With every new hardware architecture comes an accompanying software architecture, and when the two meet, there is a cambrian explosion of invention and innovation. We are experiencing this now with GPUs + transformers.

Driven primarily by curiosity, I wondered what one of the use cases for quantum computers would be. We hear about how they break encryption algorithms, but besides that, there really isn’t anything. So what can you do on a quantum computer that you can’t on a classical computer?

Biotech

Most of my work in the past couple of years has been at the intersection of computers, engineering, and biology. When we design a drug, we are designing a smaller molecule that can fit into a larger molecule to turn off the larger molecule or activating some desired function. At the molecular level, this is how a lot of biology works- stuff is expressed/repressed based on turning it on or off.

Last year, I found this paper where the authors used new computational tools to make antivenom binders to neutralize cobra toxins. The design and filtering process was done completely in silico. They then injected these binders into mice poisoned with cobra venom, and every treated mouse survived.

We could do the same simulation with a quantum computer, but there are too few qubits in the world to simulate a binder docking into a protein. A physicist I met recently that works on applying qubits to chemical models was basically fundraising to port Boltz2 to quantum, but said we are orders of magnitude away (but does not mean it is impossible, just expensive).

All that to say, we can work through a toy example today that can someday compound into fitting a binder into a protein.

What are we actually trying to compute?

Almost everything we care about in a molecule, whether a bond holds, how a reaction proceeds, how tightly a drug sits in a binding pocket; is governed by the energy of its electrons. Formally, the electronic structure problem is an eigenvalue problem:

The quantity that matters most is the ground-state energy, E0: the smallest eigenvalue of the molecular Hamiltonian H^. Differences in E0 across geometries give us potential energy surfaces, reaction barriers, and binding affinities.