Utilization of Renormalized Mean-Field Theory upon Novel Quantum Materials

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This book offers a new approach to the long-standing problem of high-Tc copper-oxide superconductors. It has been demonstrated that starting from a strongly correlated Hamiltonian, even within the mean-field regime, the competing orders revealed by experiments can be achieved using numerical calculations. In the introduction, readers will find a brief review of the high-Tc problem and the unique challenges it poses, as well as a comparatively simple numerical approach, the renormalized mean-field theory (RMFT), which provides rich results detailed in the following chapters. With an additional phase picked up by the original Hamiltonian, some behaviors of interactive fermions under an external magnetic field, which have since been experimentally observed using cold atom techniques, are also highlighted.

Nominated as an outstanding PhD thesis by National Taiwan University Provides an accessible introductory review of the field of high-Tc superconductors Describes in detail the numerical methodology of renormalized mean-field theory

Autorentext

Dr. Wei-Lin Tu obtained his dual Ph.D degrees under a co-supervision from National Taiwan University and Université Toulouse III - Paul Sabatier in 2018. His research works focus on the strongly correlated systems, especially the high-Tc cuprate superconductivity.

Inhalt

Introduction.- Renormalized Mean Field Theory.- Results I-High Tc Cuprate.- Results II-Correlated Electrons Under Magnetic Field.- Conclusions and Outlooks.

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Weitere Informationen

  • Allgemeine Informationen
    • Sprache Englisch
    • Gewicht 336g
    • Untertitel Springer Theses
    • Autor Wei-Lin Tu
    • Titel Utilization of Renormalized Mean-Field Theory upon Novel Quantum Materials
    • Veröffentlichung 20.05.2019
    • ISBN 9811378231
    • Format Fester Einband
    • EAN 9789811378232
    • Jahr 2019
    • Größe H241mm x B160mm x T12mm
    • Herausgeber Springer Nature Singapore
    • Anzahl Seiten 108
    • Lesemotiv Verstehen
    • Auflage 1st edition 2019
    • GTIN 09789811378232

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