1 citations · 3 across the 14 of their papers we have counts for
16 papers
Generating quantum error correcting codes from topological pre-thermal scars
William N. Faugno, Frank Barrows, Terry A. Loring +2
Quantum many-body scars are rare nonthermal states embedded within otherwise thermalizing spectra, making them promising candidates for storing and manipulating quantum information…
Resistive Switching and Neuromorphic Computing in Metal/Nb:SrTiO: Mechanisms, Interface Physics, and Charge Transport
Christopher Broyles, Elizabeth Krenkel, Frank Barrows +2
Resistive switching (RS) in Nb-doped SrTiO (Nb:STO) based memristive devices has attracted sustained interest in information processing and novel computing because of its formi…
Geometry-Induced Domain-Wall Pinning and Asymmetry in Nominally One-Dimensional Rydberg Arrays
Elijah Pelofske, Frank Barrows, Cristiano Nisoli
We perform experiments on QuEra's neutral-Rydberg-atom Aquila quantum computer, using quasi-adiabatic evolution on 1-dimensional models. We use hardware fine-tuning to balance the…
Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings
Riley Acker, Aman Desai, Garrett Kenyon +1
Oscillatory neural networks (ONNs) have emerged as a promising neuromorphic architecture, leveraging coupled dynamical systems to perform computation and represent information thro…
How to Train Your Resistive Network: Generalized Equilibrium Propagation and Analytical Learning
Jonathan Lin, Aman Desai, Frank Barrows +1
Machine learning is a powerful method of extracting meaning from data; unfortunately, current digital hardware is extremely energy-intensive. There is interest in an alternative an…
Autonomous Learning of Attractors for Neuromorphic Computing with Wien Bridge Oscillator Networks
Riley Acker, Aman Desai, Garrett Kenyon +1
We present an oscillatory neuromorphic primitive implemented with networks of coupled Wien bridge oscillators and tunable resistive couplings. Phase relationships between oscillato…
Direct Visualization of the Magnetic Monopole Field in a 3D Artificial Spin Ice
Arjen van den Berg, Peter Rickhaus, Frank Barrows +2
Magnetic monopoles, long hypothesised as fundamental particles carrying isolated magnetic charge, emerge in spin-ice systems as fractionalised excitations governed by the ice rule.…
Probing Antiferromagnetic Hysteresis on Programmable Quantum Annealers
Elijah Pelofske, Pratik Sathe, Cristiano Nisoli +1
Using programmable analog quantum annealing processors, we implement a sampling-based magnetic hysteresis protocol to probe the counterintuitive notion of magnetic memory in antife…
Magnetic Memory and Hysteresis from Quantum Transitions: Theory and Experiments on Quantum Annealers
Frank Barrows, Elijah Pelofske, Pratik Sathe +2
Quantum annealing leverages quantum tunneling for non-local searches, thereby minimizing memory effects that typically arise from metastabilities. Nonetheless, recent work has demo…
Magnetic Hysteresis Experiments Performed on Quantum Annealers
Elijah Pelofske, Frank Barrows, Pratik Sathe +1
While quantum annealers have emerged as versatile and controllable platforms for experimenting on correlated spin systems, the important phenomenology of magnetic memory and hyster…
A unifying approach to self-organizing systems interacting via conservation laws
Frank Barrows, Guanming Zhang, Satyam Anand +5
We present a unified framework for embedding and analyzing dynamical systems using generalized projection operators rooted in local conservation laws. By representing physical, bio…
Voltage-Controlled Oscillator and Memristor-Based Analog Computing for Solving Systems of Linear Equations
Hao Li, Rizwan S. Peerla, Frank Barrows +2
Matrix computations have become increasingly significant in many data-driven applications. However, Moores law for digital computers has been gradually approaching its limit in rec…
R-Ising: Effective resistance in random magnetic nanowires networks
Frank Barrows, Ezio Iacocca, Francesco Caravelli
Random assemblies of magnetic nanowires represent a unique class of materials with promising applications in spintronics and information storage. These assemblies exhibit complex b…
Uncontrolled learning: co-design of neuromorphic hardware topology for neuromorphic algorithms
Frank Barrows, Jonathan Lin, Francesco Caravelli +1
Hardware-based neuromorphic computing remains an elusive goal with the potential to profoundly impact future technologies and deepen our understanding of emergent intelligence. The…
Memristive Linear Algebra
Jonathan Lin, Frank Barrows, Francesco Caravelli
The advent of memristive devices offers a promising avenue for efficient and scalable analog computing, particularly for linear algebra operations essential in various scientific a…
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…