Trapped Ion Paves the Way for Industrial-Grade Quantum Computing
December 1, 2021 Maurizio Di Paolo Emilio
Trapped ion provides low error rate and a high connectivity between qubits. Quantum computing company IonQ is using this technology.
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Like the bit is the basis of any conventional digital computer, quantum bit (shortly, qubit) is the basis of any quantum processor. Among the different technologies available for building a qubit, trapped ion is the one that provides low error rate (which means the high gate fidelity) and a high connectivity between qubits. IonQ, a publicly-traded pure-play public hardware and software quantum computing company, is using this technology and has published an article in Nature that shows a significant breakthrough in error correction technology for quantum computers. In collaboration with scientists from Duke University and the Georgia Institute of Technology, this work demonstrates how quantum computers can overcome quantum computing errors, a key technical obstacle to large-scale use cases like financial market prediction or drug discovery.
In quantum computing, hardware and software components are strictly related and dependent on each other. As a matter of fact, a quantum computer is a complex system that involves not only a dedicated and advanced hardware solution, but also a software development kit (SDK) with ready-to-use application programming interface (API).
“In order to get the most out of the hardware, you need to take advantage of that at the software level,” said Chris Monroe, co-founder and chief scientist at IonQ. “You need to know what the connections are, what the architecture is, which gates are available, and this is the only information which can help you to compile programs that are more efficient.”
One of the biggest challenges in building a quantum computer is to keep the error rate as low as possible since a poor error rate can compromise the scalability of the system, and therefore the total number of qubits which can be used without affecting its reliability. IonQ’s quantum processor is powered by these atoms. From early preparation to final readout, atoms are trapped in 3D space and controlled through laser beams to ensure the required stability. The system requires precision optical and mechanical engineering and fine-grained firmware control over a multitude of components.
“Our hardware is based on individual atoms, which can be thought of as quantum bits. Individual atoms are what make our quantum system very clean and scalable,” said Monroe.
Since qubits are based on natural atoms, they don’t need to be manufactured and therefore they don’t have any manufacturing defects. This is one of the most relevant aspects for scaling. In general, as the system gets bigger, it is harder to keep it isolated. If we make a system bigger, usually errors grow. According to IonQ, that is not the case with their system, which can be scaled as large as we want, while remaining perfectly isolated.
Each qubit in solid-state systems is slightly different from the others, is very noisy, and needs to be almost perfectly isolated during a computation. That is a drawback for solid-state technology, as solid-state, by definition, is not isolated. In order to get the atoms stable (not moving at all), IonQ uses a process called laser cooling. By properly tuning the laser, this process can get the atoms to be at rest. The important thing is that this process does not require refrigeration or fancy equipment, but it just needs the laser beam. As a result, the vacuum chamber that holds the atoms can operate at room temperature; because of the vacuum, there is no heat transfer (figure 2).
IonQ’s current generation system, as well as any other quantum computer system in the world, is still not powerful enough to beat supercomputers. However, at IonQ, they think that, at some point in the future when the system gets big enough, it will beat supercomputers.
Last October, a team from Quantum Economic Development Consortium (QED-C) released the first version of an open-source suite of benchmarks for quantum computing hardware. In a research paper, QED-C benchmarks have been used to evaluate the systems provided by many of the leading quantum computing hardware developers, including IonQ’s latest generation trapped ion system, which outperformed all the other devices.
It should be noted that in the past, qubit count was widely considered in the industry as the most relevant benchmark for assessing a quantum processor power and capacity. However, as the number of qubits kept growing, a more accurate and reliable metric became necessary. In fact, fewer high-quality qubits can often do more than many low-quality ones, especially if they exhibit a lower error rate. As pointed out, a device with 100 physical qubits and a 0.1% error rate can solve more problems than a device with one million physical qubits and a 1% error rate.
IonQ has already started to run algorithms, even on their “small” 11-qubit system, with leading financial firms. As soon as larger hardware is deployed, they will most likely create commercial value. This requires software tools specifically tailored on the underlying hardware.
Monroe said, “When you learn the structure of an algorithm, you can learn shortcuts. We like to run algorithms that are co-designed, that are tightly integrated with our hardware.”
To face scaling, as mentioned before the biggest challenge when making quantum processors more powerful, both laser controllers and software are equally important.
The application of quantum computing to finance is confirmed by a recent agreement signed by IonQ with Multiverse Computing, a Spanish quantum software company that applies quantum and quantum-inspired solutions to solve complex problems in finance and deliver value. Its flagship product, Singularity, allows financial professionals to leverage quantum computing with common software tools. IonQ-Multiverse partnership will allow financial professionals to predict risk more accurately and faster than ever before. By using this integrated solution, financial institutions can simulate real-world financial challenges including fair price calculations, portfolio construction and optimization, ETF replication, risk valuation, and many other simulations with unparalleled speed and accuracy.
IonQ has already delivered a couple of their quantum computer systems on the cloud, hosted by primary partners, such as Amazon Braket, Microsoft Azure Quantum, and recently Google Cloud Platform. This will allow anybody to get access to IonQ systems. IonQ’s systems are quantum computers purchasable via the Google Cloud Marketplace, supporting Google’s Cirq and other quantum development kits. Through this partnership, IonQ’s 11 qubit systems are already available to all Google Cloud customers, while IonQ’s next-generation 32 qubit system will be available in the near future.