Explanation #1. D-Wave processors are inherently quantum mechanical, and described by open quantum systems models where the energy scale of the noise is much less than the energy scale of the central quantum system.
Explanation #2. D-Wave processors are inherently classical, and can be described by a classical model with no need to invoke quantum mechanics.
The Shin et. al. paper claims that Explanation #2 is a correct explanation of D-Wave processors. Let’s examine that claim.
Let’s see what we get when we apply our two competing explanations of what’s going on inside D-Wave processors to all of this data.
If we assume Explanation #1, we find that a single simple quantum model perfectly describes every single experiment ever done. In the case of the simpler data sets, experimental results agree with quantum mechanics with no free parameters, as it is possible to characterize every single term in the system’s Hamiltonian, including the noise terms.
Explanation #2 however completely fails on every single experiment listed above, except for the Boixo et.al. data (I’ll give you an explanation of why this is shortly). In particular, the eight qubit quantum entanglement measured in Lanting et al. can never be explained by such a model, which rules it out as an explanation of the underlying behavior of the device. Note that this is a stronger result than it’s simply a bad explanation — the model proposed in Shin et. al. makes a prediction about an experiment that you can easily perform on D-Wave processors that contradicts what is observed.
Why the model proposed works in describing the Boixo et.al. data
Because the Shin et. al. model makes predictions that contradict the experimental data for most of the experiments that have been performed on D-Wave chips, it is clearly not a correct explanation of what’s going on inside the processors. So what’s the explanation for the agreement in the case of the Boixo paper? Here’s a possibility, which we can test.
The experiment performed in the Boixo et. al. paper considered a specific use of the processors. This use involved solving a specifically chosen type of problem. It turns out that for this type of problem, multi-qubit quantum dynamics and therefore entanglement are not necessary for the hardware to reach good solutions. In other words, for this experiment, a Bad Explanation (a classical model) can be concocted that matches the results of a fully quantum system.
I’ve proposed an explanation for the agreement between the Shin et.al. model and this particular experiment — that the hardware is fundamentally quantum, but for the particular problem type run, this won’t show up because the problem type is ‘easy’ (in the sense that good solutions can be found without requiring multi-qubit dynamics, and an incorrect classical model can be proposed that nevertheless agrees with the experimental data).
How do we test this explanation? We change the problem type to one where a fundamental difference in experimental outcome between the processor hardware and any classical model is expected. If the Shin et. al. model continues to describe what is observed in that situation, then we have a meaningful result that disagrees with the ‘hardware is quantum’ explanation. If it disagrees with experiment, that supports the ‘hardware is quantum’ and the ‘type of problem originally studied is expected to show the same experimental results for quantum and classical models so it’s just a bad choice if that’s your objective’ explanations.
In the case of finding good explanations for the experimental results available for D-Wave hardware, there is a treasure trove of experimental data available. Here is just a small sample. There are experimental results available on single qubits (Macroscopic Resonant Tunneling & Landau-Zener), two qubits (cotunneling) and multiple qubits (now up to about 500) (the eight qubit Nature paper, entanglement, results at 16 qubits, the Boixo et.al. paper).
No classical model has ever been proposed that simultaneously explains all of the experiments listed above.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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