A photon is a single particle of light, and under normal circumstances, it can't be divided. But a photon is also not a particle, in the sense that it does not have a specific location. Instead, it is an extended object.

So if a photon is only partway through the process of reflecting from a perfect mirror and you yank the mirror away, what happens? The answer, from a trio of Norwegian physicists, turns out (arxiv.org link) to be more complex than I expected.

A photon divided?

Let’s first talk briefly about dividing and combining photons. If this were a common experience in our lives, then shining a single color of light through a piece of glass or reflecting it from a surface might cause photons to divide or combine. This would lead to an amazing array of colors: Our universe would be the most fantastic and legal LSD trip you could imagine. But this doesn't generally happen, hence LSD.

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There are some obvious big picture issues that stand between us and useful quantum computing. Issues like whether we can make enough high-quality hardware qubits to connect into the error-corrected logical qubits we need, and how we generate the states needed to perform universal computation on those logical qubits. But there are also many less prominent challenges that will need to be solved before we can perform calculations.

One of those challenges, which only affects some types of hardware, is calibration. For devices we manufacture, like superconducting qubits, there are always subtle variations among individual qubits. (This is not true when we use something like an atom to hold the qubit, but the lasers that control them can drift.) As a result, this hardware is put through a process called calibration, where we test different frequencies and amplitudes of the microwave pulses that control them to find the combination that produces the lowest error rates, and then save those settings for use in calculations.

However, you can't perform the typical calibration process while you're doing calculations, which means drift becomes an issue for long and complicated algorithms. Google, though, has figured out that it's possible to do calibration using the same data that's used for error correction.

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