{ "cells": [ { "cell_type": "markdown", "id": "38bf69d0", "metadata": {}, "source": [ "# Vibrational strong coupling of liquid water in a Bragg resonator: Unix socket\n", "\n", "**Authors: Xinwei Ji, Tao E. Li**\n", "\n", "Here, we introduce how to use MaxwellLink to run classical molecular dynamics (LAMMPS) simulations of liquid water under vibrational strong coupling by connecting MEEP FDTD with LAMMPS." ] }, { "cell_type": "markdown", "id": "2b33908a", "metadata": {}, "source": [ "## 1. Run with realistic Bragg resonator\n", "\n", "Let's try to setup our simulation for an abstract `Molecule` confined at the center of a Bragg resonator in 1D. \n", "\n", "This Bragg resonator is composed of a pair of parallel mirrors spaced by $\\lambda/2$, each of which consists of five periodic dielectric layers. The spacing between the neighboring dielectric layer is $\\lambda/4$. With the refrative index of each dielectric layer as $n=2$, each dielectric layer possesses a thickness of $\\lambda/8$. This Bragg resonator supports a resonant cavity mode at wavelength $\\lambda$.\n", "\n", "We also artifically enhance the current density of this abstract `Molecule` by a factor of `rescaling_factor=1e5`, so that strong coupling can form for a small ensemble of molecules coupled to the optical cavity. This abstract `Molecule` is connected to the MEEP FDTD solver via the Unix socket in local machines." ] }, { "cell_type": "code", "execution_count": 1, "id": "da51feee", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using MPI version 4.1, 1 processes\n", "[Init Molecule] Under socket mode, registered molecule with ID 0\n", "\n", "\n", " ######### MaxwellLink Units Helper #########\n", " MEEP uses its own units system, which is based on the speed of light in vacuum (c=1), \n", " the permittivity of free space (epsilon_0=1), and the permeability of free space (mu_0=1). \n", " To couple MEEP with molecular dynamics, we set [c] = [epsilon_0] = [mu_0] = [hbar] = 1. \n", " By further defining the time unit as 2.00E+01 fs, we can fix the units system of MEEP (mu).\n", "\n", " Given the simulation resolution = 20,\n", " - FDTD dt = 2.50E-02 mu (0.5/resolution) = 5.00E-01 fs\n", " - FDTD dx = 5.00E-02 mu (1.0/resolution) = 3.00E+02 nm\n", " - Time [t]: 1 mu = 2.00E+01 fs = 8.27E+02 a.u.\n", " - Length [x]: 1 mu = 6.00E+03 nm\n", " - Angular frequency [omega = 2 pi * f]: 1 mu = 2.0688E-01 eV = 1.6686E+03 cm-1 = 7.6027E-03 a.u.\n", " - Electric field [E]: 1 mu = 1.66E+03 V/m = 3.23E-09 a.u.\n", " Hope this helps!\n", " ############################################\n", "\n", "\n" ] } ], "source": [ "import numpy as np\n", "import maxwelllink as mxl\n", "import meep as mp\n", "\n", "address = \"socket_cavmd\"\n", "hub = mxl.SocketHub(unixsocket=address, timeout=10.0, latency=1e-5)\n", "\n", "resolution = 20\n", "time_units_fs = 20\n", "rescaling = 0.47\n", "\n", "# geometry 1: 1d bragg resonator\n", "pml_thickness = 2.0 * rescaling\n", "t1 = 0.125 * rescaling\n", "t2 = 0.25 * rescaling\n", "n1 = 2.0\n", "n2 = 1.0\n", "\n", "nlayer = 5\n", "layer_indexes = np.array([n2, n1] * nlayer + [1.0] + [n1, n2] * nlayer)\n", "layer_thicknesses = np.array([t2, t1] * nlayer + [0.5 * rescaling] + [t1, t2] * nlayer)\n", "\n", "layer_thicknesses[0] += pml_thickness\n", "layer_thicknesses[-1] += pml_thickness\n", "length = np.sum(layer_thicknesses)\n", "layer_centers = np.cumsum(layer_thicknesses) - layer_thicknesses/2\n", "layer_centers = layer_centers - length/2\n", "cell_size = mp.Vector3(length, 0, 0)\n", "pml_layers = [mp.PML(thickness=pml_thickness)]\n", "\n", "geometry = [mp.Block(mp.Vector3(layer_thicknesses[i], mp.inf, mp.inf),\n", " center=mp.Vector3(layer_centers[i], 0, 0), material=mp.Medium(index=layer_indexes[i]))\n", " for i in range(layer_thicknesses.size)]\n", "\n", "# geometry 2: 1d free space with metallic boundary conditions\n", "# one can comment out the following block to check energy conservation\n", "'''\n", "length = 0.5 * rescaling\n", "cell_size = mp.Vector3(length, 0, 0)\n", "geometry = []\n", "pml_layers = []\n", "'''\n", "\n", "molecule = mxl.Molecule(\n", " hub=hub,\n", " center=mp.Vector3(0, 0, 0), \n", " size=mp.Vector3(0.25, 0, 0), \n", " sigma=0.05, \n", " dimensions=1, \n", " rescaling_factor=1e5\n", ")\n", "\n", "sources_non_molecule = []\n", "sources = sources_non_molecule + molecule.sources\n", "sim = mxl.MeepSimulation(\n", " hub=hub,\n", " molecules=[molecule],\n", " cell_size=cell_size,\n", " resolution=resolution,\n", " time_units_fs=time_units_fs,\n", " sources=sources,\n", " geometry=geometry,\n", " boundary_layers=pml_layers\n", ")\n" ] }, { "cell_type": "markdown", "id": "9b4c8326", "metadata": {}, "source": [ "## 2. Python way to lunch LAMMPS on a separate terminal\n", "\n", "We then attach this abstract `Molecule` with liquid water (216 H2O molecules) simulated via the LAMMPS MD driver.\n", "\n", "Generally, using the socket interface requires to launch the EM simulation in one terminal and then start the molecular driver simulation in a separate terminal. To avoid openning a second terminal, below we introduce a python helper function `launch_lmp(...)`, which will launch LAMMPS (the `lmp_mxl` binary file) from Python (so we can stay within this notebook to finish this tutorial). \n", "\n", "The LAMMPS code performs a NVE liquid water simulation. The `fix mxl` command in the LAMMPS input file communicates between LAMMPS and MaxwellLink.\n", "\n", "In a 2021 MacBook Pro M1, this simulation takes approximately 1.5 minutes." ] }, { "cell_type": "code", "execution_count": 2, "id": "d049daa2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Launching LAMMPS via subprocess...\n", "If you prefer to run it manually, execute:\n", " ./lmp_input/launch_lmp_xml.sh socket_cavmd \n", "Preparing LAMMPS input files with port socket_cavmd...\n", "LAMMPS (29 Aug 2024 - Update 1)\n", "Reading data file ...\n", " orthogonal box = (0 0 0) to (35.233 35.233 35.233)\n", " 1 by 1 by 1 MPI processor grid\n", " reading atoms ...\n", " 648 atoms\n", " scanning bonds ...\n", " 2 = max bonds/atom\n", " scanning angles ...\n", " 1 = max angles/atom\n", " orthogonal box = (0 0 0) to (35.233 35.233 35.233)\n", " 1 by 1 by 1 MPI processor grid\n", " reading bonds ...\n", " 432 bonds\n", " reading angles ...\n", " 216 angles\n", "Finding 1-2 1-3 1-4 neighbors ...\n", " special bond factors lj: 0 0 0 \n", " special bond factors coul: 0 0 0 \n", " 2 = max # of 1-2 neighbors\n", " 1 = max # of 1-3 neighbors\n", " 1 = max # of 1-4 neighbors\n", " 2 = max # of special neighbors\n", " special bonds CPU = 0.000 seconds\n", " read_data CPU = 0.004 seconds\n", "[MaxwellLink] Will reset initial permanent dipole to zero.\n", "\n", "CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE\n", "\n", "Your simulation uses code contributions which should be cited:\n", "- Type Label Framework: https://doi.org/10.1021/acs.jpcb.3c08419\n", "The log file lists these citations in BibTeX format.\n", "\n", "CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE\n", "\n", "PPPM initialization ...