Comments about the article in Nature: The race to find quantum computing's sweet spot
Following is a discussion about this article in Nature Vol 617 25 May 2023, by Michael Brooks
To study the full text select this link:
https://www.nature.com/articles/d41586023016929
 The text in italics is copied from the article
 Immediate followed by some comments
In the last paragraph I explain my own opinion.
Reflection
Introduction

In fact, all quantum computers could be described as terrible. Decades of research have yet to yield a machine that can kick off the promised revolution in computing.

That is in agreeement with my prediction in 2002: Shor

If you believe the hype, computers that exploit the strange behaviours of the atomic realm could accelerate drug discovery, crack encryption, speed up decisionmaking in financial transactions, improve machine learning, develop revolutionary materials and even address climate change.

The most important issue is that all these applications require specific algorithms which can run on a quantum computer and which uses the advantage of qubits, superposition and entanglement. The most famous algorithm available is shor's algorithm, all the others, still have to be developped.






1. Justified scepticism

Until now, there has been good reason to be sceptical.

I agree.

Researchers have obtained only mathematical proofs that quantum computers will offer large gains over current, classical computers in simulating quantum physics and chemistry, and in breaking the publickey cryptosystems used to protect sensitive communications such as online financial transactions.

The only way to demonstrate any advantage of quantum computers is too build one. Simulating a quantum computer on a DC only demonstrates the functionality of a special QC algorithm. See for a simulation of shor's algorithm on a DC: Shor



Researchers cannot even agree on how the performance of quantum computers should be measured.

One of the utmost difficult problems is to test the execution of shor's algorithm on a QC. To test factorization on a DC is already difficult.
See also: findprim_array_x.xls.htm

Whatever the design, the clever stuff happens when qubits are carefully coaxed into ‘superposition’ states of indefinite character — essentially a mix of digital ones and zeroes, rather than definitely being one or the other.

How do you know that the mix is exactly what you want? I think that that is impossible. In a DC context this is easy: It is either one or the other.

Running algorithms on a quantum computer involves directing the evolution of these superposition states.

I expect that this is very difficult.

The quantum rules of this evolution allow the qubits to interact to perform computations that are, in practical terms, impossible using classical computers.

Exactly: What are the quantum rules?
This can be divided in two parts: What are the quantum rules in mathematical sense? What are the quantum rules in physical sense?
What ever the physical issues involved, when ever the whole process is repeated, the final solution should be the same.
This solution should agree with the result using a classical computer.

That said, useful computations are possible only on quantum machines with a huge number of qubits. What’s more, qubits and their interactions must be robust against errors introduced through the effects of etc. These disturbances can cause some of the information necessary for the computation to leak out of the processor, a situation known as decoherence. That can mean dedicating a large proportion of the qubits to errorcorrection routines that keep a computation on track.

Error correction should be performed in parallel with the normal operation of the QC. This involves extra hardware. This hardware inturn can also be the cause of errors.
In classicl computers error corrections is no issue.

This is where the scepticism about quantum computing begins.

?
There are in fact many issues.



But Holzmann and her colleagues found that tweaks to the routines — altering how the algorithmic tasks are distributed around the various quantum logic gates, for example — cut the theoretical runtime to just a few days.

Such tweaking does not seem as a very professional exercise. More detail is required.

That’s a gain in speed of around five orders of magnitude.

Ofcourse all small improvents are wellcome.

“Different options give you different results,” Holzmann says, “and we haven’t thought about many of these options yet.”

That seems strange. The final answer should be the same.








2. Quantum Hop



One example of a smallscale but classically intractable computation that might be possible on a quantum machine is finding the energies of ground and excited states of small photoactive molecules, which could improve lithography techniques for semiconductor manufacturing and revolutionize drug design.

















3. The long game












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Created: 16 July 2023
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