ingenii_quantum.visualizer

class ingenii_quantum.visualizer.QuantumVisualizer(qc)

Bases: object

static area_segment(r, h)

Calculate the area of a circular segment.

Parameters:

• r (float) – The radius of the circle.

• h (float) – The height of the segment (distance from the chord to the arc).

Returns:

The area of the circular segment.

Return type:

float

static bit_string_index(s)

Return the index of a string of 0s and 1s.

Parameters:

s (string) – bit string

Returns:

index of the string.

Return type:

int

static color_range(c1, c2, n)

Generate a color gradient between two colors.

Parameters:

• c1 (str) – The starting color in hexadecimal.

• c2 (str) – The ending color in hexadecimal.

• n (int) – The number of gradient steps.

Returns:

A list of colors in hexadecimal format.

Return type:

list

static count_control_num(gate_name)

Count the number of consecutive ‘c’ characters in a gate name.

Parameters:

gate_name (str) – The name of the gate.

Returns:

The number of consecutive ‘c’ characters.

Return type:

int

draw_arrow(vector, old_vector, position, tol=0.001)

Draw arrows connecting states between layers.

Parameters:

• vector (np.ndarray) – Current statevector (after the gate is applied).

• old_vector (np.ndarray) – Previous statevector (before the gate is applied).

• position (int) – The layer index (x-axis position in the visualization).

• tol (float) – Tolerance for non-zero probabilities.

draw_basis_states()

Draw basis states as text labels on the y-axis.

draw_bloch_sphere(theta=None, phi=None, ax=None, filename=None)

Visualize a single-qubit quantum state on the Bloch sphere.

Parameters:

• theta (float) – Polar angle for the Bloch vector (default 0).

• phi (float) – Azimuthal angle for the Bloch vector (default 0).

• ax (matplotlib.axes) – A Matplotlib axes to draw on (optional).

• filename (str) – Path to save the plot (optional).

Returns:

The Matplotlib figure object (if fig is not provided).

Return type:

matplotlib.figure.Figure

static draw_color_legend(figsize=None, ax=None, n=64, use_degrees=False, filename=None)

Plot the color legend for the qsphere and state space.

Parameters:

• figsize (tuple) – Figure size in inches.

• ax (matplotlib.axes.Axes) – An optional Axes object to be used for the visualization output. If none is specified a new matplotlib Figure will be created and used. Additionally, if specified there will be no returned Figure since it is redundant.

• n (int) – Number of divisions of the color legend.

• use_degrees (bool) – An optional boolean indicating whether to use

• numbers. (degrees or complex)

• filename (str) – File to save the plot if desired

Returns:

A matplotlib figure instance if the ax kwarg is not set

Return type:

Figure

draw_geometric_plots(filename=None, display_math=False)

Create and visualize geometric representations of a quantum state, including phase disks, the Q-sphere or Bloch sphere, and a color legend.

Parameters:

• filename (str, optional) – If provided, saves the generated plot to the specified file. Defaults to None.

• display_math (bool) – If True, show the fullness of the disks

Returns:

The created figure containing the plots.

Return type:

matplotlib.figure.Figure

draw_phase_disks(ax=None, filename=None, display_math=False)

Plot the color legend for the qsphere and state space.

Parameters:

• ax (matplotlib.axes.Axes) – An optional Axes object to be used for the visualization output. If none is specified a new matplotlib Figure will be created and used. Additionally, if specified there will be no returned Figure since it is redundant.

• filename (str) – File to save the plot if desired

• display_math (bool) – If True, show the fullness of the disk

Returns:

A matplotlib figure instance if the ax kwarg is not set

Return type:

Figure

draw_probabilities(statevector, position, tol=0.001)

Draw probability circles for a given statevector.

Parameters:

• statevector (np.ndarray) – The statevector.

• position (int) – The x-axis position of the circles.

• ax (matplotlib.axes) – axes to draw the probabilities

• tol (float) – Tolerance for non-zero probabilities.

draw_qsphere(figsize=None, ax=None, show_state_labels=True, show_state_phases=False, use_degrees=False, tol=0.001, filename=None)

Plot the qsphere representation of a quantum state. Here, the size of the points is proportional to the probability of the corresponding term in the state and the color represents the phase.

Parameters:

• figsize (tuple) – Figure size in inches.

