Update autocorrelation.ipynb

hoodlabpurdue · Feb 12, 2024 · f8ba15d · f8ba15d
1 parent 2fbdde8
commit f8ba15d
Showing 1 changed file with 47 additions and 0 deletions.
diff --git a/figures/Autocorrelation/autocorrelation.ipynb b/figures/Autocorrelation/autocorrelation.ipynb
@@ -137,6 +137,46 @@
     "        return x, y\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def g2_simulation_fun(tlist, w, j, gamma, I, Isat, dephasing, alpha, A, xoffset, yoffset, frequency='blue'):\n",
+    "    tlist = np.array(tlist)\n",
+    "    w = np.float64(w) * (-1) ** (frequency == 'red')\n",
+    "    \"\"\"\n",
+    "    delta is the total frequency detuning between two molecules\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    N = 2 # number of molecules\n",
+    "    J = j*np.ones([N,N]) # J matrix (units of Gamma=1) only uppder triangle used\n",
+    "    Gamma = gamma*np.ones([N,N]) # Gamma matrix. Only upper triangle used.\n",
+    "    np.fill_diagonal(Gamma, 1) # set all diagonals to 1. \n",
+    "    Omega = np.sqrt(I / 2 / Isat)*(np.ones(N)  -  1e-1*np.random.rand(N) ) # add random to see non-bright modes\n",
+    "\n",
+    "    delta = 2 * np.sqrt(w**2 - j**2)\n",
+    "    Delta = [-delta / 2, delta / 2] # Detuning of laser to each molecule.\n",
+    "    Ns = 4; DWFactor = alpha; vibrelax = 500;  # Ns = 2 or 4, number of states in molecules. 2 (no vibration) or 4 (2 vibrations in each).  DWFactor (0 to 1). vibrelax is the relaxation rate from v=1 to v=0 for ground and excited. Currently DWFactor does not modify Drive. \n",
+    "    q = Collective.Collective(N=N, Ns=Ns)\n",
+    "\n",
+    "    normalized_tlist = np.linspace(0, np.max(tlist) + np.abs(xoffset), 150)\n",
+    "    # y = q.Calculate_g2(N, Ns, w, Delta, normalized_tlist, J, Gamma, Omega, dephasing, DWFactor, vibrelax, plot=False)\n",
+    "    y = q.Calculate_g2(N, Ns, w, Delta, normalized_tlist, J, Gamma, Omega, dephasing, DWFactor, vibrelax, plot=False)\n",
+    "    return interp1d(\n",
+    "        np.concatenate([\n",
+    "            -np.flip(normalized_tlist) - xoffset,\n",
+    "            normalized_tlist - xoffset\n",
+    "        ]), \n",
+    "        np.concatenate([\n",
+    "            np.flip(A * y / y[-1] + yoffset),\n",
+    "            A * y / y[-1] + yoffset\n",
+    "        ]),\n",
+    "        fill_value='extrapolate'\n",
+    "    )(tlist)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 25,
@@ -310,6 +350,13 @@
     "# plt.savefig(r'C:\\Users\\chris\\Box\\HoodLab\\Papers\\superradiance_2023\\data\\sm_bunching' + \"\\\\bunching.pdf\")\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": 5,