Superlattice engineering, the introduction of periodic potentials to a material, can induce selective scattering events that modify the electrical properties of the material in predictable ways. Extending superlattice engineering to three-dimensional (3D) electronic materials can expand the tunability of their transport properties beyond traditional means such as doping. Here, we show that magnetotransport can be modified by superlattices in 3D materials based on the relative symmetry between the Fermi surface and nanostructured superlattice. We demonstrate commensuration oscillations in the ballistic transport regime of a nanostructured 3D material with the Weyl semimetal NbP. The oscillations encode information about the shared properties between the quasiparticles at the Fermi surface—including their momentum, charge, mass, and rotational symmetry—and the structure of the superlattice. These results point toward methods to engineer quantum transport in 3D electronic materials based on the mutual properties of the superlattice and Fermi surface.

The non-Hermitian skin effect (NHSE), characterized by the accumulation of a macroscopic number of bulk states at system boundaries, is a hallmark of non-Hermitian physics. However, in higher dimensions, achieving deterministic control over where skin modes accumulate remains a major challenge. Here, we propose a versatile route to program the skin-mode localization site in two-dimensional non-Hermitian lattices by combining disorder with a static electric field. While the electric field alone suppresses the NHSE in a clean system, the introduction of disorder induces transverse wave-packet transport perpendicular to the field. In nonreciprocal lattices, when the nonreciprocal hopping is misaligned with the electric field, the hopping component perpendicular to the field guides wave-packet propagation and produces boundary localization. By tuning the relative orientation between the electric field and the nonreciprocal hopping direction, the boundary localization position can be continuously and arbitrarily controlled. We further demonstrate distinct geometry-dependent manipulation of skin modes in reciprocal lattices, where controllable boundary localization emerges solely from the lattice geometry. Our results establish a robust and broadly applicable route to engineer boundary accumulation and directed transport along prescribed directions in two-dimensional non-Hermitian systems, enabling reconfigurable wave routing in classical platforms and programmable transport functionalities in quantum settings.

We propose and analyze a scheme to generate squeezed light by storing a classical probe pulse in a Bose-Einstein condensate (BEC) and exploiting the nonlinear evolution caused by atom-atom collisions during the storage time. A $\mathrm{\Lambda }$-type optical memory interface maps a chosen temporal probe mode onto a single phase-matched collective spin wave; for a coherent input, this prepares a tunable coherent spin state of a two-component BEC, with its initial spin orientation set by the stored mean excitation number and the phase relation between the probe and control fields. Collisional interactions during storage then implement one-axis-twisting dynamics and generate spin squeezing in the atomic ensemble. We account for realistic loss and finite memory and retrieval efficiencies, and model readout as a single-mode beam-splitter mapping that transfers the atomic quadrature squeezing onto a propagating optical mode. The model identifies optimal storage times and predicts that, under realistic conditions, several decibels of squeezing can be transferred to the retrieved light.

We introduce an unsupervised machine-learning framework that discovers optimally compressed representations of quantum many-body ground states. Using an autoencoder neural network architecture on reduced density matrix data from $L$-site Fermi-Hubbard models, we identify minimal latent spaces with a sharp reconstruction quality threshold at $L-1$ latent dimensions, matching the system's intrinsic degrees of freedom. We demonstrate the use of the trained decoder as a differentiable variational ansatz to minimize energy directly within the latent space. Crucially, this approach circumvents the $N$-representability problem, as the learned manifold implicitly restricts the optimization to physically valid quantities.

Quantum Monte Carlo (QMC) methods are uniquely capable of providing exact simulations of quantum many-body systems. Unfortunately, the applications of a QMC simulation are limited because extracting dynamic properties requires solving the analytic continuation problem. Across the many fields that use QMC methods, there is no universally accepted analytic continuation algorithm for extracting dynamic properties, but many publications compare to the maximum entropy method. We investigate when entropy maximization is an acceptable approach. We show that stochastic sampling algorithms reduce to entropy maximization when the Bayesian prior is near to the true solution. We investigate when is Bryan’s controversial optimization algorithm [Bryan, Eur. Biophys. J. 18, 165 (1990)] for entropy maximization (sometimes known as the maximum entropy method—MEM) appropriate to use. We show that Bryan’s algorithm is appropriate when the noise is near zero or when the Bayesian prior is near the true solution. We also investigate the mean squared error, finding a better scaling when the Bayesian prior is near the true solution than when the noise is near zero. Together, these three results indicate that enhancing the quality of the Bayesian prior enhances the validity of the MEM and has better return on investment than reducing the noise. We point to examples of improved data-driven Bayesian priors that have already leveraged this advantage. We support these results by solving the double Gaussian problem using both Bryan’s algorithm and the newly formulated dual approach to entropy maximization [Chuna et al., J. Phys. A: Math. Theor. 58, 335203 (2025)].

