Is that a lot of qubits? I have no frame of reference on this.
Edit: for context, I'm referring to D-Wave, that some years ago said they had broken the 1000-qubit mark, but their systems aren't generic quantum computers, but rather computers tham implement quantum annealing.
Having said that, IBM just unveiled a 127 qubit machine, and their roadmap is to to to scale to 433, and then 1121 qubits in the not too distant future.
https://newsroom.ibm.com/2021-11-16-IBM-Unveils-Breakthrough...
Yes. Now the most powerful quantum computers have less than 100 qubits. We have to reach 130,000,000 qubits. Take a beer meanwhile =)
No, it's much, much more than double the effort to build a QC with twice the qubits. The problem is that you want the qubits to interact with each other, but to be entirely perfectly isolated from the outside world for as long as necessary for signals from one to reach the others. The difficulty of achieving this isolation even for an instant at all increases by something like n^2 or n^3 (surface/volume of the isolated space) with the number n of qubits. Then, the more qubits you have, the more time you need for them to interact, so you multiply by an additional factor.
The numbers above are very handwavy, of course, but the point is that it's MUCH harder to build a bigger QC than a small one. So hard that it's not even clear if the current approaches can actually achieve this even in principle - we may need a different kind of qubit to scale up.
Once you have the ability to create a processor at 7nm with some bits, scaling is not so tough. Even if you cannot reliably create larger pieces of silicon, you just do something like AMD did with multiple dies connected by a fabric to mitigate risk. Absolutely worst case, you have a motherboard with multiple processors, or even computers in different buildings.
In terms of qubits, it is very likely that the problem can be distributed over multiple quantum computers. A significantly incentivized actor could definitely pull it off. If you can reliably manufacture ~100 qubit quantum computers, it's just a matter of scale.
[1] https://en.wikipedia.org/wiki/PlayStation_2_technical_specif...
No, this is very wrong. Qubits are only different from classical bits of they can communicate before becoming entangled with the environment (decoherence). You can't run some kind of "quantum cable" between two separate QCs in a rack and get twice the qubits - the interactions with the wire will break the entanglement between the qubits, and you will just have an unreliable classical computer with 100 bits of memory.
To perform a quantum computation, ALL the qubits (all your memory) must be in an entangled state together - this is the massive problem. Even worse, this state must be maintained while applying different transformations on the qubits from the outside.
From my limited understanding, you process for a given amount of time, after which you can classically pull out an answer with some given probability, with some trade off with time and noise.
I imagine it would be somewhat possible to have several quantum computers running in parallel which end early, each correctly deducing the answer with some given probability. If each of the N^x machines has a 1/N chance of having the correct answer, you could simply test each solution classically.
And that assumes there is not some way to seed the search effort classically during the setup of the quantum circuit.
An extra complication for QCs is that you also need error correcting calculations in addition to your base calculations. So, if you want to multiply 2 128-bit numbers, not only do you need at least 256 (q)bits of working memory, you need some additional number to correct for errors in the calculation - and with currently known error correcting methods, you need A LOT more.
That's why the article is giving a minimum number of qbits for the Bitcoin calculation: 10^7 physical bits, which represent a measly ~2000 logical (perfect) qubits. This is the minimum number you would need to keep entangled for your your minimum clock period.
We are currently at 10^2, and even getting to 200 is a research-level task; 10^3 is far away. Once we get to something like 10^7, we may be able to start thinking of parallelizing at the whole machine level.
Even still, it's important to understand that quantum algorithms have, as far as we know for now, an exponential advantage over classical algorithms (note: this only applies to certain algorithms, NOT any algorithm). This only applies as long as you are running in the quantum regime. That is, if a particular quantum computer can resolve a problem for N components in 1 minute, and a quantum computer of double the qubit number can finish it in 30s, 2 QCs of the first type will finish it in something like 59s, since they will not benefit from the exponential quantum speedup.