[PDF][PDF] Local minima in quantum systems
Finding ground states of quantum many-body systems is known to be hard for both classical
and quantum computers. As a result, when Nature cools a quantum system in a low …
and quantum computers. As a result, when Nature cools a quantum system in a low …
[HTML][HTML] Validity of annealed approximation in a high-dimensional system
This study investigates the suitability of the annealed approximation in high-dimensional
systems characterized by dense networks with quenched link disorder, employing models of …
systems characterized by dense networks with quenched link disorder, employing models of …
Triadic interaction in the background of a pairwise spin-glass
Developing an equilibrium solution for a pairwise spin-glass with a quenched random
infinite range shows a continuous phase transition. Models with p-spin interactions have …
infinite range shows a continuous phase transition. Models with p-spin interactions have …
Prototype Analysis in Hopfield Networks with Hebbian Learning
H McAlister, A Robins, L Szymanski - Neural computation, 2024 - direct.mit.edu
We discuss prototype formation in the Hopfield network. Typically, Hebbian learning with
highly correlated states leads to degraded memory performance. We show that this type of …
highly correlated states leads to degraded memory performance. We show that this type of …
A robust balancing mechanism for spiking neural networks
Dynamical balance of excitation and inhibition is usually invoked to explain the irregular low
firing activity observed in the cortex. We propose a robust nonlinear balancing mechanism …
firing activity observed in the cortex. We propose a robust nonlinear balancing mechanism …
Statistical physics of complex systems: glasses, spin glasses, continuous constraint satisfaction problems, high-dimensional inference and neural networks
P Urbani - arXiv preprint arXiv:2405.06384, 2024 - arxiv.org
The purpose of this manuscript is to review my recent activity on three main research topics.
The first concerns the nature of low temperature amorphous solids and their relation with the …
The first concerns the nature of low temperature amorphous solids and their relation with the …
Sequential Learning in the Dense Associative Memory
H McAlister, A Robins, L Szymanski - arXiv preprint arXiv:2409.15729, 2024 - arxiv.org
Sequential learning involves learning tasks in a sequence, and proves challenging for most
neural networks. Biological neural networks regularly conquer the sequential learning …
neural networks. Biological neural networks regularly conquer the sequential learning …
Low-resolution descriptions of model neural activity reveal hidden features and underlying system properties
R Aldrigo, R Menichetti, R Potestio - arXiv preprint arXiv:2405.14531, 2024 - arxiv.org
The analysis of complex systems such as neural networks is made particularly difficult by the
overwhelming number of their interacting components. In the absence of prior knowledge …
overwhelming number of their interacting components. In the absence of prior knowledge …
Classical Thermodynamics-based Parallel Annealing Algorithm for High-speed and Robust Combinatorial Optimization
K Kuroki, S Jimbo, TV Chu, M Motomura… - Proceedings of the …, 2024 - dl.acm.org
In recent years, quantum annealing has triggered active research on annealing methods for
solving various combinatorial optimization problems (COPs) by mapping them to the Ising …
solving various combinatorial optimization problems (COPs) by mapping them to the Ising …
Disordered Yet Directed: The Emergence of Polar Flocks with Disordered Interactions
Flocking is a prime example of how robust collective behavior can emerge from simple
interaction rules. The flocking transition has been studied extensively since the inception of …
interaction rules. The flocking transition has been studied extensively since the inception of …