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Jose L. Lado

Publications and source records attributed to Jose L. Lado.

At least 19 recordsLinked to original sources
arXiv2026

Moiré Mott correlated mosaics in twisted bilayer 1T-TaS$_2$

The tunability and twist engineering of van der Waals materials enable the emergence of electronic states not present in individual monolayers. Among them, monolayer 1T-TaS$_2$ is a well-known Mott insulating system, whose star-of-David charge density wave reconstruction realizes an emergent triangular lattice of local magnetic moments. Interestingly, in its bulk form, the insulating gap is not correlation-driven, but stems from interlayer coupling. Here, we exploit the stacking-dependent nature of the insulating gap to show that in twisted 1T-TaS$_2$ bilayers, the spatially dependent competition between many-body and single-particle gaps creates Mott-trivial mosaic superlattices, featuring regions with local magnetic moments and non-magnetic insulating regions. We further demonstrate the tunability of the mosaic correlated state with an interlayer bias, giving rise to controllable charge transfer and quenching of correlations. Our results establish twisted 1T-TaS$_2$ as a flexible platform to engineer mixed spatially modulated correlated insulating phases, arising from the moiré profile.

cond-mat.str-el↗
arXiv2026

Hamiltonian learning quantum magnets with dynamical impurity tomography

Nanoscale engineered spin systems, ranging from spins on surfaces to nanographenes, provide flexible platforms to realize entangled quantum magnets from a bottom-up approach. However, assessing the quantum many-body Hamiltonian realized in a specific experiment remains an exceptional open challenge, due to the difficulty of disentangling competing terms accounting for the many-body excitations. Here, we demonstrate a machine learning strategy to learn a quantum many-body spin Hamiltonian from scanning spectroscopy measurements of spin excitations. Our methodology leverages the spatially resolved reconstruction of the many-body excitations induced by depositing quantum impurities next to the quantum magnet. We demonstrate that our algorithm allows us to predict long-range Heisenberg exchange interactions, anisotropic exchange, and antisymmetric Dzyaloshinskii-Moriya interaction, including in the presence of sizable noise. Our methodology establishes defect-induced spatially resolved dynamical excitations in quantum magnets as a powerful strategy to understand the nature of quantum spin many-body models.

cond-mat.mes-hall↗
arXiv2026

One-dimensional quasicrystals with tensor-network finite-state automata

Quasicrystals occupy a distinctive position between the translational order of crystals and the disordered amorphous matter. Simulating this physics has remained challenging, since quasiperiodic structures lack the translational symmetry exploited for crystals and generally require costly diagonalization of large finite approximants. Quasicrystalline order admits two equivalent descriptions, a cut-and-project scheme from a higher-dimensional periodic crystal, and a discrete set of substitution rules acting on a finite alphabet. We show that the latter, written in a numeration system adapted to the substitution, defines a deterministic finite automaton with output, the digits of a site index are fed, and the automaton returns the letter occupying that site. We further exploit another equivalence to a different construction, the transition matrices are exactly the tensors of a matrix product state, whose bond dimension is the number of automaton states and is independent of system size. This allows efficient representation of extremely large tight-binding Hamiltonians in the tensor-train language, thereby yielding an exact matrix product operator for the quasicrystal Hamiltonian at any system size. We show how this framework works for two families of one-dimensional quasicrystals, the metallic-mean and $k$-bonacci families and we explicitly construct the Fibonacci, silver-mean, and Tribonacci quasicrystals. By leveraging efficient tensor-network compression and the kernel polynomial method, we compute spectral densities for chains with more than $10^9$ sites and directly resolve the hierarchical structure of the spectrum.

cond-mat.mes-hall↗
arXiv2026

Fingerprinting superconductors by disentangling Andreev and quasiparticle currents across tunable tunnel junctions