\n", " extracting TIP4P info from pair style\n", " using 12-bit tables for long-range coulomb (src/kspace.cpp:342)\n", " G vector (1/distance) = 0.16615131\n", " grid = 15 15 15\n", " stencil order = 5\n", " estimated absolute RMS force accuracy = 1.3905979e-05\n", " estimated relative force accuracy = 4.9659152e-05\n", " using double precision KISS FFT\n", " 3d grid and FFT values/proc = 10648 3375\n", "WARNING: Communication cutoff 0 is shorter than a bond length based estimate of 4.67. This may lead to errors. (src/comm.cpp:730)\n", "WARNING: Increasing communication cutoff to 21.065072 for TIP4P pair style (src/KSPACE/pair_lj_cut_tip4p_long.cpp:497)\n", "Generated 0 of 1 mixed pair_coeff terms from geometric mixing rule\n", "Neighbor list info ...\n", " update: every = 1 steps, delay = 0 steps, check = yes\n", " max neighbors/atom: 2000, page size: 100000\n", " master list distance cutoff = 19.563145\n", " ghost atom cutoff = 21.065072\n", " binsize = 9.7815724, bins = 4 4 4\n", " 1 neighbor lists, perpetual/occasional/extra = 1 0 0\n", " (1) pair lj/cut/tip4p/long, perpetual\n", " attributes: half, newton on\n", " pair build: half/bin/newton\n", " stencil: half/bin/3d\n", " bin: standard\n", "Setting up Verlet run ...\n", " Unit style : electron\n", " Current step : 0\n", " Time step : 0.5\n", "Per MPI rank memory allocation (min/avg/max) = 8.721 | 8.721 | 8.721 Mbytes\n", " Step Temp E_pair E_mol TotEng Press \n", " 0 300 -4.0744255 0.58197053 -2.5704367 71675325 \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning: grid volume is not an integer number of pixels; cell size will be rounded to nearest pixel.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "-----------\n", "Initializing structure...\n", "time for choose_chunkdivision = 0.000111 s\n", "Working in 2D dimensions.\n", "Computational cell is 3.9 x 0.05 x 0 with resolution 20\n", " block, center = (-1.41,0,0)\n", " size (1.0575,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (1,1,1)\n", " block, center = (-0.851875,0,0)\n", " size (0.05875,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (4,4,4)\n", " block, center = (-0.76375,0,0)\n", " size (0.1175,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (1,1,1)\n", " block, center = (-0.675625,0,0)\n", " size (0.05875,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (4,4,4)\n", " block, center = (-0.5875,0,0)\n", " size (0.1175,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (1,1,1)\n", " block, center = (-0.499375,0,0)\n", " size (0.05875,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (4,4,4)\n", " block, center = (-0.41125,0,0)\n", " size (0.1175,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (1,1,1)\n", " block, center = (-0.323125,0,0)\n", " size (0.05875,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (4,4,4)\n", " block, center = (-0.235,0,0)\n", " size (0.1175,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (1,1,1)\n", " block, center = (-0.146875,0,0)\n", " size (0.05875,1e+20,1e+20)\n", " axes (1,0,0), (0,1,0), (0,0,1)\n", " dielectric constant epsilon diagonal = (4,4,4)\n", " ...(+ 11 objects not shown)...\n", "time for set_epsilon = 0.000486 s\n", "-----------\n", "[MaxwellLink] Assigned a molecular ID: 0\n", "[SocketHub] CONNECTED: mol 0 <- \n", "Meep progress: 11.100000000000001/500.0 = 2.2% done in 4.0s, 176.4s to go\n", "on time step 446 (time=11.15), 0.00900104 s/step\n", "Meep progress: 21.325000000000003/500.0 = 4.3% done in 8.0s, 179.9s to go\n", "on time step 855 (time=21.375), 0.00979736 s/step\n", "Meep progress: 31.475/500.0 = 6.3% done in 12.0s, 178.9s to go\n", "on time step 1261 (time=31.525), 0.00985665 s/step\n", "Meep progress: 