Modular exponentiation Created 2026-10-06 Updated 2026-10-20
Modular exponentiation computes the remainder for an integer base , a nonnegative integer exponent , and, here, an integer modulus . It applies exponentiation by squaring while reducing after each multiplication, including each squaring. The result is the unique representative in . There is no requirement that the base be coprime to the modulus when the exponent is nonnegative.[ref]
Take , , and . Initialize ; the remaining digits give
Hence . The final operation multiplies by , since the preceding square has already been reduced. The computation never needs to construct .
In general reduce the base first, . For , initialize and process the remaining binary digits with , followed, for a digit one, by . The loop invariant is
where is the processed prefix value. The congruence is preserved because modular arithmetic respects multiplication: if , then and . Thus changing representatives never changes the final congruence class.
Both factors in every product are less than , so the unreduced product is less than , and the stored result is again less than . The same bounds hold for a gigantic exponent, such as : there are squarings, each on bounded-size residues. For base two, the corresponding ordinary power would have binary digits. The benefit is avoiding the huge ordinary power altogether, rather than constructing it and taking one final remainder. Initial reduction is essential when the supplied base is much larger than the modulus.
For , return under the same empty-product convention as exponentiation by squaring. For , require , find the modular multiplicative inverse , and compute ; the extended Euclidean algorithm can find that inverse. Its cost is separate from the positive-exponent binary powering multiplication count. For example, , while is undefined because and are not coprime.
Apply the same positive-exponent quantum Fourier transform to each of the two quantum registers. The amplitude at of the coset state is
The finite geometric series is when and zero otherwise. Therefore
There are allowed pairs, with following the uniform distribution on a finite set. The factor changes the probability amplitudes by phases depending on the output label , but has no effect on their probabilities. Using an inverse rather than forward quantum Fourier transform on both quantum registers gives the same support relation.
A modular inverse of exists precisely when . In that case the discrete logarithm is
It cannot generally be determined from every allowed pair. Put . The supported linear congruence has solutions modulo , and determines only modulo ; gives no information when . For instance and are compatible with both and . One may verify a candidate by modular exponentiation, checking . Repeated discrete-logarithm Fourier sampling finds an invertible with per-trial probability , which has the same totient lower bound from the Mertens product as before. When , the group is trivial and are determined without Fourier samples.
First require . A discrete logarithm to a generator of a group of exists only for nonzero ; the printed membership inadvertently also permits zero, for which is undefined. Zero can be rejected before any quantum circuit.
Put and write . Since is a generator of a group of order , the map is a bijection from to the multiplicative group of a finite field. Hence every nonzero has a unique with . Equality of powers of is equality of their exponents modulo , giving
The fiber over is an affine coset of the subgroup , and contains exactly pairs. This identifies the hidden subgroup problem underlying discrete-logarithm Fourier sampling; knowing numerically is not needed to construct the coset state.