One of Baseball's all-time legends — both in terms of on-field performance (Wow!) and in terms of the many awesome stories — has left us. Inner-circle Hall of Famer Rickey Henderson has died.
You can read about his career, his personality, and a couple of his unreachable Major League records in this article. This article has a collection of 25 great stories (most of them true), and this article has a collect of 10 great instances of Rickey talking about Rickey in the third person. (There is some overlap in the stories in these two collections.)
As Tom Verducci wrote in 2003, "There are certain figures in American history who have passed into the realm of cultural mythology, as if reality could no longer contain their stories: Johnny Appleseed. Wild Bill Hickok. Davy Crockett. Rickey Henderson. They exist on the sometimes narrow margin between Fact and Fiction."
Rest in peace, Rickey.
My name is Mason Porter. I am a Professor in the Department of Mathematics at UCLA. Previously I was Professor of Nonlinear and Complex Systems in the Mathematical Institute at University of Oxford. I was also a Tutorial Fellow of Somerville College.
Saturday, December 21, 2024
Monday, December 16, 2024
What Happens in Vancouver Stays in Vancouver (2024 Edition)
I'm going to Vancouver to visit friends!
Wednesday, December 11, 2024
What Happens in Cambridge (Massachusetts) Stays in Cambridge (Massachusetts)
I am flying out to Boston to give a System Dynamics seminar at MIT.
Sunday, December 08, 2024
Dick Allen and Dave Parker Elected to the Baseball Hall of Fame
Dick Allen and Dave Parker have been elected to the baseball Hall of Fame. I strongly support Dick Allen's election (which is long overdue), but I don't think that Parker should be in the Hall of Fame. (In my view, he belongs instead to the Hall of Very Good.)
Of the people on this particular Veterans Committee ballot (though the name "Veterans Committee" was retired many years ago), I was most enthusiastic about Dick Allen's candidacy. I also think that Luis Tiant, Vic Harris, and Ken Boyer belong in the Hall of Fame. Jay Jaffe has written excellent summaries of the careers and Cooperstown (i.e., Hall of Fame) cases of the people on the ballot.
Of the people on this particular Veterans Committee ballot (though the name "Veterans Committee" was retired many years ago), I was most enthusiastic about Dick Allen's candidacy. I also think that Luis Tiant, Vic Harris, and Ken Boyer belong in the Hall of Fame. Jay Jaffe has written excellent summaries of the careers and Cooperstown (i.e., Hall of Fame) cases of the people on the ballot.
Tuesday, December 03, 2024
"Dynamical Importance and Network Perturbations"
One of my papers was just published in final form. Here are some details.
Title: Dynamical Importance and Network Perturbations
Authors: Ethan Young and Mason A. Porter
Abstract: The leading eigenvalue λ of the adjacency matrix of a graph exerts much influence on the behavior of dynamical processes on that graph. It is thus relevant to relate notions of importance of network structures to λ and its associated eigenvectors. We study a previously derived measure of edge importance known as “dynamical importance,” which estimates how much λ changes when one removes an edge from a graph or adds an edge to it. We examine the accuracy of this estimate for several undirected network structures and compare it to the relative change in λ after an edge removal or edge addition. We then derive a first-order approximation of the change in the leading eigenvector. We also consider the effects of edge additions on Kuramoto dynamics on networks, and we express the Kuramoto order parameter in terms of dynamical importance. Through our analysis and computational experiments, we find that studying dynamical importance can improve understanding of the relationship between network perturbations and dynamical processes on networks.
Title: Dynamical Importance and Network Perturbations
Authors: Ethan Young and Mason A. Porter
Abstract: The leading eigenvalue λ of the adjacency matrix of a graph exerts much influence on the behavior of dynamical processes on that graph. It is thus relevant to relate notions of importance of network structures to λ and its associated eigenvectors. We study a previously derived measure of edge importance known as “dynamical importance,” which estimates how much λ changes when one removes an edge from a graph or adds an edge to it. We examine the accuracy of this estimate for several undirected network structures and compare it to the relative change in λ after an edge removal or edge addition. We then derive a first-order approximation of the change in the leading eigenvector. We also consider the effects of edge additions on Kuramoto dynamics on networks, and we express the Kuramoto order parameter in terms of dynamical importance. Through our analysis and computational experiments, we find that studying dynamical importance can improve understanding of the relationship between network perturbations and dynamical processes on networks.
Wednesday, November 27, 2024
What Happens in San Juan Capistrano Stays in San Juan Capistrano (2024 Edition)
I am in San Juan Capistrano gaming and hanging out with friends for the long weekend.
Thursday, November 21, 2024
2024 Most Valuable Player (MVP) Awards
Major League Baseball has announced the winners of the 2024 Most Valuable Player (MVP) awards. See this page for the complete distribution of votes.
