Advances show quantum computing is nearing real-world payoffs
The core of this quantum computer looks familiar enough: a silicon chip the size of a stamp. But the resemblance to your laptop ends there. The chip, cocooned within a vacuum chamber and cooled nearly to absolute zero, is patterned with 198 gold electrodes, arranged like an oval racetrack.
“We are currently using chemistry problems to advance quantum computing instead of using quantum computing to advance chemistry,” says Quantinuum’s head of strategy, Chad Edwards. “But there will be a tipping point,” where those roles will be reversed. “There has been a clear speedup in the past year,” agrees quantum physicist Louis-Paul Henry at PASQAL, a quantum computing startup based in Paris that is also focusing on chemistry.
The challenge is that qubits are fragile: The slightest jostle by an air particle, a modicum of heat, or even a stray cosmic ray can upset a qubit’s superposition state, creating an error that throws off the result. Researchers minimize these influences by chilling qubits and isolating them from their environment. They also build in redundancy.
Today’s most popular hybrid, an algorithm known as a variational quantum eigensolver , uses classical computers to approximate a molecule’s stable ground state, the lowest energy configuration that is key to its structure and how it interacts with neighbors. Then a quantum computer takes over to find the ground state’s precise solution. But today’s error-prone quantum computers typically struggle with VQEs.
To do so they need to understand how the platinum works—how oxygen and hydrogen adsorb to the catalyst, how they transfer electrons and protons through intermediate compounds, and how they finally react to form water molecules, which then dissociate from the catalyst. The computations have proved too tall a task for classical computers alone. So, researchers led by Quantinuum quantum chemist David Muñoz Ramo improved the accuracy of their simulations.
A sharper picture of interactions between potential drug molecules and their protein targets is also the goal for drug developer Insilico Medicine. Insilico researchers reported in February that, running on IBM’s 16-qubit quantum computer, could help find new inhibitors of a cell-signaling protein called KRAS that’s commonly mutated in cancers.
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