arXiv subjects

Anna Giordano

Publications and source records attributed to Anna Giordano.

At least 19 recordsLinked to original sources

arXiv2026

Fractional parametric resonance in spintronic diodes

Parametric pumping is a powerful tool for the excitation, amplification, and processing of oscillations and waves of different nature. In general, parametric resonance can occur when the pumping frequency $f_p$ and eigenfrequency of a linear mode (or wave) $f_0$ satisfy the relation $f_p$=2$f_0$/n (n=1,2,3,...). While such parametric resonance is well known in mechanical, superconductive, and quantum systems, in magnetic and spintronic systems only the lowest (n=1) parametric resonance at double the spin wave mode frequency $f_p$=2$f_0$ was thoroughly studied and explored. Here, using a theoretical analysis based on both micromagnetic simulations and an analytical model, we show the emergence of resonances at fractional frequencies $f_p$=2$f_0$/n (with n>10) in spintronic diodes driven by the simultaneous action of ac spin-transfer torque (STT, current densities < $10^6$ A/cm2) and voltage-controlled magnetic anisotropy (VCMA, effective anisotropy fields < 50 mT). The analytical model shows that parametric magnetization dynamics is irreducible to the standard Mathieu model of a parametric oscillator and demonstrates the crucial role of VCMA-driven mode frequency modulation: together with parametric coupling, it results in higher-order odd (n=3,5,7,...) fractional resonances, observed above certain VCMA pumping threshold, while simultaneous action with linear STT drive produces thresholdless even (n=4,6,8,...) resonances. This higher-order parametric dynamics is not restricted to VCMA pumping and opens new directions for the application of spintronic diodes for nonlinear signal processing and electromagnetic energy harvesting.

cond-mat.mes-hall↗

arXiv2026

A scalable and resource-efficient pipelined p-computer for probabilistic Ising machines

Probabilistic Ising machines (PIMs) based on probabilistic bits offer a hardware-friendly route to solve combinatorial optimization problems, but most digital implementations achieve high throughput by exploiting sparse interactions. This limits their applicability to dense problems, for which memory bandwidth and data movement become the dominant bottlenecks. Here, we show a resource-efficient pipelined Field-Programmable Gate Array architecture enabling high-throughput execution of fully-connected PIMs while maintaining scalability and modularity. This architecture design combines a deeply pipelined (>20 stages) probabilistic bit update path, which overlaps spin evaluation and local-field updates, with a bandwidth-aware on-chip memory organization for the coupling and bias matrices. The architecture supports 512 p-bits with 16-bit fixed-point coefficients and 1024 and 2048 p-bits with 10-bit and 2-bit coefficients, respectively, and operates at up to 300 MHz. At fixed degree of parallelization, it delivers an order-of-magnitude higher update rate than an optimized non-pipelined baseline, while improving the time-area trade-off for dense workloads. Validation on portfolio optimization and low-density parity-check decoding shows close agreement with software references and substantial reductions in time-to-solution relative to the non-pipelined design, establishing pipelining as an effective route to scalable digital probabilistic computing for dense optimization problems.

eess.SY↗

arXiv2026

A GPU-based Solver for Polarization Dynamics in Ferroelectric Materials

Ferroelectric materials can be used for the development of multiple device concepts combining non-volatility, small dimensions, low-power actuation, and electrical tunability. Such development demands efficient and precise design of simulation tools describing the polarization texture. However, most existing ferroelectric solvers are CPU-based and rely on simplified electrostatic treatments and reduced-dimensional representations of the polarization field. These approximations limit their ability to capture finite-size and boundary effects and restrict the range of domain structures and domain walls that can be realistically simulated. Here, we present a fully GPU (graphics processing units)-accelerated and scalable numerical solver, named PETASPIN_microelectrics, for computing the full polarization vector field of ferroelectric systems using the Ginzburg-Landau formalism. Our solver incorporates an optimized and validated calculation of the full electrostatic field and enables the parallel execution of multiple simulations. We systematically validated the solver with several benchmark problems, including phase transitions in BaTiO3 and ferroelectric domain wall profiles. Our simulations reproduce temperature-driven hysteretic phase transitions in BaTiO3. We also reproduce hysteresis loops and demonstrate stabilization of a three-dimensional hybrid skyrmion in a PbTiO3/SrTiO3 bilayer system. Our results show quantitative agreement with predictions from an analytical theory and prior experimental studies. The proposed solver provides an efficient, accurate platform for large-scale simulations of ferroelectric materials including stabilization of topological textures supporting predictive modeling for next-generation of ferroelectric device design.