Tunneling Andreev reflection (TAR) spectroscopy offers a powerful new approach to fingerprint superconducting pairing symmetry at the atomic scale. By leveraging the exponential sensitivity of excess tunneling decay rate to Andreev reflection, TAR robustly distinguishes between s-wave, d-wave, and more complex order parameters, overcoming limitations of traditional conductance-based techniques. Here, using atomistic superconducting transport simulations, we show that the additivity of excess decay rate enables clear separation of Andreev and quasiparticle currents. In particular, we reveal how their competition as well as higher-order scattering processes shape both the decay rate spectra and their dependence on the coupling strength. We show that this phenomenology stems from the fact that Andreev reflection dominates mid-gap conductance for s-wave superconductors, it is suppressed for the d-wave, and it coexists with quasiparticle tunneling in sign-changing symmetries if the expectation value for the superconducting gap remains finite. These distinct spectral fingerprints pave the way for atomically resolved identification of unconventional superconducting states.

cond-mat.supr-con↗
arXiv2026

Tensor-network methodology for real-space super-moiré excitons

Computing excitonic spectra in quasicrystal and super-moiré systems constitutes a formidable challenge due to the exceptional size of the excitonic Hilbert space. Here, we demonstrate a tensor-network method for the real-space Bethe-Salpeter Hamiltonian, allowing us to access the spectra of an excitonic $10^{18}$-dimensional Hamiltonian, and enabling the direct computation of bound-exciton spectral functions for systems exceeding one billion lattice sites, several orders of magnitude beyond the capabilities of conventional approaches. Our method combines a tensor-network encoding of the real-space Bethe-Salpeter Hamiltonian with a Chebyshev tensor network algorithm. This strategy bypasses explicit storage of the Hamiltonian while preserving full real-space resolution across widely different length scales. We demonstrate our methodology for one- and two-dimensional super-moiré systems, achieving the simultaneous resolution of atomistic and mesoscopic structures in the excitonic spectra in billion-size systems, showing exciton miniband formation and moiré-induced spatial confinement. Our results establish a real-space methodology enabling the simulation of excitonic physics in large-scale quasicrystal and super-moiré quantum matter.

cond-mat.str-el↗
arXiv2026

Emergent ferromagnetism in the NiI$_2$-NbSe$_2$ van der Waals heterostructure

Multiferroicity arising from non-collinear spin textures and strong spin-orbit interactions offers a route to magnetoelectric functionality in the monolayer limit. Although theory predicts that the properties of monolayer multiferroics can be tuned by strain, gating, or proximity effects, experimental demonstrations of such control remain scarce. Here we show that the magnetic ground state of monolayer NiI$_2$, a prototypical two-dimensional multiferroic, is altered by proximity to a superconducting NbSe$_2$ substrate. Using low-temperature scanning tunnelling microscopy (STM) and spectroscopy (STS), we show that the metallic substrate renormalizes the exchange interactions within NiI$_2$ and drives it into a ferromagnetic ground state. This can be visualized by probing the Yu-Shiba-Rusinov (YSR) states within the superconducting gap of the NbSe$_2$ substrate. Our results establish YSR states as an in situ probe of two-dimensional magnetism and demonstrate substrate engineering as a means of controlling magnetic order in atomically thin materials.

cond-mat.mes-hall↗
arXiv2026

Machine-learning-enabled characterization of individual ring resonators in integrated photonic lattices

Accurately determining the underlying physical parameters of individual elements in integrated photonics is increasingly difficult as device architectures become more complex. Inferring these parameters directly from spectral measurements of the system as a whole provides a practical alternative to traditional calibration, allowing characterization of photonic systems without relying on detailed device-specific models. Here, we introduce a supervised machine-learning strategy to learn the onsite losses and resonant frequency shifts of each individual ring in an array of coupled ring resonators from measured spectral power distributions of the whole array. The neural network infers these parameters with high accuracy across multiple experimental configurations. Our methodology provides a scalable and non-invasive method for extracting intrinsic parameters in coupled photonic platforms, paving the way for future development of automated calibration and control methods.

physics.optics↗
arXiv2026

Topology and criticality in non-Hermitian multimodal optical resonators through engineered losses

