13 papers
Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
Abhisek Ganguly, Santosh Ansumali, Sauro Succi
We revisit the analogy between feed-forward deep neural networks (DNNs) and discrete dynamical systems derived from neural integral equations and their corresponding partial differ…
Fluid-kinetic multiscale solver for wall-bounded turbulence
Akshay Chandran, Praveen Kumar Kolluru, Berni J. Alder +2
We present a two-level (fluid-kinetic) coupling procedure for the simulation of wall-bounded flows at Reynolds numbers up to thousands. The method combines a kinetic Direct Simulat…
Physics-Constrained Neural Closure for Lattice Boltzmann Large-Eddy Simulation
Muhammad Idrees Khan, Sauro Succi, Hua-Dong Yao +1
We present a physics-constrained, data-driven subgrid-scale (SGS) stress closure for large-eddy simulation (LES) in the lattice Boltzmann method (LBM). Trained on filtered-downsamp…
Variational-Adiabatic Quantum Solver for Systems of Linear Equations with Warm Starts
Claudio Sanavio, Fabio Mascherpa, Alessia Marruzzo +2
We propose a revisited variational quantum solver for linear systems, designed to circumvent the barren plateau phenomenon by combining two key techniques: adiabatic evolution and…
Block encoding of sparse matrices with a periodic diagonal structure
Alessandro Andrea Zecchi, Claudio Sanavio, Luca Cappelli +3
Block encoding is a successful technique used in several powerful quantum algorithms. In this work we provide an explicit quantum circuit for block encoding a sparse matrix with a…
A new kind of science
Alex Hansen, Sauro Succi
We discuss whether science is in the process of being transformed from a quest for causality to a quest for correlation in light of the recent development in artificial intelligenc…