cond-mat.mtrl-sci↗

arXiv2025

Adaptive Ising machine based on phase-locking of an auto-oscillator to a bi-harmonic external driving with noise

We introduce a universal theory of phase auto-oscillators driven by a bi harmonic signal (having frequency components close to single and double of the free-running oscillator frequency) with noise. With it, we show how deterministic phase locking and stochastic phase slips can be continuously tuned by varying the relative amplitudes and frequencies of the driving components. Using, as an example, a spin-torque nano-oscillator, we numerically validate this theory by implementing a deterministic Ising machine paradigm, a probabilistic one, and dual-mode operation of the two. This demonstration introduces the concept of adaptive Ising machines (AIM), a unified oscillator-based architecture that dynamically combines both regimes within the same hardware platform by properly tuning the amplitudes of the bi-harmonic driving relative to the noise strength. Benchmarking on different classes of combinatorial optimization problems, the AIM exhibits complementary performance compared to oscillator based Ising machines and probabilistic Ising machines, with adaptability to the specific problem class. This work introduces the first OIM capable of transitioning between deterministic and probabilistic computation taking advantage of a proper design of the trade-off between the strength of phase-locking of an auto-oscillator to a bi harmonic external driving and noise, opening a path toward scalable, CMOS compatible hardware for hybrid optimization and inference.

cond-mat.mes-hall↗

arXiv2025

Spintronic temperature nanosensor based on the resonance response of a skyrmion-hosting magnetic tunnel junction

The increasing need for efficient thermal management in nanoelectronics requires innovative thermal sensing solutions, as conventional sensors often exhibit nonlinear responses, low sensitivity, and complex calibration. We predict a temperature dependence in the response of existing skyrmion based spintronic diodes and propose their use as nanoscale thermal sensors. These devices leverage magnetic skyrmions topologically protected spin textures known for their robustness, nanoscale dimensions, and low power dynamics. We demonstrate high thermal sensitivity with a linear temperature response over a wide range. This linearity, observed in both the amplitude and frequency of the skyrmion excitation, ensures redundancy that enables precise and reliable temperature measurement. In addition, the use of multilayer systems enhances the sensitivity and robustness of the device. These results provide a foundation for skyrmion-based caloritronic devices with promising applications in spintronic sensors, thermal management, nanoelectronics, and skyrmion-caloritronics.

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arXiv2025

Skyrmions in Nanotechnology: Fundamental Properties, Experimental Advances, and Emerging Applications

Skyrmions, topologically protected textures, have been observed in different fields of nanotechnology and have emerged as promising candidates for different applications due to their topological stability, low-power operation, and dynamic response to external stimuli. First introduced in particle physics, skyrmions have since been observed in different condensed matter fields, including magnetism, ferroelectricity, photonics, and acoustics. Their unique topological properties enable robust manipulation and detection, paving the way for innovative applications in room temperature sensing, storage, and computing. Recent advances in materials engineering and device integration have demonstrated several strategies for an efficient manipulation of skyrmions, addressing key challenges in their practical implementation. In this review, we summarize the state-of-the-art research on skyrmions across different platforms, highlighting their fundamental properties and characteristics, recent experimental breakthroughs, and technological potential. We present future perspectives and remaining challenges, emphasizing the interdisciplinary impact of skyrmions on nanotechnology.

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arXiv2024

Nanoscale spin rectifiers for harvesting ambient radiofrequency energy

Radiofrequency harvesting using ambient wireless energy could be used to reduce the carbon footprint of electronic devices. However, ambient radiofrequency energy is weak (less than -20 dBm), and thermodynamic limits and high-frequency parasitic impedance restrict the performance of state-of-the-art radiofrequency rectifiers. Nanoscale spin rectifiers based on magnetic tunnel junctions have recently demonstrated high sensitivity, but suffer from a low a.c.-to-d.c. conversion efficiency (less than 1%). Here, we report a sensitive spin rectifier rectenna that can harvest ambient radiofrequency signals between -62 and -20 dBm. We also develop an on-chip co-planar waveguide-based spin rectifier array with a large zero-bias sensitivity (around 34,500 mV/mW) and high efficiency (7.81%). Self-parametric excitation driven by voltage-controlled magnetic anisotropy is a key mechanism that contributes to the performance of the spin-rectifier array. We show that these spin rectifiers can wirelessly power a sensor at a radiofrequency power of -27 dBm.

cond-mat.mtrl-sci↗

arXiv2024

Skyrmions in synthetic antiferromagnet nanorings for electrical signal generation