We investigate the impact of an isotropic antiferromagnetic Heisenberg perturbation on the toric code, focusing on the resulting quantum phase transition and the nature of the phase that emerges beyond topological order. Using neural-network quantum states, we compute ground states over a wide range of Heisenberg couplings while fully respecting the exact symmetries of the model. In the weak-coupling regime, the numerical results are in excellent agreement with an effective low-energy description derived from a Schrieffer-Wolff (SW) transformation, providing analytic control over the perturbative breakdown of topological order. We show that the Heisenberg perturbation only renormalizes local operators at low orders, whereas mixing between topological sectors occurs only at a perturbative order proportional to the system size. At intermediate values of the Heisenberg interaction, the topological phase breaks down. We estimate the critical point through a combination of the fidelity susceptibility and the logarithmic susceptibility of noncontractible Wilson loops for various system sizes. Furthermore, we utilize the topological entanglement entropy to provide a comprehensive characterization of the phase transition. Beyond the transition, an antiferromagnetic $\pm X/\pm Z$ Néel phase emerges, characterized by a fourfold-degenerate symmetry-broken manifold, which is explicitly probed using staggered-magnetization-based diagnostics. Our results show how local two-spin interactions, which naturally arise in realistic implementations of the toric code, drive the breakdown of topological order. Moreover, we establish the SW approach as a systematic framework for analyzing such perturbations in combination with variational many-body methods.

Quantum machine learning is an emergent field that continues to draw significant interest for its potential to offer improvements over classical algorithms in certain areas. However, training quantum models remains a challenging task, largely because of the difficulty in establishing an effective inductive bias when solving high-dimensional problems. In this work, we propose a training framework that prioritizes informative data points over the entire training set. This approach draws inspiration from classical techniques such as curriculum learning and hard example mining to introduce an additional inductive bias through the training data itself. By selectively focusing on informative samples, we aim to steer the optimization process toward more favorable regions of the parameter space. This data-centric approach complements existing strategies such as warm-start initialization methods, providing an additional pathway to address performance challenges in quantum machine learning. We provide theoretical insights into the benefits of prioritizing informative data for quantum models, and we validate our methodology with numerical experiments on selected recognition tasks of quantum phases of matter. Our findings indicate that this strategy could be a valuable approach for improving the performance of quantum machine learning models.

Locally noncentrosymmetric materials are attracting significant attention due to the unique phenomena associated with sublattice degrees of freedom. The recently discovered heavy-fermion superconductor ${\mathrm{CeRh}}_2{\mathrm{As}}_2$ has emerged as a compelling example of this class, garnering widespread interest for its remarkable temperature-magnetic-field phase diagram, which features a field-induced first-order superconductor-to-superconductor phase transition with nontrivial dependence on the field direction and high critical fields, as well as antiferromagnetic and potentially higher multipole orders. To investigate the complex interplay of the ordered phases in ${\mathrm{CeRh}}_2{\mathrm{As}}_2$, we develop a theoretical framework based on symmetry analysis applied to a Bogoliubov–de Gennes Hamiltonian and Landau methods. This approach allows us to propose probable symmetries of the superconducting states and elucidate their close relationship with magnetism. Among other results, we find that the near degeneracy of two pairing symmetries is naturally explained if and only if intralayer spin-orbit coupling is large compared to interlayer hopping. Intriguingly, we find that the first-order transition can be interpreted as a transition between coexistence phases of the same superconducting order parameters, albeit with distinct admixtures. This line may end in a critical end point below the superconducting critical temperature. Our approach accurately reproduces current experimental phase diagrams for varying temperature as well as out-of-plane and in-plane magnetic field, both if the transition to a magnetic phase occurs below the superconducting critical temperature and if it occurs above. Furthermore, we calculate the magnetic susceptibility and the specific heat and compare these quantities to recent experimental results.

