arXiv subjects

Shun Kanai

Publications and source records attributed to Shun Kanai.

17 recordsLinked to original sources

arXiv2026

Multi-rotational switching in a noncollinear antiferromagnet by spin-orbit torque

Spintronics has advanced through discoveries of various electrically-driven spin dynamics in nanomagnets. Here, we report a novel switching dynamics of spin systems driven by spin-orbit torque, using a noncollinear antiferromagnetic nanodot. With electric pulses spanning a wide range of durations and amplitudes, we find an unconventional insensitivity of a threshold current density to pulse duration in switch-back events. This observation is attributed to a previously unrecognized process, in which the noncollinear antiferromagnetic order undergoes multiple rotations before completing reversal, a phenomenon we term multi-rotational switching. Our theoretical analysis reveals that multi-rotational switching arises from the interplay of three key factors: current-driven coherent rotation of the noncollinear antiferromagnetic order, field-induced reorientation of the uncompensated net magnetization, and thermal fluctuations. These findings establish a microscopic mechanism governing current-induced switching in noncollinear antiferromagnets, a topic of growing interest for next-generation spintronics technologies, opening a new route to controlling antiferromagnetic order in nanodevices.

cond-mat.mes-hall↗

arXiv2026

CMOS-integrated superparamagnetic tunnel junction-based p-bit

Probabilistic computers offer promising solutions for computationally hard problems in domains such as combinatorial optimization and machine learning. A key building block in these systems is the probabilistic bit (p-bit), which relies on superparamagnetic tunnel junctions (sMTJs) as its source of randomness. A challenging threshold to cross for scaling sMTJ-based p-bit systems is integration of sMTJs with CMOS technology. In this work, we present experimental results of a p-bit unit cell using sMTJs integrated with 130 nm CMOS technology and demonstrate that the sMTJ's resistance fluctuations can generate a corresponding fluctuating digital output voltage which is tunable via the input voltage. These findings establish the feasibility of CMOS-compatible, sMTJ-based probabilistic circuits and mark a key step toward scalable hardware for real-world probabilistic computing applications.

cs.ET↗

arXiv2025

Strategies to search for two-dimensional materials with long spin qubit coherence time

Two-dimensional (2D) materials that can host qubits with long spin coherence time (T2) have the distinct advantage of integrating easily with existing microelectronic and photonic platforms, making them attractive for designing novel quantum devices with enhanced performance. However, the relative lack of 2D materials as spin qubit hosts, as well as appropriate substrates that can help maintain long T2, necessitates a strategy to search for candidates with robust spin coherence. Here, we develop a high-throughput computational workflow to predict the nuclear spin bath-driven qubit decoherence and T2 in 2D materials and heterostructures. We initially screen 1173 2D materials and find 190 monolayers with T2 > 1 ms, higher than that of naturally-abundant diamond. We then construct 1554 lattice-commensurate heterostructures between high-T2 2D materials and select 3D substrates, and we find that T2 is generally lower in a heterostructure than in the bare 2D host material; however, low-noise substrates (such as CeO2 and CaO) can help maintain high T2. To further accelerate the material screening effort, we derive analytical models that enable rapid predictions of T2 for 2D materials and heterotructures. The models offer a simple, yet quantitative, way to determine the relative contributions to decoherence from the nuclear spin baths of the 2D host and substrate in a heterostructural system. By developing a high-throughput workflow and analytical models, we expand the genome of 2D materials and their spin coherence times for the development of spin qubit platforms.

quant-ph↗

arXiv2025

Size dependence of the properties of synthetic-antiferromagnet-based stochastic magnetic tunnel junctions for probabilistic computing

Stochastic magnetic tunnel junctions (s-MTJs) are core components for spintronics-based probabilistic computing (p-computing), a promising candidate for energy-efficient unconventional computing. To achieve reliable performance under practical conditions, the use of a synthetic antiferromagnetic (SAF) free-layer configuration was proposed due to its enhanced tolerance to magnetic field perturbations. For engineering the SAF s-MTJs, we systematically investigate the properties of the SAF s-MTJs as a function of the junction size. We observe that decreasing junction size leads to shorter relaxation times, enhanced magnetic field robustness, and enhanced insensitivity to bias voltage. These findings provide key insights toward high-performance p-computers with reliable operation.

