features that transform according to irreducible representations of the point group, and hidden features retain this organization throughout the network. Equivariant linear maps and symmetry-allowed tensor products then learn nonlinear spatial correlations while preserving the required transformation laws. This approach avoids constructing a fixed set of hand-crafted invariant descriptors, whose selection requires choices about which local correlations to retain. It also allows the complexity of the learned mapping to grow without enlarging its spatial cutoff. We demonstrate the construction by learning the forces governing adiabatic dynamics in the square-lattice Holstein model. Comparisons with exact diagonalization test the accuracy of the predicted forces and the evolution of spatial correlations. Force evaluation scales linearly with system size, allowing the trained model to simulate charge-density-wave ordering on large lattices. These simulations reproduce anomalously slow coarsening of the charge-density-wave domains, illustrating the use of the learned local mapping for collective dynamics.

We present experimental results on knotting in off-lattice self-avoiding polygons in the bead-chain model. Using Clisby's tree data structure and the scale-free pivot algorithm, for each $k$ between $10$ and $27$ we generated $2^{43-k}$ polygons of size $n=2^k$. Using a new knot diagram simplification and invariant-free knot classification code, we were able to determine the precise knot type of each polygon. The results show that the number of prime summands of knot type $K$ in a random $n$-gon is very well described by a Poisson distribution. We estimate the characteristic length of knotting as $656500 \pm 2500$. We use the count of summands for large $n$ to measure knotting rates and amplitude ratios of knot probabilities more accurately than previous experiments. Our calculations agree quite well with previous on-lattice computations, and support both knot localization and the knot entropy conjecture.

We report a study of the La$_{1-x}$Ce$_x$FeSiH solid solution ($0 \leq x \leq 1$), a family of intermetallic hydrides of ZrCuSiAs-type structure, with space group $P4/nmm$. For low cerium concentrations $x \leq 0.20$, we observe the presence of superconductivity, which originates from the correlated $3d$ electrons of iron. The superconducting regime is progressively suppressed by the cerium substitution. For moderate cerium concentration $0.07 \leq x \leq 0.50$, we observe evidence of the single-ion Kondo effect and no magnetic phase transition down to 2 K. For $0.07 \leq x \leq 0.20$, the single-ion Kondo effect coexists with a superconducting ground state at low temperatures. From $x > 0.50$, we observe signatures of Kondo coherence and a heavy Fermi liquid regime at low temperature. Finally, at high cerium concentration $x \geq 0.85$, we observe signatures of magnetic ordering at low temperatures. We discuss our results by introducing temperature scales related to superconductivity, the Kondo effect, and magnetic order, which permits building a rich phase diagram temperature versus cerium content $x$. This shows that using the cerium concentration $x$ as a unique control parameter, we can explore the Kondo entanglement between correlated $3d$ and $4f$ electrons, which suggests an unusual change between the superconducting state related to the $3d$ electrons and the Kondo coherent state involving both $3d$ and $4f$ electrons.

Aluminum (Al) remains the central material for superconducting qubits, and considerable effort has been devoted to optimizing its deposition and patterning for quantum devices. However, post-processing strategies focused on oxide removal of niobium (Nb) and tantalum (Ta) -based resonators using buffered oxide etch (BOE), which can not be used for Al. This challenge becomes particularly relevant for industry-scale fabrication with multi-chip bonding, where delays between sample preparation and cooldown require surface treatments that preserve low dielectric loss during extended exposure to ambient conditions. In this work, we investigate surface modification approaches for Al resonators subjected to a 24-hour delay prior to cryogenic measurement. Passivation using self-limiting oxygen and fluorine chemistries was evaluated utilizing different plasma processes. Remote oxygen plasma treatment reduced dielectric losses, in contrast to direct oxygen plasma. A fluorine-based plasma process was developed that passivated the Al surface for subsequent BOE treatment. However, the fluorine content in the surface resulted in higher loss, identifying fluorine as an unsuitable passivation material for Al resonators. Above all, selective oxide removal using HF (hydrogen fluoride) vapor and phosphoric acid yielded median dielectric losses as low as $\tilde{\delta}_\mathrm{LP} = 5.7 \times 10^{-7}$ ($Q_\mathrm{LP} \approx 1.7\,\mathrm{M}$) with $\tilde{\delta}_\mathrm{TLS} = 3.6 \times 10^{-7}$ ($Q_\mathrm{TLS} \approx 2.8\,\mathrm{M}$) in the single photon regime. Selective oxide removal provides a promising pathway for robust Al-based qubit fabrication, as it preserves low dielectric losses for a 24-hour delay before cooldown.

