From 74dc9b4a29705f9c5ae81992d7537a75e1705bf9 Mon Sep 17 00:00:00 2001
From: Amir Mirzanejad <aqm6884@psu.edu>
Date: Fri, 8 Sep 2023 12:10:23 -0400
Subject: [PATCH] Upload New File
---
PES_of_Hamiltonian.ipynb | 120 +++++++++++++++++++++++++++++++++++++++
1 file changed, 120 insertions(+)
create mode 100644 PES_of_Hamiltonian.ipynb
diff --git a/PES_of_Hamiltonian.ipynb b/PES_of_Hamiltonian.ipynb
new file mode 100644
index 0000000..be85fc2
--- /dev/null
+++ b/PES_of_Hamiltonian.ipynb
@@ -0,0 +1,120 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "c1bacd2c-a5c0-4cd4-b78d-9728220c136c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<iframe\n",
+ " scrolling=\"no\"\n",
+ " width=\"1220px\"\n",
+ " height=\"1820\"\n",
+ " src=\"iframe_figures/figure_3.html\"\n",
+ " frameborder=\"0\"\n",
+ " allowfullscreen\n",
+ "></iframe>\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# improt dependecies\n",
+ "import plotly\n",
+ "import scipy.ndimage\n",
+ "import numpy as np\n",
+ "import scipy\n",
+ "import plotly.io as pio\n",
+ "import plotly.graph_objects as go\n",
+ "pio.renderers.default = \"iframe\"\n",
+ "\n",
+ "# Assuming Energy values from 'HubbardModelTriqs.ipynb' are stored in 'Energies_U_0.npy' file \n",
+ "Enegies_U_0 = np.load(\"Energies_U_0.npy\")\n",
+ "\n",
+ "# Apply the Gaussian filter\n",
+ "sigma = [0.1, 0.1]\n",
+ "data_smooth_U = scipy.ndimage.gaussian_filter(Enegies_U_0[:,:,0], sigma)\n",
+ "data_smooth_1_U = scipy.ndimage.gaussian_filter(Enegies_U_0[:,:,1], sigma)\n",
+ "data_smooth_2_U = scipy.ndimage.gaussian_filter(Enegies_U_0[:,:,2], sigma)\n",
+ "\n",
+ "data_smooth = Enegies_U_0[:,:,0]\n",
+ "data_smooth_1 = Enegies_U_0[:,:,1]\n",
+ "data_smooth_2 = Enegies_U_0[:,:,2]\n",
+ "\n",
+ "colorscale1 = [[0, 'yellow'], [1, 'darkorange']]\n",
+ "colorscale2 = [[0, 'darkorange'], [1, '#FF9912']]\n",
+ "colorscale3 = [[0, '#FF9912'], [1, '#FF6103']]\n",
+ "\n",
+ "fig = go.Figure()\n",
+ "\n",
+ "# Add surface trace without contours, using the smoothed data\n",
+ "fig.add_trace(go.Surface(z=data_smooth_U, colorscale=colorscale1))\n",
+ "fig.add_trace(go.Surface(z=data_smooth_1_U, colorscale=colorscale2))\n",
+ "fig.add_trace(go.Surface(z=data_smooth_2_U, colorscale=colorscale3))\n",
+ "\n",
+ "# Generate x and y indices\n",
+ "x = np.arange(0, data_smooth.shape[1])\n",
+ "y = np.arange(0, data_smooth.shape[0])\n",
+ "\n",
+ "# Add lines that correspond to constant x values\n",
+ "for i in range(data_smooth.shape[0]):\n",
+ " fig.add_trace(go.Scatter3d(x=np.full_like(y, i), y=y, z=data_smooth[:, i], mode='lines', \n",
+ " line=dict(color='black', width=5), showlegend=False)) \n",
+ "for i in range(data_smooth.shape[0]):\n",
+ " fig.add_trace(go.Scatter3d(x=np.full_like(y, i), y=y, z=data_smooth_1[:, i], mode='lines', \n",
+ " line=dict(color='black', width=3), showlegend=False))\n",
+ "for i in range(data_smooth.shape[0]):\n",
+ " fig.add_trace(go.Scatter3d(x=np.full_like(y, i), y=y, z=data_smooth_2[:, i], mode='lines', \n",
+ " line=dict(color='black', width=3), showlegend=False))\n",
+ "\n",
+ "# Adjust position of camera \n",
+ "camera_params = dict(up=dict(x=1.25,y=0,z=1),center=dict(x=0,y=0,z=0),eye=dict(x=2.9,y=-2.1,z=0.5)) \n",
+ "\n",
+ "fig.update_layout(scene_camera=camera_params)\n",
+ "\n",
+ "fig.update_layout(title='PES of Hamiltonian for U = 0', autosize=True,\n",
+ " scene = dict(xaxis = dict(title='', title_font_family=\"Arial\", title_font_color='black', title_font_size=25), \n",
+ " yaxis = dict(title='', title_font_family=\"Arial\", title_font_color='black', title_font_size=25),\n",
+ " zaxis = dict(title='', title_font_family=\"Arial\", title_font_color='black', title_font_size=25, \n",
+ " tickfont=dict(size=15), range=[-3.1,-1]),),\n",
+ " width=1200, height=1800, margin=dict(l=60, r=60, b=60, t=90))\n",
+ "\n",
+ "fig.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "beaf20ba-ea31-4a8b-87cd-ffa142c41e2c",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--
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