aiqbench analysis
This paper introduces "optimistic quantum circuits" for the in-place Quantum Fourier Transform (QFT), achieving logarithmic depth with zero ancilla qubits while tolerating errors on a negligible fraction of input states. By formalizing this approximation strategy, the authors demonstrate how to construct near-linear depth factoring circuits and provide a reduction method to handle cases requiring strict accuracy across all inputs. The work advances practical quantum algorithm design by optimizing resource usage without sacrificing asymptotic performance for most applications.
A log-depth in-place quantum Fourier transform that rarely needs ancillas
arXiv:2505.00701v3 Announce Type: replace Abstract: When designing quantum circuits for a given unitary, it can be much cheaper to achieve a good approximation on most inputs than on all inputs. In this work we formalize this idea, and propose that such "optimistic quantum circuits" are often sufficient in the context of larger quantum algorithms. For the rare algorithm in which a subroutine needs to be a good approximation on all inputs, we provide a reduction which transforms optimistic circuits into general ones. Applying these ideas, we build an optimistic circuit for the in-place quantum Fourier transform (QFT). Our circuit has depth $O(\log (n / \epsilon))$ for tunable error parameter $\epsilon$, uses $n$ total qubits, i.e. no ancillas, is local for input qubits arranged in 1D, and is measurement-free. The circuit's error is bounded by $\epsilon$ on all input states except an $O(\epsilon)$-sized fraction of the Hilbert space. The circuit is also rather simple and thus may be practically useful. Combined with recent QFT-based fast arithmetic constructions [arXiv:2403.18006], the optimistic QFT yields factoring circuits of nearly linear depth using only $2n + O(n/\log n)$ total qubits. Additionally, we apply our reduction technique to yield an approximate QFT with well-controlled error on all inputs; it is the first to achieve the asymptotically optimal depth of $O(\log (n/\epsilon))$ with a sublinear number of ancilla qubits. The reduction uses long-range gates but no measurements.
Abstract:When designing quantum circuits for a given unitary, it can be much cheaper to achieve a good approximation on most inputs than on all inputs. In this work we formalize this idea, and propose that such "optimistic quantum circuits" are often sufficient in the context of larger quantum algorithms. For the rare algorithm in which a subroutine needs to be a good approximation on all inputs, we provide a reduction which transforms optimistic circuits into general ones. Applying these ideas, we build an optimistic circuit for the in-place quantum Fourier transform (QFT). Our circuit has depth $O(\log (n / \epsilon))$ for tunable error parameter $\epsilon$, uses $n$ total qubits, i.e. no ancillas, is local for input qubits arranged in 1D, and is measurement-free. The circuit's error is bounded by $\epsilon$ on all input states except an $O(\epsilon)$-sized fraction of the Hilbert space. The circuit is also rather simple and thus may be practically useful. Combined with recent QFT-based fast arithmetic constructions [arXiv:2403.18006], the optimistic QFT yields factoring circuits of nearly linear depth using only $2n + O(n/\log n)$ total qubits. Additionally, we apply our reduction technique to yield an approximate QFT with well-controlled error on all inputs; it is the first to achieve the asymptotically optimal depth of $O(\log (n/\epsilon))$ with a sublinear number of ancilla qubits. The reduction uses long-range gates but no measurements.
14 pages; Appendix: 8 pages. v2,v3: small fixes and improvements
arXiv:2505.00701 [quant-ph]
(or arXiv:2505.00701v3 [quant-ph] for this version)
From: Gregory D. Kahanamoku-Meyer [view email] [v1] Thu, 1 May 2025 17:58:36 UTC (128 KB) [v2] Sun, 25 May 2025 20:30:24 UTC (190 KB) [v3] Mon, 14 Sep 2026 18:39:30 UTC (189 KB)
Full text under the publisher's open licence · 276 words
Related coverage

Lattice-Based Cryptography Explained
Quantum Zeitgeist · Aug 15, 2026

Graduate Student Proves a Quantum Uncertainty Principle for Fractals
Quanta Magazine · Aug 12, 2026

Game Design Creativity evals
LessWrong · Oct 12, 2026

NISQ, What Noisy Intermediate-Scale Quantum Means
Quantum Zeitgeist · Aug 30, 2026