January 19, 2025
Schematic of error mitigation in qutrit circuits.

Extending the computational reach of a superconducting qutrit processor

npj Quantum Information, Published online: 14 October 2024; doi:10.1038/s41534-024-00892-z Extending the computational reach of a superconducting qutrit processor Quantum computing with qudits is an emerging approach that exploits a larger, more connected computational space, providing […]

Scaled gate Vs. multiple (multi-qubit) Clifford implementation of quantum gates.

Pseudo twirling mitigation of coherent errors in non-Clifford gates

npj Quantum Information, Published online: 11 October 2024; doi:10.1038/s41534-024-00889-8 Pseudo twirling mitigation of coherent errors in non-Clifford gates The conventional circuit paradigm, utilizing a small set of gates to construct arbitrary quantum circuits, is hindered […]

Visualization diagram of magnetic domains in a quantum antiferromagnet using nonreciprocal directional dichroism

Illuminating quantum magnets: Light unveils magnetic domains

Scientists have used light to visualize magnetic domains, and manipulated these regions using an electric field, in a quantum antiferromagnet. This method allows real-time observation of magnetic behaviors, paving the way for advancements in next-generation […]

Trinity College Dublin

Team uncovers a quantum Mpemba effect, with a host of ‘cool’ implications

Researchers have just described the existence of the paradoxical Mpemba effect within quantum systems. Initially investigating out of pure curiosity, the discovery has bridged the gap between Aristotle’s observations two millennia ago and modern-day understanding, and opened the door to a whole host of ‘cool’ — and ‘cooling’ — implications.

An AI tool called GNNOpt can accurately predict optical spectra based solely on crystal structures and speed up the development of photovoltaic and quantum materials. ©Nguyen Tuan Hung et al.

AI speeds up the discovery of energy and quantum materials

Unearthing new LEDs, solar cells, and photodetectors requires extensive knowledge surrounding the optical properties of materials. Calculating these takes time and resources. Yet researchers unveiled a new AI tool that can accurately, and crucially much faster than quantum simulations, for predicting optical properties.