Science

Researchers are exploring the potential of quantum computing to enhance image recognition using recurrent neural networks and a novel image encoding technique.

A new software library simplifies the development of distributed quantum applications by bringing familiar parallel programming concepts to the quantum realm.

New research refines the limits of quantum statistical zero-knowledge, bringing us closer to understanding the fundamental capabilities of secure quantum computation.

New research challenges established assumptions about how much information can be gleaned from simple quantum measurements.

Researchers have shown that high-quality random numbers, typically generated by quantum processes, can be faithfully reproduced using the inherent timing variations within standard computer systems.

A new approach to quantum error correction leverages the power of Transformer networks to significantly improve decoding performance for Golay codes.

New research reveals a fundamental trade-off in quantum state verification, demonstrating that cut-and-choose protocols cannot simultaneously guarantee both strong security and practical efficiency.

A new method, MorphZ, dramatically improves the accuracy and efficiency of evidence estimation in complex Bayesian analyses.

New research reveals a fundamental architectural limitation in decoder-only models when it comes to complex causal reasoning and adapting to changing data.

A novel hashing-based approach dramatically accelerates the creation of sequence embeddings for COVID-19 spike proteins, offering a powerful tool for variant analysis.