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Notebooks associés (20)

Band Structure Investigation of Monolayer and Bilayer Graphene Using the Tight Binding Model

In [1]: import matplotlib.pyplot as plt import numpy as np from mpl_toolkits import mplot3d import itertools %matplotlib widget Band Structure of Mono and Bilayer Graphene[1]¶ If you have questions about this notebook, e-mail Oleg Malanyuk (oleg.malanyuk@epfl.ch) The purpose of this notebook is to investigate the band model of Mono and Bilayer graphene modeled with tight binding model. Tight binding model for monolayer graphene[2]¶ Monolayer graphene is a sheet of carbons aranged in a he

Cylindrical Coordinates Visualization

::: {role="main"} ::: {.jp-Cell .jp-MarkdownCell .jp-Notebook-cell} ::: {.jp-Cell-inputWrapper tabindex="0"} ::: {.jp-Collapser .jp-InputCollapser .jp-Cell-inputCollapser} ::: ::: {.jp-InputArea .jp-Cell-inputArea} ::: {.jp-InputPrompt .jp-InputArea-prompt} ::: ::: {.jp-RenderedHTMLCommon .jp-RenderedMarkdown .jp-MarkdownOutput mime-type="text/markdown"}

Important note¶{.anchor-link} {#Important-note}

This notebook is obsolete and not maintained. For an interactive display of cylidri

Wave Interference

The plotted function is the superimposition of $n$ 2d-sine functions centered in $(0,Y_i)$: $$f(x,y)=\sin\big(p\cdot\sqrt{x^2+(y-Y_i)^2}\big)$$ The parameters that can be changed are: -- $n$ the number of sources (start with 2) -- $d$ the distance between sources -- $p$ the periodicity. Higher periodicity means shorter wavelength. $p =2\pi / \lambda$. Note that in electron microscopy the usual convention is to define the wave vector as $k=1/\lambda$. -- $f$ the field o

Estimation of Electron Density and Mean Free Time for Transparent Conductors

Chapter 1: Transparent Conductors[1]¶ Instruction: The purpose of this notebook is to try and find values of electron density and mean free time for a material suitable to be used as a transparent conductors. The final estimate should be the order of the two parameters to be used[2]¶ In [1]: import numpy as np from bokeh.io import push_notebook, output_notebook, show from bokeh.layouts import row, column from bokeh.plotting import figure output_notebook() from ipywidgets import interact from collect

Introduction: Python and ethical dilemmas

Introduction: Python and ethical dilemmas¶{.anchor-link} {#Introduction:-Python-and-ethical-dilemmas}

Notebook by Athina Papageorgiou Koufidou, Cécile Hardebolle and the Responsible software team (2025). Except where otherwise noted, the content of this notebook is licensed under a {rel="license"}Creative Commons Attribution International License (CC BY 4.0 International).
[](http://creativecommons.org/licenses

Modeling and Analysis of a PN-Junction in Inhomogeneous Semiconductors.

In [1]: import matplotlib.pyplot as plt import matplotlib.ticker as mtick import numpy as np import ipywidgets as widgets import scipy.integrate as integrate from ipywidgets import interact, fixed from scipy.interpolate import interp1d from textwrap import dedent from bokeh.io import push_notebook, show, output_notebook, output_file, curdoc from bokeh.plotting import figure from bokeh.layouts import column, row from bokeh.themes import built_in_themes from bokeh.models import Range1d, BasicTickFormatter, L

Simulating a Telephone Channel using FIR Filter Design

A Telephone Channel Simulator[1]¶ In this notebook we will develop a filter that simulates the effect of a standard telephone channel. In [1]: %matplotlib inline import matplotlib.pyplot as plt import numpy as np import IPython import scipy.signal as sp from scipy.io import wavfile In [2]: plt.rcParams["figure.figsize"] = (14,4) implicit sampling rate will be the internal "clock" of our simulation. In [3]: IPython.display.Audio(s, rate=SF) Out[3]: Your browser does not support

Powder X-Ray Diffraction Analysis: Exploring Crystal Structures.

XRay Diffraction[1]¶ The purpose of this notebook is to study the powder XRay diffraction spectra of some systems. When the crystal is hit with an XRay wave, the wave is diffracted only for specific case where the Bragg condition is satisfied for one of the lattice planes in the material. For single crystal diffraction, the condition is satisfied only for specific orientation of the crystal, such that the incident ray has the correct

\theta

value for the plane. In powder XRay data, however, any plane ori

Basic Example of Anderson Localization in a 1D System

Demonstration of Anderson localization[1]¶ This notebook is intended to show a very basic example of the Anderson localization in one-dimensional system. In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline To show the idea of Anderson localization, we can consider 1D chain of

N

atoms with perio

Calculation and plotting of some important quantities relative to the electron s properties in a conventional TEM

Modeling Epidemics with Signal Processing Techniques

Epidemics and Signal Processing[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In [1]: import matplotlib.pyplot as plt import numpy as np import scipy.signal as sp import seaborn as sns sns.set() In [2]: plt.rcParams["figure.figsize"] = (14,4) The basic reproduction number[4]¶ The propagation mechanism of an epidemic such as the one caused by SARS-CoV-2 virus can be roughly modeled, at least in its inital phase, as a process in which each infected individ

Designing FIR Filters Using the Parks-McClellan Algorithm

The Parks-McClellan Filter Design Method[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

The Parks-McClellan (PM) algorithm is a clever application of advanced polynomial fitting techniques to the problem of FIR filter design. In this notebook we will explore the key ideas behind the method by considering the design of a simple Type-I lowpass filter. NOTE: This notebook uses interactive widgets. If the interactive controls do not work or show up, please fo