physics.app-ph↗

arXiv2025

Dynamical control of random telegraph noise in magnetic tunnel junctions

Faster random telegraph noise (RTN) in magnetic tunnel junctions (MTJs) would be beneficial for probabilistic computing applications. However, the interactions between the macrospin and spin waves with finite wave numbers reduce the RTN attempt frequency. We theoretically show that mode-selective heating and cooling by parametric excitation of Kittel mode or propagating spin waves can substantially increase or decrease the RTN frequency, respectively, and propose a nonlinear cooling mechanism that accelerates the switching dynamics. We outline experimental pathways to characterize the nonlinear processes that maximize the operation speed of MTJ-based probabilistic (p-) bits.

cond-mat.mes-hall↗

arXiv2025

Electrically Tunable Picosecond-scale Octupole Fluctuations in Chiral Antiferromagnets

We present a theory for the relaxation time of the octupole order parameter in nanoscale chiral antiferromagnets (AFMs) coupled to thermal baths and spin injection sources. Using stochastic spin dynamics simulations, we demonstrate that the octupole moment relaxes through two distinct mechanisms$-$escape over a barrier and precessional dephasing$-$as the barrier for octupole fluctuations is lowered relative to the thermal energy. Notably, the octupole moment relaxes orders of magnitude faster than the typical dipolar order parameters, reaching picosecond timescales. By combining Langer's theory with an effective low-energy description of octupole dynamics in chiral AFMs, we derive analytical expressions for the relaxation times. We find that relaxation in chiral AFMs parallels dipole relaxation in XY magnets, with exchange fields serving the role of the dipole fields. Further, by drawing on the analogy between order parameter dynamics in XY magnets under spin injection and current-biased Josephson junctions, we propose a new scheme for electrically tuning the octupole relaxation times. Our work offers fundamental insights for the development of next-generation spintronic devices that harness octupole order parameters for information encoding, especially in octupole-based probabilistic computing.

cond-mat.mes-hall↗

arXiv2024

Effect of nonlinear magnon interactions on the stochastic magnetization switching

Telegraph noise caused by frequent switching of the magnetization in small magnetic devices has become a useful resource for probabilistic computing. Conventional theories have been based on a linearization of the fluctuations at the extrema of the magnetic free energy. We show theoretically that the non-linearities, specifically four-magnon scatterings, reduce the equilibrium fluctuation amplitude of the magnetization as well as the switching frequencies between local minima via the decay of the homogeneous Kittel mode into two spin waves with opposite momenta. Selectively suppressing the effective temperature of the finite-k spin waves, or reducing the radius of a thin magnetic disk enhance the switching frequency and improve performance of magnetic tunnel junctions in probabilistic computing applications.

cond-mat.mes-hall↗

arXiv2024

Voltage-insensitive stochastic magnetic tunnel junctions with double free layers

Stochastic magnetic tunnel junctions (s-MTJ) is a promising component of probabilistic bit (p-bit), which plays a pivotal role in probabilistic computers. For a standard cell structure of the p-bit, s-MTJ is desired to be insensitive to voltage across the junction over several hundred millivolts. In conventional s-MTJs with a reference layer having a fixed magnetization direction, however, the stochastic output significantly varies with the voltage due to spin-transfer torque (STT) acting on the stochastic free layer. In this work, we study a s-MTJ with a "double-free-layer" design theoretically proposed earlier, in which the fixed reference layer of the conventional structure is replaced by another stochastic free layer, effectively mitigating the influence of STT on the stochastic output. We show that the key device property characterized by the ratio of relaxation times between the high- and low-resistance states is one to two orders of magnitude less sensitive to bias voltage variations compared to conventional s-MTJs when the top and bottom free layers are designed to possess the same effective thickness. This work opens a pathway for reliable, nanosecond-operation, high-output, and scalable spintronics-based p-bits.

cond-mat.mes-hall↗

arXiv2024

Double-Free-Layer Stochastic Magnetic Tunnel Junctions with Synthetic Antiferromagnets

Stochastic magnetic tunnel junctions (sMTJ) using low-barrier nanomagnets have shown promise as fast, energy-efficient, and scalable building blocks for probabilistic computing. Despite recent experimental and theoretical progress, sMTJs exhibiting the ideal characteristics necessary for probabilistic bits (p-bit) are still lacking. Ideally, the sMTJs should have (a) voltage bias independence preventing read disturbance (b) uniform randomness in the magnetization angle between the free layers, and (c) fast fluctuations without requiring external magnetic fields while being robust to magnetic field perturbations. Here, we propose a new design satisfying all of these requirements, using double-free-layer sMTJs with synthetic antiferromagnets (SAF). We evaluate the proposed sMTJ design with experimentally benchmarked spin-circuit models accounting for transport physics, coupled with the stochastic Landau-Lifshitz-Gilbert equation for magnetization dynamics. We find that the use of low-barrier SAF layers reduces dipolar coupling, achieving uncorrelated fluctuations at zero-magnetic field surviving up to diameters exceeding ($D\approx 100$ nm) if the nanomagnets can be made thin enough ($\approx 1$-$2$ nm). The double-free-layer structure retains bias-independence and the circular nature of the nanomagnets provides near-uniform randomness with fast fluctuations. Combining our full sMTJ model with advanced transistor models, we estimate the energy to generate a random bit as $\approx$ 3.6 fJ, with fluctuation rates of $\approx$ 3.3 GHz per p-bit. Our results will guide the experimental development of superior stochastic magnetic tunnel junctions for large-scale and energy-efficient probabilistic computation for problems relevant to machine learning and artificial intelligence.

