Title: Computing with p-Bits: Between a Bit and a q-Bit
Presenters: Jan Kaiser and Supriyo Datta, (Purdue University)
Feynman  used the concept of a probabilistic computer as a counterpoint to the quantum computer, noting that “ .. the only difference between a probabilistic classical world and the equations of the quantum world is that .. the probabilities would have to go negative .. ” The awesome power of quantum computing comes from exploiting these negative (more generally complex) probabilities, which in turn requires stringent experimental conditions to protect the phase.
A probabilistic computer by contrast can be built with existing technology to operate at room temperature as we have demonstrated experimentally . They lack the magic of complex probabilities, but can address a wide variety of problems ranging from optimization and sampling to quantum computing and machine learning . Results will be presented comparing a probabilistic computer to CPU/GPU for a variety of problems .
 R.P. Feynman, Int. J. Theor. Phys. 21, 467 (1982).
 W.A. Borders et al. Nature 573, 390 (2019).
 B.M. Sutton et al. IEEE Access 8, 157238 (2020).
 J. Kaiser et al. Benchmarking a Probabilistic Coprocessor (unpublished).
Jan Kaiser is currently pursuing his PhD in Electrical and Computer Engineering at Purdue University. He received his BSc and MSc degrees from the Department of Electrical Engineering and Information Science at Ruhr-University Bochum (RUB) in 2015 and 2017, respectively. He joined Prof. Datta’s group at Purdue University in Jan. 2018. His research involves probabilistic and physics-based computing, random number generation with low-barrier nanomagnets and machine learning. Jan received the Infineon Bachelor Award for Academic Excellence, the Faculty Award from the Department of Electrical Engineering and Information Science at RUB and the Ross Fellowship from Purdue University.
Supriyo Datta received his PhD from University of Illinois at Urbana-Champaign in 1979 working on surface acoustic wave devices, and has been with Purdue University since 1981. The non-equilibrium Green function (NEGF) method approach pioneered by his group for the description of quantum transport has been widely adopted in the field of nanoelectronics. He is also known for innovative theoretical proposals that have inspired new fields of research including negative capacitance devices and spintronics.
This meeting is only available to the JUMP research community, such as Principal Investigators, Postdoc researchers, Students, and Industry/Government liaisons.