Module 1 (Introduction): Brief exposition to different spin-based computing schemes provided, Advantages of such computing schemes over conventional-transistor-based digital computing schemes explained
Module 2 (Basics of Spin Physics): Single-domain model of a nanomagnet, Micromagnetics, Landau Lifschitz Gilbert equation modified with spin-transfer and spin-orbit torque terms, magnetic switching, domain-wall motion, spin oscillation
Module 3 (Basics of Computability Theory): Deterministic and Non-Deterministic Finite Automata, Regular Languages, Deterministic and Non-Deterministic Turing machines, Decidable and Undecidable Languages with Examples, Definition of an algorithm with respect to a Turing machines
Module 4 (Basics of Complexity Theory): Defining Complexity, Class P and NP, NP-Complete Problems, Space Complexity
Module 5 (Spin-based computing within the Von Neumann paradigm): Design of magnetic random access memory arrays, Nanomagnetic Logic, All Spin Logic
Module 6 (Crossbar-Array-Based Computing and Implementation through Spintronics): Sub-topics: Memory-Computing Intertwining through Crossbar Arrays of Synaptic Devices, Implementation of neural-network/ machine-learning algorithms on such arrays, Complexity analysis of such implementation, Spintronics-based implementations of crossbar arrays through domain-wall devices
Module 7 (Oscillator-Based Computing and Implementation through Spintronics): Kuramoto model for synchronization of oscillators, Oscillator-synchronization-based computing, Complexity analysis of such an algorithm, Implementation through spintronic oscillator
Module 8 (Probabilistic Computing and Implementation through Spintronics): Probabilistic computing basics, Complexity Analysis of Probabilistic Computing Algorithms, Implementation through stochastic spintronic devices
Text/References
- Michael Sipser, Introduction to the Theory of Computation, Cengage, 2013
- Stephen Blundell, Magnetism in Condensed Matter, OUP, 2011
- Spin Current, edited by Maekawa, Valenzula, Saitoh, and Kimura, OUP, 2017
- Review paper: Neuromorphic spintronics, by Jullie Grollier et al., Nature Electronics, vol. 3, 2020 (DOI:https://www.nature.com/articles/s41928-019-0360-9)
