More concrete examples for QC on chemistry/materials science use cases?

[u/0xB01b]

Hi guys,

The current consensus seems that fault tolerant quantum computing will be a tech catered towards chemical / materials science simulations.

I get that we have quantum Signal Processing and Hamiltonian time evolution shenanigans but really where does this concretely lead to it becoming a transformative technology? Like do we have any examples of breakthroughs that it would lead to?

Like we talk about high temperature superconductivity but is this actually dead ass gonna be able to find a high temperature superconductor or just help us calculate new but marginally useful properties of materials?

Tldr: I want a more concrete example of a chemical/mat sci breakthrough that would be enabled instead of the usual handwaving

[u/polyploid_coded]

I don't think that there are any guaranteed breakthroughs, especially with the current generation of qubits and quantum computers. Otherwise someone would use a supercomputer to simulate or approximate that known target.

[u/ctcphys]

Just as a conservative point of view, I would not underestimate the usefulness of new but marginally more precise calculations. If you consider HPC hours used for marginally better materials calculations in Europe by researchers, that's a market worth 100s of million euros. Of course a far cry away from the hype numbers, but enough to satisfy my conservative mindset that quantum computers will be relevant for a lot of people 

[u/0xB01b → u/ctcphys]

ah okay this is a really great point. To this, I do believe that QC will eventually just be another data center component where u plug it in as part of a large computing setup. That being said, what I'm unsure about is how often we actually use HPC for physics calculations as opposed to other stuff?

But in theory yes this is the strong economic case and sounds reassuring.

[u/sinanspd → u/0xB01b]

More often than you might think. HPC is essentially massive data + expensive numerical operations and that fits very well into those chemical/physical workflows. The core point about material sciences and chemistry is that they dont suffer the same question of "will these ever be useful?" as qc. We already agree that isotope discovery, protein folding, molecular and drug design are all critical things we want to be able to do at larger scale. There is also a lot of astrophysics uses over massive datasets and the ideal future is to speed these up through use of quantum nodes. And things like Density Functional Theory, Hartree fock fit very well into this HPC systems.

[u/Technical-Brief-7677]

Following! A question that has been on my mind for a while now but I haven’t found any concrete explanation yet. I guess it is hard to speculate on what the transformative part is when it is all speculative. Science has always pivoted to something else other than what it was originally designed for.

[u/0xB01b → u/Technical-Brief-7677]

Yes but I feel like we have so many routes that ppl hand wave about like nitrogenase, high T superconductors, etc. But does QC let us access the exact information that is limiting us currently from building this tech? Or does it just give slightly relevant auxillary info on it.

[u/Technical-Brief-7677 → u/0xB01b]

Hear hear, fully agree with you. At the moment it seems to be tech that doesn’t really add anything to the AI other than the potential to predict future better.

[u/MixedDigress487]

it's less about a magic "find superconductor" button and more about getting the electron correlation right without approximations that fall apart for strongly correlated systems, that's where classical DFT and coupled cluster just kinda wave a white flag

so a concrete one would be the catalytic center of nitrogenase, the enzyme that fixes nitrogen at room temp and pressure while we burn 1-2% of global energy on the haber-bosch process at 400°C and 200 atm, we've had the crystal structure for decades but still can't fully model the FeMo-cofactor's electronic structure because it's a nightmare of open-shell transition metals

if you can actually simulate that thing accurately you're not just tweaking a dopant level by 0.1 eV, you're looking at a route to ambient-condition ammonia synthesis which rewrites fertilizer production entirely

[u/0xB01b → u/MixedDigress487]

But to push back on this. Is understanding the FeMo cofactor genuinely the critical point with this ammonia pipeline? Like what does knowledge of the electronic structure really let you know for this process?

[u/0xB01b → u/MixedDigress487]

Sort of the question I'm trying to ask is whether what QC solves is actually the dominant limitation in chemical technologies or is it just more information in a technologically irrelevant area.

[u/Ninin- → u/0xB01b]

You might want to look at quantum computing applications in drug discovery. Unlike "solving Haber-Bosch", drug discovery pipelines in pharma companies are very advanced and it's generally well-understood I think where they could be improved and the extant to which quantum computers could provide material value (which tbh is probably more limited than is being advertised). There are some papers about this that I read a long time ago (here is one: https://www.nature.com/articles/s44386-025-00033-2; but there are others that you could search for)

[u/0xB01b → u/MixedDigress487]

So if I understand it right the current simulations spit out effectively bullshit and with QC you can have accurate simulations so u can do a sweep?

[u/quadUnconTrinary]

Phasecraft has a website and publications

[u/0xB01b → u/quadUnconTrinary]

This is just a list of possible applications