Aaron Judge of the New York Yankees was the unanimous MVP in the American League, with Bobby Witt Jr. of the Kansas City Royal receiving all 2nd-place voters. (I believe that the latter has never happened before.) The American League also had several other very strong candidates in an exceptional field. In the National League, Shohei Ohtani of the Los Angeles Dodgers was the unanimous MVP. This was his third unanimous MVP. Nobody else in Major League Baseball history has won multiple MVP awards unanimously.
Aaron Judge of the New York Yankees was the unanimous MVP in the American League, with Bobby Witt Jr. of the Kansas City Royal receiving all 2nd-place voters. (I believe that the latter has never happened before.) The American League also had several other very strong candidates in an exceptional field. In the National League, Shohei Ohtani of the Los Angeles Dodgers was the unanimous MVP. This was his third unanimous MVP. Nobody else in Major League Baseball history has won multiple MVP awards unanimously.
Wednesday, November 20, 2024
2024 Cy Young Awards
Baseball's 2024 Cy Young awards were announced today. Chris Sale of the Atlanta Braves won in the National League, and Tarik Skubal was a unanimous winner in the American League.
Tuesday, November 19, 2024
2024 Baseball Managers of the Year
The 2024 Managers of the Year in Major League Baseball are Stephen Vogt of the Cleveland Guardians and Pat Murphy of the Milwaukee Brewers.
Monday, November 18, 2024
2024 Baseball Rookies of the Year
The 2024 Rookies of the Year were announced today. Paul Skenes of the Pirates was the winner of an exceptionally strong rookie class (beating out the two Jacksons) in the National League, and Luis Gil of the Yankees was the winner (barely winning over Colton Cowser of the Orioles) of a much weaker rookie class in the American League.
Thursday, November 14, 2024
Various Major League Baseball Awards
Various Major League Baseball awards were announced today. These awards include the Comeback Players of the Year — which were Garrett Crochet in the American League and Chris Sale in he National League — and several others.
The more significant awards — Most Valuable Player, Cy Young award, Rookie of the Year, and Manager of the Year — will be announced next week. The three finalists for each award in each league were announced recently.
The more significant awards — Most Valuable Player, Cy Young award, Rookie of the Year, and Manager of the Year — will be announced next week. The three finalists for each award in each league were announced recently.
Tuesday, November 12, 2024
2024 Silver Slugger Awards
Major League Baseball has announced its 2024 Silver Slugger Awards. You'll noticed a few Dodgers among the awardees. :)
Friday, November 08, 2024
"Oscillatory Networks: Insights from Piecewise-Linear Modeling"
Another of my papers just appeared in final form. Here are some details.
Title: Oscillatory Networks: Insights from Piecewise-Linear Modeling
Authors: Stephen Coombes, Mustafa Şayli, Rüdiger Thul, Rachel Nicks, Mason A. Porter, and Yi Ming Lai
Dedication: We dedicate this paper to the memory of our dear friend and colleague Yi Ming Lai. Although he began with us on the journey to write this paper, which in part reviews some of his research activity in recent years, sadly he did not end that journey with us. RIP Yi Ming Lai 1988–2022.
Abstract: There is enormous interest—both mathematically and in diverse applications—in understanding the dynamics of coupled-oscillator networks. The real-world motivation of such networks arises from studies of the brain, the heart, ecology, and more. It is common to describe the rich emergent behavior in these systems in terms of complex patterns of network activity that reflect both the connectivity and the nonlinear dynamics of the network components. Such behavior is often organized around phase-locked periodic states and their instabilities. However, the explicit calculation of periodic orbits in nonlinear systems (even in low dimensions) is notoriously hard, so network-level insights often require the numerical construction of some underlying periodic component. In this paper, we review powerful techniques for studying coupled-oscillator networks. We discuss phase reductions, phase–amplitude reductions, and the master stability function for smooth dynamical systems. We then focus, in particular, on the augmentation of these methods to analyze piecewise-linear systems, for which one can readily construct periodic orbits. This yields useful insights into network behavior, but the cost is that one needs to study nonsmooth dynamical systems. The study of nonsmooth systems is well developed when focusing on the interacting units (i.e., at the node level) of a system, and we give a detailed presentation of how to use saltation operators, which can treat the propagation of perturbations through switching manifolds, to understand dynamics and bifurcations at the network level. We illustrate this merger of tools and techniques from network science and nonsmooth dynamical systems with applications to neural systems, cardiac systems, networks of electromechanical oscillators, and cooperation in cattle herds.
Title: Oscillatory Networks: Insights from Piecewise-Linear Modeling
Authors: Stephen Coombes, Mustafa Şayli, Rüdiger Thul, Rachel Nicks, Mason A. Porter, and Yi Ming Lai
Dedication: We dedicate this paper to the memory of our dear friend and colleague Yi Ming Lai. Although he began with us on the journey to write this paper, which in part reviews some of his research activity in recent years, sadly he did not end that journey with us. RIP Yi Ming Lai 1988–2022.
