Prefix Arithmetic

While syntactically more compact/elegant, infix arithmetic expressions allow barely any customization regarding precision, method etc. which can be detrimental when efficiency is a concern. Because of this we expose the underlying prefix arithmetic functions:

In-place adders

fourier_adder(a, b[, perform_QFT])	In-place adder function based on this paper Performs the addition
cuccaro_adder(qf2, qf1, *args[, ...])	In-place adder function based on this paper Performs the addition
gidney_adder(qf2, qf1, *args[, ...])	In-place adder function based on this paper performs the addition
qcla(a, b[, radix_base, radix_exponent, ...])	Implementation of the higher radix quantum carry lookahead adder (QCLA) as described here.

QuantumFloat processing

sbp_mult(factor_1_qf, factor_2_qf[, output_qf])	Performs multiplication based on the evaluation of semi-boolean polynomials.
sbp_add(summand_1_qf, summand_2_qf[, output_qf])	Performs addition based on the evaluation of semi-boolean polynomials.
sbp_sub(summand_1_qf, summand_2_qf[, output_qf])	Performs subtraction based on the evaluation of semi-boolean polynomials.
hybrid_mult(x, y[, output_qf, init_op, ...])	An advanced algorithm for multiplication which has better depth, gate-count and compile time than sbp_mult.
inpl_add(*args[, permeability, is_qfree, verify])
inpl_mult(qf, mult_int[, treat_overflow])	Performs inplace multiplication of a QuantumFloat with a classical integer.
q_divmod(numerator, divisor[, adder, prec])	Performs division up to arbitrary precision.
q_div(numerator, divisor[, prec])	Performs division up to arbitrary precision and uncomputes the remainder.
qf_inversion(qf[, prec])	Calculates the multiplicative inverse of a QuantumFloat.

QuantumArray processing

q_matmul(q_array_0, q_array_1[, ...])	Matrix multiplication for QuantumArrays.
semi_classic_matmul(q_matrix, cl_matrix[, ...])	Performs matrix multiplication between a classical numpy array and a QuantumArray
inplace_matrix_app(vector, matrix)	Performs inplace matrix application to a vector-valued QuantumArray.
dot(a, b[, out])	Port of the popular numpy function with similar semantics.
tensordot(a, b, axes)	Port of numpy tensordot with similar semantics.