Quantum supremacy in driven quantum many-body systems
Jirawat Tangpanitanon, Supanut Thanasilp, Marc-Antoine Lemonde, Ninnat, Dangiam, Dimitris G. Angelakis

TL;DR
This paper proposes that quantum supremacy can be achieved in generic driven quantum many-body systems, expanding the potential platforms for demonstrating quantum advantage beyond traditional methods.
Contribution
It introduces a new approach to attain quantum supremacy using periodically-driven quantum many-body systems, supported by eigenstate thermalization hypothesis and complexity theory.
Findings
Quantum supremacy feasible in driven many-body systems
Examples include disordered Ising and Bose-Hubbard chains
Framework broadens experimental platforms for quantum advantage
Abstract
A crucial milestone in the field of quantum simulation and computation is to demonstrate that a quantum device can compute certain tasks that are impossible to reproduce by a classical computer with any reasonable resources. Such a demonstration is referred to as quantum supremacy. One of the most important questions is to identify setups that exhibit quantum supremacy and can be implemented with current quantum technology. The two standard candidates are boson sampling and random quantum circuits. Here, we show that quantum supremacy can be obtained in generic periodically-driven quantum many-body systems. Our analysis is based on the eigenstate thermalization hypothesis and strongly-held conjectures in complexity theory. To illustrate our work, We give examples of simple disordered Ising chains driven by global magnetic fields and Bose-Hubbard chains with modulated hoppings. Our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum many-body systems · Quantum Computing Algorithms and Architecture · Complex Network Analysis Techniques
