IonQ laid out its five-year roadmap for trapped ion quantum computers and plans to achieve broad quantum advantage by 2025.
The company plans to deploy rack-mounted modular quantum computers small enough to be networked together in a datacenter by 2023. That will result in a quantum advantage in building for machine learning, the company expects.
In October, IonQ announced a new 32-qubit quantum computer with 99.9% fidelity available in private beta and promised two next-gen computers were in the works.
IonQ has a new metric, Algorithmic Qubits, that takes the log base 2 of IBM’s quantum volume. So IonQ defines Algorithmic Qubits as “the largest number of effectively perfect qubits you can deploy for a typical quantum program.” The benchmark takes error correction into account, has a direct relationship to qubit count, and represents the number of “useful” encoded qubits in a particular quantum computer. Algorithmic Qubits is a proxy for the ability to execute real quantum algorithms for a given input size.
IonQ has even introduced an Algorithmic Qubit Calculator to help you compare quantum computing systems. Unsurprisingly, IonQ’s quantum computers come out on top using this metric.
Regardless, IonQ is laying out its roadmap using its new Algorithmic Qubits metric. The company will focus on improving the quality of its quantum logic gate operations to continue to increase Algorithmic Qubits, or usable qubits. It will then work on implementing quantum error correction with low overhead and scaling the number of physical qubits to boost its metric further. (VentureBeat)