A college professor of mine suggested a restaurant business to our class. He taught statistical mechanics, the physics of many-body systems. Examples range from jet fuel to ice cubes and primeval soup. Such systems contain 1024 Particles each – so many particles that we wouldn’t be able to track them all if we tried. We can collect little information about the particles, so their actions look random.

A drunk also goes for a walk. Imagine a college student who stayed outside an hour late (outside of the pandemic) and accepted one too many red plastic cups. He’s halfway down the sidewalk where he’s clutching a lamp post on the way home. Each step has a 50% chance of carrying it to the left and a 50% chance of carrying it to the right. This scenario is repeated every Friday. On average, he is back at the lamppost five minutes after arriving at the lamppost. But if we wait a while T.We have a good chance of finding him some distance away  sqrt {T} Path. These properties characterize a simple one aimless walk.

Random walks appear in statistical physics. For example, imagine a grain of pollen that has fallen onto a thin film of water. The water molecules sniff the grain that happens to run across the film. Robert Brown observed this walk in 1827, so we’ll name it Brownian motion. Or consider a magnet at room temperature. The components of the magnet do not run over the surface, but are based on random walk mathematics. And in quantum many-body systems, information can spread through a random walk.

So my professor of statistical mechanics said someone should open a restaurant near MIT. Serve lo mein and peking duck and name the restaurant the random wok.

This is the professor who years later confronted another alumna and me at a snack buffet.

“Do you know what that is?” he asked, waving a pastry in front of us. We stared for a moment, concluded that the obvious answer would not be enough, and shook our heads.

“A brownie on the move!”

Not only pollen grains undergo Brownian movement, and it is not only drunks who take casual walks. Many people happen to go to their careers and try and discard alternatives along the way. We may think we know our destination, but we collide with a water molecule and change course.

So is the thrust of Random walks, a podcast that I contributed to an interview on last month. Abhigyan Ray, a student in Mumbai, created the podcast. Courses, he thought, only familiarize us with success in science. Stereotypes turn scientists into lonely geniuses who work in closed offices and quiet laboratories. He decided to highlight the collaborations, the wrong turns, the lessons learned the hard way – the random ways – of science. The respondents range from a Microsoft researcher to a Harvard computer scientist to a professor of neurobiology to a genomicist.

You can find my episode on Instagram, Apple Podcasts, Google Podcasts, and Spotify. We discuss bridging disciplines; the usefulness of liberal arts education in physics; Quantum limits;; and the joys of poking fun at my graduate advisor, blogger, and director of the Institute for Quantum Information and Matter, John Preskill.



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