cond-mat.mes-hall↗

arXiv2024

CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning

Extending Moore's law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. One important class of problems involve sampling-based Monte Carlo algorithms used in probabilistic machine learning, optimization, and quantum simulation. Here, we combine stochastic magnetic tunnel junction (sMTJ)-based probabilistic bits (p-bits) with Field Programmable Gate Arrays (FPGA) to create an energy-efficient CMOS + X (X = sMTJ) prototype. This setup shows how asynchronously driven CMOS circuits controlled by sMTJs can perform probabilistic inference and learning by leveraging the algorithmic update-order-invariance of Gibbs sampling. We show how the stochasticity of sMTJs can augment low-quality random number generators (RNG). Detailed transistor-level comparisons reveal that sMTJ-based p-bits can replace up to 10,000 CMOS transistors while dissipating two orders of magnitude less energy. Integrated versions of our approach can advance probabilistic computing involving deep Boltzmann machines and other energy-based learning algorithms with extremely high throughput and energy efficiency.

cond-mat.mes-hall↗

arXiv2023

A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms

The transistor celebrated its 75${}^\text{th}$ birthday in 2022. The continued scaling of the transistor defined by Moore's Law continues, albeit at a slower pace. Meanwhile, computing demands and energy consumption required by modern artificial intelligence (AI) algorithms have skyrocketed. As an alternative to scaling transistors for general-purpose computing, the integration of transistors with unconventional technologies has emerged as a promising path for domain-specific computing. In this article, we provide a full-stack review of probabilistic computing with p-bits as a representative example of the energy-efficient and domain-specific computing movement. We argue that p-bits could be used to build energy-efficient probabilistic systems, tailored for probabilistic algorithms and applications. From hardware, architecture, and algorithmic perspectives, we outline the main applications of probabilistic computers ranging from probabilistic machine learning and AI to combinatorial optimization and quantum simulation. Combining emerging nanodevices with the existing CMOS ecosystem will lead to probabilistic computers with orders of magnitude improvements in energy efficiency and probabilistic sampling, potentially unlocking previously unexplored regimes for powerful probabilistic algorithms.

cs.ET↗

arXiv2021

Generalized scaling of spin qubit coherence in over 12,000 host materials

Spin defect centers with long quantum coherence times ($T_2$) are key solid-state platforms for a variety of quantum applications. Recently, cluster correlation expansion (CCE) techniques have emerged as a powerful tool to simulate the $T_2$ of defect electron spins in these solid-state systems with good accuracy. Here, based on CCE, we uncover an algebraic expression for $T_2$ generalized for host compounds with dilute nuclear spin baths, which enables a quantitative and comprehensive materials exploration with a near instantaneous estimate of the coherence. We investigate more than 12,000 host compounds at natural isotopic abundance, and find that silicon carbide (SiC), a prominent widegap semiconductor for quantum applications, possesses the longest coherence times among widegap non-chalcogenides. In addition, more than 700 chalcogenides are shown to possess a longer $T_2$ than SiC. We suggest new potential host compounds with promisingly long $T_2$ up to 47 ms, and pave the way to explore unprecedented functional materials for quantum applications.

quant-ph↗

arXiv2020

Qubit guidelines for solid-state spin defects

Defects with associated electron and nuclear spins in solid-state materials have a long history relevant to quantum information science going back to the first spin echo experiments with silicon dopants in the 1950s. Since the turn of the century, the field has rapidly spread to a vast array of defects and host crystals applicable to quantum communication, sensing, and computing. From simple spin resonance to long-distance remote entanglement, the complexity of working with spin defects is fast advancing, and requires an in-depth understanding of their spin, optical, charge, and material properties in this modern context. This is especially critical for discovering new relevant systems dedicated to specific quantum applications. In this review, we therefore expand upon all the key components with an emphasis on the properties of defects and the host material, on engineering opportunities and other pathways for improvement. Finally, this review aims to be as defect and material agnostic as possible, with some emphasis on optical emitters, providing a broad guideline for the field of solid-state spin defects for quantum information.

