Parallelizing Quantum Algorithms in the NISQ era
Showcasing techniques for parallellizing quantum algorithms, with use cases in Variational Quantum Algorithms: VQE and QAOA.
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
Introduction to Quantum Technologies, such as Quantum Computing, Quantum Communications, and Quantum Ket Distriburion, with a focus in Quantum Cryptography
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
This work conducts an analysis and proposes a scalable and sufficiently flexible architecture to address the primary challenges in integrating a quantum computer into a supercomputing center
This work conducts an analysis and proposes a scalable and sufficiently flexible architecture to address the primary challenges in integrating a quantum computer into a supercomputing center.