• ax (matplotlib.axes.Axes) – An optional Axes object to be used for the visualization output. If none is specified a new matplotlib Figure will be created and used. Additionally, if specified there will be no returned Figure since it is redundant.

• show_state_labels (bool) – An optional boolean indicating whether to show labels for each basis state.

• show_state_phases (bool) – An optional boolean indicating whether to show the phase for each basis state.

• use_degrees (bool) – An optional boolean indicating whether to use radians or degrees for the phase values in the plot.

• tol (float) – tolerance to show basis state on the sphere

• filename (str) – File to save the plot if desired

Returns:

A matplotlib figure instance if the ax kwarg is not set

Return type:

Figure

draw_state_space(plot_circuit=False, plot_phase_disks=False, display_math=False, filename=None)

Visualize the quantum circuit’s evolution. Optionally include the circuit diagram.

Parameters:

• plot_circuit (bool) – If True, include the quantum circuit diagram in the figure.

• plt_phase_disks (bool) – If True, include the diagram of phase disks in the figure.

• display_math (bool) – If True, include the value of the statevectors in the figure.

• filename (str) – File name to save the figure.

Returns:

figure of the state space

Return type:

matplotlib.pyplot.figure

static flip_bit(bitstring, i)

Flip the bit at position i in a binary string.

Parameters:

• bitstring (str) – The binary string.

• i (int) – The position of the bit to flip (0-indexed).

Returns:

The binary string with the bit at position i flipped.

Return type:

str

static get_colors(n)

Generate a full cyclic color map with gradients.

Parameters:

n (int) – Total number of colors.

Returns:

A list of colors in hexadecimal format.

Return type:

list

get_statevectors()

Extract statevectors and gate information from the quantum circuit.

Returns:

(list of statevectors, gate set)

Return type:

tuple

get_transformed_bitstrings(unitary, tol=1e-08)

Compute the transformation of all basis states under a unitary matrix and output the transformed bitstrings.

Parameters:

• unitary (np.ndarray) – The unitary matrix of size (2^n, 2^n).

• tol (float) – Tolerance for considering a value as non-zero.

Returns:

A dictionary mapping input bitstrings to their transformed bitstrings.

Return type:

dict

static height_for_probability(radius, prob, total_area)

Calculate the height (h) of a circular segment corresponding to a given probability.

Parameters:

• radius (float) – Radius of the circle.

• prob (float) – Desired probability (fraction of the circle’s area to fill).

• total_area (float) – Total area of the circle.

Returns:

Height (h) of the segment.

Return type:

float

static hex_to_rgb(hex_str)

Convert a hexadecimal color string to an RGB tuple.

Parameters:

hex_str (str) – The hexadecimal color string.

Returns:

The RGB color as a numpy array.

Return type:

np.ndarray

static lex_index(n, k, lst)

Return the lex index of a combination..

Parameters:

• n (int) – the total number of options .

• k (int) – The number of elements.

• lst (list) – list

Returns:

returns int index for lex order

Return type:

int

Raises:

VisualizationError – if length of list is not equal to k

static n_choose_k(n, k)

Return the number of combinations for n choose k.

Parameters:

• n (int) – the total number of options .

• k (int) – The number of elements.

Returns:

binomial coefficient

Return type:

int

static phase_to_rgb(complex_number, n=64, tol=0.001, return_black=True)

Map a phase of a complex number to a color.

Parameters:

• complex_number (complex) – The input complex number.

• n (int) – Number of colors in the gradient.

Returns:

RGB color in hexadecimal format.

Return type:

str

static statevector_to_angles(phi)

Convert a quantum statevector into spherical coordinates (theta, phi) for Bloch sphere representation.

Parameters:

phi (ndarray) – A 2-element array-like object representing a single-qubit statevector.

Returns:

Polar angle (0 to pi). phi (float): Azimuthal angle (0 to 2*pi).

