梦游天姥吟留别 梦游天姥吟留别 李白 海客谈瀛洲,烟涛微茫信难求; 越人语天姥,云霞明灭或可睹。 天姥连天向天横,势拔五岳掩赤城。 天台四万八千丈,对此欲倒东南倾。 我欲因之梦吴越,一夜飞度镜湖月。 湖月照我影,送我至剡溪。 谢公宿处今尚在,渌水荡漾清猿啼。 脚著谢公屐,身登青云梯。 半壁见海日,空中闻天鸡。 千岩万转路不定,迷花倚石忽已暝。 熊咆龙吟殷岩泉,栗深林兮惊层巅。 云青青兮欲雨,水澹澹兮生烟。 列缺 2023-11-02 Poem #Ancient Chinese
Mathematics for New Technologies in Finance MNTF Mathematics for New Technologies in Finance professor : Josef Teichmann author : walkerchi Approximation Weierstrass Weierstrass Approximation Theorem AAA is dense in C(X,Rm)={fi∣fi∈Cpw0,fi 2023-08-30 Note #ETH Zürich #Deep Learning #Mathematic #Finance
Computational Quantum Physics Quantum Basics Hilbert space : H=C2n\mathcal H = \mathbb C^{2^n}H=C2n wave function : ∣ϕ⟩∈H\ket \phi\in \mathcal H∣ϕ⟩∈H a spin-12\frac{1}{2}21 system, H=C2\mathcal H=\mathbb C^2H=C2, ϕ=α∣↑⟩+β∣↓⟩∣α∣ 2023-08-28 Note #ETH Zürich #Physics #Quantum Physics #Quantum Computing
Quantum Information Processing:Concept QIP1Quantum Information Processing:Concept professor : Jonathan Home author : walkerchi Quantum State unitary : S†S=SS†=IS^\dagger S = SS^\dagger= IS†S=SS†=I Hermitian : S†=SS^\dagger=SS†=S proj 2023-08-25 Note #ETH Zürich #Physics #Quantum Physics #Quantum Computing
Numerical Method for Partial Differential Equation NumPDENumerical Method for Partial Differential Equation professor : Ralf Hiptmair author: walkerchi Basic Mathematic Theorem Gauss’s Theorem : ∫Ωdiv j dx=∫∂Ωj⋅n dS(x)\int_\Omega \text{div}~\textbf 2023-08-10 Note #ETH Zürich #Mathematic #Partial Differential Equation
Computational Physics Question Card 1. RNG What is Mersenne number? what is Mersenne prime number ? Mn=2n−1M_n = 2^n-1Mn=2n−1, when MnM_nMn is prime What is the advantage and disadvantage of multiplicative RNG and additive RNG? m 2023-08-09 Question Card #ETH Zürich #Physics #Mathematic #Computational Physics #Julia #Distributed Computing
Computational Physics [ICP]Introduction to Computational Physics Professor: Andreas Adelmann 1. Random Number Generator Congruential RNG xi=(cxi−1)mod px_i = (cx_{i-1})mod~p xi=(cxi−1)mod p maximal period is p−1p-1p−1, 2023-08-08 Note #ETH Zürich #Physics #Mathematic #Computational Physics #Julia #Distributed Computing
Neural Operators and Operator Networks vs Parametric Approach: A General Comparison Neural Operators and Operator Networks vs Parametric Approach: A General Comparison We explore the use of different neural operator architectures for solving partial differential equations (PDEs). Spe 2023-07-14 Project #ETH Zürich #Deep Learning #AI for Science #PINN
Optimizing the Social Force Model: Investigating Memory Layouts and Register Pressure Optimizing the Social Force Model: Investigating Memory Layouts and Register Pressure Helbing and Molńar’s Social Force Model provides a quite realistic description of pedestrian dynamics. However, it 2023-06-23 Project #ETH Zürich #Intel #Hardware #SIMD #CPU #N-body Problem
Model Cascades for Efficient Image Search Model Cascades for Efficient Image Search Modern neural encoders offer unprecedented text-image retrieval (TIR) accuracy. However, their high computational cost impedes an adoption to large-scale imag 2023-05-23 Project #ETH Zürich #Deep Learning #Efficiency #Image Text Retrivel