Abhinav Parihar

Learn More
1Department of Electrical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA, 2School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA, 3Department of Materials Science and Engineering, Cornell University, Ithaca, New York 14853, USA, 4Department of Materials Science and(More)
Articles you may be interested in Fully synchronous solutions and the synchronization phase transition for the finite-N Kuramoto model Micromagnetic study of phase-locking in spin-transfer nano-oscillators driven by currents and ac fields Electrical oscillations induced by the metal-insulator transition in VO 2 Computing with networks of synchronous(More)
Harnessing the computational capabilities of dynamical systems has attracted the attention of scientists and engineers form varied technical disciplines over decades. The time evolution of coupled, non-linear synchronous oscillatory systems has led to active research in understanding their dynamical properties and exploring their applications in(More)
As complementary metal–oxide–semiconductor (CMOS) scaling continues to offer insurmountable challenges, questions about the performance capabilities of Boolean, digital machine based on Von-Neumann architecture, when operated within a power budget, have also surfaced. Research has started in earnest to identify alternative computing paradigms that provide(More)
While Boolean logic has been the backbone of digital information processing, there exist classes of computationally hard problems wherein this paradigm is fundamentally inefficient. Vertex coloring of graphs, belonging to the class of combinatorial optimization, represents one such problem. It is well studied for its applications in data sciences, life(More)
In this paper we review recent work on novel computing paradigms using coupled oscillatory dynamical systems. We explore systems of relaxation oscillators based on linear state transitioning devices, which switch between two discrete states with hysteresis. By harnessing the dynamics of complex, connected systems we embrace the philosophy of “let physics do(More)
A stochastic neuron, a key hardware kernel for implementing stochastic neural networks, is constructed using an insulator-metal-transition (IMT) device based on electrically induced phase-transition in series with a tunable resistance. We show that such an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron. Spiking statistics(More)
In this paper we review recent work on computational paradigms involving coupled relaxation oscillators built using metal-insulator-transition (MIT) devices. Such oscillators made using MIT devices based on Vanadium-Dioxide thin films are very compact and can be realized in hardware. Networks of such oscillators have interesting phase and frequency dynamics(More)