Density Functional Theory: Foundations and Applications
Explore fundamental concepts and practical implementations of Density Functional Theory for understanding complex quantum mechanical systems.
Explore fundamental concepts and practical implementations of Density Functional Theory for understanding complex quantum mechanical systems.
This advanced course provides a comprehensive introduction to Density Functional Theory (DFT), a powerful method for studying interacting electrons in quantum systems. Designed for students and researchers with a strong background in physics or chemistry and knowledge of quantum mechanics, the course covers the fundamental concepts, mathematical foundations, and practical applications of DFT. Participants will learn about the evolution from many-body problems to density-based approaches, the Hohenberg-Kohn theorems, Kohn-Sham formalism, and various approximation strategies. The curriculum emphasizes both theoretical understanding and practical implementation, preparing learners to apply DFT in their own research across fields such as condensed matter physics, quantum chemistry, and materials science. Through a combination of lectures, readings, and assignments, students will gain insights into the strengths and limitations of DFT, as well as its historical development and current frontiers.
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What you'll learn
Understand the transition from many-body problems to density-based approaches
Master the mathematical foundations of DFT, including functional derivatives
Comprehend the Hohenberg-Kohn theorems and their implications
Explore the Kohn-Sham formalism and its implementation
Analyze various approximation strategies for exchange-correlation functionals
Understand the concept of band gaps in DFT and their calculation
Skills you'll gain
This course includes:
4.77 Hours PreRecorded video
12 assignments
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There are 3 modules in this course
This course provides a thorough introduction to Density Functional Theory (DFT), covering its foundations, formalism, and practical applications. The curriculum is structured into three main modules: the transition from many-body problems to DFT, the Kohn-Sham formalism, and approximation strategies. Students will learn about the Hohenberg-Kohn theorems, functional derivatives, exchange-correlation potentials, and various approximation methods including LDA, GGA, and hybrid functionals. The course emphasizes both theoretical understanding and practical implementation, discussing topics such as band gap calculations and self-consistent field methods. By integrating historical context and current research perspectives, the course offers a comprehensive view of DFT's development and its role in modern computational physics and chemistry.
From the Many-Body problem to Density Functional Theory
Module 1 · 8 Hours to complete
From density to the Kohn-Sham world
Module 2 · 9 Hours to complete
Approximations and strategies
Module 3 · 6 Hours to complete
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Instructors
Researcher
My research activity is mainly based on the theoretical study, via the state-of-the-art of numerical methods, of electronic properties of real materials. I am particularly interested in the study of the limits of actual approaches and approximations, in order to propose solutions to go towards a better comprehension and description of the physics of the studied system. Several research lines are currently investigated: i) exciton dispersion and dimensionality effects; ii) new kernels for TDDFT; iii) interconnection among different spectroscopies (EELS, IXS, PES). An important part of my activity is also devoted to code developments. I am the coordinator of the ab initio codes DP (linear response TDDFT code) and EXC (Bethe-Salpeter equation code).
Research Director at the CNRS
After a master degree in Germany and a PhD in Italy, I got settled in France. I believe in international, open, diverse and inclusive science. We need each other to tackle hard problems together! As a founding member of the European Theoretical Spectroscopy Facility, it has always been my aim to promote collaborations and to ease transfer of knowledge.
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