470 citations · 1.3k across the 24 of their papers we have counts for
25 papers
Stochastic binary networks with asymmetric and time-delayed interactions
Hantao Zhang, Sidra Gibeault, Matthew W. Daniels +4
Stochastic binary networks are widely used to describe collective dynamics in complex systems and to perform neuromorphic computation, yet realistic networks often contain both asy…
Strain effects on the fluctuation properties in noncollinear antiferromagnets: a first-principles and macrospin-based study
Mohammad M. Rahman, Farzad Mahfouzi, Matthew W. Daniels +1
We present a theoretical investigation of epitaxial strain effects on the magnetic fluctuation properties of MnSn noncollinear antiferromagnets. Employing density functional th…
Sampling from exponential distributions in the time domain with superparamagnetic tunnel junctions
Temitayo N. Adeyeye, Sidra Gibeault, Daniel P. Lathrop +8
In the superparamagnetic regime, magnetic tunnel junctions switch between two resistance states due to random thermal fluctuations. The dwell time distribution in each state is exp…
Layer Ensemble Averaging for Improving Memristor-Based Artificial Neural Network Performance
Osama Yousuf, Brian Hoskins, Karthick Ramu +8
Artificial neural networks have advanced due to scaling dimensions, but conventional computing faces inefficiency due to the von Neumann bottleneck. In-memory computation architect…
Measurement-driven Langevin modeling of superparamagnetic tunnel junctions
Liam A. Pocher, Temitayo N. Adeyeye, Sidra Gibeault +7
Superparamagnetic tunnel junctions are important devices for a range of emerging technologies, but most existing compact models capture only their mean switching rates. Capturing q…
Programmable electrical coupling between stochastic magnetic tunnel junctions
Sidra Gibeault, Temitayo N. Adeyeye, Liam A. Pocher +9
Superparamagnetic tunnel junctions (SMTJs) are promising sources of randomness for compact and energy efficient implementations of probabilistic computing techniques. Augmenting an…