If your model can't predict its limits, it is an indication that you are already past its limits.
When you build a model, you build it to map the range of behaviors you are interested in. When mathematical infinities of any kind (like infinite computational power) emerge it's usually a strong hint that the model is not applicable, not an invitation to fantasize about the things you will be able to achieve following your model outside of its region of trust.
You question your hypothesis and then look for an alternative model that is more probable. You don't spend your resources doubling down on blind model following.
Assuming some priors and Bayesian updating your beliefs about how the world works is probably a better strategy.
I am not a Physicist so I don't have skin in this game, but the QM scene really look like a mix between snake oil vendor and religion, and doing more of this "science" by marketing firms isn't really any scientist should wish for.
All the physical theories we had so far require infinite computational power, because they work with real numbers, it's easy to say that it is wrong, but that's not really useful without saying what is right.
There are several interpretations of quantum mechanics that predict quantum computers not working in different ways, to find which one of them is correct you need an experiment that is not described by traditional view. Building quantum computers is the first experiment that has a chance to show what exactly is wrong with QM. Even the people who think there is nothing wrong with QM agree that quantum computer not working would be a bigger discovery than working, and are considering all the alternatives, so i don't see how it is anything like a religion.
Working with real numbers, doesn't mean requiring infinite computational power. Numerical integration can make the integration error arbitrary small, even without symplectic integrators, this mean you can work with finite-precision number instead.
The thing with building a quantum computer is that the original hard test (breaking RSA) is being watered down. Until you prove that you've done it you only get non-results telling you that you are not there yet but you don't know why and require ever more funds. So the incentives are badly aligned and you prove a softer test that you try to sell as something as good as the hard test. If you are not familiar with bias you might even fool yourself into thinking you are making progress because you managed to reach the softer goal you have set for yourself while you are adding complexity to obscure your theoretical shortcomings.
>Building quantum computers is the first experiment that has a chance to show what exactly is wrong with QM.
Don't blindly trust experiments : Bell officially proved that what's very probably wrong is right.
Especially when they require expensive equipment or specialized knowledge to reproduce. If there is something wrong with the protocol you can easily falsely convince yourself. Putting a non-zero prior on unknowns unknowns should be a must.
If you ever try to question the Gospel of Non-Locality, you will find yourself cast aside like many before as the vast literature show.
When you build a model, you build it to map the range of behaviors you are interested in. When mathematical infinities of any kind (like infinite computational power) emerge it's usually a strong hint that the model is not applicable, not an invitation to fantasize about the things you will be able to achieve following your model outside of its region of trust.
You question your hypothesis and then look for an alternative model that is more probable. You don't spend your resources doubling down on blind model following.
Assuming some priors and Bayesian updating your beliefs about how the world works is probably a better strategy.
I am not a Physicist so I don't have skin in this game, but the QM scene really look like a mix between snake oil vendor and religion, and doing more of this "science" by marketing firms isn't really any scientist should wish for.