Large-scale quantum computing with trapped ions is a promising field. However, many trapped-ion systems rely on arrays of multiple ions of multiple difference species, and this complicates any possible setup.
Allcock et al. seek to simplify this arrangement by developing a system using ions of only one species. The researchers provide multiple possible arrangements of these single-species ions, assigning different functions to each ion based on its energy level.
In an analysis of existing trapped-ion systems, the researchers identified several characteristics that such a system would need to have to become useful, including high fidelity, low noise, and easy read and write ability. This is only doable in existing trapped-ion systems by employing multiple species of ion, which creates additional challenges.
The method solves this problem by making use of multiple independent states. The researchers propose assigning each feature to a different state to create effective trapped-ion systems without the complexity of multiple species of ion. In addition, the researchers propose several possible arrangements of these states to accomplish a variety of tasks, including writing, storing, and reading information.
“It just doesn’t make any sense to limit the contribution of each atom to two states,” said author Wes Campbell. “They have huge internal state spaces…. It actually takes very few resources to start tapping into those in helpful ways.”
The researchers are planning to survey ion candidates to understand their state space more fully in preparation for future applications.
Source: “omg Blueprint for trapped ion quantum computing with metastable states,” by David T. C. Allcock, Wesley C. Campbell, John Chiaverini, Isaac L. Chuang, Eric Hudson, Isam Daniel Moore, Anthony Ransford, Conrad Roman, Jeremy M. Sage, and David Wineland, Applied Physics Letters (2021). This article can be accessed at https://doi.org/10.1063/5.0069544.
This paper is part of the Emerging Qubit Systems - Novel Materials, Encodings and Architectures Collection. Learn more here.