Publications

Quantum circuit compilation for fermionic excitations using the Jordan-Wigner mapping

Published in arXiv, 2026

This note bridges the gap between theoretical second quantization and practical quantum hardware by detailing the Jordan-Wigner mapping for the Unitary Coupled Cluster Singles and Doubles (UCCSD) ansatz. Using the hydrogen molecule in a minimal basis as a case study, we explicitly derive the Pauli strings required for single and double excitations. Additionally, we discuss the translation of these operators into quantum circuits, with a focus on implementation nuances such as the difference between mathematical rotations and physical gates like the SX gate.

Recommended citation: Renata Wong (2026). "Quantum circuit compilation for fermionic excitations using the Jordan-Wigner mapping" arXiv. 2601.07890. https://arxiv.org/abs/2601.07890

A quantum Bluestein algorithm for arbitrary size quantum Fourier transform

Published in arXiv, 2025

We propose a quantum analogue of Bluestein’s algorithm (QBA) that implements an exact N-point Quantum Fourier Transform (QFT) for arbitrary N. Our construction factors the N-dimensional QFT unitary into three diagonal quadratic-phase gates and two standard radix-2 QFT subcircuits of size M=2^m (with M≥2N−1). This achieves asymptotic gate complexity O((logN)^2) and uses O(logN) qubits, matching the performance of a power-of-two QFT on m qubits while avoiding the need to embed into a larger Hilbert space. We validate the correctness of the algorithm through a concrete implementation in Qiskit and classical simulation, confirming that QBA produces the exact N-point discrete Fourier transform on arbitrary-length inputs.

Recommended citation: Nan-Hong Kuo and Renata Wong (2025). "A quantum Bluestein algorithm for arbitrary size quantum Fourier transform" arXiv. 2512.15349. https://arxiv.org/abs/2512.15349

Support vector machine kernels as quantum propagators

Published in arXiv, 2025

In this work, we establish the equivalence between Support Vector Machine (SVM) kernels and quantum Greens functions.

Recommended citation: Nan-Hong Kuo and Renata Wong (2025). "Support vector machine kernels as quantum propagators" arXiv. 2502.11153. https://arxiv.org/abs/2502.11153

Bioinspired Quantum Oracle Circuits for Biomolecular Solutions of the Maximum Cut Problem

Published in IEEE Transactions on NanoBioscience, 2024

Given an undirected, unweighted graph with n vertices and m edges, the maximum cut problem is to find a partition of the n vertices into disjoint subsets and such that the number of edges between them is as large as possible. Classically, it is an NP-complete problem, which has potential applications ranging from circuit layout design, statistical physics, computer vision, machine learning and network science to clustering. In this paper, we propose a biomolecular and a quantum algorithm to solve the maximum cut problem for any graph G.

Recommended citation: Weng-Long Chang, Renata Wong, Yu-Hao Chen, Wen-Yu Chung, Ju-Chin Chen, Athanasios V. Vasilakos (2024). "Bioinspired Quantum Oracle Circuits for Biomolecular Solutions of the Maximum Cut Problem" IEEE Transactions on NanoBioscience 23(3): 499-506, DOI: 10.1109/TNB.2024.3395420. https://ieeexplore.ieee.org/abstract/document/10510482

Making the zeroth-order process fidelity independent of state preparation and measurement errors

Published in arXiv, 2023

In this work, we demonstrate that the zero-fidelity, an approximation to the process fidelity, when combined with randomized benchmarking, becomes robust to state preparation and measurement (SPAM) errors.

Recommended citation: Yu-Hao Chen and Renata Wong and Hsi-Sheng Goan (2023). "Making the zeroth-order process fidelity independent of state preparation and measurement errors" arXiv. 2312.08590. https://arxiv.org/abs/2312.08590