arXiv subjects

Xueyu Guo

Publications and source records attributed to Xueyu Guo.

6 recordsLinked to original sources

arXiv2026

Integrated magnonic neural circuits based on nonlinear wave neurons

Artificial intelligence is driving intense interest in alternative computing hardware capable of neural information processing beyond conventional charge-based electronics. Among emerging approaches, wave-based computing promises highly parallel and energy-efficient operation, but scalable physical neural hardware has remained elusive because wave systems generally lack cascadable nonlinear neurons with signal regeneration and phase-robust operation. Here we demonstrate integrated magnonic neural circuits based on nonlinear threshold neurons realized in nanoscale yttrium iron garnet waveguides. The neurons perform weighted summation of multiple spin-wave inputs, while a pump-controlled nonlinear activation defines continuously tunable firing thresholds. Owing to deeply nonlinear spin-wave dynamics, the activated neurons emit self-normalized outputs whose intensities are largely independent of the input amplitudes, while nonlinear phase self-adjustment suppresses sensitivity to the relative input phases, enabling deterministic neuron-to-neuron cascading without external signal restoration. We experimentally realize programmable threshold neurons, reconfigurable weighted classification and deterministic cascading between sequential neuronal stages, and further demonstrate reconfigurable physical pattern recognition in a seven-neuron integrated magnonic circuit through experimental classification of the binary letter patterns 'HUST'. These results establish nonlinear magnons as a scalable platform for integrated neural hardware and position nonlinear wave dynamics as a general paradigm for physical neuromorphic computing.

cond-mat.mtrl-sci↗

arXiv2026

True random number generation through stochastic magnonic bistability

True random number generators (TRNGs) underpin modern cryptography, yet existing implementations face fundamental trade-offs between speed, scalability, and entropy quality. Here, we demonstrate that stochastic switching in the bistable regime of spin-wave dynamics provides a physical entropy source for high-quality random number generation. Our magnonic random number generator (mRNG), based on a lithography-patterned microstrip on yttrium iron garnet (YIG), exploits thermal fluctuations near the nonlinear bistable regime to generate random bitstreams that pass all 15 NIST SP 800-22 statistical tests at rates with 20 Mb/s. We implement a random-bit multiplier using synchronized mRNG units and demonstrate scalability to 200-nm-wide nanoscale waveguides, establishing spin-wave bistability as a viable physical entropy source for integrated random number generation.

cond-mat.mtrl-sci↗

arXiv2026

Stimulated Magnonic Frequency Combs

Magnonic frequency combs, characterized by a series of discrete frequency lines, have emerged as a promising frontier in magnon spintronics, with potential applications in advanced information processing and sensing technologies. Although the three-magnon scattering process is widely recognized as a fundamental mechanism for generating these combs, its experimental realization has remained challenging due to the high threshold power and strict conservation of momentum and energy. In this work, we propose a novel mechanism for the stimulated generation of magnonic frequency combs that overcomes these limitations. Our approach offers precise and efficient control over key comb properties, including spacing between spectral lines and the number of lines, marking a significant advancement in the field. We substantiate this mechanism through a robust combination of theoretical modeling, micromagnetic simulations, and experimental validation. This study not only demonstrates the feasibility of our method but also opens new pathways for integrating magnonic frequency combs into practical spintronic devices.

cond-mat.mes-hall↗

arXiv2026

Integrated magnonic chip using cascaded logic

The transistor transformed not only electronics but everyday life, and the integrated circuit - now simply the "chip" - made computation scalable and ubiquitous. Magnonics has long promised a parallel path to low-energy information processing by using spin waves instead of charge. Progress, however, has been limited by two fundamental obstacles: intrinsic attenuation of spin waves and the requirement for precisely normalised output intensity and input phase to ensure reliable logic operation - conditions that are difficult to maintain in large-scale circuits owing to inevitable imperfections. Here, we report an integrated magnonic circuit that overcomes both limitations through engineered nonlinearity in nanoscale yttrium iron garnet waveguides. Nonlinear self-adjustment of the spin wave phase renders logic operation insensitive to the relative phases of the inputs, while a deeply nonlinear, threshold-activated self-normalised excitation restores and standardises the output intensity. Using space-resolved micro-focused Brillouin light scattering, we demonstrate reconfigurable AND, OR and three-input majority gates and realise deterministic cascading across sequential stages, establishing a scalable on-chip logic primitive. The architecture operates with gigahertz frequencies, supports dynamic threshold control for functional reconfiguration, and is compatible with scalable integration, making it attractive for adaptive and neuromorphic computing. By resolving phase-independent operation and signal restoration at the level of device physics, this work advances magnonics from isolated proof-of-concept devices towards integrated magnonic chips that can complement advanced CMOS in energy-constrained computing tasks.

cond-mat.mtrl-sci↗

arXiv2024

Fast switchable unidirectional magnon emitter

Magnon spintronics is an emerging field that explores the use of magnons, the quanta of spin waves in magnetic materials for information processing and communication. Achieving unidirectional information transport with fast switching capability is critical for the development of fast integrated magnonic circuits, which offer significant advantages in high-speed, low-power information processing. However, previous unidirectional information transport has primarily focused on Damon-Eshbach spin wave modes, which are non-switchable as their propagation direction is defined by the direction of the external field and cannot be changed in a short time. Here, we experimentally demonstrate a fast switchable unidirectional magnon emitter in the forward volume spin wave mode by a current-induced asymmetric Oersted field. Our findings reveal significant nonreciprocity and nanosecond switchability, underscoring the potential of the method to advance high-speed spin-wave processing networks.

cond-mat.mes-hall↗

arXiv2024

All-magnonic repeater based on bistability

Bistability, a universal phenomenon found in diverse fields such as biology, chemistry, and physics, describes a scenario in which a system has two stable equilibrium states and resets to one of the two states. The ability to switch between these two states is the basis for a wide range of applications, particularly in memory and logic operations. Here, we present a universal approach to achieve bistable switching in magnonics, the field processing data using spin waves. As an exemplary application, we use magnonic bistability to experimentally demonstrate the still missing magnonic repeater. A pronounced bistable window is observed in a 1um wide magnonic conduit under an external rf drive characterized by two magnonic stable states defined as low and high spin-wave amplitudes. The switching between these two states is realized by another propagating spin wave sent into the rf driven region. This magnonic bistable switching is used to design the magnonic repeater, which receives the original decayed and distorted spin wave and regenerates a new spin wave with amplified amplitude and normalized phase. Our magnonic repeater is proposed to be installed at the inputs of each magnonic logic gate to overcome the spin-wave amplitude degradation and phase distortion during previous propagation and achieve integrated magnonic circuits or magnonic neuromorphic networks.

physics.app-ph↗