LEARNING OUTCOMES
The student obtains on different traditional fields of materials physics the basic knowledge about materials' ionic and electronic properties, materials-related phenomena, and models used to describe them. Thereafter, she or he can apply this knowledge to follow broadly the modern materials research and become a researcher on a particular materials physics' field based on experimental or theoretical (computational) methods.
Credits: 5
Schedule: 28.02.2022 - 02.06.2022
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Jose Lado Villanueva
Contact information for the course (applies in this implementation):
jose.lado@aalto.fi
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Selected topics in materials physics: Electron dynamics in periodic solids, physics of semiconductors, lattice defects, dielectric properties of solids, magnetism. The last two topics include also interaction of materials with electromagnetic fields.
applies in this implementation
Selected topics on quantum materials and quantum matter: topological insulators, fractional quantum Hall effect, superconductors and Majorana physics, quantum spin-liquids, symmetry broken states, tensor-networks and quantum machine learning.
List of lectures:
Lecture 1: Second quantization, mean-field and spontaneous symmetry breaking
Lecture 2: Symmetries, reciprocal space, Bloch’s theorem
Lecture 3: Band structure theory, tight binding, nearly free electron and k.p
Lecture 4: Linear response theory, Kubo formalism
Lecture 5: Topological band structure theory
Lecture 6: Electrons in a magnetic field, quantum Hall effect and Landau Levels
Lecture 7: Fractionalization in quantum materials: The fractional quantum Hall effect
Lecture 8: Superconductivity, Nambu representation and Majorana physics
Lecture 9: Magnetism, magnons, quantum magnetism and spinons
Lecture 10: Numerical methods: density functional theory and tensor network formalism
Lecture 11: Machine learning in quantum materials
Assessment Methods and Criteria
valid for whole curriculum period:
Lectures with pre-assignments, group presentations on selected topics in quantum materials, individual exercise and oral exam. Grading is based on weighted average of the previous tasks.
applies in this implementation
Lectures with pre-assignments, group presentations on selected topics in quantum materials, individual exercise and oral exam. Grading is based on weighted average of the previous tasks.
Workload
valid for whole curriculum period:
Contact teaching includes lectures and group presentations, group work and independent work.
DETAILS
Study Material
valid for whole curriculum period:
S. Elliott: The Physics and Chemistry of Solids
applies in this implementation
Many-Body Quantum Theory in Condensed Matter Physics, Henrik Bruus and Karsten Flensberg
The Oxford Solid State Basics, Steven H. Simon
Topological Quantum: Lecture Notes, Steven H. Simon
Solid State Physics, Giuseppe Grosso and Giuseppe Pastori Parravicini
Lecture notes: Solid State Theory, Manfred Sigrist
Lecture Notes: Introduction to Condensed Matter Theory, Titus Neupert
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Period:
2020-2021 Spring IV-V
2021-2022 Spring IV-V
Course Homepage: https://mycourses.aalto.fi/course/search.php?search=PHYS-E0421
Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.
Registration via WebOodi.
applies in this implementation
The aim of this course is to provide students with the fundamental concepts of modern solid-state theory, focusing on emergent phenomena in quantum materials. The course connects with a variety of concepts from previous courses of statistical physics, quantum mechanics and electromagnetism. The course especially emphasizes the importance of collective behavior, quasiparticles and emergent behavior in complex quantum systems. Among others, the course presents the topological characterization of electronic systems, spontaneous symmetry and emergent quasiparticles, superconductivity, quantum spin liquids, fractional quantum Hall effect, tensor network and neural network quantum many-body algorithms and machine learning applied to quantum materials.