The magneto-optical properties of a Zn$_{0.99}$Mn$_{0.01}$Se/Be$_{0.93}$Mn$_{0.07} $Te diluted magnetic semiconductor heterostructure with type-II band alignment are investigated at cryogenic temperatures down to 16 mK. The temperature of the Mn spin system, which at the lowest possible laser power reaches 270 mK, is evaluated from the giant Zeeman splitting of the direct exciton in the Zn$_{0.99}$Mn$_{0.01}$Se layers subject to an external magnetic field. The degree of circular polarization of the direct and indirect optical transitions, induced by the magnetic field, is a sensitive indicator for the laser heating of the Mn spin system. Evidence of spin glass formation in the Mn spin system of the Be$_{0.93}$Mn$_{0.07}$Te layers with the critical temperature of $T_{SG}=400$ mK is found.

Controlling the chirality and yield of carbon nanotubes is essential for their diverse applications from macroscopic composites to nanoelectronics. Floating-catalyst chemical vapor deposition is widely employed as a scalable synthesis route, where catalysts inevitably traverse spatially varying environments. However, prevailing interpretations of nanotube growth largely rely on ensemble monitoring or static, post-growth snapshots. Here, we combine digital isotope labeling with programmed temperature modulation to reconstruct the dynamic growth histories of supported individual nanotubes. Growth rates exhibit hysteresis and extraordinary sensitivity to temperature changes, indicating irreversible catalyst coarsening; nevertheless, the nanotube chirality remains robustly preserved across lengths exceeding 300 um. This sharp contrast between kinetic adaptability and structural memory in nanotube growth indicates that chirality control can be established at the nucleation stage, while allowing independent optimization of subsequent elongation. Our findings further call for a re-examination of static interpretations of diameter-determination mechanisms derived from post-growth snapshots.

Two widely used model-free lower bounds on the steady-state entropy production rate of a continuous-time Markov jump process are the thermodynamic uncertainty relation (TUR) bound $\sigma_\text{TUR}$, derived from the mean and variance of a current, and the waiting-time distribution (WTD) bound $\sigma_\mathcal{L}$, derived from the irreversibility of partially observed transition sequences together with their waiting times. It has been conjectured that $\sigma_{\mathcal L}$ is always at least as tight as $\sigma_{\mathrm{TUR}}$ when both are constructed from the same partially observed link. Here we provide four-state counterexamples in a nonequilibrium steady state where $\sigma_{\mathcal L}<\sigma_{\mathrm{TUR}}$. This result shows that no universal ordering exists between these two inference bounds under partial observation.

This work derives the Navier–Stokes hydrodynamic equations for a model of a confined, quasi-two-dimensional, $s$-component mixture of inelastic, smooth, hard spheres. Using the inelastic version of the revised Enskog theory, macroscopic balance equations for mass, momentum, and energy are obtained, and constitutive equations for the fluxes are determined through a first-order Chapman–Enskog expansion. As for elastic collisions, the transport coefficients are given in terms of the solutions of a set of coupled linear integral equations. Approximate solutions to these equations for diffusion transport coefficients and shear viscosity are achieved by assuming steady-state conditions and considering leading terms in a Sonine polynomial expansion. These transport coefficients are expressed in terms of the coefficients of restitution, concentration, the masses and diameters of the mixture's components, and the system's density. The results apply to moderate densities and are not limited to particular values of the coefficients of restitution, concentration, mass, and/or diameter ratios. As an application, the thermal diffusion factor is evaluated to analyze segregation driven by temperature gradients and gravity, providing criteria that distinguish whether larger particles accumulate near the hotter or colder boundaries.

To reveal a microscopic mechanism for the anomalous minimization and dependence of the superfluid critical velocity on a moving obstacle potential in a atomic Bose-Einstein condensate [\href{https://link.aps.org/doi/10.1103/PhysRevA.91.053615}{Phys.~Rev.~A 91, 053615 (2015)}], we introduce a considerably simplified model of superflow along a step potential. The energy spectrum and wave functions of the lowest-energy excitations in this system are well described by the semi-classical analysis based on the Bogoliubov theory. We found that the critical velocity is minimized and becomes zero when the potential height equals the hydrostatic chemical potential, which corresponds to the critical point of the local condensation phase transition inside the step potential. In a finite-size system, the critical velocity $v_\mathrm{c}$ obeys a power-law scaling with the system size $L_x$ as $v_\mathrm{c}\propto L_x^{-0.963}$. This criticality provides an explanation of the power-law scaling of the minimum critical velocity observed in the experiment.

The development of plasmonics and related applications in the terahertz range faces limitations due to the intrinsic high electron density of standard metals. All-dielectric systems are profitable alternatives, which allows for customized modulation of the optical response upon doping. Here we focus on plasmon-based hyperbolic metamaterials realized stacking doped III-V semiconductors that have been shown to be optically active in the terahertz spectral region. By using a multi-physics multi-scale theoretical approach, we unravel the role of doping and geometrical characteristics (e.g., thickness, composition, grating) in the modulation of high-k plasmon-polariton modes across the metamaterial.

