| Publication Type | Tesis de Grau i Màster // BSc and MSc Thesis |
| Year of Publication | 2023 |
| Authors | Andrea Iglesias Munilla |
| Director | F.-Javier heredia |
| Tipus de tesi | MSc Thesis |
| Titulació | Master in Data Science |
| Centre | Facultat d'Informàtica de Barcelona |
| Data defensa | 30/06/2023 |
| Nota // mark | 9.5 |
| Key Words | teaching; unit commitment; quantum computing; QUBO |
| Abstract | This thesis explores the application of quantum computing techniques to solve Quadratic Unconstrained Binary Optimization problems, with a focus on the Unit Commitment problem. The thesis provides an introduction to quantum computing, including its mathematical foundation and the distinction between classical and quantum systems. It then discusses Variational Quantum Algorithms and explores various quantum computing platforms. Then a novel formulation of the Unit Commitment problem is presented, along with its implementation using the Qiskit library. The results obtained from the implementation are summarized, highlighting the process of using quantum computing for solving optimization problems. |
| DOI / handle | http://hdl.handle.net/2117/394532 |
| URL | Click Here |
| Export | Tagged XML BibTex |
Optimization through quantum computing
Tue, 07/25/2023 - 19:05 — admin