9 papers
Biologically Realistic Dynamics for Nonlinear Classification in CMOS+X Neurons
Steven Louis, Hannah Bradley, Artem Litvinenko +3
Spiking neural networks encode information in spike timing and offer a pathway toward energy efficient artificial intelligence. However, a key challenge in spiking neural networks…
Temporal magnon-qubit Mach-Zehnder interferometer
Cody Trevillian, Steven Louis, Vasyl Tyberkevych
A temporal magnon-qubit Mach-Zehnder (MZ) interferometer is proposed. The interferometer is based on controllable entanglement of a microwave qubit and a magnonic state, achieved b…
Time-Domain Two-Magnon Interference Enabled by a Tunable Beamsplitter
Cody Trevillian, Steven Louis, Vasyl Tyberkevych
This letter presents a model system for controllable two-magnon interference in the time domain. This two-magnon interference, i.e., a magnonic analog to the photonic Hong-Ou-Mande…
A CMOS+X Spiking Neuron With On-Chip Machine Learning
Steven Louis, Matthew Blake Abramson, Hannah Bradley +8
We present the design and numerical simulation of a spiking neuron in a proof-of-concept model of on-chip machine learning. Built within the CMOS+X framework, the spiking neuron co…
Generation of Ultra-Broadband Frequency Comb in Strongly Bistable Nonlinear Magnonic Resonator
Yu Jiang, Vasyl Tyberkevych, Yizhong Huang +4
Magnonic frequency combs (MFCs) offer a promising route to compact, energy-efficient platforms for on-chip coherent microwave signal generation and processing. Conventional on-chip…
Adaptive Ising machine based on phase-locking of an auto-oscillator to a bi-harmonic external driving with noise
Eleonora Raimondo, Andrea Grimaldi, Vasyl Tyberkevych +6
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 freq…