CESGA leads the first case of the use of quantum computing for the modeling of taste perception worldwide Oil and water don’t mix, they say. If we were to look for a way to modernize this popular expression we might ask: do beer and quantum computing mix? Well, actually, they
Showcasing techniques for parallellizing quantum algorithms, with use cases in Variational Quantum Algorithms: VQE and QAOA.
Showcasing a Quantum Recurrent Neural Network model for Time Series predictions, and results obtained for datasets with many variables
Introducing methods to simulate entanglement between QPUs in the scenarios of classical communication, and no communication.
Showcasing the Gate Cutting method for Variational Quantum Algorithms, to reduce the number of necessary qubits and the effect of noise. Results for VQE and Ising model.
Using the Differential Evolution optimizer to avoid local minima in NISQ-era Variational Quantum Algorithms, such as VQE for the Ising model.
Showcasing a Quantum Recurrent Neural Network model for Time Series predictions, and results obtained for datasets with many variables.
Introduction to Quantum Algorithms: both for foundational algorithms (Shor, Grover, QFT) and for NISQ-era algorithms: Variational Quantum Circuits
Showcasing a Quantum Recurrent Neural Network model for Time Series predictions, and results obtained single-variable datasets.
Using the Differential Evolution optimizer to avoid local minima in NISQ-era Variational Quantum Algorithms, such as VQE for the Ising model