Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms

• URL: http://arxiv.org/abs/2506.13865v2
• Date: Mon, 30 Jun 2025 16:17:09 GMT
• Title: Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms
• Authors: Kasidit Srimahajariyapong, Supanut Thanasilp, Thiparat Chotibut,
• Abstract summary: Variational quantum algorithms (VQAs) promise near-term quantum advantage, yet parametrized quantum states commonly built from the digital gate-based approach often suffer from scalability issues such as barren plateaus.<n>We study an analog VQA ans"atze composed of $M$ quenches of a disordered Ising chain, whose dynamics is native to several quantum simulation platforms.
• Score: 1.7136832159667206
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Variational quantum algorithms (VQAs) promise near-term quantum advantage, yet parametrized quantum states commonly built from the digital gate-based approach often suffer from scalability issues such as barren plateaus, where the loss landscape becomes flat. We study an analog VQA ans\"atze composed of $M$ quenches of a disordered Ising chain, whose dynamics is native to several quantum simulation platforms. By tuning the disorder strength we place each quench in either a thermalized phase or a many-body-localized (MBL) phase and analyse (i) the ans\"atze's expressivity and (ii) the scaling of loss variance. Numerics shows that both phases reach maximal expressivity at large $M$, but barren plateaus emerge at far smaller $M$ in the thermalized phase than in the MBL phase. Exploiting this gap, we propose an MBL initialisation strategy: initialise the ans\"atze in the MBL regime at intermediate quench $M$, enabling an initial trainability while retaining sufficient expressivity for subsequent optimization. The results link quantum phases of matter and VQA trainability, and provide practical guidelines for scaling analog-hardware VQAs.

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