"Forecasting Elections Using Compartmental Models of Infection"

One of my particularly exciting papers just came out in final form. Here are some details (and a convenient tweet for you to spread it on social media).

Title: Forecasting Elections Using Compartmental Models of Infection

Authors: Alexandria Volkening, Daniel F. Linder, Mason A. Porter, and Grzegorz A. Rempala

Abstract: Forecasting elections---a challenging, high-stakes problem---is the subject of much uncertainty, subjectivity, and media scrutiny. To shed light on this process, we develop a method for forecasting elections from the perspective of dynamical systems. Our model borrows ideas from epidemiology, and we use polling data from United States elections to determine its parameters. Surprisingly, our model performs as well as popular forecasters for the 2012 and 2016 U.S. presidential, senatorial, and gubernatorial races. Although contagion and voting dynamics differ, our work suggests a valuable approach for elucidating how elections are related across states. It also illustrates the effect of accounting for uncertainty in different ways, provides an example of data-driven forecasting using dynamical systems, and suggests avenues for future research on political elections. We conclude with our forecasts for the senatorial and gubernatorial races on 6 November 2018 (which we posted on 5 November 2018).

The published version of our paper on forecasting elections using dynamical systems (with compartmental models of infection) is now live: https://t.co/t2IXPBiXSG

On my webpage: https://t.co/YVfya7jbjy

2020 election forecasts: https://t.co/UQ9MXqAJLh

[cc @al_volkening] pic.twitter.com/CKBbrzt8Vj

— Mason Porter (@masonporter) October 28, 2020

2020* World Champion Los Angeles Dodgers!!!

The Los Angeles Dodgers have won the World Series! 

 Of course, the whole year gets an asterisk (not just the Baseball season). 

 I have been waiting for 32 years, but under the dumpster-fire circumstances of everything, I am much less excited than I would normally be. I'm still very happy about it, but the excitement is less than it would be in normal times. Still, it's great! 

 Let's do this again next year when I can enjoy it more! 

There was some late-breaking news right after the game, and it turns out that Justin Turner was removed from today's game because of a positive COVID-19 test. 

So far, I have received two congratulatory e-mails from undergraduate students of mine and one from a friend. Corey Seager is the World Series; he was also the NLCS MVP. 

Clayton Kershaw has exorcised his demons a bit, and he now has more strikeouts than any other pitcher in postseason history. Obviously, he has benefited from playoffs with many more rounds than used to be the case. 

I need to get a plush COVID-19 with a Dodger cap.

"Songs and Lyrics by Tom Lehrer"

Here's some great news!

Tom Lehrer has released, into the public domain, the lyrics of his songs (also including sheet music for some), including many that you've probably never heard of!!!

There are also alternative lyrics for several songs.

Go here: https://t.co/VKtRztNu1Q

— Mason Porter (@masonporter) October 19, 2020

The Dodgers are Heading to the World Series! (2020 Edition)

The Dodgers have come from behind from a deficit of 3 games to 1 to defeat the Atlanta Braves in game 7 of the National League Championship Series. We're heading to the World Series! 

(It hasn't been announced yet as I write this, but I assume that Corey Seager is going to be named the Most Valuable Player of the NLCS.)

Update: As expected, Seager has been named the MVP.

"Stochastic Block Models are a Discrete Surface Tension"

A paper of mine that was published in advanced access in spring 2019 has finally received its final journal coordinates, so I am blogging about it now (even though it is old news). Here are some details.

  

Title: Stochastic Block Models are a Discrete Surface Tension

Authors: Zachary M. Boyd, Mason A. Porter, and Andrea L. Bertozzi 

Abstract: Networks, which represent agents and interactions between them, arise in myriad applications throughout the sciences, engineering, and even the humanities. To understand large-scale structure in a network, a common task is to cluster a network’s nodes into sets called “communities,” such that there are dense connections within communities but sparse connections between them. A popular and statistically principled method to perform such clustering is to use a family of generative models known as stochastic block models (SBMs). In this paper, we show that maximum-likelihood estimation in an SBM is a network analog of a well-known continuum surface-tension problem that arises from an application in metallurgy. To illustrate the utility of this relationship, we implement network analogs of three surface-tension algorithms, with which we successfully recover planted community structure in synthetic networks and which yield fascinating insights on empirical networks that we construct from hyperspectral videos.

"The Multiplex Nature of Global Financial Contagions"

Our new article came out today. Here are some details.

