diff --git "a/LabFisica3/Practica 3 - Difracci\303\263n/Informe P3 Difraccion.pdf" "b/LabFisica3/Practica 3 - Difracci\303\263n/Informe P3 Difraccion.pdf"
new file mode 100644
index 0000000000000000000000000000000000000000..54642cc79c15ddaf3c2824743e233e087d4130c4
Binary files /dev/null and "b/LabFisica3/Practica 3 - Difracci\303\263n/Informe P3 Difraccion.pdf" differ
diff --git "a/LabFisica3/Practica 3 - Difracci\303\263n/difraccion.ipynb" "b/LabFisica3/Practica 3 - Difracci\303\263n/difraccion.ipynb"
index 2ee975626c2bb72da31e458e9ddfd35b9e024293..066ce1e8b02866a88aebeb10ea5a4794def46c5e 100644
--- "a/LabFisica3/Practica 3 - Difracci\303\263n/difraccion.ipynb"	
+++ "b/LabFisica3/Practica 3 - Difracci\303\263n/difraccion.ipynb"	
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -149,12 +149,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1000x500 with 2 Axes>"
       ]
@@ -212,7 +212,7 @@
     "plt.subplot(1, 2, 1)\n",
     "plt.imshow(np.abs(grating), cmap='gray')\n",
     "plt.title('Diffraction Grating')\n",
-    "plt.axis('off')\n",
+    "# plt.axis('off')\n",
     "\n",
     "# Plot the Fourier transform on a logarithmic scale\n",
     "plt.subplot(1, 2, 2)\n",
diff --git a/LabFisica3/Practica 4 - Resonancia en tubo/Informe P4 Resonancia.pdf b/LabFisica3/Practica 4 - Resonancia en tubo/Informe P4 Resonancia.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..228a1c17b19b34126ad41415b12bcade38a08f4d
Binary files /dev/null and b/LabFisica3/Practica 4 - Resonancia en tubo/Informe P4 Resonancia.pdf differ
diff --git a/LabFisica3/Practica 4 - Resonancia en tubo/pipe_simulation.mph b/LabFisica3/Practica 4 - Resonancia en tubo/pipe_simulation.mph
new file mode 100644
index 0000000000000000000000000000000000000000..517b0559badb5eeb23837762c328b649fd0b71ad
Binary files /dev/null and b/LabFisica3/Practica 4 - Resonancia en tubo/pipe_simulation.mph differ
diff --git a/README.md b/README.md
index 0dafda9c6844746d7b371d45fe1274ae92773968..b25c4c51fae19fff145637dc0ab0319178674407 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,8 @@ Repositorio para alojar códigos, datos, documentos y demás archivos relacionad
 Actualmente se consideran los cursos:
 - Métodos Matemáticos para Físicos 1
 - Algoritmos y Arquetipos de Computación de Alto Rendimiento
+- Lab Física 3
+- Métodos Matemáticos para Físicos 2
 
 <center>
     <img src="https://media.giphy.com/media/13HgwGsXF0aiGY/giphy.gif">