Login to Edit
- Theor./Math. Physics Seminar
- Memcomputing: a brain-inspired topological computing paradigm
- Massimiliano Di Ventra
- Lidow, Nathan Rosen (300)
Which features make the brain such a powerful and energy-efficient computing machine? Can we reproduce them in the solid state, and if so, what type of computing paradigm would we obtain? I will show that a machine that uses memory to both process and store information, like our brain, and is endowed with intrinsic parallelism and information overhead - namely takes advantage, via its collective state, of the network topology related to the problem - has a computational power far beyond our standard digital computers . We have named this novel computing paradigm “memcomputing” [2, 3]. As an example, I will show the polynomial-time solution of prime factorization, the NP-hard version of the subset-sum problem and the Max-SAT using polynomial resources and self-organizing logic gates, namely gates that self-organize to satisfy their logical proposition . I will also demonstrate that these machines are described by a Witten-type topological field theory and they compute via an instantonic phase where a transient long-range order develops due to the effective breakdown of topological supersymmetry . The digital memcomputing machines that we propose can also be efficiently simulated, are scalable and can be easily realized with available nanotechnology components, and may help reveal aspects of computation of the brain.
 F. L. Traversa and M. Di Ventra, Universal Memcomputing Machines, IEEE Transactions on Neural Networks and Learning Systems 26, 2702 (2015).
 M. Di Ventra and Y.V. Pershin, Computing: the Parallel Approach, Nature Physics 9, 200 (2013).
 M. Di Ventra and Y.V. Pershin, Just add memory, Scientific American 312, 56 (2015).
 F. L. Traversa and M. Di Ventra, Polynomial-time solution of prime factorization and NP-complete problems with digital memcomputing machines, Chaos: An Interdisciplinary Journal of Nonlinear Science 27,
 M. Di Ventra, F. L. Traversa and I.V. Ovchinnikov, Topological field theory and computing with instantons, arXiv:1609.03230.
Massimiliano Di Ventra obtained his undergraduate degree in Physics summa cum laude from the University of Trieste (Italy) in 1991 and did his PhD studies at the Ecole Polytechnique Federale de Lausanne
(Switzerland) in 1993-1997. He has been Visiting Scientist at IBM T.J.
Watson Research Center and Research Assistant Professor at Vanderbilt University before joining the Physics Department of Virginia Tech in
2000 as Assistant Professor. He was promoted to Associate Professor in
2003 and moved to the Physics Department of the University of California, San Diego, in 2004 where he was promoted to Full Professor in 2006.
Di Ventra's research interests are in the theory of electronic and transport properties of nanoscale systems, non-equilibrium statistical mechanics, DNA sequencing/polymer dynamics in nanopores, and memory effects in nanostructures for applications in unconventional computing and biophysics.
He has been invited to deliver more than 250 talks worldwide on these topics (including 10 plenary/keynote presentations, 9 talks at the March Meeting of the American Physical