If you’ve been paying attention to the quantum computing space, you’ve probably heard all about how these futuristic computers are gonna solve problems way faster than the old-school classical ones. They’re supposed to be these game-changers, transforming industries left and right, from pharmaceuticals to energy. But here’s the thing, most of these claims are based on big talk about algorithms and how they scale when the problem sizes get ridiculously huge. But what we really wanna know is, which specific problems can quantum computers actually handle better than the classical ones? And what kind of cool quantum algorithms can we run to solve these problems?
At Google Quantum AI, we’ve been teaming up with industry and academic buddies to dig into these questions. We’ve been debunking the hype and getting down to the nitty-gritty. In 2022, we took on the chemistry of a badass enzyme family called cytochrome P450. These enzymes do some serious drug metabolizing in our bodies, and they’re super important for the pharmaceutical industry. So, we showed how a quantum computer could step up to the plate and tackle the complex electron relationships that determine the effectiveness of these enzymes. Turns out, a quantum computer would be way more accurate and efficient in studying this chemistry.
But we didn’t stop there. We also looked into finding a sustainable alternative to cobalt for lithium-ion batteries. Cobalt mining is a whole mess, so we wanted to see if quantum computers could help us out. We partnered up with BASF, QSimulate, and some smart folks at Macquarie University to develop techniques for simulating materials with periodic atomic structures. Specifically, we checked out this lithium nickel oxide (LNO) material that could potentially replace cobalt in batteries. The thing is, we don’t fully understand all the properties of LNO, so we designed quantum algorithms to study its energies. And let me tell you, it’s gonna take millions of qubits to do this on a quantum computer, but hey, we’re making progress.
Our latest adventure took us to the realm of fusion reactor dynamics. We teamed up with Sandia National Laboratories and our Macquarie University pals to simulate the crazy conditions of inertial confinement fusion (ICF) experiments. You got these high-intensity lasers, a metallic cavity, and some deuterium-tritium fuel. When everything gets heated up, fusion happens and it’s a big party of nuclear reactions. But simulating all that with classical computers is a nightmare. So, we took a shot at using a quantum computer to tackle the plasma dynamics in these experiments. It’s a computationally demanding task, but we’re pushing the boundaries, my friends.
Now, look, I gotta be real with you. Running these algorithms on a quantum computer ain’t happening anytime soon. We’re talking years down the line. But that’s why it’s important to start working on this stuff now. We’re laying the groundwork, figuring out the resources we need, and getting ready for that future where quantum computers are the real deal. Plus, along the way, we’ve already made some serious improvements in terms of the cost and efficiency of running these algorithms. So, yeah, it’s a long road ahead, but we’re making moves and getting closer to unleashing the true potential of quantum computing.