Abstract: There is enormous interest—both mathematically and in diverse applications—in understanding the dynamics of coupled-oscillator networks. The real-world motivation of such networks arises from studies of the brain, the heart, ecology, and more. It is common to describe the rich emergent behavior in these systems in terms of complex patterns of network activity that reflect both the connectivity and the nonlinear dynamics of the network components. Such behavior is often organized around phase-locked periodic states and their instabilities. However, the explicit calculation of periodic orbits in nonlinear systems (even in low dimensions) is notoriously hard, so network-level insights often require the numerical construction of some underlying periodic component. In this paper, we review powerful techniques for studying coupled-oscillator networks. We discuss phase reductions, phase–amplitude reductions, and the master stability function for smooth dynamical systems. We then focus, in particular, on the augmentation of these methods to analyze piecewise-linear systems, for which one can readily construct periodic orbits. This yields useful insights into network behavior, but the cost is that one needs to study nonsmooth dynamical systems. The study of nonsmooth systems is well developed when focusing on the interacting units (i.e., at the node level) of a system, and we give a detailed presentation of how to use saltation operators, which can treat the propagation of perturbations through switching manifolds, to understand dynamics and bifurcations at the network level. We illustrate this merger of tools and techniques from network science and nonsmooth dynamical systems with applications to neural systems, cardiac systems, networks of electromechanical oscillators, and cooperation in cattle herds.
Sunday, November 03, 2024
Saturday, November 02, 2024
What Happens in Seoul Stays in Seoul (2024 Edition)
I am off to Seoul to speak in a workshop on Theoretical Challenges in Network Science! I really enjoy visiting Seoul, and I am very happy to have another chance to visit.
Wednesday, October 30, 2024
Dodgers Win the 2024 World Series!!!!
The Dodgers have won the 2024 World Series!
Today was the 5th game of the series. The 5-run deficit that the Dodgers overcame is the largest comeback to win a clinching game in World Series history. Walker Buehler came into the 9th inning to get the save two innings after he started game 3. (Gerrit Cole of the Yankees threw more than 100 pitches today. He's the first pitcher to do that in the World Series in either 21 or 27 World Series games. The broadcasters indicated the number in the 6th inning, but I forgot which one it is.) Here is the game's box score.
Obviously, Freddie Freeman was named the series MVP.
Mookie Betts is now the only active player with 3 World Series rings.
I was very happy when the Dodgers won in 2020, but that season has a giant asterisk, and I have been able to enjoy things much more with this year's World Series championship in a proper season.
Thankfully, now that the World Series is over, I won't have to see any more of these damn political commercials anymore this year. Sweet relief.
Today was the 5th game of the series. The 5-run deficit that the Dodgers overcame is the largest comeback to win a clinching game in World Series history. Walker Buehler came into the 9th inning to get the save two innings after he started game 3. (Gerrit Cole of the Yankees threw more than 100 pitches today. He's the first pitcher to do that in the World Series in either 21 or 27 World Series games. The broadcasters indicated the number in the 6th inning, but I forgot which one it is.) Here is the game's box score.
Obviously, Freddie Freeman was named the series MVP.
Mookie Betts is now the only active player with 3 World Series rings.
I was very happy when the Dodgers won in 2020, but that season has a giant asterisk, and I have been able to enjoy things much more with this year's World Series championship in a proper season.
Thankfully, now that the World Series is over, I won't have to see any more of these damn political commercials anymore this year. Sweet relief.
Thursday, October 24, 2024
"Using Mathematics to Study how People Influence Each Other’s Opinions"
Our article for teenagers and preteens about mathematical modeling of opinion dynamics has just been published in final form. Here are some details.
Title: Using Mathematics to Study how People Influence Each Other’s Opinions
Authors: Grace J. Li, Jiajie (Jerry) Luo, Kaiyan Peng, and Mason A. Porter
Abstract: People sometimes change their opinions when they discuss things with each other. Researchers can use mathematics to study opinion changes in simplifications of real-life situations. These simplified scenarios, which are examples of mathematical models, help researchers explore how people influence each other through their social interactions. In today’s digital world, these models can help us learn how to promote the spread of accurate information and reduce the spread of inaccurate information. In this article, we discuss a simple mathematical model of opinion changes that arise from social interactions. We briefly describe what opinion models can tell us and how researchers try to make them more realistic.
Title: Using Mathematics to Study how People Influence Each Other’s Opinions
Authors: Grace J. Li, Jiajie (Jerry) Luo, Kaiyan Peng, and Mason A. Porter
Abstract: People sometimes change their opinions when they discuss things with each other. Researchers can use mathematics to study opinion changes in simplifications of real-life situations. These simplified scenarios, which are examples of mathematical models, help researchers explore how people influence each other through their social interactions. In today’s digital world, these models can help us learn how to promote the spread of accurate information and reduce the spread of inaccurate information. In this article, we discuss a simple mathematical model of opinion changes that arise from social interactions. We briefly describe what opinion models can tell us and how researchers try to make them more realistic.
