OAM_KIST package

Submodules

OAM_KIST.holography module

OAM_KIST.holography.encode_hologram(Amp, Phase, X, Y, pixel_pitch, d, N_steps=0, M=1, prepare=False, measure=False, save=False, path='', name='', use_inv_sinc_minus=False)[source]

phase mask for given amplitude and phase map of superimposed OAM mode.

입력받은 위상, 진폭 정보를 논문 공식에 대입하여 이 상태를 인코딩하는 SLM 홀로그램을 생성합니다. Fundamental Gaussian 모드와의 분리를 위해서 간격이 d 픽셀인 그레이팅이 적용됩니다. 상태 준비에 사용될지, 측정에 사용될지에 따라서 그레이팅의 방향이 바뀝니다. 변수 parity가 이것을 반영합니다. 생성된 홀로그램을 저장할 수 있습니다.

Parameters:

  • Amp (np.ndarray[float]) – amplitude map of superimposed OAM mode. 0. <= *Amp <= 1.

  • Phase (np.ndarray[float]) – phase map of superimposed OAM mode. -pi < *Phase <= pi

  • X (np.ndarray[float]) – x dependent meshgrid.

  • Y (np.ndarray[float]) – y dependent meshgrid.

  • pixel_pitch (float) – pixel size. specified at device document

  • d (float) – grating width. dimension in # of pixel

  • N_steps (float) – number of steps per grating with period d. N_steps=0 is equal to N_steps=d (continuous)

  • M (int) – phase depth. M is basically 1

  • prepare (bool) – decide whether to prepare.

  • measure (bool) – decide whether to measure.

  • save (bool) – decide whether to save.

  • path (string) – directory path for images. needed only when arg save is True

  • name (string) – filename of this image. needed only when arg save is True

  • use_inv_sinc_minus (bool) – whether to use inverse sinc in domain [-pi,0] or not.

Returns:

returns carculated hologram. if arg save is False(default), a hologram in numpy ndarray. And if not, hologram is saved in the directory addording to arg path.

Return type:

np.ndarray[float] or None

Example

>>> import numpy as np
>>> slm_res = [1920, 1080]
>>> slm_pitch = 8e-1
>>> input_w0 = 0.8e-3
>>> grating_width, grating_step, phase_depth = 8, 8, 1
>>> grating_parameter = [grating_width, grating_step, phase_depth]
>>> target_l = [-3, -1, 1, 3]
>>> target_p = np.zeros_like(target_l)
>>> target_weights = [0.4, 0.03, 0.07, 0.5]
>>> img_path, img_name = "./img", "superposition_oam"
>>> superposition_args = [slm_res, slm_pitch, input_w0, target_l, target_p, target_weights, True, False]
>>> fields = generate_oam_superposition(*superposition_args)
>>> hologram_args = [*fields, slm_pitch, *grating_parameter, True, False]
>>> prepare_hologram = encode_hologram(*hologram_args)
>>> hologram_args = hologram_args.append([True, img_path, img_name, False])
>>> encode_hologram(*hologram_args)
OAM_KIST.holography.encode_hologram_405(Amp, Phase, X, Y, pixel_pitch, d, N_steps=0, M=1, prepare=False, measure=False, save=False, path='', name='', use_inv_sinc_minus=False)[source]

phase mask for given amplitude and phase map of superimposed OAM mode.

입력받은 위상, 진폭 정보를 논문 공식에 대입하여 이 상태를 인코딩하는 SLM 홀로그램을 생성합니다. Fundamental Gaussian 모드와의 분리를 위해서 간격이 d 픽셀인 그레이팅이 적용됩니다. 상태 준비에 사용될지, 측정에 사용될지에 따라서 그레이팅의 방향이 바뀝니다. 변수 parity가 이것을 반영합니다. 생성된 홀로그램을 저장할 수 있습니다.

Parameters:

  • Amp (np.ndarray[float]) – amplitude map of superimposed OAM mode. 0. <= *Amp <= 1.

  • Phase (np.ndarray[float]) – phase map of superimposed OAM mode. -pi < *Phase <= pi

  • X (np.ndarray[float]) – x dependent meshgrid.

  • Y (np.ndarray[float]) – y dependent meshgrid.

