Special-Unitary Parameterization for Trainable Variational Quantum Circuits
- URL: http://arxiv.org/abs/2507.05535v1
- Date: Mon, 07 Jul 2025 23:21:02 GMT
- Title: Special-Unitary Parameterization for Trainable Variational Quantum Circuits
- Authors: Kuan-Cheng Chen, Huan-Hsin Tseng, Samuel Yen-Chi Chen, Chen-Yu Liu, Kin K. Leung,
- Abstract summary: SUN-VQC is a variational-circuit architecture whose elementary layers are single exponentials of a symmetry-restricted Lie subgroup.<n>We show that SUN-VQCs sustain order-of-rotation larger gradient signals, converge 2--3$times$ faster, and reach higher final fidelities than depth-matched Pauli circuits.
- Score: 7.2687813325879045
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We propose SUN-VQC, a variational-circuit architecture whose elementary layers are single exponentials of a symmetry-restricted Lie subgroup, $\mathrm{SU}(2^{k}) \subset \mathrm{SU}(2^{n})$ with $k \ll n$. Confining the evolution to this compact subspace reduces the dynamical Lie-algebra dimension from $\mathcal{O}(4^{n})$ to $\mathcal{O}(4^{k})$, ensuring only polynomial suppression of gradient variance and circumventing barren plateaus that plague hardware-efficient ans\"atze. Exact, hardware-compatible gradients are obtained using a generalized parameter-shift rule, avoiding ancillary qubits and finite-difference bias. Numerical experiments on quantum auto-encoding and classification show that SUN-VQCs sustain order-of-magnitude larger gradient signals, converge 2--3$\times$ faster, and reach higher final fidelities than depth-matched Pauli-rotation or hardware-efficient circuits. These results demonstrate that Lie-subalgebra engineering provides a principled, scalable route to barren-plateau-resilient VQAs compatible with near-term quantum processors.
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