Ah, quantum computing – the queen of the buzzwords that ignites imaginations with thoughts of futuristic technology and miraculous solutions. But for me, when I hear the word “quantum,” first I think about my beloved quantum chemistry, then I’m transported back to the roaring 20s in Berlin. Picture it: sharp vests, tight corsets, and ticking jazz. While Max Planck studied light bulbs to overcome ultraviolet disasters, a young Albert Einstein, fresh from a long day at the patent office, solved the photoelectric effect and other mysteries of the universe.
Yes, my friends, the word “quantum” is not just a buzzword – it’s been around for more than a century.
So, how did we get to quantum computing?
Well, it all started with the mischief-maker Richard Feynman convincing everyone that we need them to simulate quantum phenomena. And now, after decades of playing around with algorithms, quantum computing is the talk of the town. It’s like a wild stallion, just breaking free from the gate and ready to change the game for a multitude of industries.
Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical.
Richard Feynman
Quantum computing is the solution to problems that we didn’t even think we had. Steve Jobs, are you listening up there?
But let’s not get ahead of ourselves. The truth is, we don’t know just how powerful quantum computing will be or when exactly it will disrupt the world. But that doesn’t mean we can’t dream… So, if we assume that quantum computing is going to be a game-changer (and I believe it will be), then what do we do with a stallion hardware?
We need to start thinking about software and potential applications.
“What would then be quantum computing’s killer app,” you ask?
Drumroll please… it’s quantum chemistry, baby!
Quantum Chemistry, What’s that?
Now, I know what you’re thinking. “Quantum healing, quantum yoga, quantum chemistry!”
No, dude. No.
Quantum chemistry is the application of quantum mechanics to chemical systems. It makes use of the Schrödinger equation (Schrödinger, the cat guy) and later approaches, such as Density Functional Theory, to describe and predict the chemical and physical properties of molecules and materials.
Remember the 60s? The Beatles vs. the Rolling Stones? And us, all looking up to the sky, thrilled by the landing on the moon. While all that was happening, quantum chemistry was already making its mark in the world of science. Fast forward a few decades, and computational chemistry labs employing quantum chemistry are all over academia and industry. I myself use it every day with my colleagues to predict the properties of alloys and metals, electrode materials, and molecules of biological interest.
Imagine asking your software: “Hey Hal, what reactions should I expect if I mix that resin with my solvent? How can I modify a polymer so it binds more strongly a metal surface? How will this protein evolve in time?”
Hal closes its eyes, performs a couple of calculations, and mumbles the answer.
If it sounds like a dream, well, it is.
Let’s get real.
Quantum chemistry works. And you don’t have to wait for quantum computers to apply it to real-world phenomena. You can run quantum chemical simulations on your average classical supercomputer right now. On your laptop even.
So, where is the catch?
Even with the most powerful (classical) supercomputers and hours of calculation on hundreds of CPUs, quantum chemical simulations can only go so far in capturing the complexity of molecular and atomic interactions.
Man, the world of atoms is a mess of electronic correlations, spin contaminations, and entanglements!
Remember the joke about the physicist and the spherical cow? Well, if you run quantum chemistry on your laptop, the cow will be a sphere. With more computational power, you can add legs, a tail, eyes, and horns. (Wait, do cows have horns?)
More computational power means better models for your molecular system and more accurate answers from our Hals.
Quantum unicorns all around
At the end, that naughty boy of Feynman was right. And that’s where quantum computing comes in. With its potentially greater power, quantum computing promises to take quantum chemistry simulations to the next level to explore molecular and chemical reactions in ways we never thought possible.
We could go from describing a chemical problem and grasping some hints of the real world to replacing wet labs with a lot of Hals. You could get the correct answer without even entering that lab. We could completely skip real-world testing and go straight to production.
Again, unicorns and dry and wet dreams.
So, what’s the hold up?
Currently, quantum computers are still in their experimental stage. More than actual computers, you should imagine them like fancy toys for physicists to play in a luxury basement. Despite this, much progress has been made, and companies are taking notice and investing in their development. With the quantum race heating up, we won’t have to wait for centuries before quantum computers can tackle real-world challenges.
Imagine full quantum simulations of an entire battery cell! DNA processes! Protein folding… viruses! It has already been done to some extent years ago employing cutting-edge approaches.
Quantum computing could make this as easy as pie. Quantum chemistry running on quantum computers is the ultimate holy-grail combo.
That’s why industries across the board are preparing for its arrival. Life sciences, materials science, and chemical R&D are just a few of the areas that could see major changes.
It’s exciting. We are experiencing the birth of a new era. Quantum computing is still in its early days, but it’s got the potential of disrupting quantum chemical applications to predict real-world phenomena.
A big wave is coming. I’m already on my quantum surfboard.
Let’s ride it together.
Scientific Reading List:
1) Chemistry and Quantum Mechanics in 2019: Give Us Insight and Numbers – Frank Neese 2019
2) Quantum Chemistry in the Age of Quantum Computing – Yudong Cao 2019
3) Quantum chemistry as a benchmark for near-term quantum computers – Alexander J. McCaskey 2019
4) Quantum Information and Computation for Chemistry – Jonathan Olson 2017
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