Spectroscopy

Related notebooks (19)

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

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

Digital Simulation of Guitar Feedback in I Feel Fine by The Beatles

I Feel Fine, Digitally[1]¶ This notebook is a little musing inspired by the "internal mechanics" of a very famous audio snippet, namely the guitar sound at the beginning of the song "I Feel Fine", written and recorded by the Beatles in 1964. The historical significance of the record lies in the following claim by John Lennon:

 "I defy anybody to find a record... unless it is some old blues
 record from 1922... that uses feedback that way. So I claim it for
 the Beatles. Before H

Advantages of Digital Transmission over Analog Transmission

[1]Paolo Prandoni, [2]EPFL Analog vs Digital Transmission In this notebook we will explore the advantages of digital transmission over analog transmission. We will model the case of transmission over a long (e.g. transoceanic) cable in which several repeaters are used to compensate for the attenuation incurred by the signal. In [1]: import matplotlib import matplotlib.pyplot as plt import numpy as np import IPython from scipy.io import wavfile plt.rcParams["figure.figsize"] = (14,4)

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

Classical Monte Carlo Simulations of the Ising Model on Square Lattice

"## Classical Monte-Carlo simulations of the Ising model on square lattice\n", "\n", "The Ising model considers the following Hamiltonian\n", "\n", "

\\hat{\\mathcal{H}} = -J\\displaystyle\\sum_{}\\sigma_i \\sigma_j

,\n", "\n", "in which spins

\\sigma_i

can take only two discrete values

\\sigma_i \\in \\{-1,+1\\}

. Below, we will consider spins on two-dimensional square lattice taking into account couplings

J

only for the nearest neighbor sites. For

J > 0

the ferromagneti

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

Modèle d atmosphère

(troposphère) est une atmosphère adiabatique et la deuxième couche (stratosphère) une atmosphère isotherme. coefficient $\gamma =1.4$. La transition se fait à $h_\text{trans}$, choisie. $d p = -\rho g\,d h$. La loi des gaz parfait se réécrit $$T=\frac{pM}{R\rho}$$ La portion adiabatique impose $$ p\rho^{-\gamma} = \text{cte}=p_0\rho_0^{-\gamma}\quad\Longrightarrow\quad \rho=\rho_0 \left(\frac{p}{p_0}\right)^{\frac{1}{\gamma}}$$ $$ d p = -\rho_0 g \left(\fra

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

Drude Model

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Drude Model¶{.anchor-link} {#Drude-Model}

Plots the dielectric function and loss function in the Drude model ::: ::: ::: ::: ::: {.jp

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

Tight-Binding Approximation for 2D Lattices: Square, Triangular, Lieb, and Honeycomb

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

from future import print_function

from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets %matplotlib inline In [2]: def band(nkl,kpoints,ham): :param k: wave number nk=32 # Define the position of the original lattice #klines=np.zeros((nkl-1,nk)) n=0 d=np.size(ham([0.0,0.0]),1) evk=np.zeros((nknkl-nk-1,d)) lenk=np.zeros((nknkl-nk-1,d)) for i in range(0,nkl-1)

Interactive Phonon Band Structure Visualization

In [1]: import numpy as np import matplotlib.pyplot as plt from matplotlib import animation from matplotlib import rc import ipywidgets as ipw from ipywidgets import interact,interactive import ipywidgets as widgets from IPython.display import HTML %matplotlib widget global global_K1 global global_K2 global global_branche global global_selected_k In [2]: def get_closest_point(clic_x,clic_y): # Get the data from the figure ax= plt.gca() # get axis handle acoustic_data = ax.lines[1] op

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

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

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

Ewald Sphere

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

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

Cylindrical Coordinates Visualization

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

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

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

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