Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/199220
Title: | A mathematical framework for quantum neural networks |
Author: | Urgell Ollé, Núria |
Director/Tutor: | Juliá-Díaz, Bruno |
Keywords: | Computació evolutiva Treballs de fi de grau Ordinadors quàntics Xarxes neuronals (Informàtica) Aprenentatge automàtic Evolutionary computation Bachelor's theses Quantum computers Neural networks (Computer science) Machine learning |
Issue Date: | Jan-2023 |
Abstract: | [en] This thesis focuses on dissipative quantum neural networks, a subfield of quantum machine learning. Classical neural networks and the fundamental concepts of quantum mechanics, crucial for understanding quantum machine learning, are introduced from a mathematical perspective. We exhibit the parallelism between the training algorithms of classical neural networks and dissipative quantum neural networks and establish a mathematical framework to describe classical and quantum neural networks. |
Note: | Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2023, Director: Bruno Juliá-Díaz |
URI: | http://hdl.handle.net/2445/199220 |
Appears in Collections: | Treballs Finals de Grau (TFG) - Matemàtiques |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
tfg_urgell_olle_nuria.pdf | Memòria | 1.44 MB | Adobe PDF | View/Open |
This item is licensed under a
Creative Commons License