Digital computing is based on a deterministic bit with two values, 0 and 1. Quantum computing is based on a q-bit which is a delicate superposition of 0 and 1. This talk draws attention to something in-between that could be viewed as a poor man’s q-bit, namely, a p-bit which is a robust classical entity fluctuating between 0 and 1, and can be built with existing technology to operate at room temperature[1]. Specifically I will present (1) experimental results demonstrating that MRAM technology with small modifications can be used to build p-circuits that implement quantum-inspired optimization algorithms[2], and (2) SPICE simulations showing that p-circuits can be used to emulate a broad class of quantum Hamiltonians[3].

Dr. Supriyo Datta is known for the work of his group on quantum transport which has been widely adopted in the field of nanoelectronics. It combines the non‐equilibrium Green function (NEGF) formalism of many-body physics with the Landauer formalism from mesoscopic physics, and is described in his books. He is also known for innovative proposals that have inspired extensive experimental efforts in molecular electronics, negative capacitance devices and spintronics.

Integrative Data Science Initiative Purdue Quantum Science Engineering Institute, The Chemistry, Physics, and Computer Science Departments at Purdue University Electrical and Computer Engineering at Purdue, Discovery Park, Entanglement Institute

1. K.Y. Camsari et al. “Stochastic p-bits for Invertible Boolean Logic,” Phys. Rev. X, 3, 031014 (2017);
2. W.A. Borders et al. “Integer Factorization using Stochastic Magnetic Tunnel Junctions,” Nature (in press);
3. K.Y.Camsari et al. “Scalable Emulation of Stoquastic Hamiltonians with Room Temperature p-Bits,” arXiv preprint arXiv:1810.07144.

Researchers should cite this work as follows:

• Supriyo Datta (2019), "p-Bits for Quantum-inspired Algorithms," https://nanohub.org/resources/31596.

  BibTex | EndNote