Ewald Sphere

Ewald Sphere¶{.anchor-link} {#Ewald-Sphere}

Play with the Ewald Sphere This schematics represent the Ewald sphere for a typical high

Illustrating Band Structures in Solids: Free Electrons and Atomic Orbitals

In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib widget The emergence of band structures[1]¶ If you have questions about this notebook, e-mail Oleg Malanyuk (oleg.malanyuk@epfl.ch) This jupyter notebook is intended to provide a illustration of the band structures in solides, starting from the points of v

Understanding and Plotting the Discrete Fourier Transform (DFT)

Plotting the DFT[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will look at the practical issues associated to plotting the DFT and in particular the DFT of real-world signals. We will examine how to map the DFT coefficients to real-world frequencies and we will investigate the frequency resolution of the DFT and the effects of zero padding. In [1]:

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.p

Exploring Chemical Potential for Fermions in 3D at Finite Temperature

This notebook gives a simple illustration to the variation of chemical potential for Fermions in 3D, following the Fermi-Dirac statistics in finite temperature. " In 3D, we have the density of states

\\rho \\propto \\sqrt{E}

. At zero temperature, the distribution of electrons just follows

g(E)=a \\sqrt{E}

and the Fermi energy is determined by the total occupied number

N_{occ}

E_f

is the energy such that

N_{occ}=\\int_{0}^{E_f} g(E) dE

\n", " \n", "In finite temperature, however, o

Adaptive Echo Cancellation using LMS Filter

Adaptive Echo Cancellation[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will use the adaptive LMS filter to estimate the impulse response of a reverberating room. A typical use case is handsfree telephony: since the received signal, amplified and played by the speaker, is picked up by the microphone, we need to eliminate it from the signal that is transmitted back in order to avoid a feedback loop. The signal picked up by the microph

Exploring Quantization and Oversampling through One-Bit Music

One-Bit Music[1]¶ In this notebook we will talk about quantization and oversampling and we will do so by taking a trip down memory lane to revisit the early from monophonic square waves, introduce polyphony by way of pulse-width modulation and finish with the basics of sigma-delta quantization. pacman In [1]: import matplotlib import matplotlib.pyplot as plt import numpy as np import scipy.signal as sp from scipy.io import wavfile import IPython In [2]: import sys ! wget -q -O mus

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will explore various ways to implement a system that changes the voice of a speaker. Typical applications for these techniques, strictly sorted by plausibility, include international spy missions and prank telephone calls, and devices such as the one displayed here can be easily bought on the web... or in a novelty shop. No description has been provided for t

Whistle-Activated Keylock System Implementation

Whistling Keylock[1]¶ In this notebook we will implement a simple "whistle-activated" keylock, that is, an access control system where the password is a pre-defined melody. To program the lock, you record your musical passphrase and then, to open the lock, you whistle it back. Although the implementation will be simple and skip most of the fine details that would be necessary to produce a truly robust system, we need to take into account at least the following points: * The syste

Graph Chat

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Notebooks associés (20)

Band Structure Investigation of Monolayer and Bilayer Graphene Using the Tight Binding Model

Cylindrical Coordinates Visualization

Important note¶{.anchor-link} {#Important-note}

This notebook is obsolete and not maintained. For an interactive display of cylidri

Wave Interference

Estimation of Electron Density and Mean Free Time for Transparent Conductors

Introduction: Python and ethical dilemmas

Introduction: Python and ethical dilemmas¶{.anchor-link} {#Introduction:-Python-and-ethical-dilemmas}

Modeling and Analysis of a PN-Junction in Inhomogeneous Semiconductors.

Simulating a Telephone Channel using FIR Filter Design

Powder X-Ray Diffraction Analysis: Exploring Crystal Structures.

\theta

value for the plane. In powder XRay data, however, any plane ori

Basic Example of Anderson Localization in a 1D System

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline To show the idea of Anderson localization, we can consider 1D chain of

N

atoms with perio

Calculation and plotting of some important quantities relative to the electron s properties in a conventional TEM

Modeling Epidemics with Signal Processing Techniques

Epidemics and Signal Processing[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Designing FIR Filters Using the Parks-McClellan Algorithm

The Parks-McClellan Filter Design Method[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Ewald Sphere

Ewald Sphere¶{.anchor-link} {#Ewald-Sphere}

Play with the Ewald Sphere This schematics represent the Ewald sphere for a typical high

Illustrating Band Structures in Solids: Free Electrons and Atomic Orbitals

In [1]: import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt

from future import print_function

Understanding and Plotting the Discrete Fourier Transform (DFT)

Plotting the DFT[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

first our usual bookkeeping

%matplotlib inline import matplotlib import matplotlib.p

Exploring Chemical Potential for Fermions in 3D at Finite Temperature

This notebook gives a simple illustration to the variation of chemical potential for Fermions in 3D, following the Fermi-Dirac statistics in finite temperature. " In 3D, we have the density of states

\\rho \\propto \\sqrt{E}

. At zero temperature, the distribution of electrons just follows

g(E)=a \\sqrt{E}

and the Fermi energy is determined by the total occupied number

N_{occ}

E_f

is the energy such that

N_{occ}=\\int_{0}^{E_f} g(E) dE

\n", " \n", "In finite temperature, however, o

Adaptive Echo Cancellation using LMS Filter

Adaptive Echo Cancellation[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Exploring Quantization and Oversampling through One-Bit Music

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Whistle-Activated Keylock System Implementation