arXiv subjects

Davi R. Rodrigues

Publications and source records attributed to Davi R. Rodrigues.

At least 19 recordsLinked to original sources

arXiv2026

Designing dislocation-driven polar vortex networks in twisted perovskites

Twisting two atomic layers produces a geometric moire pattern, but bonding-induced interfacial reconstruction fundamentally transforms this into an ordered dislocation network - a distinction obscured in weakly-bonded van der Waals systems. Although in-plane topological vortex nanostructures arising from twisting-induced lateral strain modulation have been linked to periodic moire patterns in freestanding perovskite layers and 2D bilayers, their coupling to the interfacial dislocation network in twisted layers remains unresolved. Here we demonstrate that twisting freestanding SrTiO3 layers undergo interfacial reconstruction into a network of screw dislocations, accompanied by the emergence of in-plane topological vortices. Unlike in previous reports, these vortices are associated with the periodicity of the dislocation network rather than with geometric moire patterns. Four-dimensional scanning transmission electron microscopy (4D-STEM) reveals long-range ordered vortex-antivortex arrays with nearly continuous polarisation rotation. A machine-learning interatomic potential, trained on first-principles calculations, together with phase-field modelling, confirms that competing strains within the dislocation network stabilize polar vortex-antivortex pairs and drive the emergence of an electronic superlattice with a well-defined periodicity. Our results establish twist-controlled dislocation networks as a new and versatile route to designing local polar and electronic structures in oxide materials.

cond-mat.mtrl-sci↗

arXiv2026

Magneto-mechanical reservoir computing combining a two-dimensional network of nonlinear mass-spring resonators with magnetic tunnel junctions

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.

cond-mat.mes-hall↗

arXiv2025

Multi-value Probabilistic Computing with current-controlled Skyrmion Diffusion

Magnetic systems are highly promising for implementing probabilistic computing paradigms because of the fitting energy scales and conspicuous non-linearities. While conventional binary probabilistic computing has been realized, implementing more advantageous multi-value probabilistic computing (MPC) remains a challenge. Here, we report the realization of MPC by leveraging the thermally activated diffusion of magnetic skyrmions through an effectively non-flat energy landscape defined by a discrete number of pinning sites. The time-averaged spatial distribution of the diffusing skyrmions directly realizes a discrete probability distribution, which is tunable by current-generated spin-orbit torques, and can be quantified by non-perturbative electrical measurements. Even a very straightforward implementation with global tuning, already allows us to demonstrate the softmax computation - a core function in artificial intelligence. As a key advance, we demonstrate invertible logic without the need to create a network of probabilistic devices, offering major scalability advantages. Our proof of concept can be generalized to multiple skyrmions and can accommodate multiple locally tunable inputs and outputs using magnetic tunnel junctions, potentially enabling the representation of highly complex distribution functions.

cond-mat.mtrl-sci↗

arXiv2025

Predicting sampling advantage of stochastic Ising Machines for Quantum Simulations

Stochastic Ising machines, sIMs, are highly promising accelerators for optimization and sampling of computational problems that can be formulated as an Ising model. Here we investigate the computational advantage of sIM for simulations of quantum magnets with neural-network quantum states (NQS), in which the quantum many-body wave function is mapped onto an Ising model. We study the sampling performance of sIM for NQS by comparing sampling on a software-emulated sIM with standard Metropolis-Hastings sampling for NQS. We quantify the sampling efficiency by the number of computational steps required to reach iso-accurate stochastic estimation of the variational energy and show that this is entirely determined by the autocorrelation time of the sampling. This enables predictions of sampling advantage without direct deployment on hardware. Although sampling of the quantum Heisenberg models studied exhibits much longer autocorrelation times on sIMs, the massively parallel sampling of hardware sIMs leads to a projected speed-up of 100 to 10000, suggesting great opportunities for studying complex quantum systems at larger scales.

