Components

The notebook will describe the different component that can be added to the beamline, their parameters, and how to inspect the neutrons that reach each component.

import scipp as sc
import tof

meter = sc.Unit('m')
Hz = sc.Unit('Hz')
deg = sc.Unit('deg')

We begin by making a source pulse using the profile from ESS.

source = tof.Source(facility='ess', neutrons=1_000_000)
source.plot()

Adding a detector

We first add a Detector component which simply records all the neutrons that reach it. It does not block any neutrons, they all travel through the detector without being absorbed.

detector = tof.Detector(distance=30.0 * meter, name='detector')

# Build the instrument model
model = tof.Model(source=source, detectors=[detector])
model

Model:
  Source: Source:
  pulses=1, neutrons per pulse=1000000
  frequency=14.0 Hz
  facility='ess'
  Choppers:
  Detectors:
    detector: Detector(name=detector, distance=30.0 m)

# Run and plot the rays
res = model.run()
res.plot()

Plot(ax=<Axes: xlabel='Time [μs]', ylabel='Distance [m]'>, fig=<Figure size 640x480 with 2 Axes>)

As expected, the detector sees all the neutrons from the pulse. Each component in the instrument has a .plot() method, which allows us to quickly visualize histograms of the neutron counts at the detector.

res.detectors['detector'].plot()

The data itself is available via the .toa, .wavelength, .birth_time, and .speed properties, depending on which one you wish to inspect.

print(res.detectors['detector'].toa)
print(res.detectors['detector'].wavelength)
print(res.detectors['detector'].birth_time)
print(res.detectors['detector'].speed)

toa: min=1557.5797752646392 µs, max=153795.23492869534 µs, events=1000000
wavelength: min=0.19851914881207178 Å, max=19.891459448812775 Å, events=1000000
birth_time: min=12.449180272791654 µs, max=4981.477640155045 µs, events=1000000
speed: min=198.88103315393266 m/s, max=19927.719969545215 m/s, events=1000000

Adding a chopper

Next, we add a chopper in the beamline, with a frequency, phase, distance from source, and a set of open and close angles for the cutouts in the rotating disk.

chopper1 = tof.Chopper(
    frequency=10.0 * Hz,
    open=sc.array(
        dims=['cutout'],
        values=[30.0, 50.0],
        unit='deg',
    ),
    close=sc.array(
        dims=['cutout'],
        values=[40.0, 80.0],
        unit='deg',
    ),
    phase=0.0 * deg,
    distance=8 * meter,
    name="Chopper1",
)
chopper1

Chopper(name=Chopper1, distance=8.0 m, frequency=10.0 Hz, phase=0.0 deg, direction=CLOCKWISE, cutouts=2)

We can directly set this on our existing model, and re-run the simulation.

model.add(chopper1)
res = model.run()
res.plot()

Plot(ax=<Axes: xlabel='Time [μs]', ylabel='Distance [m]'>, fig=<Figure size 640x480 with 2 Axes>)

As expected, the two openings now create two bursts of neutrons, separating the wavelengths into two groups.

If we plot the chopper data,

res.choppers['Chopper1'].toa.plot()

we notice that the chopper sees all the incoming neutrons, and blocks many of them (gray), only allowing a subset to pass through the openings (blue).

The detector now sees two peaks in its histogrammed counts:

res.detectors['detector'].toa.plot()

Multiple choppers

It is of course possible to add more than one chopper. Here we add a second one, further down the beam path, which splits each of the groups into two more groups.

chopper2 = tof.Chopper(
    frequency=5.0 * Hz,
    open=sc.array(
        dims=['cutout'],
        values=[30.0, 40.0, 55.0, 70.0],
        unit='deg',
    ),
    close=sc.array(
        dims=['cutout'],
        values=[35.0, 48.0, 65.0, 90.0],
        unit='deg',
    ),
    phase=0.0 * deg,
    distance=20 * meter,
    name="Chopper2",
)

model.add(chopper2)
res = model.run()
res.plot()

Plot(ax=<Axes: xlabel='Time [μs]', ylabel='Distance [m]'>, fig=<Figure size 640x480 with 2 Axes>)

The distribution of neutrons that are blocked and pass through the second chopper looks as follows:

res.choppers['Chopper2'].plot()

while the detector now sees 4 peaks

res.detectors['detector'].plot()

To view the blocked rays on the time-distance diagram of the model, use

res.plot(visible_rays=100, blocked_rays=5000)

Plot(ax=<Axes: xlabel='Time [μs]', ylabel='Distance [m]'>, fig=<Figure size 640x480 with 2 Axes>)

Adding a monitor

Detectors can be placed anywhere in the beam path, and in the next example we place a detector (which will act as a monitor) between the first and second chopper.

monitor = tof.Detector(distance=15.0 * meter, name='monitor')

model.add(monitor)
res = model.run()
res.plot()

Plot(ax=<Axes: xlabel='Time [μs]', ylabel='Distance [m]'>, fig=<Figure size 640x480 with 2 Axes>)

res.detectors['monitor'].plot()

Counter-rotating chopper

By default, choppers are rotating clockwise. This means than when open and close angles of the chopper windows are defined as increasing angles in the anti-clockwise direction, the first window (with the lowest opening angles) will be the first one to pass in front of the beam.

To make a chopper rotate in the anti-clockwise direction, use the direction argument:

chopper = tof.Chopper(
    frequency=10.0 * Hz,
    open=sc.array(
        dims=['cutout'],
        values=[280.0, 320.0],
        unit='deg',
    ),
    close=sc.array(
        dims=['cutout'],
        values=[310.0, 330.0],
        unit='deg',
    ),
    direction=tof.AntiClockwise,
    phase=0.0 * deg,
    distance=8 * meter,
    name="Counter-rotating chopper",
)

model = tof.Model(source=source, detectors=[detector], choppers=[chopper])
res = model.run()

res.plot()

Plot(ax=<Axes: xlabel='Time [μs]', ylabel='Distance [m]'>, fig=<Figure size 640x480 with 2 Axes>)