Non-Hermitian topological matter provides a platform for engineering phenomena that go beyond the capabilities of Hermitian systems, enabling the use of losses to engineer topological phenomena. Non-Hermitian models often rely on artificial platforms made of engineered lattices because controlling losses in natural compounds is challenging. Although typical models for non-Hermitian photonic matter are often single mode, photonic systems are often multimodal, producing mixing between different normal modes in each site. In this work, we explore a generalized family of multimodal non-Hermitian lattices, featuring multiple resonant modes. We show that these multimodal models are capable of featuring topological modes and criticality, similar to the artificial single-mode models often considered. We analyze the robustness of these non-Hermitian topological modes to fluctuation of local losses, disorder, and artificial gauge field. We show that these effects can be captured via both a full microscopic model and effective multiorbital models. Specifically, we show that due to their multiorbital nature, the localization properties of non-Hermitian multiorbital models can be controlled by an external gauge field. Our results demonstrate that internal orbital degrees of freedom provide a promising strategy to engineer controllable non-Hermitian topology and criticality.

physics.optics↗
arXiv2026

Observation of electromagnons in a monolayer multiferroic

Van der Waals multiferroics have emerged as a promising platform to explore novel magnetoelectric phenomena. Recently, it has been shown that monolayer NiI$_2$ hosts robust type-II multiferroicity down to the two-dimensional limit, a giant dynamical magnetoelectric coupling at terahertz frequencies, and an electrically switchable spin polarization. These developments present the possibility of engineering ultrafast, low-energy-consumption, and electrically-tunable spintronic devices based on the collective excitations of the multiferroic order, electromagnons. However, the direct visualization of these bosonic modes in real space and within the monolayer limit remains elusive. Here, we report the atomic-scale observation of electromagnons in monolayer NiI$_2$ using low-temperature scanning tunneling microscopy. By tracking the thermal evolution of the multiferroic phase, we establish the energy scale and resolve coherent in-gap excitations of the symmetry-broken multiferroic state. Comparison with first-principles and spin-model calculations reveals that the low-energy modes originate from electromagnon excitations. Spatially resolved inelastic tunneling spectroscopy maps show a stripe-like modulation of the local spectral function at electromagnon energies, matching theoretical predictions. These results provide direct evidence of the internal structure of electromagnons and establish a methodology to probe these modes at the atomic scale, opening avenues for electrically tunable spintronics.

cond-mat.mtrl-sci↗
arXiv2026

Interaction-driven electronic ferroelectricity in van der Waals heterostructures

Strong electronic correlations in narrow-band systems provide a promising route to realize emergent quantum phases. While ferroelectricity in van der Waals materials is typically associated with inversion symmetry breaking driven by lattice distortions, interlayer sliding, or moiré reconstruction, the possibility of generating ferroelectricity directly from electronic interactions remains largely unexplored. Here, using molecular beam epitaxy, scanning tunneling microscopy, and ab initio calculations, we investigate two stacking geometries of bilayer 1T-TaSe$_2$, A-C and A-C$'$, formed by coupled Star-of-David charge density wave phases. We show that both stackings realize quasi-one-dimensional interacting chains, but are governed by distinct interaction mechanisms. In the A-C stacking, strong interlayer hybridization leads to dimerization and the formation of a band insulating state. In contrast, the A-C$'$ stacking is dominated by interlayer Coulomb interactions, producing a spontaneous charge imbalance between layers that gives rise to an out-of-plane ferroelectric polarization. Furthermore, we demonstrate that ferroelectric and antiferroelectric interchain configurations can be stabilized and electrically switched by an external field. Our results prove that bilayer 1T-TaSe$_2$ is a platform for interaction-driven electronic ferroelectricity, establishing an overlooked family of charge-ordered correlated states in 1T-TaSe$_2$ multilayers.

cond-mat.mtrl-sci↗
arXiv2026

Electrical Control of Altermagnetism in a Quasi-1D Magnet

Altermagnetism is a collinear magnetic state characterized by momentum-dependent spin splitting in fully compensated materials. While widely investigated in systems governed by three- or two-dimensional exchange interactions, its extension to quasi-one-dimensional magnets remains almost unexplored. Focusing on the experimentally established AgCrP$_2$S$_6$ van der Waals magnet, we demonstrate that antiferromagnetic chains embedded in a two-dimensional lattice provide a general route to altermagnetism. Combining first-principles calculations and spin-space-group analysis, we show that out-of-plane symmetry breaking can generate a nonrelativistic d-wave spin splitting. An external out-of-plane electric field validates this mechanism, where the induced splitting increases linearly with field strength and reverses sign with field direction. We rationalize such behaviour by constructing an effective tight-binding model, which links the altermagnetic response to anisotropic third-neighbor interchain hoppings. Additionally, we show that Janus substitution also induces a d-wave spin texture, while ferroelectric interfacing with CuInP$_2$S$_6$ enables polarization-controlled spin-split bands in a fully compensated ferrimagnetic state. Our results establish quasi-one-dimensional antiferromagnets as building blocks for altermagnetism.

