aiqbench analysis
This research demonstrates that in quantum circuit Born machines, the entangling layer can be restricted to Clifford circuits without sacrificing model performance, as nonstabilizerness is effectively generated by trainable single-qubit rotations. The study further reveals that loss functions remain invariant across a wide range of entangler nonstabilizerness levels and provides an analytical method to identify states with minimal stabilizer Rényi entropy. These findings offer significant insights into optimizing variational quantum algorithms by decoupling entanglement generation from the resource cost of non-stabilizer operations.
Nonstabilizerness of the entangling layer in quantum circuit Born machines
arXiv:2609.32025v1 Announce Type: new Abstract: The entangling layer of a quantum circuit Born machine can supply both entanglement and nonstabilizerness. In this work we show that the entangling layer can be a Clifford circuit, which supplies no nonstabilizerness. We use an architecture in which a fixed, non-trainable entangler is reused in every layer and only single-qubit rotations are optimized. There, a Clifford entangler reaches the same Kullback--Leibler divergence as a near-Haar one at sufficient circuit depth, and entanglers spanning zero to Haar-typical nonstabilizerness reach the same loss, up to a small offset for a free-fermion matchgate entangler. A doping control that raises the entangler's nonstabilizerness while leaving the entangling power of every gate unchanged leaves the loss flat. With a Clifford entangler the nonstabilizerness of the trained state comes entirely from the rotations, which take the trained circuit outside the stabilizer formalism. We also show that, among all pure states whose Born distribution is a given target, the one whose amplitudes are the positive square roots of the probabilities has the smallest stabilizer R\'enyi entropy, so this minimum can be computed without training.
Abstract:The entangling layer of a quantum circuit Born machine can supply both entanglement and nonstabilizerness. In this work we show that the entangling layer can be a Clifford circuit, which supplies no nonstabilizerness. We use an architecture in which a fixed, non-trainable entangler is reused in every layer and only single-qubit rotations are optimized. There, a Clifford entangler reaches the same Kullback--Leibler divergence as a near-Haar one at sufficient circuit depth, and entanglers spanning zero to Haar-typical nonstabilizerness reach the same loss, up to a small offset for a free-fermion matchgate entangler. A doping control that raises the entangler's nonstabilizerness while leaving the entangling power of every gate unchanged leaves the loss flat. With a Clifford entangler the nonstabilizerness of the trained state comes entirely from the rotations, which take the trained circuit outside the stabilizer formalism. We also show that, among all pure states whose Born distribution is a given target, the one whose amplitudes are the positive square roots of the probabilities has the smallest stabilizer Rényi entropy, so this minimum can be computed without training.
arXiv:2609.32025 [quant-ph]
(or arXiv:2609.32025v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2609.32025 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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