Muon spin rotation (${\mu }^{+}\mathrm{SR}$) was used to investigate the magnetic properties of cobalt-intercalated $2H-{\mathrm{NbSe}}_2$ (${\mathrm{Co}}_{1/4}{\mathrm{NbSe}}_2$). ${\mathrm{Co}}_{1/4}{\mathrm{NbSe}}_2$ is predicted to be an altermagnet, and while neutron diffraction has proposed its magnetic structure, the microscopic details of this remain unclear. Therefore, a local probe investigation of the magnetism in ${\mathrm{Co}}_{1/4}{\mathrm{NbSe}}_2$ is essential. Our results reveal a sharp second-order transition to a full-volume-fraction, homogeneous magnetic order below $T_{\mathrm{N}}=168\mathrm{K}$. The moments are aligned antiparallel along the $c$ axis, consistent with neutron diffraction and altermagnetism. ${\mu }^{+}\mathrm{SR}$ reveals that the state remains stable under a $c$-axis magnetic field up to $0.78\mathrm{T}$, with magnetization measurements suggesting that this robust regime extends to at least 5 T. Within the time sensitivity of ${\mu }^{+}\mathrm{SR}$, no precursor slow magnetic fluctuations were detected above $T_{\mathrm{N}}$, which is important for interpreting the band splitting in the paramagnetic state reported by photoemission studies.

Electron-phonon interactions play a central role in determining charge and heat transport in condensed matter systems, but in disordered and low-dimensional materials, this coupling can be strongly suppressed, leading to nontrivial transport phenomena. One striking manifestation is the appearance of bistable current-voltage ($I\text{−}V$) characteristics, where an imbalance between electrical heating and electron-phonon cooling yields multiple nonequilibrium steady states. In this work, we experimentally investigate this phenomenon in amorphous $a\text{−}{\mathrm{Y}}_x{\mathrm{Si}}_{1-x}$ thin films, where disorder can be tuned by thermal annealing. We identify the critical disorder at which bistability emerges and characterize the associated jumps in nonlinear $I\text{−}V$ curves. To interpret these results, we develop a microscopic derivation of the phenomenological hot-electron model and extend it by incorporating electric-field-assisted hopping and phonon-mediated intergrain transitions, allowing quantitative agreement with experimental data across different disorder regimes. Complementary numerical simulations confirm the robustness of our extended framework. Our combined experimental, analytical, and numerical results provide a comprehensive description of electron-phonon decoupling and its impact on transport in disordered systems, offering a platform for studying nonequilibrium phases.

We propose a quantum algorithm for computing one-quasiparticle excitation energies in the thermodynamic limit by combining numerical linked-cluster expansions (NLCEs) and the variational quantum eigensolver (VQE). Our approach uses VQE to block diagonalize the cluster Hamiltonian through a single-unitary transformation. This unitary is then postprocessed using the projective cluster-additive transformation (PCAT) to ensure cluster additivity, a key requirement for NLCE convergence. We benchmark our method on the transverse-field Ising model (TFIM) in one and two dimensions, and with longitudinal field, computing one-quasiparticle dispersions in the high-field polarized phase. We compare two cost function classes, trace minimization and variance based, demonstrating their effectiveness with the Hamiltonian variational ansatz (HVA). For pure TFIM, $\lceil N/2\rceil$ layers of HVA suffice: $\mathrm{NLCE}+\mathrm{VQE}$ matches exact diagonalization. For TFIM with longitudinal field, where parity symmetry breaks and PCAT becomes essential, both $\lceil N/2\rceil$ and $N$ layers of HVA converge with increasing cluster size, with $N$ layers providing improved accuracy. Our results establish PCAT as a cluster-additive framework that extends variational quantum algorithms to excited-state calculations in the thermodynamic limit via NLCE. While demonstrated with VQE, the PCAT postprocessing approach, which requires only low-energy eigenspace information, applies to any quantum eigenstate preparation method.

We establish a quantitative relation between the altermagnetic spin splitting and different higher-order multipoles of the charge and magnetization density around the magnetic atoms. Magnetic multipoles such as octupoles or triakontadipoles have been suggested as potential ferroic order parameters for $d$- and $g$-wave altermagnetism, respectively, based mainly on qualitative symmetry arguments. We use first-principles-based electronic structure calculations to establish a clear quantitative relation between the strength of the altermagnetic spin splitting and the magnitude of certain local multipoles. We vary the magnitude of these multipoles either by applying an appropriate constraint on the charge density or by varying a corresponding structural distortion mode, using two simple perovskite materials, ${\mathrm{SrCrO}}_3$ and ${\mathrm{LaVO}}_3$, as model systems. Our analysis indicates that in general the altermagnetic spin splitting is not exclusively determined by the lowest-order nonzero magnetic multipole, but results from a superposition of contributions from different multipoles with comparable strength, suggesting the need for a multicomponent order parameter to describe altermagnetism. We also discuss different measures to quantify the overall spin splitting of a material, without relying on features that might be specific to only individual bands.