quant-ph↗

arXiv2024

Roadmap for Unconventional Computing with Nanotechnology

In the "Beyond Moore's Law" era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same time, adopting a variety of nanotechnologies will offer benefits in energy cost, computational speed, reduced footprint, cyber resilience, and processing power. The time is ripe for a roadmap for unconventional computing with nanotechnologies to guide future research, and this collection aims to fill that need. The authors provide a comprehensive roadmap for neuromorphic computing using electron spins, memristive devices, two-dimensional nanomaterials, nanomagnets, and various dynamical systems. They also address other paradigms such as Ising machines, Bayesian inference engines, probabilistic computing with p-bits, processing in memory, quantum memories and algorithms, computing with skyrmions and spin waves, and brain-inspired computing for incremental learning and problem-solving in severely resource-constrained environments. These approaches have advantages over traditional Boolean computing based on von Neumann architecture. As the computational requirements for artificial intelligence grow 50 times faster than Moore's Law for electronics, more unconventional approaches to computing and signal processing will appear on the horizon, and this roadmap will help identify future needs and challenges. In a very fertile field, experts in the field aim to present some of the dominant and most promising technologies for unconventional computing that will be around for some time to come. Within a holistic approach, the goal is to provide pathways for solidifying the field and guiding future impactful discoveries.

cs.ET↗

arXiv2023

Voltage-Controlled High-Bandwidth Terahertz Oscillators Based On Antiferromagnets

Producing compact voltage-controlled frequency generators and sensors operating in the terahertz (THz) regime represents a major technological challenge. Here, we show that noncollinear antiferromagnets (NCAFM) with kagome structure host gapless self-oscillations whose frequencies are tunable from 0 Hz to the THz regime via electrically induced spin-orbit torques (SOTs). The auto-oscillations' initiation, bandwidth, and amplitude are investigated by deriving an effective theory, which captures the reactive and dissipative SOTs. We find that the dynamics strongly depends on the ground state's chirality, with one chirality having gapped excitations, whereas the opposite chirality provides gapless self-oscillations. Our results reveal that NCAFMs offer unique THz functional components, which could play a significant role in filling the THz technology gap.

cond-mat.mes-hall↗

arXiv2023

Manipulating chiral-spin transport with ferroelectric polarization

A collective excitation of the spin structure in a magnetic insulator can transmit spin-angular momentum with negligible dissipation. This quantum of a spin wave, introduced more than nine decades ago, has always been manipulated through magnetic dipoles, (i.e., timereversal symmetry). Here, we report the experimental observation of chiral-spin transport in multiferroic BiFeO3, where the spin transport is controlled by reversing the ferroelectric polarization (i.e., spatial inversion symmetry). The ferroelectrically controlled magnons produce an unprecedented ratio of up to 18% rectification at room temperature. The spin torque that the magnons in BiFeO3 carry can be used to efficiently switch the magnetization of adja-cent magnets, with a spin-torque efficiency being comparable to the spin Hall effect in heavy metals. Utilizing such a controllable magnon generation and transmission in BiFeO3, an alloxide, energy-scalable logic is demonstrated composed of spin-orbit injection, detection, and magnetoelectric control. This observation opens a new chapter of multiferroic magnons and paves an alternative pathway towards low-dissipation nanoelectronics.

physics.app-ph↗

arXiv2023

A spintronic Huxley-Hodgkin-analogue neuron implemented with a single magnetic tunnel junction

Spiking neural networks aim to emulate the brain's properties to achieve similar parallelism and high-processing power. A caveat of these neural networks is the high computational cost to emulate, while current proposals for analogue implementations are energy inefficient and not scalable. We propose a device based on a single magnetic tunnel junction to perform neuron firing for spiking neural networks without the need of any resetting procedure. We leverage two physics, magnetism and thermal effects, to obtain a bio-realistic spiking behavior analogous to the Huxley-Hodgkin model of the neuron. The device is also able to emulate the simpler Leaky-Integrate and Fire model. Numerical simulations using experimental-based parameters demonstrate firing frequency in the MHz to GHz range under constant input at room temperature. The compactness, scalability, low cost, CMOS-compatibility, and power efficiency of magnetic tunnel junctions advocate for their broad use in hardware implementations of spiking neural networks.