41.825/500.0 = 8.4% done in 16.0s, 175.5s to go\n", "on time step 1675 (time=41.875), 0.00966452 s/step\n", "Meep progress: 51.825/500.0 = 10.4% done in 20.0s, 173.3s to go\n", "on time step 2074 (time=51.85), 0.0100325 s/step\n", "Meep progress: 61.300000000000004/500.0 = 12.3% done in 24.0s, 172.1s to go\n", "on time step 2453 (time=61.325), 0.0105861 s/step\n", "Meep progress: 71.275/500.0 = 14.3% done in 28.1s, 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to go\n", "on time step 12049 (time=301.225), 0.0104989 s/step\n", "Meep progress: 310.725/500.0 = 62.1% done in 124.2s, 75.7s to go\n", "on time step 12436 (time=310.9), 0.0103457 s/step\n", "Meep progress: 320.675/500.0 = 64.1% done in 128.2s, 71.7s to go\n", "on time step 12835 (time=320.875), 0.0100505 s/step\n", "Meep progress: 330.90000000000003/500.0 = 66.2% done in 132.2s, 67.6s to go\n", "on time step 13244 (time=331.1), 0.00978893 s/step\n", "Meep progress: 341.0/500.0 = 68.2% done in 136.2s, 63.5s to go\n", "on time step 13648 (time=341.2), 0.00990643 s/step\n", "Meep progress: 350.975/500.0 = 70.2% done in 140.2s, 59.5s to go\n", "on time step 14046 (time=351.15), 0.0100716 s/step\n", "Meep progress: 361.07500000000005/500.0 = 72.2% done in 144.2s, 55.5s to go\n", "on time step 14452 (time=361.3), 0.00986244 s/step\n", "Meep progress: 370.85/500.0 = 74.2% done in 148.2s, 51.6s to go\n", "on time step 14841 (time=371.025), 0.0103139 s/step\n", "Meep progress: 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0.0103158 s/step\n", "Meep progress: 461.5/500.0 = 92.3% done in 184.3s, 15.4s to go\n", "on time step 18470 (time=461.75), 0.00969312 s/step\n", "Meep progress: 472.1/500.0 = 94.4% done in 188.3s, 11.1s to go\n", "on time step 18897 (time=472.425), 0.00937008 s/step\n", "Meep progress: 482.675/500.0 = 96.5% done in 192.3s, 6.9s to go\n", "on time step 19320 (time=483), 0.00948708 s/step\n", "Meep progress: 492.95000000000005/500.0 = 98.6% done in 196.3s, 2.8s to go\n", "on time step 19728 (time=493.2), 0.00982038 s/step\n", "run 0 finished at t = 500.0 (20000 timesteps)\n", "[SocketHub] DISCONNECTED: mol 0 from \n", "[MaxwellLink] Server requested stop/exit, exiting gracefully...\n", "[SocketHub] Unlinked unix socket path /tmp/socketmxl_socket_cavmd\n" ] } ], "source": [ "import shlex\n", "import subprocess\n", "import time\n", "\n", "def launch_lmp(address: str, sleep_time: float = 0.5):\n", " cmd = (\n", " f\"./lmp_input/launch_lmp_xml.sh {address} \"\n", " )\n", " print('Launching LAMMPS via subprocess...')\n", " print('If you prefer to run it manually, execute:')\n", " print(' ' + cmd)\n", " argv = shlex.split(cmd)\n", " proc = subprocess.Popen(argv)\n", " time.sleep(sleep_time)\n", " return proc\n", "\n", "launch_lmp(address)\n", "\n", "sim.run(steps=2e4) " ] }, { "cell_type": "markdown", "id": "32909ef4", "metadata": {}, "source": [ "After the simulation, we then visualize the final EM distribution in real space.\n", "\n", "Apparently, strong EM enhancement is observed at the center of the cavity." ] }, { "cell_type": "code", "execution_count": 4, "id": "5480fa61", "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "eps_data = sim.get_array(center=mp.Vector3(), size=cell_size, component=mp.Dielectric).reshape((-1,1))\n", "ez_data = sim.get_array(center=mp.Vector3(), size=cell_size, component=mp.Ez).reshape((-1,1))\n", "plt.figure()\n", "plt.imshow(eps_data.transpose(), extent=[0, 20, 0, 5], interpolation='spline36', cmap='binary')\n", "plt.imshow(ez_data.transpose(), extent=[0, 20, 0, 