I read a good analogy somewhere about how quantum computing relates to traditional (classical) computing. The difference between quantum computers and regular computers is like the difference between lasers and light bulbs. You wouldn’t light up your dining room with lasers— if you want to see your food, you use light bulbs. Lasers and light bulbs serve different purposes even though they both involve light. Similarly, you’re not going to balance your checkbook, surf the web or tweet your friends with a quantum computer. A quantum computer will solve a different set of problems.
Quantum computers may be good at solving problems that scale up too quickly for regular (or “classical”) computers. For example, breaking cryptography involves factoring large numbers. The reason that algorithms such as the RSA scheme — a widely used encryption algorithm — work well is that even the fastest classical supercomputer would take much longer than the age of the universe to factor the encrypted numbers. Theoretically, a quantum computer could solve the problem in hours.
Quantum computers may also be useful to simulate chemical compounds with large numbers of atoms or molecules. Current computers can simulate only a tiny number of atoms or molecules, and scaling up increases the computing time astronomically. We are now starting a program to determine how quantum computing may help with computational problems in high-energy physics.
While quantum computers have been a theoretical idea for several decades, it’s only recently that scientists have figured out how to build them. The past year has seen the technology for superconducting quantum computers really take off, and several companies such as Intel, Google and IBM have quantum computers available for use. The quantum computers they have right now, however, aren’t powerful enough to do anything super useful, except to teach us more about quantum computing! But bigger computers that may be able to solve real-world problems are coming very soon, and many people are waiting impatiently to try them.
Adam Lyon is a Fermilab scientist on the Muon g-2 experiment.
This is a version of an article that ran in the December issue of Computing Bits.