Tuesday, October 22, 2024
RIP Fernando Valenzuela (1960–2024)
Dodger great Fernando Valenzuela died today. I knew that he was really sick and he seemed to be in trouble, but of course I was hoping that he would pull through. Fernando is one of those players that will always be synonymous with the Dodgers, and I was very pleased when the Dodgers finally officially (and belatedly) retired his uniform number in 2023.
You can read more about Fernando Valenzuela on Wikipedia page.
Update: Here is ESPN's article about Valenzuela's death.
Update (10/24/24): I'll add a bit more detail.
For baseball in Los Angeles, Fernando Valenzuela is a legend.
Among other things, he changed the entire fan base of the Dodger organization. He is an absolutely pivotal figure in the history of the Dodgers.
On the performance side, he of course had an incredible beginning and an amazing peak. He started the All Star Game as a rookie, and he's the only player to win the Rookie of the Year and Cy Young Award in the same year. He's also the last MLB player with 20+ complete games in one season.
Update (10/26/24): Here is an obituary article by Jay Jaffe.
You can read more about Fernando Valenzuela on Wikipedia page.
Update: Here is ESPN's article about Valenzuela's death.
Update (10/24/24): I'll add a bit more detail.
For baseball in Los Angeles, Fernando Valenzuela is a legend.
Among other things, he changed the entire fan base of the Dodger organization. He is an absolutely pivotal figure in the history of the Dodgers.
On the performance side, he of course had an incredible beginning and an amazing peak. He started the All Star Game as a rookie, and he's the only player to win the Rookie of the Year and Cy Young Award in the same year. He's also the last MLB player with 20+ complete games in one season.
Update (10/26/24): Here is an obituary article by Jay Jaffe.
Monday, October 21, 2024
What Happens in Atlanta Stays in Atlanta (2024 Edition)
I am heading to Atlanta for the first time since DragonCon 2013. I will be attending the 2024 SIAM Conference on Mathematics of Data Science (MDS), and it even takes place in one of the Dragon*Con hotels. :)
Sunday, October 20, 2024
The Dodgers are Going to the World Series!!!
The Dodgers beat the Mets in the 6th game of the National League Championship Series (NLCS), and we're now off to the World Series to face the Yankees!
This is the 12th time that Dodgers and the Yankees (our traditional rivals) are facing each other in the World Series, though it's the first time since 1981.
The Dodgers scored a record number (46) of runs for an NLCS (and the second-highest total for any league championship series), and — I think, if I understood the broadcast correctly — Shohei Ohtani reached base a record number of times for a postseason series.
The NLCS most valuable player (MVP) is Tommy Edman.
This is the 12th time that Dodgers and the Yankees (our traditional rivals) are facing each other in the World Series, though it's the first time since 1981.
The Dodgers scored a record number (46) of runs for an NLCS (and the second-highest total for any league championship series), and — I think, if I understood the broadcast correctly — Shohei Ohtani reached base a record number of times for a postseason series.
The NLCS most valuable player (MVP) is Tommy Edman.
Friday, October 11, 2024
Dodgers Advance to the National League Championship Series!
After being on the brink of elimination, the Dodgers beat the Padres 2–0 to advance to the National League Championship Series!!!! We were down 2 games to 1, and we won the next two games to get past the Padres.
There was one home run from Kiké Hernández, and then later there was one home run from Teoscar Hernández. Therefore, it was also Hernández 2, Padres 0.
We'll be facing the Mets in a rematch of the 1988 NLCS.
There was one home run from Kiké Hernández, and then later there was one home run from Teoscar Hernández. Therefore, it was also Hernández 2, Padres 0.
We'll be facing the Mets in a rematch of the 1988 NLCS.
Wednesday, October 09, 2024
What Happens in Boston Stays in Boston
I'm on my way to Boston for the workshop to celebrate David Campbell's 80th birthday! It will surely be chaotic. :)
Tuesday, October 08, 2024
2024 Nobel Prize in Physics Awarded for Applications of Statistical Physics to Machine Learning!
The 2024 Nobel Prize in Physics has been awarded to physicist John Hopfield and computer scientist Geoffrey Hinton.
The official prize citation is "for foundational discoveries and inventions that enable machine learning with artificial neural networks". However, I strongly prefer the phrasing along the lines of "for the statistical-physics basis of neural networks", which is how mathematical physicist Barry Simon described it.
Here is the information, press release, and other materials from The Nobel Foundation.
