3. Vector Chirped Z-transform (VCZT)

[1]:

from diffractio import degrees, um
from diffractio import np

from diffractio.scalar_masks_XY import Scalar_mask_XY
from diffractio.scalar_sources_XY import Scalar_source_XY

from diffractio.vector_sources_XY import Vector_source_XY

[2]:

size = 25 * um
x0 = np.linspace(-size / 2, size / 2, 512)
y0 = np.linspace(-size / 2, size / 2, 256)

focal = 16 * um
wavelength = 0.6328 * um

[ ]:

u0 = Scalar_source_XY(x0, y0, wavelength)
u0.gauss_beam(
    r0=(0 * um, 0 * um),
    w0=(32 * um, 32 * um),
    z0=0 * um,
    A=1,
    theta=0 * degrees,
    phi=0 * degrees,
)

[4]:

t = Scalar_mask_XY(x0, y0, wavelength)
t.lens_cylindrical(x0=0, focal=focal, angle=90 * degrees)
t.lens(r0=(0.0, 0.0), focal=focal)

[5]:

u1 = t * u0

EM1 = Vector_source_XY(x0, y0, wavelength)
EM1.constant_polarization(u=u1, v=(1, 1j))
EM1.pupil()

[6]:

EM1.draw("intensities", logarithm=0)

../../../_images/source_tutorial_vector_algorithms_VCZT_6_0.png

3.1. to value

[7]:

x_out = 0.0
y_out = 0.0
z = focal

[8]:

%%time
EM2_1D=EM1.VCZT(z, x_out, y_out, verbose=True)
print(EM2_1D)

((-2.914244570650705-12.016921496269976j), (12.016921496269976-2.914244570650705j), (-4.39648317751562e-14-7.66053886991358e-15j))
CPU times: user 60.7 ms, sys: 122 ms, total: 183 ms
Wall time: 60.9 ms

3.2. to x_field

[9]:

size_out = 16 * um
x_out = np.linspace(-size_out / 2, size_out / 2, 512)
y_out = 0.0
z = focal

[10]:

%%time
EM2_1D=EM1.VCZT(z, x_out, y_out)
EM2_1D.draw('intensities');

CPU times: user 99.9 ms, sys: 70.3 ms, total: 170 ms
Wall time: 94.8 ms

../../../_images/source_tutorial_vector_algorithms_VCZT_12_1.png

3.3. to z_field

[11]:

x_out = 0.0
y_out = 0.0
z = np.linspace(focal - 10 * um, focal + 4 * um, 64)

[12]:

%%time
EM2=EM1.VCZT(z, x_out, y_out, verbose=False);

CPU times: user 2 s, sys: 752 ms, total: 2.75 s
Wall time: 2.76 s

[13]:

EM2.draw("intensities")

../../../_images/source_tutorial_vector_algorithms_VCZT_16_0.png

3.4. to XZ_field

[14]:

size_out = 12 * um
x_out = np.linspace(-size_out / 2, size_out / 2, 128)
y_out = 0.0
z = np.linspace(focal - 2 * um - 6 * um, focal - 2 * um + 6 * um, 64)

[15]:

%%time
EM2=EM1.VCZT(z, x_out, y_out)

CPU times: user 1.57 s, sys: 553 ms, total: 2.13 s
Wall time: 2.06 s

[16]:

EM2.draw("intensities", logarithm=1e-1)

../../../_images/source_tutorial_vector_algorithms_VCZT_20_0.png

3.5. to XY_field

[17]:

size_out = 4 * um
x_out = np.linspace(-size_out / 2, size_out / 2, 512)
y_out = np.linspace(-size_out / 2, size_out / 2, 512)
z = focal - 3 * um

[18]:

%%time
EM2=EM1.VCZT(z, x_out, y_out)

CPU times: user 84.8 ms, sys: 28 ms, total: 113 ms
Wall time: 113 ms

[19]:

EM2.draw("intensities", logarithm=1e-1)

../../../_images/source_tutorial_vector_algorithms_VCZT_24_0.png

3.6. to XYZ_field

[20]:

size_out = 6 * um
x_out = np.linspace(-size_out / 2, size_out / 2, 32)
y_out = np.linspace(-size_out / 2, size_out / 2, 64)
z = np.linspace(focal - 2 * um - 6 * um, focal - 2 * um + 6 * um, 16)

[21]:

%%time
EM3=EM1.VCZT(z, x_out, y_out)

CPU times: user 580 ms, sys: 135 ms, total: 714 ms
Wall time: 673 ms

[22]:

EM3.draw_XZ("intensities", y0=0, logarithm=1e-1)

<Figure size 480x360 with 0 Axes>

../../../_images/source_tutorial_vector_algorithms_VCZT_28_1.png

[23]:

EM3.draw_YZ("intensities", x0=0, logarithm=1e-1)

<Figure size 480x360 with 0 Axes>

../../../_images/source_tutorial_vector_algorithms_VCZT_29_1.png