Engineered dissipation for quantum information science
Abstract
Quantum information processing relies on the precise control of non-classical states in the presence of many uncontrolled environmental degrees of freedom. The interactions between the relevant degrees of freedom and the environment are often viewed as detrimental, as they dissipate energy and decohere quantum states. Nonetheless, when controlled, dissipation is an essential tool for manipulating quantum information: dissipation engineering enables quantum measurement, quantum-state preparation and quantum-state stabilization. The advances in quantum technologies, marked by improvements of characteristic coherence times and extensible architectures for quantum control, have coincided with the development of such dissipation engineering tools that interface quantum and classical degrees of freedom. This Review presents dissipation as a fundamental aspect of the measurement and control of quantum devices, and highlights the role of dissipation engineering in quantum error correction and quantum simulation. Controlled dissipation can be used to protect quantum information, control dynamics and enforce constraints. This Review explains the basic principles and overviews the applications of dissipation engineering to quantum error correction, quantum sensing and quantum simulation. Dissipation is essential for quantum information processing: resetting to the ground state, measurement and cooling all require dissipation. Carefully engineered dissipation can protect quantum…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.