frontend module

Module contents (__init___.py)

class frontend.AdiabaticProgram(H_init: ExpressionBase, H_final: ExpressionBase, total_time: float, time_steps: int, num_all: int)

Bases: object

The adiabatic program stores the required data for AQC. It should be returned from Frontend after converted, and then passed to the Backend to run as adiabatic.

Parameters:

• H_init (ExpressionBase) – The language expression of the initial Hamiltonian.

• H_final (ExpressionBase) – The language expression of the final Hamiltonian.

• total_time (float) – The running time for the AQC.

• time_steps (int) – The number of time steps.

• num_all (int) – The number of all qubits, including both state and clock qubits.

compile() → tuple[spmatrix, spmatrix]

Compile the language expression of the Hamiltonians.

Returns:

The compiled Hamiltonians.

Return type:

tuple[sp.spmatrix, sp.spmatrix]

class frontend.Frontend

Bases: object

Frontend is where the real translation happens. It is the implementation of the proposed translation of the papers we found.

unitaries_to_program(Us: list[spmatrix]) → AdiabaticProgram

Translate a list of unitaries into an adiabatic program.

Parameters:

Us (list[sp.spmatrix]) – list of unitaries.

Returns:

The adiabatic program.

Return type:

AdiabaticProgram

Submodules

• frontend.compress module

Implemented frontends

• frontend.clock package
  • ClockAdiabaticProgram
    • ClockAdiabaticProgram.compile()
  • ClockFrontend
    • ClockFrontend.gen_H_clock()
    • ClockFrontend.gen_H_clockinit()
    • ClockFrontend.gen_H_input()
    • ClockFrontend.gen_H_l_sum()
    • ClockFrontend.gen_H_l_sum_part_check_clock()
    • ClockFrontend.gen_H_l_sum_part_unitary()
    • ClockFrontend.unitaries_to_program()
• frontend.planar_clock package
  • PlanarClockAdiabaticProgram
    • PlanarClockAdiabaticProgram.compile()
  • PlanarClockFrontend
    • PlanarClockFrontend.unitaries_to_program()
• frontend.tensor package
  • TensorAdiabaticProgram
    • TensorAdiabaticProgram.compile()
  • TensorFrontend
    • TensorFrontend.encode_U()
    • TensorFrontend.gen_H_in()
    • TensorFrontend.gen_H_out()
    • TensorFrontend.gen_H_prop()
    • TensorFrontend.lamb_n()
    • TensorFrontend.project()
    • TensorFrontend.unitaries_to_program()