cond-mat.mes-hall↗

arXiv2022

Dzyaloshinskii-Moriya Induced Spin-Transfer Torques in Kagome Antiferromagnets

In recent years antiferromagnets (AFMs) have become very promising for nanoscale spintronic applications due to their unique properties such as THz dynamics and absence of stray fields. Manipulating antiferromagnetic textures is currently, however, limited to very few exceptional material symmetry classes allowing for staggered torques on the magnetic sublattices. In this work, we predict for kagome AFMs with broken mirror symmetry a new coupling mechanism between antiferromagnetic domain walls (DWs) and spin currents, produced by the relativistic Dzyaloshinskii-Moriya interaction (DMI). We microscopically derive the DMI's free energy contribution for the kagome AFMs. Unlike ferromagnets and collinear AFMs, the DMI does not lead to terms linear in the spatial derivatives but instead renormalizes the spin-wave stiffness and anisotropy energies. Importantly, we show that the DMI induces a highly nontrivial twisted DW profile that is controllable via two linearly independent components of the spin accumulation. This texture manipulation mechanism goes beyond the concept of staggered torques and implies a higher degree of tunability for the current-driven DW motion compared to conventional ferromagnets and collinear AFMs.

cond-mat.mtrl-sci↗

arXiv2022

Skyrmion pinning energetics in thin film systems

A key issue for skyrmion dynamics and devices are pinning effects present in real systems. While posing a challenge for the realization of conventional skyrmionics devices, exploiting pinning effects can enable non-conventional computing approaches if the details of the pinning in real samples are quantified and understood. We demonstrate that using thermal skyrmion dynamics, we can characterize the pinning of a sample and we ascertain the spatially resolved energy landscape. To understand the mechanism of the pinning, we probe the strong skyrmion size and shape dependence of the pinning. Magnetic microscopy imaging demonstrates that in contrast to findings in previous investigations, for large skyrmions the pinning originates at the skyrmion boundary and not at its core. The boundary pinning is strongly influenced by the very complex pinning energy landscape that goes beyond the conventional rigid quasi-particle description. This gives rise to complex skyrmion shape distortions and allows for dynamic switching of pinning sites and flexible tuning of the pinning.

cond-mat.mtrl-sci↗

arXiv2021

Nonzero Skyrmion Hall Effect in Topologically Trivial Structures

It is widely believed that the skyrmion Hall effect, often disruptive for device applications, vanishes for overall topologically trivial structures such as (synthetic) antiferromagnetic skyrmions and skyrmioniums due to a compensation of Magnus forces. In this manuscript, however, we report that in contrast to the case of spin-transfer torque driven skyrmion motion, this notion is generally false for spin-orbit torque driven objects. We show that the skyrmion Hall angle is directly related to their helicity and imposes an unexpected roadblock for developing faster and lower input racetrack memories based on spin-orbit torques.

cond-mat.mes-hall↗

arXiv2021

Spin-wave driven bidirectional domain wall motion in kagome antiferromagnets

We predict a mechanism to controllably manipulate domain walls in kagome antiferromagnets via a single linearly polarized spin-wave source. We show by means of atomistic spin dynamics simulations of antiferromagnets with kagome structure that the speed and direction of the domain wall motion can be regulated by only tuning the frequency of the applied spin-wave. Starting from microscopics, we establish an effective action and derive the corresponding equations of motion for the spin-wave-driven domain wall. Our analytical calculations reveal that the coupling of two spin-wave modes inside the domain wall explains the frequency-dependent velocity of the spin texture. Such a highly tunable spin-wave-induced domain wall motion provides a key component toward next-generation fast, energy-efficient, and Joule-heating-free antiferromagnetic insulator devices.

cond-mat.mes-hall↗

arXiv2021

Nonlinear dynamics of topological ferromagnetic textures for frequency multiplication

We propose that the non-linear radio-frequency dynamics and nanoscale size of topological magnetic structures associated to their well-defined internal modes advocate for their use as in-materio scalable frequency multipliers for spintronic systems. Frequency multipliers allow for frequency conversion between input and output frequencies, and thereby significantly increase the range of controllably accessible frequencies. In particular, we explore the excitation of eigenmodes of topological magnetic textures by fractions of the corresponding eigenfrequencies. We show via micromagnetic simulations that low-frequency perturbations to the system can efficiently excite bounded modes with a higher amplitude. For example, we excited the eigenmodes of isolated ferromagnetic skyrmions by applying half, a third and a quarter of the corresponding eigenfrequency. We predict that the frequency multiplication via magnetic structures is a general phenomenon which is independent of the particular properties of the magnetic texture, and works also for magnetic vortices, droplets and other topological textures.

