11 papers
Quantum algorithms for stochastic nonlinear differential equations
Sergey Bravyi, Adam Byrne, Mykhaylo Zayats +1
Stochastic nonlinear dynamics underlie many models in engineering and computational physics, yet accurate high-dimensional simulation remains challenging. We present a quantum algo…
TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics
Tobia Boschi, Andrea Loreti, Nicola C. Amorisco +13
We present TokaMind, to our knowledge the first open-source foundation model for tokamak plasma dynamics, based on a Multi-Modal Transformer (MMT) and pretrained on heterogeneous d…
TokaMark: A Comprehensive Benchmark for MAST Tokamak Plasma Models
Cécile Rousseau, Samuel Jackson, Rodrigo H. Ordonez-Hurtado +13
Development and operation of commercially viable fusion energy reactors such as tokamaks require accurate predictions of plasma dynamics from sparse, noisy, and incomplete sensors…
Quantum simulation of a noisy classical nonlinear dynamics
Sergey Bravyi, Robert Manson-Sawko, Mykhaylo Zayats +1
We present an end-to-end quantum algorithm for simulating nonlinear dynamics described by a system of stochastic dissipative differential equations with a quadratic nonlinearity. T…
WaveGAS: Waveform Relaxation for Scaling Graph Neural Networks
Jana Vatter, Mykhaylo Zayats, Marcos Martínez Galindo +4
With the ever-growing size of real-world graphs, numerous techniques to overcome resource limitations when training Graph Neural Networks (GNNs) have been developed. One such appro…
Reducing data resolution for better super-resolution: Reconstructing turbulent flows from noisy observation
Kyongmin Yeo, Małgorzata J. Zimoń, Mykhaylo Zayats +1
A super-resolution (SR) method for the reconstruction of Navier-Stokes (NS) flows from noisy observations is presented. In the SR method, first the observation data is averaged ove…