Quantum Supremacy Using a Programmable Superconducting Processor

Quantum Supremacy Using a Programmable Superconducting Processor
drive.google.com

”””While our processor takes about 200 seconds to sample one instance of the quantum circuit 1 million times, a state-of-the-art supercomputer would require approximately 10,000 years to perform the equivalent task.”””

”””Quantum processors based on superconducting qubits can now perform computations in a Hilbert space of dimension 2^53 ≈ 9 × 10^15, beyond the reach of the fastest classical supercomputers available today. To our knowledge, this experiment marks the first computation that can only be performed on a quantum processor. Quantum processors have thus reached the regime of quantum supremacy. We expect their computational power will continue to grow at a double exponential rate: the classical cost of simulating a quantum circuit increases exponentially with computational volume, and hardware improvements will likely follow a quantum-processor equivalent of Moore’s law [52, 53], doubling this computational volume every few years. To sustain the double exponential growth rate and to eventually offer the computational volume needed to run well-known quantum algorithms, such as the Shor or Grover algorithms [19, 54], the engineering of quantum error correction will have to become a focus of attention.

The “Extended Church-Turing Thesis” formulated by Bernstein and Vazirani [55] asserts that any “reasonable” model of computation can be efficiently simulated by a Turing machine. Our experiment suggests that a model of computation may now be available that violates this assertion. We have performed random quantum circuit sampling in polynomial time with a physically realized quantum processor (with sufficiently low error rates), yet no efficient method is known to exist for classical computing machinery. As a result of these developments, quantum computing is transitioning from a research topic to a technology that unlocks new computational capabilities. We are only one creative algorithm away from valuable near-term applications.”””

Also what is the error rate?

How I understand it: the "computation" is actually "sampling" the cubits? And then sampling results in the sets of random numbers, which don't have uniform but some specific distribution (specific for quantum effects). Then they claim that such a distribution could not be achieved using classical computer so fast, if the classical computer has to do the simulation of the cubits. And therefore, they claim that their quantum process is better.

But couldn't one do a similar conceptual setup even before, e.g. measuring some noise source (e.g. a semiconductor based diode etc) and then claiming that measuring the source is faster than simulating on the digital computer the analog behavior of the noise source?

The interesting step here is that the source is not a single element but a set of quantum qubits, which is much harder to simulate, but on another side it appears that dealing with the behavior that doesn't allow e.g. Shor algorithm on the same setup is avoided by decision to do what was done.

Seems like a clever trick, but I miss in which aspects it makes the hoped-for outcome (e.g. breaking some crypto keys using Shor) in any way more achievable than before.

Please don't assume that I really know what I write, but consider this as a possibility to explain to the not fully informed public which however shows an interest in the topic.