cond-mat.mtrl-sci↗
arXiv2026

Parity-dependent double degeneracy and spectral statistics in the projected dice lattice

We investigate the spectral statistics of an interacting fermionic system derived by projecting the Hubbard interaction onto the two lowest-energy, degenerate flat bands of the dice lattice subjected to a $π$-flux. Surprisingly, the distributions of level spacings and gap ratios correspond to distinct Gaussian ensembles, depending on the parity of the particle number. For an even number of particles, the spectra conform to the Gaussian Orthogonal Ensemble, as expected for a time-reversal-symmetric Hamiltonian. In stark contrast, the odd-parity sector exhibits exact double degeneracy of all eigenstates even after resolving all known symmetries, and the Gaussian Unitary Ensemble accurately describes the spacing distribution between these doublets. The simultaneous emergence of two different random-matrix ensembles within a single physical system constitutes an unprecedented finding, opening new avenues for both random matrix theory and flat-band physics.

cond-mat.str-el↗
arXiv2026

Quantum circuit algorithm for topological invariants of second order topological many-body quantum magnets

Topological quantum matter represents a flexible playground to engineer unconventional excitations. While non-interacting topological single-particle systems have been studied in detail, topology in quantum many-body systems remains an open problem. Specifically, in the quantum many-body limit, one of the challenges lies in the computational complexity of obtaining the many-body ground state and its many-body topological invariant. While algorithms to compute ground states with quantum computers have been heavily investigated, algorithms to compute topological invariants in a quantum computer are still under active development. Here we demonstrate a quantum circuit to compute the many-body topological invariant of a second-order topological quantum magnet encoded in qubits. Our algorithm relies on a quantum circuit adiabatic evolution in transverse paths in parameter space, and we uncover hidden topological invariants depending on the traversed path. Our work puts forward an algorithm to leverage quantum computers to characterize many-body topological quantum matter.

quant-ph↗
arXiv2026

Tensor network solvers for ultra-large tight-binding Hamiltonians: algorithms and applications

Understanding quantum materials at meso and even macroscopic scales requires tight-binding calculations on system sizes where explicit matrix representations become prohibitively costly. This represents a major bottleneck to rationalize phenomena in moiré and super-moiré heterostructures and quasicrystals. Here, we present a unified tensor-network methodology to solve tight-binding problems at exceptionally large scales, by mapping a system of $N = 2^L$ sites onto a many-body problem of $L$ pseudospin sites, which is subsequently solved with tensor network algorithms. For Hamiltonians with compressible real-space structure, the tensor network bond dimension remains modest, typically of order a few tens, independent of $N$. Tensor network representations of arbitrary hopping functions including long-range, spatially modulated, and twisted-layer couplings are built with quantics tensor cross interpolation, and all physical observables are evaluated entirely with tensor network algebra without explicit matrix storage or diagonalization. We demonstrate applications to spectral functions, momentum-space spectra via the tensor-network quantum Fourier transform, real-space topological invariants, real-time dynamics, correlation induced symmetry breaking with self-consistent mean-field calculations, non-Hermitian phenomena, and excitonic many-body physics. Our methodology enables routinely solving systems with billions of sites, by leveraging the tensor network compressibility of real-space structures, and establishing a flexible framework to study quantum matter at ultra-large length scales. The methodology is implemented in the open-source Julia package TensorBinding.

