Quantum-Enhanced State Spaces for Smarter Sequences

A novel architecture blends the power of quantum circuits with state space models to tackle long-range dependencies in sequential data.

A novel architecture blends the power of quantum circuits with state space models to tackle long-range dependencies in sequential data.

A new reinforcement learning framework autonomously stabilizes quantum error correction by adapting to system drift and maximizing performance.
A new cost model, FLASQ, offers a more realistic assessment of resource requirements for early fault-tolerant quantum algorithms.

A novel technique leverages network capacity regions to pinpoint loss probabilities, even amidst noisy channel conditions.

A new protocol efficiently certifies complex quantum states using only a small number of single-qubit Pauli measurements.

Researchers quantify coherence in quantum algorithms, revealing its impact on performance with the Bernstein-Vazirani algorithm.
A new approach to protecting quantum information leverages the unique properties of squeezed vacuum states.

New techniques dramatically reduce the physical qubit overhead for fault-tolerant quantum computing with surface codes.

A new approach utilizes high-rate quantum LDPC codes to enable efficient, addressable gate-based computation.

A new full-stack framework promises to optimize quantum computations by tightly integrating hardware and software design.