AlphaQubit: AI to identify errors in Quantum Computers

When maintaining a quantum memory, you measure parity checks of the quantum error correcting code. These parity checks don&#x27;t contain any information about the logical state, just (partial) information about the error, so the logical quantum information remains coherent through the process (i.e. the logical part of the state is not collapsed).<p>These measurements are classical data, and a computation is required in order to infer the most likely error that led to the measured syndrome. This process is known as decoding.<p>This work is a model that acts as a decoding algorithm for a very common quantum code -- the surface code. The surface code is somewhat like the quantum analog of a repetition code in a sense.

&gt;AlphaQubit, a recurrent-transformer-based neural-network architecture that learns to predict errors in the logical observable based on the syndrome inputs (Methods and Fig. 2a). This network, after two-stage training—pretraining with simulated samples and finetuning with a limited quantity of experimental samples (Fig. 2b)—decodes the Sycamore surface code experiments more accurately than any previous decoder (machine learning or otherwise)<p>&gt;One error-correction round in the surface code. The X and Z stabilizer information updates the decoder’s internal state, encoded by a vector for each stabilizer. The internal state is then modified by multiple layers of a syndrome transformer neural network containing attention and convolutions.<p>I can&#x27;t seem to find a detailed description of the architecture beyond this bit in the paper and the figure it references. Gone are the days when Google handed out ML methodologies like candy... (note: not criticizing them for being protective of their IP, just pointing out how much things have changed since 2017)

So, an inherently error-prone computation is being corrected by another very error prone computation?

How can a classical system detect&#x2F;correct errors in a quantum one? I thought all the error correction algos for quantum also relied on qbits e.g. Shor Code.

Quantum computing + AI is undoubtedly the hype singularity.

We&#x27;re almost there, now we just need to incorporate crypto here somehow :)

Part of the problem of this form of benchmarking is that in some domains we wouldn&#x27;t only be interested in the percent of times that an error channel is successfully mitigated, we would also be interested in the distribution of types of errors for cases where an error channel isn&#x27;t successfully mitigated. The paper appears to be silent on that matter.

This all feels like the &quot;with a computer&quot; patents of yore.

I go on the front page and there’s nowhere to complain about AI hype?!<p>The one AI thing is semi-legitimate sounding?<p>What is YC coming to.

Interesting. I don&#x27;t know too much about quantum computers tbh.<p>Quantum computer parts list:<p>- Everything you need<p>- A bunch of GPUs

Been trying for the longest time, I still don’t understand how quantum computing work. It’s always something-something tries all possible combinations and viola, your answer.