quant-ph↗

arXiv2020

Memristive control of mutual SHNO synchronization for neuromorphic computing

Synchronization of large spin Hall nano-oscillators (SHNO) arrays is an appealing approach toward ultra-fast non-conventional computing based on nanoscale coupled oscillator networks. However, for large arrays, interfacing to the network, tuning its individual oscillators, their coupling, and providing built-in memory units for training purposes, remain substantial challenges. Here, we address all these challenges using memristive gating of W/CoFeB/MgO/AlOx based SHNOs. In its high resistance state (HRS), the memristor modulates the perpendicular magnetic anisotropy (PMA) at the CoFeB/MgO interface purely by the applied electric field. In its low resistance state (LRS), and depending on the voltage polarity, the memristor adds/subtracts current to/from the SHNO drive. The operation in both the HRS and LRS affects the SHNO auto-oscillation mode and frequency, which can be tuned up to 28 MHz/V. This tuning allows us to reversibly turn on/off mutual synchronization in chains of four SHNOs. We also demonstrate two individually controlled memristors to tailor both the coupling strength and the frequency of the synchronized state. Memristor gating is therefore an efficient approach to input, tune, and store the state of the SHNO array for any non-conventional computing paradigm, all in one platform.

physics.app-ph↗

arXiv2020

Giant voltage control of spin Hall nano-oscillator damping

Spin Hall nano-oscillators (SHNOs) are emerging spintronic devices for microwave signal generation and oscillator based neuromorphic computing combining nano-scale footprint, fast and ultra-wide microwave frequency tunability, CMOS compatibility, and strong non-linear properties providing robust large-scale mutual synchronization in chains and two-dimensional arrays. While SHNOs can be tuned via magnetic fields and the drive current, neither approach is conducive for individual SHNO control in large arrays. Here, we demonstrate electrically gated W/CoFeB/MgO nano-constrictions in which the voltage-dependent perpendicular magnetic anisotropy, tunes the frequency and, thanks to nano-constriction geometry, drastically modifies the spin-wave localization in the constriction region resulting in a giant 42 % variation of the effective damping over four volts. As a consequence, the SHNO threshold current can be strongly tuned. Our demonstration adds key functionality to nano-constriction SHNOs and paves the way for energy-efficient control of individual oscillators in SHNO chains and arrays for neuromorphic computing.

physics.app-ph↗

arXiv2018

Magnetic and transport properties of Sb2Te3 doped with high concentration of Cr

We report on molecular beam epitaxy and properties of a magnetic topological insulator, Cr doped Sb2Te3. The composition analysis reveals that Cr replaces Sb site, and x-ray diffraction confirms that single phase textured crystal structure can be obtained for (CrxSb1-x)2Te3 with x up to 0.44. Further increase in x results in phase separation or precipitates in the material. The Curie temperature TC increases with x up to 0.44, and reaches to 250 K, which is the highest TC observed till now in magnetically doped topological insulators.

cond-mat.mtrl-sci↗

arXiv2017

Magnetization dynamics and its scattering mechanism in thin CoFeB films with interfacial anisotropy

Studies of magnetization dynamics have incessantly facilitated the discovery of fundamentally novel physical phenomena, making steady headway in the development of magnetic and spintronics devices. The dynamics can be induced and detected electrically, offering new functionalities in advanced electronics at the nanoscale. However, its scattering mechanism is still disputed. Understanding the mechanism in thin films is especially important, because most spintronics devices are made from stacks of multilayers with nanometer thickness. The stacks are known to possess interfacial magnetic anisotropy, a central property for applications, whose influence on the dynamics remains unknown. Here, we investigate the impact of interfacial anisotropy by adopting CoFeB/MgO as a model system. Through systematic and complementary measurements of ferromagnetic resonance (FMR), on a series of thin films, we identify narrower FMR linewidths at higher temperatures. We explicitly rule out the temperature dependence of intrinsic damping as a possible cause, and it is also not expected from existing extrinsic scattering mechanisms for ferromagnets. We ascribe this observation to motional narrowing, an old concept so far neglected in the analyses of FMR spectra. The effect is confirmed to originate from interfacial anisotropy, impacting the practical technology of spin-based nanodevices up to room temperature.

cond-mat.mtrl-sci↗