41 citations · 126 across the 14 of their papers we have counts for
15 papers
Network analysis of memristive device circuits: dynamics, stability and correlations
Frank Barrows, Forrest C. Sheldon, Francesco Caravelli
Networks with memristive devices are a potential basis for the next generation of computing devices. They are also an important model system for basic science, from modeling nanosc…
Number of attractors in the critical Kauffman model is exponential
T. M. A. Fink, F. C. Sheldon
The Kauffman model is the archetypal model of genetic computation. It highlights the importance of criticality, at which many biological systems seem poised. In a series of advance…
Insights from number theory into the critical Kauffman model with connectivity one
F. C. Sheldon, T. M. A. Fink
The Kauffman model of genetic computation highlights the importance of criticality at the border of order and chaos. The model with connectivity one is of special interest because…
Characterizing contaminant noise in barcoded perturbation experiments
Forrest Sheldon
Bursting cells lead to ambient RNA that contaminates sequencing data. This process is especially problematic in perturbation experiments where transcription factors are implanted i…
The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware
Alpha Renner, Forrest Sheldon, Anatoly Zlotnik +2
The capabilities of natural neural systems have inspired new generations of machine learning algorithms as well as neuromorphic very large-scale integrated (VLSI) circuits capable…
Global minimization via classical tunneling assisted by collective force field formation
Francesco Caravelli, Forrest C. Sheldon, Fabio L. Traversa
Simple dynamical models can produce intricate behaviors in large networks. These behaviors can often be observed in a wide variety of physical systems captured by the network of in…
Phases of memristive circuits via an interacting disorder approach
Francesco Caravelli, Forrest C. Sheldon
We study the phase diagram of memristive circuit models in the replica-symmetric case using a novel Lyapunov function for the dynamics of these devices. Effectively, the model we p…
Fully analog memristive circuits for optimization tasks: a comparison
Forrest C. Sheldon, Francesco Caravelli, Carleton Coffrin
We introduce a Lyapunov function for the dynamics of memristive circuits, and compare the effectiveness of memristors in minimizing the function to widely used optimization softwar…
The Computational Capacity of LRC, Memristive and Hybrid Reservoirs
Forrest C. Sheldon, Artemy Kolchinsky, Francesco Caravelli
Reservoir computing is a machine learning paradigm that uses a high-dimensional dynamical system, or \emph{reservoir}, to approximate and predict time series data. The scale, speed…
Critical branching processes in digital memcomputing machines
Sean R. B. Bearden, Forrest C. Sheldon, Massimiliano Di Ventra
Memcomputing is a novel computing paradigm that employs time non-locality (memory) to solve combinatorial optimization problems. It can be realized in practice by means of non-line…
Taming a non-convex landscape with dynamical long-range order: memcomputing Ising benchmarks
Forrest Sheldon, Fabio L. Traversa, Massimiliano Di Ventra
Recent work on quantum annealing has emphasized the role of collective behavior in solving optimization problems. By enabling transitions of clusters of variables, such solvers are…
Stress-testing memcomputing on hard combinatorial optimization problems
Forrest Sheldon, Pietro Cicotti, Fabio L. Traversa +1
Memcomputing is a novel paradigm of computation that utilizes dynamical elements with memory to both store and process information on the same physical location. Its building block…
Evidence of an exponential speed-up in the solution of hard optimization problems
Fabio L. Traversa, Pietro Cicotti, Forrest Sheldon +1
Optimization problems pervade essentially every scientific discipline and industry. Many such problems require finding a solution that maximizes the number of constraints satisfied…
Phase-dependent noise in Josephson junctions
Forrest Sheldon, Sebastiano Peotta, Massimiliano Di Ventra
In addition to the usual superconducting current, Josephson junctions (JJs) support a phase-dependent conductance related to the retardation effect of tunneling quasi-particles. Th…
Phase Transitions and Duality in Adiabatic Memristive Networks
Forrest C. Sheldon, Massimiliano Di Ventra
The development of neuromorphic systems based on memristive elements - resistors with memory - requires a fundamental understanding of their collective dynamics when organized in n…