Discretization Classes

Grid1d

class scqubits.Grid1d(min_val, max_val, pt_count)[source]

Data structure and methods for setting up discretized 1d coordinate grid, generating corresponding derivative matrices.

Parameters
  • min_val (float) – minimum value of the discretized variable

  • max_val (float) – maximum value of the discretized variable

  • pt_count (int) – number of grid points

broadcast(event, **kwargs)

Request a broadcast from CENTRAL_DISPATCH reporting event.

Parameters
  • event (str) – event name from EVENTS

  • **kwargs

Return type

None

classmethod create_from_file(filename)

Read initdata and spectral data from file, and use those to create a new SpectrumData object.

Returns

new SpectrumData object, initialized with data read from file

Return type

SpectrumData

classmethod deserialize(io_data)

Take the given IOData and return an instance of the described class, initialized with the data stored in io_data.

Return type

Serializable

filewrite(filename)

Convenience method bound to the class. Simply accesses the write function.

Return type

None

first_derivative_matrix(prefactor=1.0, periodic=False)[source]

Generate sparse matrix for first derivative of the form \(\partial_{x_i}\). Uses STENCIL setting to construct the matrix with a multi-point stencil.

Parameters
  • prefactor (Union[float, complex]) – prefactor of the derivative matrix (default value: 1.0)

  • periodic (bool) – set to True if variable is a periodic variable

Return type

dia_matrix

Returns

sparse matrix in dia format

get_initdata()[source]

Returns dict appropriate for creating/initializing a new Grid1d object. :rtype: dict

grid_spacing()[source]
Return type

float

Returns

spacing between neighboring grid points

make_linspace()[source]

Returns a numpy array of the grid points :rtype: ndarray

receive(event, sender, **kwargs)

Receive a message from CENTRAL_DISPATCH and initiate action on it.

Parameters
  • event (str) – event name from EVENTS

  • sender (DispatchClient) – original sender reporting the event

  • **kwargs

Return type

None

second_derivative_matrix(prefactor=1.0, periodic=False)[source]

Generate sparse matrix for second derivative of the form \(\partial^2_{x_i}\). Uses STENCIL setting to construct the matrix with a multi-point stencil.

Parameters
  • prefactor (Union[float, complex]) – optional prefactor of the derivative matrix (default value = 1.0)

  • periodic (bool) – set to True if variable is a periodic variable (default value = False)

Return type

dia_matrix

Returns

sparse matrix in dia format

serialize()

Convert the content of the current class instance into IOData format.

Return type

IOData


GridSpec

class scqubits.core.discretization.GridSpec(minmaxpts_array)[source]

Class for specifying a general discretized coordinate grid (arbitrary dimensions).

Parameters

minmaxpts_array (ndarray) – array of with entries [minvalue, maxvalue, number of points]

broadcast(event, **kwargs)

Request a broadcast from CENTRAL_DISPATCH reporting event.

Parameters
  • event (str) – event name from EVENTS

  • **kwargs

Return type

None

classmethod create_from_file(filename)

Read initdata and spectral data from file, and use those to create a new SpectrumData object.

Returns

new SpectrumData object, initialized with data read from file

Return type

SpectrumData

classmethod deserialize(io_data)

Take the given IOData and return an instance of the described class, initialized with the data stored in io_data.

Return type

Serializable

filewrite(filename)

Convenience method bound to the class. Simply accesses the write function.

Return type

None

receive(event, sender, **kwargs)

Receive a message from CENTRAL_DISPATCH and initiate action on it.

Parameters
  • event (str) – event name from EVENTS

  • sender (DispatchClient) – original sender reporting the event

  • **kwargs

Return type

None

serialize()

Convert the content of the current class instance into IOData format.

Return type

IOData

unwrap()[source]

Auxiliary routine that yields a tuple of the parameters specifying the grid.

Return type

Tuple[ndarray, ndarray, Union[List[int], ndarray], int]