64 citations · 136 across the 7 of their papers we have counts for
5 papers · 1 filter
Photovoltaic power forecasting using quantum machine learning
Asel Sagingalieva, Stefan Komornyik, Arsenii Senokosov +6
Accurate forecasting of photovoltaic power is essential for reliable grid integration, yet remains difficult due to highly variable irradiance, complex meteorological drivers, site…
Numerical solution of the incompressible Navier-Stokes equations for chemical mixers via quantum-inspired Tensor Train Finite Element Method
Egor Kornev, Sergey Dolgov, Karan Pinto +3
The solution of computational fluid dynamics problems is one of the most computationally hard tasks, especially in the case of complex geometries and turbulent flow regimes. We pro…
Optimization of chemical mixers design via tensor trains and quantum computing
Nikita Belokonev, Artem Melnikov, Maninadh Podapaka +3
Chemical component design is a computationally challenging procedure that often entails iterative numerical modeling and authentic experimental testing. We demonstrate a novel opti…
Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes
Alexandr Sedykh, Maninadh Podapaka, Asel Sagingalieva +3
Finding the distribution of the velocities and pressures of a fluid by solving the Navier-Stokes equations is a principal task in the chemical, energy, and pharmaceutical industrie…
Quantum algorithms applied to satellite mission planning for Earth observation
Serge Rainjonneau, Igor Tokarev, Sergei Iudin +8
Earth imaging satellites are a crucial part of our everyday lives that enable global tracking of industrial activities. Use cases span many applications, from weather forecasting t…