Naturally, I am strongly in favor of more Nobel Prizes being awarded for foundational interdisciplinary work, as that is the world in which I live. Unsurprisingly, many traditional physicists are arguing against and doing their common practice of staking territorial claim (as we also often see on the job market and in other arenas). This is an old battle, and we can look forward to a later phase when somebody gets a physics Nobel Prize for work in networks. That said, I am grateful to see people arguing about science, rather than about other ideological things!
The official prize citation is "for foundational discoveries and inventions that enable machine learning with artificial neural networks". However, I strongly prefer the phrasing along the lines of "for the statistical-physics basis of neural networks", which is how mathematical physicist Barry Simon described it.
Here is the information, press release, and other materials from The Nobel Foundation.
Naturally, I am strongly in favor of more Nobel Prizes being awarded for foundational interdisciplinary work, as that is the world in which I live. Unsurprisingly, many traditional physicists are arguing against and doing their common practice of staking territorial claim (as we also often see on the job market and in other arenas). This is an old battle, and we can look forward to a later phase when somebody gets a physics Nobel Prize for work in networks. That said, I am grateful to see people arguing about science, rather than about other ideological things!
Friday, September 20, 2024
"Adapting InfoMap to Absorbing Random Walks Using Absorption-Scaled Graphs"
One of my papers just came out in final published form. Here are some details.
Title: Adapting InfoMap to Absorbing Random Walks Using Absorption-Scaled Graphs
Authors: Esteban Vargas Bernal, Mason A. Porter, and Joseph H. Tien
Abstract: InfoMap is a popular approach to detect densely connected "communities" of nodes in networks. To detect such communities, InfoMap uses random walks and ideas from information theory. Motivated by the dynamics of disease spread on networks, whose nodes can have heterogeneous disease-removal rates, we adapt InfoMap to absorbing random walks. To do this, we use absorption-scaled graphs (in which edge weights are scaled according to absorption rates) and Markov time sweeping. One of our adaptations of InfoMap converges to the standard version of InfoMap in the limit in which the node-absorption rates approach 0. We demonstrate that the community structure that one obtains using our adaptations of InfoMap can differ markedly from the community structure that one detects using methods that do not account for node-absorption rates. We also illustrate that the community structure that is induced by heterogeneous absorption rates can have important implications for susceptible–infected–recovered (SIR) dynamics on ring-lattice networks. For example, in some situations, the outbreak duration is maximized when a moderate number of nodes have large node-absorption rates.
Title: Adapting InfoMap to Absorbing Random Walks Using Absorption-Scaled Graphs
Authors: Esteban Vargas Bernal, Mason A. Porter, and Joseph H. Tien
Abstract: InfoMap is a popular approach to detect densely connected "communities" of nodes in networks. To detect such communities, InfoMap uses random walks and ideas from information theory. Motivated by the dynamics of disease spread on networks, whose nodes can have heterogeneous disease-removal rates, we adapt InfoMap to absorbing random walks. To do this, we use absorption-scaled graphs (in which edge weights are scaled according to absorption rates) and Markov time sweeping. One of our adaptations of InfoMap converges to the standard version of InfoMap in the limit in which the node-absorption rates approach 0. We demonstrate that the community structure that one obtains using our adaptations of InfoMap can differ markedly from the community structure that one detects using methods that do not account for node-absorption rates. We also illustrate that the community structure that is induced by heterogeneous absorption rates can have important implications for susceptible–infected–recovered (SIR) dynamics on ring-lattice networks. For example, in some situations, the outbreak duration is maximized when a moderate number of nodes have large node-absorption rates.
Thursday, September 19, 2024
Shohei Ohtani Joins the 50/50 Club (and Has One of the Best Single-Game Performances in Baseball History)
Shoehei Ohtani makes a habit of doing things that none of us have ever seen before.
During today's game, he became the inaugural member of the "50/50 Club", as he now has both 50+ home runs and 50+ stolen bases this year. No member of the 50-home-run club had ever stolen even as many as 30 bases before.
He also joined the club in spectular fashion today with a game for the ages. Ohtani's performance today was one of the best single-game performances in Major League Baseball history. He went 6 for 6 with 2 doubles, 3 home runs, 10 runs batted in, 4 runs, and 2 stolen bases. There have been only 16 games in Baseball history in which a player has 10+ RBIs; this is the first one by a Dodger. This is the first time in Baseball history that a player has had 3+ home runs and 2+ stolen bases in the same game.
Since the RBI became an official statistic in 1920, Shohei Ohtani is now the only player in Baseball history who has a game — any game, so they each can occur in different games — in their career with 10+ RBIs, 6+ hits, 5+ extra-base hits, 3+ HRs, and 2+ SBs. Any game. Ohtani did them all in the same game. Amazing!
I have never seen any game like this in my life before.
(P.S. The Dodgers clinched a playoff berth with their victory today.)
