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We start from this formula of SOC expression in DFT: \(H_{SOC}=\sum_i\xi_i(r)\vec{L}_i\cdot\vec{S}_i\)
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The large deviation principle defines a rate function $I(\mathbf{x})$ that: \(\lim_{n\to\infty}-\frac{1}{n}\ln p(\mathbf{x})=I(\mathbf{x})\)
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The one-band Hubbard Model is the simplest model for the interactive electrons in solid.
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The Wannier Function is the Fourier transform of the bloch functions. Since bloch function have a gauge freedom, that one can choose a phase function that is periodic in K space and won’t change the bloch function’s functionality, so the wanneir function can be formed in varies ways.
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About local and non-local functional: https://physics.stackexchange.com/questions/121816/local-versus-non-local-functionals variation of functionals: Mathematical Physics p.1051 deduction from many body electronic potential to hatree potential and exchange energy. https://chem.libretexts.org/Bookshelves/Physical_and_Theoretical_Chemistry_Textbook_Maps/Advanced_Theoretical_Chemistry_(Simons)/06%3A_Electronic_Structure/6.03%3A_The_Hartree-Fock_Approximation
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The present chapter is the first in a series of four Chapters (VI, VII, IX and X) devoted to the study of angular momenta in quantum mechanics. This is an extremely important problem, and the results we are going to establish are used in many domains of physics: the classification of atomic, molecular and nuclear spectra, the spin of elementary particles, magnetism, etc… - Quantum Mechanics Volume 1 (Cohen-Tannoudji)
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As an example, the central force problem used all knowledge of the basic principles in classical mechanics, which is a good practice to review all knowledge that have learnt in the first two chapters of Classical Mechanics (Goldstein)
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The note is summarized from several good textbook, includes Goldstein’s ‘Classical Mechanics’, Griffiths’s ‘Introduction to Electrodynamics’ and Cohen’s ‘Quantum Mechanics Volume 1’
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“The theory of fermions is one of the great triumphs of twentieth-century physics. Most of the credit belongs to Paul Dirac, who started, like Einstein, with some simple assumptions and laid the foundations for the Pauli exclusion principle of chemistry, Fermi statistics in solids, and antimatter in particle physics.”
The basic problem of Schrodinger equation is it doesn’t contain relativistic effect, since if we wrote: \(\begin{align*} i\hbar \frac{\partial}{\partial t}\psi=H\psi=\left[\frac{-\hbar^2\nabla^2}{2m}+U\right]\psi \end{align*}\) we can see the kinetic terms is not relativistically invariant. The conserved quantities in special relativity is $E^2=(mc^2)^2+(cp)^2$. However, if the time derivitive term has second order. Then the equation will become like: \(\begin{align} \left(i\hbar\frac{\partial}{\partial t}\right)^2\psi&=-\hbar^2\frac{\partial^2}{\partial t^2}\psi\\ &=\left[m^2c^4+c^2(-\hbar^2\nabla^2)\right]\psi\\ &=E^2\psi\\ \Leftrightarrow -\frac{1}{c^2}\frac{\partial^2}{\partial t^2}\psi&=\frac{m^2c^2}{\hbar^2}\psi-\nabla^2\psi \end{align}\) There will be two problem appears:
Abundant engaging talks and discussions, set against the backdrop of a beautiful and tranquil city.
Only after putting up the post did I realize that the QR code on it had already expired, prompting me to create a patch for it. LOL.
Tianjin has become a second home to me, a serene city where everyone relishes their own pace and finds peace.
Published in arxiv, 2021
We design a metric to estimating information entropy in neural networks.
Recommended citation: Zhouyin, Zhanghao, and Ding Liu. "Understanding neural networks with logarithm determinant entropy estimator." arXiv preprint arXiv:2105.03705 (2021). http://floatingCatty.github.io/files/2105.03705.pdf
Published in arxiv, 2022
We implement a quantum transport simulator based on Non-equilibrium Green’s Function with PyTorch, and customly design the gradient computation.
Recommended citation: Zhou, Yingzhanghao, et al. "AD-NEGF: An End-to-End Differentiable Quantum Transport Simulator for Sensitivity Analysis and Inverse Problems." arXiv preprint arXiv:2202.05098 (2022). http://floatingCatty.github.io/files/2202.05098.pdf
Published in arxiv, 2023
A deep learning package for tight-binding approach with $ab$ $initio$ accuracy.
Recommended citation: Gu, Qiangqiang, et al. "DeePTB: A deep learning-based tight-binding approach with $ ab $ $ initio $ accuracy." arXiv preprint arXiv:2307.04638 (2023). http://floatingCatty.github.io/files/2307.04635.pdf