  • pixel_pitch (float) – pixel size. specified at device document

  • d (float) – grating width. dimension in # of pixel

  • N_steps (float) – number of steps per grating with period d. N_steps=0 is equal to N_steps=d (continuous)

  • M (int) – phase depth. M is basically 1

  • prepare (bool) – decide whether to prepare.

  • measure (bool) – decide whether to measure.

  • save (bool) – decide whether to save.

  • path (string) – directory path for images. needed only when arg save is True

  • name (string) – filename of this image. needed only when arg save is True

  • use_inv_sinc_minus (bool) – whether to use inverse sinc in domain [-pi,0] or not.

Returns:

returns carculated hologram. if arg save is False(default), a hologram in numpy ndarray. And if not, hologram is saved in the directory addording to arg path.

Return type:

np.ndarray[float] or None

Example

>>> import numpy as np
>>> slm_res = [1920, 1080]
>>> slm_pitch = 8e-1
>>> input_w0 = 0.8e-3
>>> grating_width, grating_step, phase_depth = 8, 8, 1
>>> grating_parameter = [grating_width, grating_step, phase_depth]
>>> target_l = [-3, -1, 1, 3]
>>> target_p = np.zeros_like(target_l)
>>> target_weights = [0.4, 0.03, 0.07, 0.5]
>>> img_path, img_name = "./img", "superposition_oam"
>>> superposition_args = [slm_res, slm_pitch, input_w0, target_l, target_p, target_weights, True, False]
>>> fields = generate_oam_superposition(*superposition_args)
>>> hologram_args = [*fields, slm_pitch, *grating_parameter, True, False]
>>> prepare_hologram = encode_hologram(*hologram_args)
>>> hologram_args = hologram_args.append([True, img_path, img_name, False])
>>> encode_hologram(*hologram_args)
OAM_KIST.holography.generate_oam_superposition(res, pixel_pitch, beam_w0, l_modes, p_modes, weights, prepare=True, measure=False, displacement=[0, 0])[source]

Creat E field of superimposed OAM mode (Interferogram method)

Parameters:

  • res (list[int]) – resolution of SLM. [x resolution, y resolution]

  • pixel_pitch (float) – pixel size. specified at device document

  • beam_w0 (float) – beam-waist at z=0.

  • l_modes (list[int]) – selected l indices for superposion. list with length 1 for eigen mode

  • p_modes (list[int]) – selected p indices for superposion. list with length 1 for eigen mode

  • weights (list[float]) – weights for selected l modes.

  • prepare (bool) – whether to prepare the OAM superposition before generating superposition

  • measure (bool) – whether to measure the OAM superposition before generating superposition

Returns:

information about E field and meshgrid i.e. superimosed

Return type:

np.ndarray[float], np.ndarray[float], np.ndarray[float], np.ndarray[float]

Example

>>> import numpy as np
>>> slm_res = [1920, 1080]
>>> slm_pitch = 8e-1
>>> input_w0 = 0.8e-3
>>> target_l = [-3, -1, 1, 3]
>>> target_p = np.zeros_like(target_l)
>>> target_weights = [0.4, 0.03, 0.07, 0.5]
>>> superposition_args = [slm_res, slm_pitch, input_w0, target_l, target_p, target_weights, True, False]
>>> fields = generate_oam_superposition(*superposition_args)

OAM_KIST.utils module

OAM_KIST.utils.diffraction(l, n, res)[source]
OAM_KIST.utils.inv_sinc(x)[source]

Inverse Sinc function.

Parameters:

x (float or np.ndarray) – Normalized Amplitude (0.0 ~ 1.0)

Returns:

Phase value (0.0 ~ -pi)

Return type:

float or np.ndarray

OAM_KIST.utils.inv_sinc_minus(x)[source]

Inverse Sinc function in minus domain.

Parameters:

x (float or np.ndarray) – Normalized Amplitude (0.0 ~ 1.0)

Returns:

Phase value (-pi ~ 0.0)

Return type:

float or np.ndarray

Module contents

OAM_KIST.encode_hologram(Amp, Phase, X, Y, pixel_pitch, d, N_steps=0, M=1, prepare=False, measure=False, save=False, path='', name='', use_inv_sinc_minus=False)[source]

phase mask for given amplitude and phase map of superimposed OAM mode.