During today's game, he became the inaugural member of the "50/50 Club", as he now has both 50+ home runs and 50+ stolen bases this year. No member of the 50-home-run club had ever stolen even as many as 30 bases before.
He also joined the club in spectular fashion today with a game for the ages. Ohtani's performance today was one of the best single-game performances in Major League Baseball history. He went 6 for 6 with 2 doubles, 3 home runs, 10 runs batted in, 4 runs, and 2 stolen bases. There have been only 16 games in Baseball history in which a player has 10+ RBIs; this is the first one by a Dodger. This is the first time in Baseball history that a player has had 3+ home runs and 2+ stolen bases in the same game.
Since the RBI became an official statistic in 1920, Shohei Ohtani is now the only player in Baseball history who has a game — any game, so they each can occur in different games — in their career with 10+ RBIs, 6+ hits, 5+ extra-base hits, 3+ HRs, and 2+ SBs. Any game. Ohtani did them all in the same game. Amazing!
I have never seen any game like this in my life before.
(P.S. The Dodgers clinched a playoff berth with their victory today.)
Thursday, September 12, 2024
2024 Ig Nobel Prizes
The 2024 Ig Nobel Prizes were awarded in a ceremony this evening.
There are so many great ones this year that it's hard to pick my favorites.
There are so many great ones this year that it's hard to pick my favorites.
Tuesday, September 10, 2024
What Happens in Ann Arbor Stays in Ann Arbor
I am off to Ann Arbor, Michigan. I'll be visiting University of Michigan to give a colloquium in their Department of Computational Medicine & Bioinformatics.
Sunday, August 18, 2024
What Happens in Los Alamos Stays in Los Alamos
I am heading over to Los Alamos for a networks workshop.
That's right. I'll be spending a few days in the wild, wild West.
That's right. I'll be spending a few days in the wild, wild West.
Friday, August 16, 2024
"Persistent Homology for Resource Coverage: A Case Study of Access to Polling Sites"
One of my paper was published in final form last week. Here are some details.
Title: Persistent Homology for Resource Coverage: A Case Study of Access to Polling Sites
Authors: Abigail Hickok, Benjamin Jarman, Michael Johnson, Jiajie Luo, and Mason A. Porter
Abstract: It is important to choose the geographical distributions of public resources in a fair and equitable manner. However, it is complicated to quantify the equity of such a distribution; important factors include distances to resource sites, availability of transportation, and ease of travel. We use persistent homology, which is a tool from topological data analysis, to study the availability and coverage of polling sites. The information from persistent homology allows us to infer holes in a distribution of polling sites. We analyze and compare the coverage of polling sites in Los Angeles County and five cities (Atlanta, Chicago, Jacksonville, New York City, and Salt Lake City), and we conclude that computation of persistent homology appears to be a reasonable approach to analyzing resource coverage.
Title: Persistent Homology for Resource Coverage: A Case Study of Access to Polling Sites
Authors: Abigail Hickok, Benjamin Jarman, Michael Johnson, Jiajie Luo, and Mason A. Porter
Abstract: It is important to choose the geographical distributions of public resources in a fair and equitable manner. However, it is complicated to quantify the equity of such a distribution; important factors include distances to resource sites, availability of transportation, and ease of travel. We use persistent homology, which is a tool from topological data analysis, to study the availability and coverage of polling sites. The information from persistent homology allows us to infer holes in a distribution of polling sites. We analyze and compare the coverage of polling sites in Los Angeles County and five cities (Atlanta, Chicago, Jacksonville, New York City, and Salt Lake City), and we conclude that computation of persistent homology appears to be a reasonable approach to analyzing resource coverage.
Wednesday, August 07, 2024
What Happens in Glasgow Stays in Glasgow
I am off to Glasgow for the 2024 World Science-Fiction Convention (i.e., WorldCon). I am involved in a talk and some panels.
Wednesday, July 17, 2024
Saturday, July 13, 2024
What Happens in Oxford Stays in Oxford
I am off to Oxford to spend most of the next few weeks. I'll also have a short embedded trip to Frankfurt and will be heading to Glasgow after my time in Oxford.
Thursday, July 11, 2024
RIP Barry Wellman (1942–2024)
I'm very sad to hear about sociologist Barry Wellman's death.
He was one of the people who welcomed me warmly to the Sunbelt community (though he did make a point to inform me, with much spittle flying in the process, of course, that the Dodgers shouldn't have left Brooklyn).
I figured (but never officially knew) that Barry had been sick for a while, given his sudden lack of activity starting a couple of years ago on Facebook and SOCnet after always making a point of stressing that the point of such social gathering spaces (including social media) was to be very active, so he always purposely did that.
(h/t through the SOCnet mailing list)
He was one of the people who welcomed me warmly to the Sunbelt community (though he did make a point to inform me, with much spittle flying in the process, of course, that the Dodgers shouldn't have left Brooklyn).