Current-driven magnetic skyrmions show promise as carriers of information bits in racetrack magnetic memory applications. Specifically, the utilization of skyrmions in synthetic antiferromagnetic (SAF) systems is highly attractive due to the potential to suppress the Skyrmion Hall effect, which causes a transverse displacement of driven skyrmions relative to the drift direction. In this study, we demonstrate, through analytical calculations and micromagnetic simulations, that in the case of a nanoring geometry, current-driven skyrmions achieve a stable circular motion with a constant frequency, which is a prerequisite for a skyrmion-based clock device. Notably, the operational frequency in a SAF nanoring surpasses that in a bilayer ferromagnetic-heavy metal nanoring and lies in the GHz regime for current densities of 20 MA/cm^2. We also find that the performance of skyrmions in SAF nanorings is comparable to that of radial Neel domain walls for low current densities (approximately 15 MA/cm^2) and low skyrmion densities (Nsk~6). Additionally, we introduce a novel skyrmionic three-phase AC alternator based on a SAF nanoring, which operates at frequencies in the GHz regime. Our findings underscore the potential of SAF nanorings as constituent materials in clock devices with tunable frequencies operating in the GHz regime

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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↗

arXiv2022

Tuning the coexistence regime of incomplete and tubular skyrmions in ferro/ferri/ferromagnetic trilayers

The development of skyrmionic devices requires a suitable tuning of material parameters in order to stabilize skyrmions and control their density. It has been demonstrated recently that different skyrmion types can be simultaneously stabilized at room temperature in heterostructures involving ferromagnets, ferrimagnets and heavy metals, offering a new platform of coding binary information in the type of skyrmion instead of the presence/absence of skyrmions. Here, we tune the energy landscape of the two skyrmion types in such heterostructures by engineering the geometrical and material parameters of the individual layers. We find that a fine adjustment of the ferromagnetic layer thickness and thus its magnetic anisotropy, allows the trilayer system to support either one of the skyrmion types or the coexistence of both and with varying densities.

cond-mat.mtrl-sci↗

arXiv2022

Temperature gradient-driven magnetic skyrmion motion

The static and dynamic properties of skyrmions have recently received increased attention due to the potential application of skyrmions as information carriers and for unconventional computing. While the current-driven dynamics has been explored deeply, both theoretically and experimentally, the theory of temperature gradient-induced dynamics - Skyrmion-Caloritronics - is still at its early stages of development. Here, we move the topic forward by identifying the role of entropic torques due to the temperature dependence of magnetic parameters. Our results show that, skyrmions move towards higher temperatures in single-layer ferromagnets with interfacial Dzyaloshinski-Moriya interactions, whereas, in multilayers, they move to lower temperatures. We analytically and numerically demonstrate that the opposite behaviors are due to different scaling relations of the material parameters as well as a non-negligible magnetostatic field gradient in multilayers. We also find a spatially dependent skyrmion Hall angle in multilayers hosting hybrid skyrmions due to variations of the thickness dependent chirality as the skyrmion moves along the temperature gradient.

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arXiv2022

Computing with injection-locked spintronic diodes

Spintronic diodes (STDs) are emerging as a technology for the realization of high-performance microwave detectors. The key advantages of such devices are their high sensitivity, capability to work at low input power, and compactness. In this work, we show a possible use of STDs for neuromorphic computing expanding the realm of their functionalities to implement analog multiplication, which is a key operation in convolutional neural networks (CNN). In particular, we introduce the concept of degree of rectification (DOR) in injection-locked STDs. Micromagnetic simulations are used to design and identify the working range of the STDs for the implementation of the DOR. Previous experimental data confirm the applicability of the proposed solution, which is tested in image processing and in a CNN that recognizes handwritten digits.

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arXiv2022

Reliability of Neural Networks Based on Spintronic Neurons

Spintronic technology is emerging as a direction for the hardware implementation of neurons and synapses of neuromorphic architectures. In particular, a single spintronic device can be used to implement the nonlinear activation function of neurons. Here, we propose how to implement spintronic neurons with a sigmoidal and ReLU-like activation functions. We then perform a numerical experiment showing the robustness of neural networks made by spintronic neurons all having different activation functions to emulate device-to-device variations in a possible hardware implementation of the network. Therefore, we consider a vanilla neural network implemented to recognize the categories of the Mixed National Institute of Standards and Technology database, and we show an average accuracy of 98.87 % in the test dataset which is very close to the 98.89% as obtained for the ideal case (all neurons have the same sigmoid activation function). Similar results are also obtained with neurons having a ReLU-like activation function.

