
Algorithms 5
contributed
Wed, 28 Jan 2026, 13:00 - 13:00
- Inverse Nonlinear Fast Fourier Transform: Closing A Chapter in Quantum Signal ProcessingHongkang Ni (Stanford University); Rahul Sarkar (University of California, Berkeley); Lexing Ying (Stanford University); Lin Lin (University of California, Berkeley)[abstract]Abstract: The nonlinear Fourier transform (NLFT) extends the classical Fourier transform by replacing addition with matrix multiplication. While the NLFT on $\mathrm{SU}(1,1)$ has been widely studied, its $\mathrm{SU}(2)$ variant has only recently attracted attention due to emerging applications in quantum signal processing (QSP) and quantum singular value transformation (QSVT). In this paper, we investigate the inverse NLFT on $\mathrm{SU}(2)$ and establish the numerical stability of the layer stripping algorithm for the first time under suitable conditions. Furthermore, we develop a fast and numerically stable algorithm, called inverse nonlinear fast Fourier transform, for performing inverse NLFT with near-linear complexity. This algorithm is applicable to computing phase factors for both QSP and the generalized QSP (GQSP).
- A log-depth in-place quantum Fourier transform that rarely needs ancillasGregory D. Kahanamoku-Meyer (MIT); John Blue (MIT); Thiago Bergamaschi (UC Berkeley); Craig Gidney (Google); Isaac Chuang (MIT)[abstract]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/ϵ)) for tunable error parameter ϵ, 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 ϵ on all input states except an ϵ-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, 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/ϵ)) with a sublinear number of ancilla qubits. The reduction uses long-range gates but no measurements.
- Catalytic z-rotations in constant T-depthIsaac Kim (UC Davis)[abstract]Abstract: We show that the $T$-depth of any single-qubit $z$-rotation can be reduced to $3$ if a certain catalyst state is available. To achieve an $\epsilon$-approximation, it suffices to have a catalyst state of size polynomial in $\log(1/\epsilon)$. This implies that $\mathsf{QNC}^0_f/\mathsf{qpoly}$ admits a finite universal gate set consisting of Clifford+$T$. In particular, there are catalytic constant $T$-depth circuits that approximate multi-qubit Toffoli, adder, and quantum Fourier transform arbitrarily well. We also show that the catalyst state can be prepared in time polynomial in $\log (1/\epsilon)$.