Quantum Supremacy: A technological frontier or simply malarkey. Part II.

Just when we thought the race for Quantum Supremacy (QS) is obsolete and over, five days ago, Google has once again claim to have achieved QS; Although, unlike the absolute nature of their initial assertion in their 2019 publication, they made this one with a punch of salt and a bucket full of modesty. If at this point you are still wondering, “what is quantum supremacy?”, then note that this simply means a computational point where we can find a problem that a quantum computer can solve in a reasonable time, for which a classical computer cannot solve in any reasonable or given time.

Because the original meaning of the term “quantum supremacy,” as proposed by John Preskill in 2012, was to describe the point where quantum computers can do things that classical computers can’t, this threshold has not been met.

If you missed the first part of this newsletter, please read the first part for background and continuity: https://www.dhirubhai.net/pulse/quantum-supremacy-technological-frontier-simply-malarkey-wejeyan-revnc

The concept of QS from a general point of view can be misleading. One might mistake this to mean a situation where we have quantum computers ruling over classical computers; but that is not the case. As much as we look forward to the mind-blowing computational capabilities of quantum computers, one thing that is certain at this point is that we would always need classical computers, if not for anything else then at least, to translate computational solutions (of classical computers themselves or other quantum computers) into forms and structures that we have come to understand, and have built our entire science and technological foundations upon. ?

A notable property of quantum supremacy is that it can be feasibly achieved by near-term quantum computers, since it does not require a quantum computer to perform any useful task or use high-quality quantum error correction, both of which are long-term goals.

At this point, it is important to note that QS is a theoretical target, and not a useful technological concept. So, to the contemporary technologist who is looking to make a boat load of money from quantum technological advancement, QS is simply malarkey. The problems that most QS claim believe they have solved are usually not useful for contemporary technological application: they are usually theoretical abstractions. And, although a now common theoretical concept such as “complex numbers” which was once theoretically abstract (to the point that it was believed to have mysterious and metaphysical implications), has now found application in innumerable fields and technological applications, the important and technologically applicable problems that we require of QS are still very far away from being feasible.

Most of these important problems require more qubit processor than Google’s Sycamore can ever imagine at the moment, while on the other hand, we do not have any handle whatsoever on how to create a quantum mechanical solution for other problems – Shor’s algorithm for example. Practically speaking, the list of problems we know right now that are suited for quantum computation is less than a drop in the ocean of problems we can compute classically. So even as a theoretical target, we are still searching for quantum computational problems – useful or not – to test and play with, abstractly, on our quantum computers. ?

Then why do big tech companies make achieving QS seems like a big technological breakthrough? Why are they spending a lot of money and research manpower on these theoretical abstractions that are of no current use or value? Firstly, it is our thirst to learn and conquer our environment, and subject natural processes to our imperialistic control that has been the most driving force of our technological advancements. So, at this point, QS serves as a theoretical-computational landmark from which unprecedented technological innovations can be achieved. At the point where we can completely say that we have achieved quantum supremacy, and that our quantum computers can make computations of many more problems that are beyond the computational capabilities of classical computers, we have opened doors to a new world of computational reality and possibilities, and a new realm of technological advancement.

The difficulty of proving what cannot be done with classical computing is a common problem in definitively demonstrating quantum supremacy.

It is imperative to understand that the task of achieving QS comes in two categories; first is developing a working theoretical principle upon which to test and confirm QS, and the second task is the engineering of building the mechanical components of the quantum computer that would perform the aforementioned test. The first category can be divided into analysis of algorithm, and computational complexity theory. While analysis of algorithm deals with analyzing the amount of resources (time and memory) needed for the quantum algorithm to solve a problem, the computational complexity theory focuses on general questions about all possible algorithms that can be used to solve the same problem. The second category is the responsibility of the computer theoreticians and engineers to figure out. Then after crossing all Ts and doting all Is, the problem solved has to be unsolvable by any classical computer. To quote a comment made on the first part of this article by Patrick Van Esch:

“…in order for a problem to be "solved" one has to be able to check the solution, otherwise we cannot claim to have solved it. Now, that checking can only be done with a classical computer of course, because only a classical computer can provide in principle, a logically verifiable path: logic is "classical" because it is sequential and discrete. But if a problem can be verified by a classical computer, that means that the solution space is discrete and finite, otherwise one couldn't even INTRODUCE the solution into a classical computer. And every finite discrete space can IN PRINCIPLE be scanned by a classical computer, even though it might be vastly impractical. So, every solution that can be checked by a classical computer can also be found by a classical computer, at least in principle, even though it might not be practical. For instance, factorizing a huge integer is ALWAYS in principle possible by a classical computer even though it might not be feasible in practice: it is sufficient to try all divider candidates up to sqrt(n).”

While balancing the conundrums of whether QS is a technological frontier or simply malarkey, there is a flip side to the problem that we all seems to have turned our backs to: Can current quantum computers perform the computational tasks that contemporary classical computers can? If they cannot, then how is there any validity in the concept of QS? Although, theoretically, in complexity theory, it is presumed in general that quantum computers can simulate any classical algorithm, when and at what point in our advancement of quantum computers can we replace Watson (IBM’s supercomputer, with all its present functionalities) with Sycamore, Google’s quantum computer, which is believed to have achieved Quantum Supremacy?

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Next week’s publication: Quantum Logic and Quantum Logic Gates: A peek into the beauty and meaning of the Machine Language of Quantum Computers.