I figured (but never officially knew) that Barry had been sick for a while, given his sudden lack of activity starting a couple of years ago on Facebook and SOCnet after always making a point of stressing that the point of such social gathering spaces (including social media) was to be very active, so he always purposely did that.
(h/t through the SOCnet mailing list)
Friday, June 28, 2024
RIP Martin Mull (1943–2024)
Comedic actor, musician, and painter Martin Mull dies yesterday.
I found out about him via the song "Dueling Tubas", which I first learned about in Physics 2a through an acoustics demo by now-Nobel Laureate David Politzer.
My musically-inclined classmates were in emotional pain.
I found out about him via the song "Dueling Tubas", which I first learned about in Physics 2a through an acoustics demo by now-Nobel Laureate David Politzer.
My musically-inclined classmates were in emotional pain.
Tuesday, June 18, 2024
RIP Willie Mays (1931–2024)
The legendary Willie Mays died today. Mays was the oldest living baseball Hall of Famer; he took the mantle in 2021 when Tommy Lasorda died. You can see Willie Mays' statistics on this page.
I believe that Luis Aparicio is now the oldest living baseball Hall of Famer.
I believe that Luis Aparicio is now the oldest living baseball Hall of Famer.
Friday, June 14, 2024
"Emergence of Polarization in a Sigmoidal Bounded-Confidence Model of Opinion Dynamics"
A paper of mine was just published in final form. Here are zome details.
Title: Emergence of Polarization in a Sigmoidal Bounded-Confidence Model of Opinion Dynamics
Authors: Heather Z. Brooks, Philip S. Chodrow, and Mason A. Porter
Abstract: We study a nonlinear bounded-confidence model (BCM) of continuous-time opinion dynamics on networks with both persuadable individuals and zealots. The model is parameterized by a nonnegative scalar \gamma, which controls the steepness of a smooth influence function. This influence function encodes the relative weights that individuals place on the opinions of other individuals. When \gamma = 0, this influence function recovers Taylor's averaging model; when \gamma \rightarrow \infty, the influence function converges to that of a modified Hegselmann--Krause (HK) BCM. Unlike the classical HK model, however, our sigmoidal bounded-confidence model (SBCM) is smooth for any finite \gamma. We show that the set of steady states of our SBCM is qualitatively similar to that of the Taylor model when \gamma is small and that the set of steady states approaches a subset of the set of steady states of a modified HK model as \gamma \rightarrow \infty. For certain special graph topologies, we give analytical descriptions of important features of the space of steady states. A notable result is a closed-form relationship between graph topology and the stability of polarized states in a simple special case that models echo chambers in social networks. Because the influence function of our BCM is smooth, we are able to study it with linear stability analysis, which is difficult to employ with the usual discontinuous influence functions in BCMs.
Title: Emergence of Polarization in a Sigmoidal Bounded-Confidence Model of Opinion Dynamics
Authors: Heather Z. Brooks, Philip S. Chodrow, and Mason A. Porter
Abstract: We study a nonlinear bounded-confidence model (BCM) of continuous-time opinion dynamics on networks with both persuadable individuals and zealots. The model is parameterized by a nonnegative scalar \gamma, which controls the steepness of a smooth influence function. This influence function encodes the relative weights that individuals place on the opinions of other individuals. When \gamma = 0, this influence function recovers Taylor's averaging model; when \gamma \rightarrow \infty, the influence function converges to that of a modified Hegselmann--Krause (HK) BCM. Unlike the classical HK model, however, our sigmoidal bounded-confidence model (SBCM) is smooth for any finite \gamma. We show that the set of steady states of our SBCM is qualitatively similar to that of the Taylor model when \gamma is small and that the set of steady states approaches a subset of the set of steady states of a modified HK model as \gamma \rightarrow \infty. For certain special graph topologies, we give analytical descriptions of important features of the space of steady states. A notable result is a closed-form relationship between graph topology and the stability of polarized states in a simple special case that models echo chambers in social networks. Because the influence function of our BCM is smooth, we are able to study it with linear stability analysis, which is difficult to employ with the usual discontinuous influence functions in BCMs.
Friday, May 31, 2024
What Happens in Warsaw Stays in Warsaw
I am heading to Warsaw to participate a couple of days in the WAW 2024 conference. This is my first trip to Poland in several years, and unfortunately it's going to be very brief.
Wednesday, May 22, 2024
"Inference of Interaction Kernels in Mean-Field Models of Opinion Dynamics"
A paper of mine just came out in final form. Here are some details about it.