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arXiv2021

Perspectives on spintronic diodes

Spintronic diodes are emerging as disruptive candidates for impacting several technological applications ranging from the Internet of Things to Artificial Intelligence. In this letter, an overview of the recent achievements on spintronic diodes is briefly presented, underling the major breakthroughs that have led these devices to have the largest sensitivity measured up to date for a diode. For each class of spintronic diodes (passive, active, resonant, non-resonant), we indicate the remaining developments to improve the performances as well as the future directions. We also dedicate the last part of this perspective to new ideas for developing spintronic diodes in multiphysics systems by combining 2-dimensional materials and antiferromagnets.

cond-mat.mes-hall↗

arXiv2021

Role of magnetic skyrmions for the solution of the shortest path problem

Magnetic skyrmions are emerging as key elements of unconventional operations having unique properties such as small size and low current manipulation. In particular, it is possible to design skyrmion-based neurons and synapses for neuromorphic computing in devices where skyrmions move along the current direction (zero skyrmion Hall angle). Here, we show that, for a given graph, skyrmions can be used in optimization problems facing the calculation of the shortest path. Our tests show a solution with the same path length as computed with Algorithm. In addition, we also discuss how skyrmions act as positive feedback on this type of problem giving rise to a self-reinforcement of the path which is a possible solution.

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arXiv2020

Coexistence of distinct skyrmion phases observed in hybrid ferromagnetic/ferrimagnetic multilayers

Materials hosting magnetic skyrmions at room temperature could enable new computing architectures as well as compact and energetically efficient magnetic storage such as racetrack memories. In a racetrack device, information is coded by the presence/absence of magnetic skyrmions forming a chain that is moved through the device. The skyrmion Hall effect that would eventually lead to an annihilation of the skyrmions at the edges of the racetrack can be suppressed for example by anti-ferromagnetically-coupled skyrmions. However, avoiding modifications of the inter-skyrmion distances in the racetrack remains challenging. As a solution to this issue, a chain of bits could also be encoded by two different solitons such as a skyrmion and a chiral bobber. The major limitation of this approach is that it has solely been realized in B20-type single crystalline material systems that support skyrmions only at low temperatures, thus hindering the efficacy for future applications. Here we demonstrate that a hybrid ferro/ferri/ferromagnetic multilayer system can host two distinct skyrmion phases at room temperature. By matching quantitative magnetic force microscopy data with micromagnetic simulations, we reveal that the two phases represent tubular skyrmions and partial skyrmions (similar to skyrmion bobbers). Furthermore, the tubular skyrmion can be converted into a partial skyrmion. Such multilayer systems may thus serve as a platform for designing skyrmion memory applications using distinct types of skyrmions and potentially for storing information using the vertical dimension in a thin film device.

cond-mat.mtrl-sci↗

arXiv2020

Domain periodicity in an easy-plane antiferromagnet with Dzyaloshinskii-Moriya interaction

Antiferromagnetic spintronics is a promising emerging paradigm to develop high-performance computing and communications devices. From a theoretical point of view, it is important to implement simulation tools that can support a data-driven development of materials having specific properties for particular applications. Here, we present a study focusing on antiferromagnetic materials having an easy-plane anisotropy and interfacial Dzyaloshinskii-Moriya interaction (IDMI). An analytical theory is developed and benchmarked against full numerical micromagnetic simulations, describing the main properties of the ground state in antiferromagnets and how it is possible to estimate the IDMI from experimental measurements. The effect of the IDMI on the electrical switching dynamics of the antiferromagnetic element is also analyzed. Our theoretical results can be used for the design of multi-terminal heavy metal/antiferromagnet memory devices.

cond-mat.mes-hall↗

arXiv2018

Micromagnetic understanding of the skyrmion Hall angle current dependence in perpendicular magnetized ferromagnets

The understanding of the dynamical properties of skyrmion is a fundamental aspect for the realization of a competitive skyrmion based technology beyond CMOS. Most of the theoretical approaches are based on the approximation of a rigid skyrmion. However, thermal fluctuations can drive a continuous change of the skyrmion size via the excitation of thermal modes. Here, by taking advantage of the Hilbert-Huang transform, we demonstrate that at least two thermal modes can be excited which are non-stationary in time. In addition, one limit of the rigid skyrmion approximation is that this hypothesis does not allow for correctly describing the recent experimental evidence of skyrmion Hall angle dependence on the amplitude of the driving force, which is proportional to the injected current. In this work, we show that, in an ideal sample, the combined effect of field-like and damping-like torques on a breathing skyrmion can indeed give rise to such a current dependent skyrmion Hall angle. While here we design and control the breathing mode of the skyrmion, our results can be linked to the experiments by considering that the thermal fluctuations and/or disorder can excite the breathing mode. We also propose an experiment to validate our findings.

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