Quantum Spin Control: Balancing Speed and Reliability

A new variational algorithm optimizes state transfer in complex spin chains, revealing fundamental limits between performance and noise resilience.

A new variational algorithm optimizes state transfer in complex spin chains, revealing fundamental limits between performance and noise resilience.

New research reveals that decoding latency and communication bottlenecks pose significant challenges to building larger, more practical quantum computers.
Researchers are exploring how parameterized quantum circuits can create word embeddings that capture semantic relationships, potentially offering advantages over classical methods.

New research reveals that quantum noise isn’t always random, and leveraging its predictable, metastable patterns could significantly improve algorithm stability.

Researchers detail a practical approach to constructing universal quantum gates within lift-connected surface codes, bringing scalable error correction closer to reality.

New research reveals that the scalability of fault-tolerant quantum computing presents a significant hurdle for complex simulations, especially in the demanding field of homogeneous catalysis.
As quantum computing moves from theory to practice, a new field—Quantum Design Automation—is emerging to tackle the complex engineering hurdles of building scalable and reliable systems.

A novel approach combines the strengths of variational quantum circuits and classical neural networks to accurately classify complex entangled quantum states.

A new analysis reveals how attackers can exploit signature replay vulnerabilities in smart contracts, and introduces a system for automatically detecting these critical flaws.
Researchers have developed an optimized quantum encoding technique that significantly improves the efficiency and resilience of molecular simulations.