Method to Char­ac­ter­ize Large Quantum Computers

A quantum computer.

Quantum devices are becoming ever more complex and powerful. (Image: via Pixabay)

Quantum computers are becoming ever more complex and powerful. Researchers at the University of Innsbruck, in collaboration with the Johannes Kepler University Linz and the University of Technology Sydney, are now presenting a method to characterize even large quantum computers using only a single measurement setting.

The gold standard for the characterization of quantum computers is so-called quantum tomography, which in analogy to medical tomography, can draw a complete picture of a quantum system from a series of snapshots of the system.

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While offering plenty of insights, the number of measurements required for tomography increases rapidly, with three times as many sizes as are necessary for every additional qubit. Due to the sheer time it takes to perform all these measurements, tomography has only been possible on devices with few qubits.

However, recent developments in quantum computers have successfully scaled up system sizes much beyond the capabilities of tomography, making their characterization a daunting bottleneck.

View inside an ion trap, the heart of an ion trap quantum computer.
View inside an ion trap, the heart of an ion trap quantum computer. (Image: C. Lackner via University of Innsbruck)

Pictured from a single measurement setting

A team of physicists led by Martin Ringbauer from the Department of Experimental Physics at the University of Innsbruck, in collaboration with theoretical physicists from Linz and Sydney, have now developed and demonstrated a practical approach for characterizing even large-scale quantum systems, relying just on a single measurement setting, independent of the system size.

This is achieved by moving parts away from the binary computation inherent to quantum computers and their classical predecessors. The atomic ions used for quantum information processing feature much more than just the two-qubit levels to which it is artificially restricted. Engaging more levels holds the potential to store significantly more information per particle. Innsbruck physicist Roman Stricker said:

“Extending qubits to four-level ququarts thus enables us to store and measure the entire information necessary for tomography in one go.”

The team has demonstrated a highly efficient characterization approach by combining this method of measuring with a data analysis approach named “classical shadows,” initially developed by Richard Küng from Johannes Kepler University Linz and colleagues.

Using the combined techniques, they were, for the first time, able to characterize an eight-qubit system in real-time. Küng emphasizes that their framework has the potential to enable real-time characterizations of large future devices, which is a significant next step toward the scalability of quantum computers.

An IBM quantum computer.
An IBM quantum computer. (Image: Lars Plougmann via Flicker)

Widely applicable technique for quantum computers

The main technological challenge was to precisely transfer the qubit information into the four states of the ququart and then extract it in a single run of the experiment. Michael Meth from the University of Innsbruck explained:

“Our readout capabilities so far could only distinguish between two levels per detection, so we adapted our setup such that we can detect three times in a row to identify all four levels.”

Thomas Monz said:

“We managed to overcome this problem by programming a fast camera readout and counteract detection-induced heating of the ions by employing an extra laser cooling step.”

These adaptions are crucial to prevent the loss of quantum information during the extended detection process. Martin Ringbauer, who led the Innsbruck team, emphasizes:

“All the building blocks developed in this work readily apply to other quantum computer architectures that have access to higher-dimensional information carriers.”

The research work was published in the journal PRX Quantum and funded by the Austrian Science Fund FWF, through the SFB BeyondC, the Austrian Research Promotion Agency FFG, and the European Union, among others.

Provided by the University of Innsbruck [Note: Materials may be edited for content and length.]

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