You won’t be traveling by quantum teleportation

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This article appeared in the spring print issue of Popular Science, but has also been published online.

Quantum teleportation is real, but it’s not what you think

A commute so quick you could just die

For Popular Science:

In 2017, physicists beamed photons from Tibet to a satellite passing more than 300 miles overhead. These particles jumping through space evoked wide-eyed sci-fi fantasies back on Earth: Could Star Trek transporters be far behind? Sorry for the buzzkill, but this real-world trick, called quantum teleportation, probably won’t ever send your body from one place to another. It’s essentially a super-secure data transfer, which is tough to do with the jumble of code that makes a human.

Photons and teensy bits of atoms are the most complex bodies we can send over long distances in a flash. Each particle of the same type—photon, neutron, ­electron—​is largely the same as every other member of its subatomic species.

Configurations known as quantum states distinguish them. Two photons spinning clockwise, for example, are identical. You can’t make one zip elsewhere with no lag time (sorry, that’s magic), but you can create its duplicate in another spot. Not so useful for moving people, but valuable for instantaneous, secure communication.

[Read the rest at Popular Science]

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The mathematics of knowledge networks in the brain

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

This article is for SIAM News, the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While the article contains equations, I wrote it to be understandable even if you skip over the math.

Understanding Knowledge Networks in the Brain

For SIAM News:

One strength of the human mind is its ability to find patterns and draw connections between disparate concepts, a trait that often enables science, poetry, visual art, and a myriad of other human endeavors. In a more concrete sense, the brain assembles acquired knowledge and links pieces of information into a network. Knowledge networks also seem to have a physical aspect in the form of interconnected neuron pathways in the brain.

During her invited address at the 2018 SIAM Annual Meeting, held in Portland Ore., last July, Danielle Bassett of the University of Pennsylvania illustrated how brains construct knowledge networks. Citing early 20th century progressive educational reformer John Dewey, she explained that the goal of a talk—and learning in general—is to map concepts from the speaker/teacher’s mind to those of his or her listeners. When the presenter is successful, the audience gains new conceptual networks.

More generally, Bassett explored how humans acquire knowledge networks, whether that process can be modeled mathematically, and how such models may be tested experimentally. Fundamental research on brain networks can potentially facilitate the understanding and treatment of conditions as diverse as schizophrenia and Parkinson’s disease.

[Read the rest at SIAM News…]

Squeezing light to detect more gravitational waves

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

This article appeared in the fall print issue of Popular Science, but I missed that this article had also been published online.

Something called ‘squeezed light’ is about to give us a closer look at cosmic goldmines

Gravitational wave detection is going through an even tighter squeeze.

For Popular Science:

In 2015, scientists caught evidence of a ­cosmic throwdown that took place 1.3 billion light-​years away. They spied this binary black-hole collision by capturing gravitational waves—­ripples in spacetime created when massive objects ­interact—​for the first time. But now physicists want to see even farther. Doing so could help them accurately measure waves cast off by colliding neutron stars, impacts that might be the source of many Earthly elements, including gold. For that, they need the most sensitive gravitational-wave detectors ever.

The devices that nab waves all rely on the same mechanism. The U.S.-based Laser Interferometer Gravitational-Wave Observatory (LIGO) and its European counterpart, Virgo, fire lasers down two mile-plus-long arms with mirrors at their ends. Passing waves wiggle the mirrors less than the width of an atom, and scientists measure the ripples based on when photons in the laser light bounce off them and come back. Ordinarily, photons exit the lasers at random intervals, so the signals are fuzzy.

[Read the rest at Popular Science]

The secret to good digital animation is physics

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

This article is a little different from the fare you’re used to getting from me: it’s for SIAM News, which is the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While the article contains equations, I wrote it to be understandable even if you skip over the math.

The Serious Mathematics of Digital Animation

For SIAM News:

While computer simulations have a wide range of uses, their goals are generally similar: find the simplest model that recreates the properties of the system under investigation. For scientific systems, this involves matching observed or experimental phenomena as precisely as necessary.

But what about movie simulations? Should they match the processes they replicate so closely? Computer-generated imagery (CGI) is a common feature in both animated and live-action films. For these CGI systems, creating visuals that look right is an important task. However, Joseph Teran of the University of California, Los Angeles believes that starting from physical models is still a good idea.