cond-mat.mes-hall↗

arXiv2021

Current-induced H-shaped-skyrmion creation and their dynamics in the helical phase

Inevitable for the basic principles of skyrmion racetrack-like applications is not only their confined motion along one-dimensional channels but also their controlled creation and annihilation. Helical magnets have been suggested to naturally confine the motion of skyrmions along the tracks formed by the helices, which also allow for high-speed skyrmion motion. We propose a protocol to create topological magnetic structures in a helical background. We furthermore analyse the stability and current-driven motion of the skyrmions in a helical background with in-plane uniaxial anisotropy fixing the orientation of the helices.

cond-mat.mes-hall↗

arXiv2020

Spin-transfer torque-driven motion, deformation, and instabilities of magnetic skyrmions at high currents

In chiral magnets, localized topological magnetic whirls, magnetic skyrmions, can be moved by spin polarized electric currents. Upon increasing the current strength, with prospects for high-speed skyrmion motion for spintronics applications in mind, isolated skyrmions deform away from their typical circular shape. We analyze the influence of spin-transfer torques on the shape of a single skyrmion, including its stability upon adiabatically increasing the strength of the applied electric current. For rather compact skyrmions at uniaxial anisotropies well above the critical anisotropy for domain wall formation, we find for high current densities that the skyrmion assumes a non-circular shape with a tail, reminiscent of a shooting star. For larger and hence softer skyrmions close to the critical anisotropy, in turn, we observe a critical current density above which skyrmions become unstable. We show that above a second critical current density the shooting star solution can be recovered also for these skyrmions.

cond-mat.mes-hall↗

arXiv2020

Facilitating domain wall injection in magnetic nanowires by electrical means

We investigate how to facilitate the injection of domain walls in chiral ferromagnetic nanowires by electrical means. We calculate the critical current density above which domain walls are injected into the nanowire depending on the material parameters and the source of interaction including spin-transfer torques as well as spin-orbit torques. We demonstrate that the Dzyaloshinskii-Moriya interaction can significantly reduce the required critical current to inject the types of domain walls favored by the Dzyaloshinskii-Moriya interaction. We find that in chiral magnets it is only possible to shed a single domain wall by means of spin-orbit torques, as they modify the ground state orientation of the system. In contrast, for spin-transfer-torque induced shedding of domain walls, we show that there exist two different critical current densities for the two different domain wall chiralities, respectively. Additionally, for the consecutive creation of domain walls by means of spin-transfer torques, we find that the interaction between the domain walls cannot be neglected and even may lead to the pairwise annihilation of consecutive domain walls with opposite chiralities.

cond-mat.mes-hall↗

arXiv2019

Spin eigen-excitations of an antiferromagnetic skyrmion

We theoretically predict and classify the localized modes of a skyrmion in a collinear uniaxial antiferromagnet and discuss how they can be excited. As a central result, we find two branches of skyrmion eigenmodes with distinct physical properties characterized by being low or high energy excitations. The frequency dependence of the low-energy modes scales as $R_0^{-2}$ for skyrmions with large radius $R_0$. Furthermore, we predict localized high-energy eigenmodes, which have no direct ferromagnetic counterpart. Except for the breathing mode, we find that all localized antiferromagnet skyrmion modes, both in the low and high-energy branch, are doubly degenerated in the absence of a magnetic field and split otherwise. We explain our numerical results for the low-energy modes within a string model representing the skyrmion boundary.

cond-mat.str-el↗

arXiv2018

Effective description of domain wall strings

The analysis of domain wall dynamics is often simplified to one dimensional physics. For domain walls in thin films, more realistic approaches require the description as two dimensional objects. This includes the study of vortices and curvatures along the domain walls as well as the influence of boundary effects. Here we provide a theory in terms of soft modes that allows to analytically study the physics of extended domain walls and their stability. By considering irregular shaped skyrmions as closed domain walls, we analyze their plasticity and compare their dynamics with those of circular skyrmions. Our theory directly provides an analytical description of the the excitation modes of magnetic skyrmions, previously only accessible by sophisticated micromagnetic numerical calculations and spectral analysis. These analytical expressions provide the scaling behaviour of the different physics on parameters that experiments can test.

cond-mat.mes-hall↗