Return type:

theta (float)

ingenii_quantum.hybrid_networks

• ingenii_quantum.hybrid_networks.edge_detection
  • EdgeDetector2D
    • EdgeDetector2D.size
    • EdgeDetector2D.backend
    • EdgeDetector2D.shots
    • EdgeDetector2D.run()
  • EdgeDetector3D
    • EdgeDetector3D.size
    • EdgeDetector3D.backend
    • EdgeDetector3D.shots
    • EdgeDetector3D.run()
  • EdgeDetectorBase
    • EdgeDetectorBase.n_dimensions
    • EdgeDetectorBase.size
    • EdgeDetectorBase.backend
    • EdgeDetectorBase.shots
    • EdgeDetectorBase.total_qb
    • EdgeDetectorBase.anc_qb
    • EdgeDetectorBase.data_qb
    • EdgeDetectorBase.device
    • EdgeDetectorBase.run_box()
    • EdgeDetectorBase.run_image_qiskit()
    • EdgeDetectorBase.run_image_torch()
• ingenii_quantum.hybrid_networks.filters
  • QuantumFilters2D
    • QuantumFilters2D.shape
    • QuantumFilters2D.stride
    • QuantumFilters2D.encoding
    • QuantumFilters2D.shots
    • QuantumFilters2D.backend
  • QuantumFilters3D
    • QuantumFilters3D.shape
    • QuantumFilters3D.stride
    • QuantumFilters3D.encoding
    • QuantumFilters3D.shots
    • QuantumFilters3D.backend
  • QuantumFiltersBase
    • QuantumFiltersBase.n_dimensions
    • QuantumFiltersBase.shape
    • QuantumFiltersBase.stride
    • QuantumFiltersBase.encoding
    • QuantumFiltersBase.shots
    • QuantumFiltersBase.backend
    • QuantumFiltersBase.nqbits
    • QuantumFiltersBase.device
    • QuantumFiltersBase.unitaries_list
    • QuantumFiltersBase.num_filters
    • QuantumFiltersBase.num_features
    • QuantumFiltersBase.gates_name
    • QuantumFiltersBase.info
    • QuantumFiltersBase.gate_names
    • QuantumFiltersBase.generate_qc()
    • QuantumFiltersBase.generate_reservoirs()
    • QuantumFiltersBase.generate_unitaries()
    • QuantumFiltersBase.get_quantum_filters()
    • QuantumFiltersBase.load_gates()
    • QuantumFiltersBase.load_reservoirs()
    • QuantumFiltersBase.load_unitaries()
• ingenii_quantum.hybrid_networks.layers
  • QuantumFCLayer
    • QuantumFCLayer.input_size
    • QuantumFCLayer.n_layers
    • QuantumFCLayer.encoding
    • QuantumFCLayer.ansatz
    • QuantumFCLayer.observables
    • QuantumFCLayer.backend
    • QuantumFCLayer.nqbits
    • QuantumFCLayer.dev
    • QuantumFCLayer.apply_ansatz()
    • QuantumFCLayer.create_layer()
    • QuantumFCLayer.get_shapes()
    • QuantumFCLayer.qnn_layer()
    • QuantumFCLayer.qnn_layer_QAOA()
• ingenii_quantum.hybrid_networks.qinsp_filter
  • QuantumInspiredImageProcessor
    • QuantumInspiredImageProcessor.check_convergence()
    • QuantumInspiredImageProcessor.process()
    • QuantumInspiredImageProcessor.select_image()
    • QuantumInspiredImageProcessor.sum_neighbours()
    • QuantumInspiredImageProcessor.transformation()
• ingenii_quantum.hybrid_networks.statistics
  • EntanglingCapacity
    • EntanglingCapacity.generate_random_params()
    • EntanglingCapacity.meyer_wallach_entanglement()
  • Expressibility
    • Expressibility.compute_expressibility()
    • Expressibility.generate_random_params()
    • Expressibility.haar_fidelity()
    • Expressibility.pqc_fidelity()
• ingenii_quantum.hybrid_networks.utils
  • roll_numpy()
  • roll_torch()

ingenii_quantum.qubo

• ingenii_quantum.qubo.graph
  • apply_similarity()
  • canberra_distance()
  • chebyshev_distance()
  • create_graph()
  • euclidean_distance()
  • gaussian_similarity()
  • image_to_grid_graph()
  • jensen_shannon_divergence()
  • minkowski_distance()
• ingenii_quantum.qubo.segmentation
  • QUBO_formulation()
  • decode_binary_string()
  • gurobi_qubo_solver()

ingenii_quantum.tensor_networks

• ingenii_quantum.tensor_networks.VBMF
  • EVBMF()
  • EVBsigma2()
  • VBMF()
  • VBsigma2()
  • estimate_ranks()
  • phi0()
  • phi1()
  • tau()
• ingenii_quantum.tensor_networks.tucker_decomposition
  • count_params()
  • tucker_decomposition_conv_layer()