Title: "The multiplex nature of global financial contagions"

Authors: R. Maria del Rio-Chanona, Yevgeniya Korniyenko, Manasa Patnam, and Mason A. Porter

Abstract: As illustrated by the 2008 global financial crisis, the financial distress of one country can trigger financial distress in other countries. We examine the problem of identifying such “systemically important” countries (i.e., countries whose financial distress can trigger further distress), which is important for assessing global financial stability. Using data on bilateral financial positions that are split by asset type, we build a multiplex global financial network in which nodes represent countries, edges encode cross-country financial assets of various types, and layers represent asset types. We examine the temporal evolution of a measure of node importance known as MultiRank centrality, and we find that several major European countries decrease in rank and that several major Asian countries increase in rank since 2008. We then develop a multiplex threshold model of financial contagions in which a shock can propagate either within a layer or between layers. We find that the number of systemically important countries can be twice as large when we take into account the heterogeneity of financial exposures (i.e., when using a multiplex network) than in a contagion on an associated aggregate global financial network (i.e., on a monolayer network), as is often examined in other studies. We also study the extent to which buffers can reduce the propagation of financial distress. Our analysis suggests that accounting for both intralayer and interlayer propagation of contagions in a multiplex structure of financial assets is important for understanding interconnected financial systems of countries.

RIP Joe Morgan (1943–2020)

The baseball world has lost another great one. Second baseman Joe Morgan died today. We have lost a lot of Hall of Famers in the past few weeks (most recently Whitey Ford, before today).

Dodgers Advance to the National League Championship Series!

The Dodgers have just finished sweeping the San Diego Padres in their National League Division Series matchup and are heading to the National League Championship Series, where they will face (and hopefully defeat) the Atlanta Braves.

Some Notable American Physical Society Spring 2021 Prizes

The American Physical Society (APS) has announced its Spring 2021 prizes. It includes some awards to some great people in topics of interest to me. Here are ones that I want to highlight.

2021 Dannie Heineman Prize for Mathematical Physics

Joel L. Lebowitz, Rutgers University

For seminal contributions to nonequilibrium and equilibrium statistical mechanics, in particular, studies of large deviations in nonequilibrium steady states and rigorous analysis of Gibbs equilibrium ensembles.

2021 Leo P. Kadanoff Prize

Sidney Redner, Santa Fe Institute

For leadership in transcending traditional disciplinary boundaries by applying and advancing deep concepts and methods of statistical physics to gain novel insights into diverse real-world phenomena.

2021 Lars Onsager Prize

Lev P. Pitaevskii, INO-CNR BEC Center, University of Trento; Kapitza Institute for Physical Problems, Russian Academy of Sciences

For originating the Gross-Pitaevskii theory of non-uniform Bose-Einstein condensates and subsequent extensive contributions to the theory of quantum fluids, especially as applied to ultracold atomic gases.

2021 Early Career Award for Soft Matter Research

Eleni Katifori, University of Pennsylvania

For the seminal use of physical principles in understanding living transport networks.

2020 Nobel Prize in Physics

The 2020 Nobel Prize in Physics was announced today.

The first thing that I noticed was that my Mathematical Institute (Unversity of Oxford) colleague Roger Penrose got half the prize. Additionally, Andrea Ghez from UCLA's physics department shared the other half of the prize with Reinhard Genzel. Ghez also got a Ph.D. from Caltech in 1992, so several of my institutions (and my former home department at Oxford!) did very well today. Congratulations!

Here is the terse citation: 

The Royal Swedish Academy of Sciences has decided to award the Nobel Prize in Physics 2020 with one half to Roger Penrose "for the discovery that black hole formation is a robust prediction of the general theory of relativity" and and the other half jointly to Reinhard Genzel and Andrea Ghez "for the discovery of a supermassive compact object at the centre of our galaxy".

Some other websites to look at are the popular blurb and more advanced information from the Nobel page. Additionally, here are UCLA's press release and a blurb from University of Oxford's Mathematical Institute.

RIP Bob Gibson (1935–2020)

Baseball has lost yet another immortal. Hall of Fame pitcher Bob Gibson died today at the age of 84. (Tip of the cap to Gregg Schneider.)

Dodgers Advance to the Division Series!

Clayton Kershaw had his most dominant performance of 2020, advancing the Dodgers over the Brewers in their "Wild Card Series". This advances us to a Division Series against the winner of the Cardinals–Padres series. The Padres are a more dangerous team, but they're also a more interesting one, so I hope that we play them.