Let be a unitary operator and suppose initially that the target is an eigenstate with , . Use control qubits, so . Hadamard gates prepare the uniform superposition . For each binary control position , apply the controlled unitary gate . The resulting state isApply the inverse quantum Fourier transform, with convention , and measure the control. The exact amplitude and probability areFor an exactly representable phase , orthogonality of roots of unity makes the outcome certain. Otherwise the finite geometric series givesThe estimate is , with phases interpreted modulo one.
To prove an error bound, choose a nearest label to on the circular grid and put in the interval . For , concavity of sine on gives , while . Therefore the nearest-integer success bound for quantum phase estimation isHere . At an exact grid point the probability is one. If two nearest labels tie, either one separately has the displayed lower bound.
For high confidence one can prove a stronger quantum phase estimation tail bound. Let be the centered distance between and , chosen with . The denominator estimate implies away from the exact-phase case. A label at circular integer distance from has , and there are at most two labels at each such distance. For , summing the tails givesOn the complementary event the circular phase error is at most . Thus, for desired bits of accuracy, take with and to obtainTaking makes the right side at most . This adds only control qubits. Efficient QFT is not by itself a guarantee of efficient controlled powers of an arbitrary : implementing them by repeated oracle calls uses calls. The modular-arithmetic application has efficient powers, as follows.
Assume and , and let be the multiplicative order of modulo . Define the unitary operator on , and extend it as the identity on unused computational-basis labels of the binary register. Coprimality makes multiplication a permutation, so this extension really is unitary. The orbit of consists of the distinct states . Its modular multiplication eigenstates areThe last relation follows by shifting the index cyclically; orthogonality follows from the finite Fourier sum. We do not need to know to prepare one of these eigenstates: the readily prepared target obeysRunning quantum phase estimation on this state produces the mixture of the eigenphase distributions, each with weight , because the target eigenstates are orthogonal. Thus it samples a uniformly random phase label and estimates with the bounds just proved. Equivalently the state before the inverse QFT is , which is obtained by quantum modular exponentiation directly.
The controlled power multiplies by , whose constant is computed by repeated squaring. Under the assumed efficient modular exponentiation, these controlled multiplications and the QFT use a number of gates polynomial in the register lengths. Taking requires only phase qubits. The nearest-label event has probability at least and yields an estimate within of . Since , continued-fraction recovery in quantum order finding then identifies the reduced fraction . The denominator is , not necessarily : when and are coprime it is the desired order, and when they are not it is only a divisor. One may test candidate denominators using modular exponentiation and repeat with fresh samples; denominators from successful samples can also be combined by a least common multiple. The probability of a nearest-label sample with coprime to is at least . These qualifications explain exactly what the phase estimate yields without falsely assuming that the unknown order or an eigenstate was available at the start.
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