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])
`sbp_sub`(summand_1_qf, summand_2_qf[, output_qf])
`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.