입력받은 위상, 진폭 정보를 논문 공식에 대입하여 이 상태를 인코딩하는 SLM 홀로그램을 생성합니다. Fundamental Gaussian 모드와의 분리를 위해서 간격이 d 픽셀인 그레이팅이 적용됩니다. 상태 준비에 사용될지, 측정에 사용될지에 따라서 그레이팅의 방향이 바뀝니다. 변수 parity가 이것을 반영합니다. 생성된 홀로그램을 저장할 수 있습니다.

Parameters:

  • Amp (np.ndarray[float]) – amplitude map of superimposed OAM mode. 0. <= *Amp <= 1.

  • Phase (np.ndarray[float]) – phase map of superimposed OAM mode. -pi < *Phase <= pi

  • X (np.ndarray[float]) – x dependent meshgrid.

  • Y (np.ndarray[float]) – y dependent meshgrid.

  • pixel_pitch (float) – pixel size. specified at device document

  • d (float) – grating width. dimension in # of pixel

  • N_steps (float) – number of steps per grating with period d. N_steps=0 is equal to N_steps=d (continuous)

  • M (int) – phase depth. M is basically 1

  • prepare (bool) – decide whether to prepare.

  • measure (bool) – decide whether to measure.

  • save (bool) – decide whether to save.

  • path (string) – directory path for images. needed only when arg save is True

  • name (string) – filename of this image. needed only when arg save is True

  • use_inv_sinc_minus (bool) – whether to use inverse sinc in domain [-pi,0] or not.

Returns:

returns carculated hologram. if arg save is False(default), a hologram in numpy ndarray. And if not, hologram is saved in the directory addording to arg path.

Return type:

np.ndarray[float] or None

Example

>>> import numpy as np
>>> slm_res = [1920, 1080]
>>> slm_pitch = 8e-1
>>> input_w0 = 0.8e-3
>>> grating_width, grating_step, phase_depth = 8, 8, 1
>>> grating_parameter = [grating_width, grating_step, phase_depth]
>>> target_l = [-3, -1, 1, 3]
>>> target_p = np.zeros_like(target_l)
>>> target_weights = [0.4, 0.03, 0.07, 0.5]
>>> img_path, img_name = "./img", "superposition_oam"
>>> superposition_args = [slm_res, slm_pitch, input_w0, target_l, target_p, target_weights, True, False]
>>> fields = generate_oam_superposition(*superposition_args)
>>> hologram_args = [*fields, slm_pitch, *grating_parameter, True, False]
>>> prepare_hologram = encode_hologram(*hologram_args)
>>> hologram_args = hologram_args.append([True, img_path, img_name, False])
>>> encode_hologram(*hologram_args)
OAM_KIST.generate_oam_superposition(res, pixel_pitch, beam_w0, l_modes, p_modes, weights, prepare=True, measure=False, displacement=[0, 0])[source]

Creat E field of superimposed OAM mode (Interferogram method)

Parameters:

  • res (list[int]) – resolution of SLM. [x resolution, y resolution]

  • pixel_pitch (float) – pixel size. specified at device document

  • beam_w0 (float) – beam-waist at z=0.

  • l_modes (list[int]) – selected l indices for superposion. list with length 1 for eigen mode

  • p_modes (list[int]) – selected p indices for superposion. list with length 1 for eigen mode

  • weights (list[float]) – weights for selected l modes.

  • prepare (bool) – whether to prepare the OAM superposition before generating superposition

  • measure (bool) – whether to measure the OAM superposition before generating superposition

Returns:

information about E field and meshgrid i.e. superimosed

Return type:

np.ndarray[float], np.ndarray[float], np.ndarray[float], np.ndarray[float]

Example

>>> import numpy as np
>>> slm_res = [1920, 1080]
>>> slm_pitch = 8e-1
>>> input_w0 = 0.8e-3
>>> target_l = [-3, -1, 1, 3]
>>> target_p = np.zeros_like(target_l)
>>> target_weights = [0.4, 0.03, 0.07, 0.5]
>>> superposition_args = [slm_res, slm_pitch, input_w0, target_l, target_p, target_weights, True, False]
>>> fields = generate_oam_superposition(*superposition_args)