Quickstart#

This is a basic Tidy3D script showing the FDTD simulation of a delectric cube in the presence of a point dipole.

Before running this notebook, make sure to have:

[ ]:

# import packages and authenticate (if needed)
import numpy as np
import matplotlib.pylab as plt

import tidy3d as td
import tidy3d.web as web
# web.configure("YOUR API KEY GOES HERE")

[2]:

# set up parameters of simulation (length scales are micrometers)
freq0 = td.C_0 / 0.75

Create a Structure from a Geometry like this Rectangular Prism Box and a custom Medium.

[3]:

square = td.Structure(
    geometry=td.Box(center=(0, 0, 0), size=(1.5, 1.5, 1.5)),
    medium=td.Medium(permittivity=2.0)
)

Create a Source. In this case it is a Point Dipole which is a uniform current source with a zero size.

[4]:

# create source
source = td.PointDipole(
    center=(-1.5, 0, 0),
    source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10.0),
    polarization="Ey",
)

Create a Monitor like this FieldMonitor to record electromagnetic fields in the frequency domain for our base frequency freq0. By default, this monitor is centered at the (0,0,0) = (x,y,z) coordinate and we specify a infinite xy plane in which to record the fields through the size parameter.

[5]:

# create monitor
monitor = td.FieldMonitor(
    size=(td.inf, td.inf, 0),
    freqs=[freq0],
    name="fields",
    colocate=True,
)

All these components are used to create a Simulation:

[6]:

sim = td.Simulation(
    size=(4, 3, 3),
    grid_spec=td.GridSpec.auto(min_steps_per_wvl=25),
    structures=[square],
    sources=[source],
    monitors=[monitor],
    run_time=120/freq0,
)

[7]:

# visualize in 3D
sim.plot_3d()

[8]:

print(
    f"simulation grid is shaped {sim.grid.num_cells} for {int(np.prod(sim.grid.num_cells)/1e6)} million cells."
)

simulation grid is shaped [179, 147, 147] for 3 million cells.

The python web API is used to run your simulation quickly in the cloud. The output data is stored in a SimulationData container.

[9]:

# run simulation
data = td.web.run(sim, task_name="quickstart", path="data/data.hdf5", verbose=True)

[09:31:15] Created task 'quickstart' with task_id
           'fdve-a65fc275-cb18-4630-adf2-0a4e976bf5fbv1'.

           View task using web UI at
           'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a65fc275-cb18-
           4630-adf2-0a4e976bf5fbv1'.

[09:31:17] status = queued

[09:31:27] status = preprocess

[09:31:32] Maximum FlexCredit cost: 0.025. Use 'web.real_cost(task_id)' to get
           the billed FlexCredit cost after a simulation run.

           starting up solver

           running solver

           To cancel the simulation, use 'web.abort(task_id)' or
           'web.delete(task_id)' or abort/delete the task in the web UI.
           Terminating the Python script will not stop the job running on the
           cloud.

[09:31:39] early shutoff detected, exiting.

           status = postprocess

[09:31:44] status = success

[09:31:45] View simulation result at
           'https://tidy3d.simulation.cloud/workbench?taskId=fdve-a65fc275-cb18-
           4630-adf2-0a4e976bf5fbv1'.

[09:31:46] loading SimulationData from data/data.hdf5

[10]:

# see the log
print(data.log)

Simulation domain Nx, Ny, Nz: [179, 147, 147]
Applied symmetries: (0, 0, 0)
Number of computational grid points: 4.0184e+06.
Using subpixel averaging: True
Number of time steps: 7.5140e+03
Automatic shutoff factor: 1.00e-05
Time step (s): 3.9959e-17


Compute source modes time (s):     0.0422
Compute monitor modes time (s):    0.0026
Rest of setup time (s):            2.1802

Running solver for 7514 time steps...
- Time step    300 / time 1.20e-14s (  4 % done), field decay: 1.00e+00
- Time step    498 / time 1.99e-14s (  6 % done), field decay: 1.00e+00
- Time step    601 / time 2.40e-14s (  8 % done), field decay: 2.60e-01
- Time step    901 / time 3.60e-14s ( 12 % done), field decay: 2.62e-03
- Time step   1202 / time 4.80e-14s ( 16 % done), field decay: 6.38e-05
- Time step   1502 / time 6.00e-14s ( 20 % done), field decay: 2.22e-06
Field decay smaller than shutoff factor, exiting solver.

Solver time (s):                   1.2144
Data write time (s):               0.0036

This monitor data can be easily plotted through available plot methods. You can also save, modify, and custom plot the raw FieldData and more.

[11]:

# plot the field data stored in the monitor
ax = data.plot_field("fields", "Ey", z=0)

See all our examples to help you with your own designs!