We theoretically explore a dynamical generalization of the Aubry-André model in two dimensions formed by superimposing two square-lattice potentials. Motivated by the rich physics emerging at different twist angles between the two lattices at equilibrium, we introduce periodic twisting by continuously rotating one of the lattices with respect to the other in the plane. We demonstrate that the distinct time-dependent twisting in this system gives rise to an intricate form of periodic multifrequency driving that changes with the distance from the rotation axis. We find that the incommensurate nature of the potential no longer plays the pivotal role as it does in the static case. Rather, the tunneling can be understood in terms of a local, spatially varying dynamical localization effect, which we show to yield ring-shaped states localized within the bulk that have interesting transport signatures. Quantifying the eigenstates with the Bott index and local Chern marker, we find that there is a zoo of states with nontrivial topological signatures, the most ubiquitous of which result in relatively uniform ring-shaped regions of the Chern marker. We investigate the origin of these effects from various angles and identify that hybridization between different delocalized ring states plays a vital role. Finally, we discuss possible experimental realizations in quantum simulation settings. Our results open an avenue of investigation with periodic twisting inducing a spatially varying multifrequency drive.

We explore the correlated dynamics underlying the formation of the quantum Peregrine soliton, a prototypical rogue-wave excitation, utilizing interaction quenches from repulsive to attractive couplings in an ultracold bosonic gas confined in a one-dimensional box trap. The latter emulates the so-called semiclassical initial conditions and the associated gradient catastrophe scenario facilitating the emergence of a high-density, doubly localized waveform. The ensuing multiorbital variant of the Peregrine soliton features notable deviations from its mean-field sibling, including a reduced peak amplitude, wider core, absence of the side density dips, and earlier formation times. Moreover, Peregrine soliton generation yields coherence losses, while experiencing two-body bunching within each of its sides, which show anti-bunching between each other. Controllable seeding of the Peregrine soliton is also demonstrated by tuning the atom number or the box length, while reducing the latter favors the generation of the time-periodic Kuznetsov-Ma breather. Our results highlight that correlations reshape the morphology of rogue waves in the genuinely quantum, nonintegrable realm, while setting the stage for the emergent field of quantum dispersive hydrodynamics.

We demonstrate strong coupling in a solid-state hybrid quantum system comprising a fixed-frequency coplanar-waveguide resonator, a superconducting transmon qubit, and an ensemble of nitrogen-vacancy centers in diamond. Frequency-domain spectroscopy reveals a characteristic three-mode avoided crossing, consistent with excitations being distributed across all three subsystems through hybridized eigenmodes. At higher probe powers, we observe nonlinear features and signatures of transmon-${}^{14}\mathrm{N}$ nuclear-spin interactions, highlighting the accessibility of higher-excitation manifolds in this architecture. These results establish an experimentally accessible regime of hybrid cavity QED that integrates superconducting and spin degrees of freedom, providing a platform for exploring complex multicomponent dynamics and developing hybrid quantum interfaces.

We propose a robust platform for simulating chiral quantum magnetism using linear arrays of trapped asymmetric-top molecules, specifically 1,2-propanediol (${\mathrm{C}}_3{\mathrm{H}}_8{\mathrm{O}}_2$). By mapping the Stark-dressed rotational states onto an effective spin-$1/2$ subspace, we rigorously derive a generalized $XXZ$ Heisenberg Hamiltonian governing the underlying many-body dynamics. Unlike standard solid-state models where the topological Dzyaloshinskii-Moriya interaction (DMI) is introduced phenomenologically, we demonstrate that DMI emerges ab initio from the molecular stereochemistry. Specifically, the interference between the transition dipole moments of heterochiral enantiomer pairs (left- and right-handed), which breaks inversion symmetry, generates a tunable DMI that stabilizes a chiral Luttinger liquid phase. Through a comprehensive phase-diagram analysis, we identify an optimal experimental regime characterized by intermolecular separations of $r\approx 1.5\mathrm{nm}$ and intermediate electric-field strengths $d\varepsilon /B\approx 2.5$. In this window, the system is protected from trivial field-polarized phases and exhibits a robust gapless spin-spiral texture. Our results establish 1,2-propanediol arrays as a versatile quantum simulator, providing a direct microscopic link between molecular chirality and topological many-body phases.

We investigate and compare two particle number-conserving protocols for the preparation of a topologically nontrivial state. The first is derived from thermally coupling the system to a cold bath, while the second is based on engineered dissipation. We numerically study the time required to reach the target state as well as its robustness against physically important perturbations. Crucially, in both protocols, the cooling capability is limited by dissipatively induced diffusion processes. The resulting quadratic scaling of the cooling time with system size is also corroborated analytically using mean-field approximations and a purely classical random-walk model. Furthermore, we find that the engineered protocol admits a unique and stable dark state, which contributes to an ongoing discussion regarding the applicability of dissipative state preparation to many-body systems.