# Topological Field Theory and Computing with Instantons

@article{Ventra2016TopologicalFT, title={Topological Field Theory and Computing with Instantons}, author={Massimiliano Di Ventra and Fabio L. Traversa and Igor V. Ovchinnikov}, journal={Annalen der Physik}, year={2016}, volume={529} }

It is well known that dynamical systems may be employed as computing machines. However, not all dynamical systems offer particular advantages compared to the standard paradigm of computation, in regard to efficiency and scalability. Recently, it was suggested that a new type of machines, named digital –hence scalable– memcomputing machines (DMMs), that employ non‐linear dynamical systems with memory, can solve complex Boolean problems efficiently. This result was derived using functional…

## 26 Citations

Memcomputing: Leveraging memory and physics to compute efficiently

- Computer ScienceArXiv
- 2018

This work discusses how to employ one such property, memory (time non-locality), in a novel physics-based approach to computation: Memcomputing, and focuses on digital memcomputing machines that are scalable.

Taming a non-convex landscape with dynamical long-range order: memcomputing the Ising spin-glass

- Computer SciencePhysical review. E
- 2019

Evidence is given that a benchmark derived from quantum annealing studies is solvable in polynomial time using digital memcomputing machines, which utilize a collection of dynamical components with memory to represent the structure of the underlying optimization problem.

Critical branching processes in digital memcomputing machines

- Computer Science
- 2019

It is shown that memcomputing machines self-tune to a critical state in which avalanches are characterized by a branching process, and that this state persists across the majority of their evolution.

MemComputing: An efficient topological computing paradigm

- Computer Science2017 IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS)
- 2017

This work introduces memcomputing, a novel computing paradigm that employs memory (time non-locality) to both store and process information on the same physical location to solve complex problems very efficiently both in hardware and in software.

Critical branching processes in memcomputing

- Computer ScienceEPL (Europhysics Letters)
- 2019

It is shown that memcomputing machines self-tune to a critical state in which avalanches are characterized by a branching process, and that this state persists across the majority of their evolution.

Instantons in self-organizing logic gates

- PhysicsArXiv
- 2017

This work provides a physical understanding of self-organizing logic gates and can serve as an inspiration for, new models of bi-directional logic gates that are emerging as important tools in physics-inspired, unconventional computing.

Chaos as a symmetry-breaking phenomenon

- PhysicsModern Physics Letters B
- 2019

Chaos is an ubiquitous and fundamental phenomenon with a wide range of features pointing to a similar phenomenology. Although apparently distinct, it is natural to ask if all these features emerge…

Stress-Testing Memcomputing on Hard Combinatorial Optimization Problems

- Computer ScienceIEEE Transactions on Neural Networks and Learning Systems
- 2020

The simulations of DMMs still scale linearly in both time and memory up to these very large problem sizes versus the exponential requirements of the state-of-the-art solvers, which further reinforce the advantages of the physics-based memcomputing approach compared with traditional ones.

MemComputing: a brain-inspired computing paradigm

- Computer Science
- 2018

It is shown that a machine that uses memory to both process and store information, like the authors' brain, and is endowed with intrinsic parallelism and information overhead has a computational power far beyond their standard digital computers.

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