5], interpolation='spline36', cmap='RdBu', alpha=0.9)\n", "plt.axis('off')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "c39fdfd2", "metadata": {}, "source": [ "## 3. Plot IR spectrum of liquid water" ] }, { "cell_type": "code", "execution_count": 5, "id": "577cbd5a", "metadata": {}, "outputs": [ { "data": { "image/png": "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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from maxwelllink.tools import ir_spectrum\n", "import matplotlib.pyplot as plt\n", "\n", "fs_to_au = 1 / 0.02418884254\n", "\n", "mux = np.array([ad[\"mux_au\"] for ad in molecule.additional_data_history])\n", "muy = np.array([ad[\"muy_au\"] for ad in molecule.additional_data_history])\n", "muz = np.array([ad[\"muz_au\"] for ad in molecule.additional_data_history])\n", "t = np.array([ad[\"time_au\"] for ad in molecule.additional_data_history]) / fs_to_au\n", "\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(t, mux, label=\"X\")\n", "plt.plot(t, muy, label=\"Y\")\n", "plt.plot(t, muz, label=\"Z\")\n", "plt.xlabel(\"Time (fs)\")\n", "plt.ylabel(\"Dipole Moment (a.u.)\")\n", "plt.title(\"Dipole Moment vs Time\")\n", "plt.legend()\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "freq, sp_x = ir_spectrum(mux, 0.5*time_units_fs/resolution, field_description=\"square\")\n", "freq, sp_y = ir_spectrum(muy, 0.5*time_units_fs/resolution, field_description=\"square\")\n", "freq, sp_z = ir_spectrum(muz, 0.5*time_units_fs/resolution, field_description=\"square\")\n", "\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(freq, sp_x, label=\"X\")\n", "plt.plot(freq, sp_y, label=\"Y\")\n", "plt.plot(freq, sp_z, label=\"Z\")\n", "plt.xlim(0, 5000)\n", "plt.xlabel(\"Frequency (cm$^{-1}$)\")\n", "plt.ylabel(\"Spectral Power\")\n", "plt.title(\"Infrared Spectrum\")\n", "plt.legend()\n", "plt.tight_layout()\n", "\n", "plt.show()\n", "\n" ] }, { "cell_type": "markdown", "id": "46faa442", "metadata": {}, "source": [ "## 4. How to understand energy conservation?\n", "\n", "We can also check energy conservation as below. \n", "\n", "**The energy of the molecular system is reduced** because the molecular system is continuously emitting EM field.\n", "\n", "If the absorbing boundary conditions for the EM field are turned off (as in # geometry 2 in the first code block), i.e., using the geometry below instead of a Bragg resonator with absorbing boundary conditions (PML): \n", "\n", "```python\n", "length = 0.5 * rescaling\n", "cell_size = mp.Vector3(length, 0, 0)\n", "geometry = []\n", "pml_layers = []\n", "```\n", "energy conservation for the molecular system should be greatly improved. The readers may have a try.\n", "\n", "**More importantly, when a larger water system is coupled to the cavity with a smaller rescaling factor**, the IR emission of the molecular system will be greatly reduced, thus also improving energy conservation in the molecular system.\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "f9bf6041", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# also plot energy conservation dynamics\n", "energy_molecule = np.array([ad[\"energy_au\"] for ad in molecule.additional_data_history])\n", "\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(t, energy_molecule, label=\"Molecule Energy\")\n", "plt.xlabel(\"Time (fs)\")\n", "plt.ylabel(\"Energy (au)\")\n", "plt.title(\"Energy Conservation\")\n", "plt.legend()\n", "plt.tight_layout()\n" ] } ], "metadata": { "kernelspec": { "display_name": "mxl", "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": "3.13.9" }, "title": "Socket TLS Workflow" }, "nbformat": 4, "nbformat_minor": 5 }