3 papers
quant-ph2026
Quantum SEDONet: Spectrally-Embedded Quantum Deep Operator Networks for Partial Differential Equations
Muhammad Abid, Arth Sojitra, Bipin Tiwari +1
Quantum DeepONet accelerates neural-operator inference by evaluating an orthogonally parameterized network on a quantum computer, reproducing in ideal simulation the accuracy of it…
physics.flu-dyn2026
Accelerating Bayesian inverse design in computational fluid dynamics using neural operators
Bipin Tiwari, Omer San
Bayesian inverse design provides a principled framework for inferring aerodynamic geometries from sparse flow observations while quantifying uncertainty. However, its practical use…
cs.LG2026
The impact of observation density on Bayesian inversion of latent dynamics in shock-dominated flows
Bipin Tiwari, Muhammad Abid, Omer San
Inferring unknown initial states in shock-dominated compressible flows from sparse and noisy measurements is a challenging ill-posed inverse problem due to nonlinear wave interacti…