During his invited address at the 2018 SIAM Annual Meeting, held in Portland, Ore., this July, Teran pointed out that beginning with a mathematical system is often easier than drawing from real life. Many movies model a system’s various forces and internal structures with partial differential equations (PDEs) for this reason. While solving these equations to produce CGI is computationally expensive, such methods have become powerful tools for creating realistic visual cinematic effects.

[Read the rest at SIAM News]

The knotty problem of DNA tangling

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

This article is a little different from the fare you’re used to getting from me: it’s for SIAM News, which is the magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While the article contains equations, I wrote it to be understandable even if you skip over the math.

I will also have you know, I only included one of the many knot-theory puns I came up with while writing the piece. Professionalism, people. Professionalism.

Untangling DNA with Knot Theory

For SIAM News:

Long before there were sailors, nature learned to tie—and untie—knots. Certain DNA types, proteins, magnetic fields, fluid vortices, and other diverse phenomena can manifest in the form of loops, which sometimes end up tangled. But knots, kinks, and tangles are often undesirable for the system in which they occur; for instance, knotted DNA can kill its cell. In such cases, nature finds ways to restore order.

Mariel Vazquez of the University of California, Davis, uses topology to understand the knotting and unknotting of real-world molecules. Specifically, she and her colleagues employ topological concepts from knot theory to demonstrate that cells detangle DNA with optimal efficiency.

During her talk at the 2018 SIAM Annual Meeting, held in Portland, Ore., this July, Vazquez emphasized her work’s multidisciplinary nature; although she focuses on DNA, her research has applications beyond molecular biology.

[Read the rest at SIAM News]

The math behind leopard spots and chemical waves

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

This article is a little different from the fare you’re used to getting from me: it’s for SIAM News, which is the glossy magazine for members of the Society for Industrial and Applied Mathematics (SIAM). The audience for this magazine, in other words, is professional mathematicians and related researchers working in a wide variety of fields. While the article contains equations, I wrote it to be understandable even if you skip over the math.

Leopard Spots, Frog Eggs, and the Spectrum of Nonlinear Diffusion Processes

For SIAM News:

Stripes, spots, or a mix of both appear on the skin of many animals — from tigers to beetles to whale sharks. These patterns are typically unique to individual creatures, and biologists often use them for identification. While distinct patterns may seem random, they obey certain rules that suggest a common underlying description. Striping and spotting occur in many unrelated species, implying that both evolutionary advantages and simple biochemical mechanisms drive such patterns.

As Björn Sandstede of Brown University noted during his invited address at the 2018 SIAM Annual Meeting, held in Portland, Ore., this July, similar patterns appear in certain chemical reactions and granular material under vibration. Nonlinear reactions and diffusion describe biological and non-biological patterns, producing stable concentrations in this space.

Alan Turing—best known for his work in computer science and cryptography—first made the mathematical connection between nonlinear diffusion processes and animal stripes in the 1950s. Many researchers have applied the resulting model to demonstrate how various species get their spots and describe nonlinear waves in chemical reactions.

[Read the rest at SIAM News]

A black hole in a bathtub and other analog experiments

[ This blog is dedicated to tracking my most recent publications. Subscribe to the feed to keep up with all the science stories I write! ]

Studying impossible systems with analogues

How do you study a phenomenon that cannot be replicated on Earth? You study one that has nothing to do with it, but looks incredibly similar mathematically.

For Physics World:

Some experiments simply can’t be done. It’s a hard truth that physicists learn to face at an early stage in their careers. Some phenomena we want to study require conditions that are out of reach with our current techniques and technologies.

This is especially true when physicists make predictions about the very early universe. Theories hypothesize, for example, that certain particles may have been created during this high-energy period, but our colliders are just not powerful enough to replicate those conditions, which means we cannot create the particles ourselves. The physics that exists only in or around black holes poses a similar problem. Since these massive objects are very far away (the closest known is thousands of light-years distant) and would require hitherto unfeasible amounts of energy to make in the lab, we’re not able to test our theories about them.

[Read the rest at Physics World]