Simon's problem asks for the hidden string promised by exactly when . It is the hidden subgroup problem on with hidden subgroup .
For an unknown nonzero period, a collision reveals the period . Birthday problem sampling finds one using queries with bounded error. A matching lower bound follows by choosing the period and output labels randomly: without a collision, queries rule out at most candidate periods. For , almost all periods remain consistent with the transcript. The exponential separation is in query complexity, compared with Simon's algorithm's linear quantum query count.
Simon's algorithm prepares hidden-subgroup coset states, applies the quantum Fourier transform over , and samples vectors satisfying over . Repeated samples and Gaussian elimination recover with oracle queries and polynomial computation.
With a nonzero hidden period, Simon's algorithm samples uniformly from its -dimensional orthogonal complement over the binary field. At rank , a new sample raises the rank with probability . Summing the geometric waiting times gives an expected queries. After samples, the probability of insufficient rank is less than , by a union bound over the nonzero linear functionals that could annihilate all samples.
If the hidden string is zero, one oracle-Hadamard run samples every with probability . If the hidden string is nonzero, it samples every satisfying with probability and every other string with probability zero. Pairing with makes the forbidden amplitudes cancel.
For a subspace , its orthogonal complement is , where the dot product is evaluated modulo two.

Articles by others on the same topic (1)

Simon's problem, often referred to in the context of computer science and quantum computing, specifically relates to a problem introduced by computer scientist Daniel Simon in 1994. The problem is a demonstration of the power of quantum computation over classical computation and serves as a foundational example illustrating how quantum algorithms can solve certain problems more efficiently than any classical algorithm.