Coupled networks of mass-spring resonators have attracted growing attention across multiple fundamental and applied research directions, including reservoir computing for artificial intelligence. This has led to the exploration of platforms capable of tasks such as acoustic-wave classification, smart sensing, predictive maintenance, and adaptive vibration control. This work introduces a multiphysics reservoir based on a two-dimensional network of coupled nonlinear mass-spring resonators. Each mass has a magnetic tunnel junction on top of it, working as spin diode, used as a spintronic read-out. As a proof-of-concept, we have benchmarked this reservoir with the task of vowel-recognition reaching accuracy above 95$\%$. Because the device accepts elastic excitations directly, signal injections are simplified, making it well-suited for realtime sensing and edge computation. We also studied the effect of nonlinearity, demonstrating how it influences the reservoir dynamics, and assessed its robustness under node-to-node variation of the elastic constants.

Circuits based on superconducting nanostructures are among the most promising platforms for quantum computing. Understanding how device geometry governs nonlinear electrodynamics is crucial for implementing superconducting quantum technologies. However, to date, research has largely been limited to superconducting nanostructures with collinearly aligned static and dynamic applied magnetic fields. Here, we analyze the dynamics of Meissner currents and Abrikosov vortices in a superconducting nanocube exposed to combined static and microwave magnetic fields, extending the analysis to a more general excitation geometry. We demonstrate that, in a noncollinear configuration,the magnetization component parallel to the static field develops a dominant second-harmonic response under the microwave driving. This effect is strongly enhanced when Meissner currents saturate at static fields just below the thresholds for successive vortex nucleation. By numerically solving the time-dependent Ginzburg-Landau equations, we show that the response originates from Meissner-current saturation combined with the nonlinear oscillations of normal-phase indentations, yielding an anisotropic second-harmonic signal that is directionally separated from, and not overshadowed by, the first-harmonic component of the dynamic magnetization. These findings are relevant for superconducting devices that require controllable high-frequency nonlinearity.

Conveyor-mode shuttling in gated Si/SiGe devices enables adiabatic transfer of single electrons, electron patterns and spin qubits confined in quantum dots across several microns with a scalable number of signal lines. To realize their full potential, linear shuttle lanes must connect into a two-dimensional grid with controllable routing. We introduce a T-junction device linking two independently driven shuttle lanes. Electron routing across the junction requires no extra control lines beyond the four channels per conveyor belt. We measure an inter-lane charge transfer fidelity of $F = 100.0000000^{+0}_{-9\times 10^{-7}}\,\%$ at an instantaneous electron velocity of $270\,\mathrm{mm}\,\mathrm{s}^{-1}$. The filling of 54 quantum dots is controlled by simple atomic pulses, allowing us to swap electron patterns, laying the groundwork for a native spin-qubit SWAP gate. This T-junction establishes a path towards scalable, two-dimensional quantum computing architectures with flexible spin qubit routing for quantum error correction.

In this work, we propose a scheme to realize the layer Hall effect in the ferromagnetic topological insulator Bi$_2$Se$_3$ via proximity to $d$-wave altermagnets. We show that an altermagnet and an in-plane magnetic field applied near one surface gap the corresponding Dirac cone, yielding an altermagnet-induced half-quantized Hall effect. When altermagnets with antiparallel Néel vectors are placed near the top and bottom surfaces, giving rise to the layer Hall effect with vanishing net Hall conductance, i.e., the altermagnet-induced layer Hall effect. In contrast, altermagnets with parallel Néel vectors lead to a quantized Chern insulating state, i.e., the altermagnet-induced anomalous Hall effect. We further analyze the dependence of the Hall conductance on the orientation of the in-plane magnetic field and demonstrate that the layer Hall effect becomes observable under a perpendicular electric field. Our results establish a route to engineer altermagnet-induced topological phases in ferromagnetic topological insulators.

The discovery and design of new materials are paramount in the development of green technologies. High entropy oxides represent one such group that has only been tentatively explored, mainly due to the inherent problem of navigating vast compositional spaces. Thanks to the emergence of machine learning, however, suitable tools are now readily available. Here, the task of finding oxygen carriers for chemical looping processes has been tackled by leveraging active learning-based strategies combined with first-principles calculations. High efficiency and efficacy have, moreover, been achieved by exploiting the power of recently developed machine learning interatomic potentials. Firstly, the proposed approaches were validated based on an established computational framework for identifying high entropy perovskites that can be used in chemical looping air separation and dry reforming. Chief among the insights thus gained was the identification of the best performing strategies, in the form of greedy or Thompson-based sampling based on uncertainty estimates obtained from Gaussian processes. Building on this newfound knowledge, the concept was applied to a more complex problem, namely the discovery of high entropy oxygen carriers for chemical looping oxygen uncoupling. This resulted in both qualitative as well as quantitative outcomes, including lists of specific materials with high oxygen transfer capacities and configurational entropies. Specifically, the best candidates were based on the known oxygen carrier CaMnO3 but also contained a variety of additional species, of which some, e.g., Ti; Co; Cu; and Ti, were expected while others were not, e.g., Y and Sm. The results suggest that adopting active learning approaches is critical in materials discovery, given that these methods are already shifting research practice and soon will be the norm.