000110301 001__ 110301
000110301 005__ 20220210105301.0
000110301 037__ $$aTAZ-TFG-2021-3093
000110301 041__ $$aeng
000110301 1001_ $$aSancho Lorente, Teresa
000110301 24200 $$aClassification of quantum phase transitions using quantum machine learning
000110301 24500 $$aClasificación de transiciones de fase cuánticas mediante aprendizaje automático cuántico.
000110301 260__ $$aZaragoza$$bUniversidad de Zaragoza$$c2021
000110301 506__ $$aby-nc-sa$$bCreative Commons$$c3.0$$uhttp://creativecommons.org/licenses/by-nc-sa/3.0/
000110301 520__ $$aIn this dissertation we discuss an example of quantum computing supremacy based on classification of quantum phase transitions. To do so, we focus our attention in the quantum Ising model and present the results of characterizing its phase transition making use of a machine learning algorithm used to do classification tasks and known as Support Vector Machines. <br /><br />
000110301 521__ $$aGraduado en Física
000110301 540__ $$aDerechos regulados por licencia Creative Commons
000110301 700__ $$aZueco Láinez, David$$edir.
000110301 7102_ $$aUniversidad de Zaragoza$$bFísica de la Materia Condensada$$cFísica de la Materia Condensada
000110301 8560_ $$f761344@unizar.es
000110301 8564_ $$s399952$$uhttps://zaguan.unizar.es/record/110301/files/TAZ-TFG-2021-3093_ANE.pdf$$yAnexos (eng)
000110301 8564_ $$s986929$$uhttps://zaguan.unizar.es/record/110301/files/TAZ-TFG-2021-3093.pdf$$yMemoria (eng)
000110301 909CO $$ooai:zaguan.unizar.es:110301$$pdriver$$ptrabajos-fin-grado
000110301 950__ $$a
000110301 951__ $$adeposita:2022-02-10
000110301 980__ $$aTAZ$$bTFG$$cCIEN
000110301 999__ $$a20210628141855.CREATION_DATE