About track

Quantum Reservoir Computing (QRC) is a near-term quantum machine learning paradigm for temporal data processing that requires no gradient-based optimization of the quantum system and is suited to noisy intermediate-scale quantum hardware. Participants will design and benchmark simulation-friendly QRC systems and apply them to real-world industry problems where chaotic dynamics and nonlinear temporal dependencies are central, including financial volatility prediction and climate and weather time-series forecasting. Teams will demonstrate performance across different qubit counts and realistic noise models, benchmark against classical baselines, and implement a common benchmark to validate that the quantum reservoir exhibits sufficient expressivity for forecasting complex, regime-shifting systems.

Timeline

Start

Mar 2026 Wed, ET

End

Sep 2026 Sat, ET

Why this track exists?

This challenge asks participants to design, build, and benchmark simulation-friendly QRC systems (5–20 qubits) and apply them to real-world industry problems where chaotic dynamics, nonlinear temporal dependencies, and regime shifts make QRC’s unique strengths directly relevant.

Who is this track for?

No audience yet.

Prizes & Outcomes

No prizes yet.

How to get started

Submit your Phase 3 submissions via the Aqora Competition page for each of your chosen Challenge(s) due 11:59 PM (EST) on Sunday, July 26. Important: One submission is required per team and must match submission criteria or risk disqualification.