Quantum Period Finding is Compression Robust

We study quantum period finding algorithms such as Simon and Shor (and its variants Eker\aa-H\aa stad and Mosca-Ekert). For a periodic function $f$ these algorithms produce -- via some quantum embedding of $f$ -- a quantum superposition $\sum_x |x\rangle|f(x)\rangle$, which requires a certain amount of output qubits that represent $|f(x)\rangle$. We show that one can lower this amount to a single output qubit by hashing $f$ down to a single bit in an oracle setting. Namely, we replace the embedding of $f$ in quantum period finding circuits by oracle access to several embeddings of hashed versions of $f$. We show that on expectation this modification only doubles the required amount of quantum measurements, while significantly reducing the total number of qubits. For example, for Simon's period finding algorithm in some $n$-bit function $f: \mathbb{F}_2^n \rightarrow \mathbb{F}_2^n$ our hashing technique reduces the required output qubits from $n$ down to $1$, and therefore the total amount of qubits from $2n$ to $n+1$. We also show that Simon's algorithm admits real world applications with only $n+1$ qubits by giving a concrete realization of a hashed version of the cryptographic Even-Mansour construction. Our oracle-based hashed version of the Eker\aa-H\aa stad algorithm for factoring $n$-bit RSA reduces the required qubits from $(\frac 3 2 + o(1))n$ down to $(\frac 1 2 + o(1))n$. In principle our hashing approach also works for the Mosca-Ekert algorithm, but requires strong properties of the hash function family. A hashed version of Mosca-Ekert with as few as $\mathcal{O}(\log n)$ qubits would imply classical polynomial time factoring. Therefore, the search for suitable hash functions might open a new path to factoring in ${\cal P}$.