cond-mat.str-el↗
arXiv2026

Learning Inhomogeneous Heisenberg Hamiltonians in Nanographene Spin Chains

Inferring microscopic Hamiltonians from experimental data is a central challenge in quantum materials and quantum simulation. In low-dimensional spin systems, exchange interactions are often assumed to be spatially uniform, despite structural and environmental inhomogeneities that can locally modify the coupling. Here, we leverage a local, length-independent machine learning methodology to reconstruct spatially modulated exchange interactions directly from inelastic scanning tunneling spectroscopy maps. We demonstrate this approach with nanographene spin chains, identifying both near-uniform and inhomogeneous regimes across the synthesized magnets. The reconstructed models quantitatively reproduce the experimental spectra and recover the correct scaling of the excitation gap with system size. Our results establish a general strategy to bridge local spectroscopic measurements with effective many-body Hamiltonians.

cond-mat.mes-hall↗
arXiv2026

Cross-Platform Autonomous Control of Minimal Kitaev Chains

Contemporary quantum devices are reaching new limits in size and complexity, allowing for the experimental exploration of emergent quantum modes. However, this increased complexity introduces significant challenges in device tuning and control. Here, we demonstrate autonomous tuning of emergent Poor Man's Majorana zero modes in a minimal realization of a Kitaev chain. We achieve this task using cross-platform transfer learning. First, we train a tuning model on a theory model. Next, we retrain it using a Kitaev chain realization in a two-dimensional electron gas. Finally, we apply this model to tune a Kitaev chain realized in quantum dots coupled through a semiconductor-superconductor section in a one-dimensional nanowire. Utilizing a convolutional neural network, we predict the tunneling and Cooper pair splitting rates from differential conductance measurements, employing these predictions to adjust the electrochemical potential to a Poor Man's Majorana sweet spot. The algorithm successfully converges to an immediate vicinity of a sweet spot (within 1.5 mV in 67.6% of attempts and within 4.5 mV in 80.9% of cases), typically finding a sweet spot in 45 minutes or less. This advancement is a stepping stone towards autonomous tuning of emergent modes in interacting systems, and towards foundational tuning machine learning models that can be deployed across a range of experimental platforms.

cond-mat.mes-hall↗
arXiv2026

Real-space spectral functions of three-dimensional billion-size topological non-Hermitian matter with tensor networks

Non-Hermitian systems host a wide range of unconventional topological phenomena while large-scale simulations in finite three dimensional systems remain challenging because of the rapidly growing number of sites. In particular, higher-order topological corner modes are often studied only in small lattices, where strong finite-size effects can mask their intrinsic behavior. Here, we develop a tensor-network framework that combines quantics tensor cross interpolation with the kernel polynomial method, enabling compact representations of large non-Hermitian tight-binding Hamiltonians and direct calculations of real-space spectral functions for systems exceeding one billion lattice sites. Using this approach, we investigate three-dimensional non-Hermitian higher-order topological insulators with with structured real-space geometries. The unprecedented system size enables direct access to the macroscopic regime and allows corner-mode spectral responses to be resolved in genuinely three-dimensional systems. By tuning the loss strength, we identify distinct in-gap corner modes across weak- and strong-loss regimes. Our results establish tensor-network algorithms as a powerful strategy to perform real-space spectral calculations in exceptionally large non-Hermitian systems.

cond-mat.mes-hall↗
arXiv2026

Tensor network approach to momentum-resolved spectroscopy in non-periodic super-moiré systems

Computing spectral functions in large, non-periodic super-moiré systems remains an open problem due to the exceptionally large system size that must be considered. Here, we establish a tensor network methodology that allows computing momentum-resolved spectral functions of non-interacting and interacting super-moiré systems at an atomistic level. Our methodology relies on encoding an exponentially large tight-binding problem as an auxiliary quantum many-body problem, solved with a many-body kernel polynomial tensor network algorithm combined with a quantum Fourier transform tensor network. We demonstrate the method for one and two-dimensional super-moiré systems, including super-moiré with non-uniform strain, interactions treated at the mean-field level, and quasicrystalline super-moiré patterns. Furthermore, we demonstrate that our methodology allows us to compute momentum-resolved spectral functions restricted to selected regions of a super-moiré, enabling direct imaging of position-dependent electronic structure and minigaps in super-moiré systems with non-uniform strain. Our results establish a powerful methodology to compute momentum-resolved spectral functions in exceptionally large super-moiré systems, providing a tool to directly model quantum twisting microscope experiments in twisted van der Waals heterostructures.

cond-mat.str-el↗