MY BOOK CHAPTER! The architecture of Fermilab

I’m a science writer by profession (obviously), but occasionally I get the chance to write about something fun that’s only tangentially related to science. A while back, Belt Publishers — which publishes books and a magazine about the part of the American Midwest known as the Rust Belt — solicited pitches for chapters on a book about Midwestern architecture, and I sent them (shhh) a portion of my book I couldn’t get published. Belt liked what I sent them, and the result is I have a chapter in the forthcoming anthology Midwestern Architectural Journeys (edited by Zach Mortice), available October 15, 2019!

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When Brilliant Physicists Toiled Under a Beer-Can Roof

The inspired and eccentric design of a hub of Cold War physics research, the Fermi National Accelerator Lab in Illinois

One thing I didn’t have space to write about: one of the physicists who led an experiment at Fermilab was neighbor to New Yorker cartoonist George Booth. Their friendship led to Booth designing a mascot for the experiment, which ultimately wasn’t used, but still graces the outside of one of the buildings. [Credit: moi]

Chapter excerpt published by CityLab:

I didn’t come to the prosaically named Silicon Detector building for its roof. I was there to look at some cutting-edge telescope technology, soon to be implemented at one of the world’s leading observatories. But here I was looking up at the interior of a funky squashed geodesic dome, constructed of triangles in muted reds, blues, and golds, like an electron micrograph of a virus built of stained glass by Buckminster Fuller.

The Silicon Detector (or SiDet) building itself is a squat concrete structure with sloping sides and a trapezoidal profile, a distinctly 1970s structure. The geometric dome originally was intended to be a patriotic red, white, and blue, but time has faded it into autumnal colors. The panels are made out of recycled beer and soda cans with their ends cut off, arranged between two sheets of colored plastic reinforced with glass. Light shines through the cans, but not so brightly as to create a glare.

The SiDet building is all the more striking for what and where it is: It’s a physics lab devoted to the fabrication of next-generation detectors for experiments and telescopes. More specifically, SiDet was originally part of a facility meant to study neutrinos: very fast-moving, low-mass particles that are notoriously hard to detect. Similarly, the facility itself is hidden from the general public’s view behind a security perimeter on the grounds of the Fermi National Accelerator Laboratory, more commonly known as Fermilab.

[Read the rest at Citylab, and order the book from Belt]

Protecting privacy with mathematics

The linked 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.

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

Using Differential Privacy to Protect the United States Census

Census data must simultaneously be publicly available and protect the privacy of the people it describes. Differential privacy is a method that injects noise into the data to hide the presence of individual responses, while preserving the general statistical structure of the data. [Credit: moi, which is why I’m not a professional graphic artist]

For SIAM News:

In 2006, Netflix hosted a competition to improve its algorithm for providing movie recommendations to customers based on their past choices. The DVD rental and video streaming service shared anonymized rental records from real subscribers, assuming that their efforts to remove identifying information sufficiently protected user identities. This assumption was wrong; external researchers quickly proved that they could pinpoint personal details by correlating other public data with the Netflix database, potentially exposing private information.

This fatal flaw in the Netflix Prize challenge highlights multiple issues concerning privacy in the information age, including the simultaneous need to perform statistical analyses while protecting the identities of people in the dataset. Merely hiding personal data is not enough, so many statisticians are turning to differential privacy. This method allows researchers to extract useful aggregate information from data while preserving the privacy of individuals within the sample.

“Even though researchers are just trying to learn facts about the world, their analyses might incidentally reveal sensitive information about particular people in their datasets,” Aaron Roth, a statistician at the University of Pennsylvania, said. “Differential privacy is a mathematical constraint you impose on an algorithm for performing
data analysis that provides a formal guarantee of privacy.”

[read the rest at SIAM News…]

Gaining time for brain cancer patients with mathematics

The linked 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.

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

Mathematical Modeling Gains Days for Brain Cancer Patients

For SIAM News:

Glioblastoma, or glioblastoma multiforme, is a particularly aggressive and almost invariably fatal type of brain cancer. It is infamous for causing the deaths of U.S. Senators John McCain and Ted Kennedy, as well as former U.S. Vice President Joe Biden’s son Beau. Though glioblastoma is the second-most common type of brain tumor—affecting roughly three out of every 100,000 people—medicine has struggled to find effective remedies; the U.S. Food and Drug Administration has approved only four drugs and one device to counter the condition in 30 years of research. The median survival rate is less than two years, and only about five percent of all patients survive five years beyond the initial diagnosis.

Given these terrible odds, medical researchers strive for anything that can extend the effectiveness of treatment. The nature of glioblastoma itself is responsible for many obstacles; brain tumors are difficult to monitor noninvasively, making it challenging for physicians to determine the adequacy of a particular course of therapy.

Figure 1. Magnetic resonance imaging scan of the brain. Public domain image.
Kristin Rae Swanson and her colleagues at the Mayo Clinic believe that mathematical models can help improve patient outcomes. Using magnetic resonance imaging (MRI) data for calibration, they constructed the proliferation-invasion (PI) model — a simple deterministic equation to estimate how cancer cells divide and spread throughout the brain. Rather than pinpoint every cell’s location, the model aims to categorize the general behavior of each patient’s cancer to guide individualized treatment.

[Read the rest at SIAM News]

You won’t be traveling by quantum teleportation

[ 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 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]

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]