Antiferromagnetically ordered particles are represented by red and blue spheres in this artist’s impression. The particles are in an array of optical traps. Credit: Chen Lei
Topics: Applied Physics, Computer Science, Quantum Computer, Quantum Mechanics
Experiments on the Fermi–Hubbard model can now be made much larger, more uniform, and more quantitative.
A universal quantum computer—capable of crunching the numbers of any complex problem posed to it—is still a work in progress. But for specific problems in quantum physics, there’s a more direct approach to quantum simulation: Design a system that captures the physics you want to study, and then watch what it does. One of the systems most widely studied that way is the Fermi–Hubbard model (FHM), in which spin-up and spin-down fermions can hop among discrete sites in a lattice. Originally conceived as a stripped-down description of electrons in a solid, the FHM has attracted attention for its possible connection to the mysterious physics of high-temperature superconductivity.
Stripped down, though it may be, the FHM defies solution, either analytical or numerical, except in the simplest cases, so researchers have taken to studying it experimentally. In 2017, Harvard University’s Markus Greiner and colleagues made a splash when they observed antiferromagnetic order—a checkerboard pattern of up and down spins—in their FHM experiment consisting of fermionic atoms in a 2D lattice of 80 optical traps. (See Physics Today, August 2017, page 17.) The high-temperature-superconductor phase diagram has an antiferromagnetic phase near the superconducting one, so the achievement promised more exciting results to come. But the small size of the experiment limited the observations the researchers could make.
A 10 000-fold leap for a quintessential quantum simulator, Johanna L. Miller, Physics Today.
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