Title: Inference of Interaction Kernels in Mean-Field Models of Opinion Dynamics
Authors: Weiqi Chu, Qin Li, and Mason A. Porter
Abstract: In models of opinion dynamics, many parameters — either in the form of constants or in the form of functions — play a critical role in describing, calibrating, and forecasting how opinions change with time. When examining a model of opinion dynamics, it is beneficial to infer its parameters using empirical data. In this paper, we study an example of such an inference problem. We consider a mean-field bounded-confidence model with an unknown interaction kernel between individuals. This interaction kernel encodes how individuals with different opinions interact and affect each other's opinions. Because it is often difficult to quantitatively measure opinions as empirical data from observations or experiments, we assume that the available data takes the form of partial observations of a cumulative distribution function of opinions. We prove that certain measurements guarantee a precise and unique inference of the interaction kernel and propose a numerical method to reconstruct an interaction kernel from a limited number of data points. Our numerical results suggest that the error of the inferred interaction kernel decays exponentially as we strategically enlarge the data set.
Title: Inference of Interaction Kernels in Mean-Field Models of Opinion Dynamics
Authors: Weiqi Chu, Qin Li, and Mason A. Porter
Abstract: In models of opinion dynamics, many parameters — either in the form of constants or in the form of functions — play a critical role in describing, calibrating, and forecasting how opinions change with time. When examining a model of opinion dynamics, it is beneficial to infer its parameters using empirical data. In this paper, we study an example of such an inference problem. We consider a mean-field bounded-confidence model with an unknown interaction kernel between individuals. This interaction kernel encodes how individuals with different opinions interact and affect each other's opinions. Because it is often difficult to quantitatively measure opinions as empirical data from observations or experiments, we assume that the available data takes the form of partial observations of a cumulative distribution function of opinions. We prove that certain measurements guarantee a precise and unique inference of the interaction kernel and propose a numerical method to reconstruct an interaction kernel from a limited number of data points. Our numerical results suggest that the error of the inferred interaction kernel decays exponentially as we strategically enlarge the data set.
Saturday, April 27, 2024
Shōgun (2024)
I just finished watching the 2024 Shōgun, which I enjoyed very much.
I read the book around December 1988 — followed over the next years of reading every single other Asia-saga novel that James Clavell wrote — during my elementary school's winter break. I was so captivated that that was basically all I did during that winter break. I was already a slow reader back then, and now I read much more slowly than I did back then. (I also don't have time to basically only read a book nonstop for a couple of weeks.) I was fascinated by the epic combined with the portrayal of how East and West saw each other through their interactions. This was the first book in my life that had ever captivated me that way, and I was really excited when I saw a poster for the new miniseries a few months ago.
The 2024 series did a great job of capturing that, and it was aspects of those interactions and contrasting views (and part of the scene of peeing in a garden to consummate an agreement, and I am pretty sure that I know which scene in the new tv series corresponds to that vignette) that really stood out to me. However, most of this runs together through all of Clavell's works, and I can't really separate Shōgun from the others. I had forgotten almost all of the plot, but from Wikipedia it seems that the new series adapted it very well.
I never watched the 1980 miniseries. There was a 1988 miniseries of Nobel House. I also never watched that one, but I did notice Shōgun and Tai-Pan (and knew that Nobel House was by the same author, and Tai-Pan also caught my eye because of the Apple II game of almost the same name that was inspired by the novel) on a bookshelf in my parents' house (nobody else in the household had read these epic books), so I picked up Shōgun, which became an important part of my own personal history, even though I forgot so much of it.
I suppose that a new Nobel House miniseries may be possible? That one, too, was a particularly awesome book. (I also enjoyed the others, although I gave up on Tai-Pan the first time and started over and read it only a couple of years after, because I could put up with the rougher writing of that earlier work with the thoughts of it as a prequel to Nobel House.)
I read the book around December 1988 — followed over the next years of reading every single other Asia-saga novel that James Clavell wrote — during my elementary school's winter break. I was so captivated that that was basically all I did during that winter break. I was already a slow reader back then, and now I read much more slowly than I did back then. (I also don't have time to basically only read a book nonstop for a couple of weeks.) I was fascinated by the epic combined with the portrayal of how East and West saw each other through their interactions. This was the first book in my life that had ever captivated me that way, and I was really excited when I saw a poster for the new miniseries a few months ago.
The 2024 series did a great job of capturing that, and it was aspects of those interactions and contrasting views (and part of the scene of peeing in a garden to consummate an agreement, and I am pretty sure that I know which scene in the new tv series corresponds to that vignette) that really stood out to me. However, most of this runs together through all of Clavell's works, and I can't really separate Shōgun from the others. I had forgotten almost all of the plot, but from Wikipedia it seems that the new series adapted it very well.
I never watched the 1980 miniseries. There was a 1988 miniseries of Nobel House. I also never watched that one, but I did notice Shōgun and Tai-Pan (and knew that Nobel House was by the same author, and Tai-Pan also caught my eye because of the Apple II game of almost the same name that was inspired by the novel) on a bookshelf in my parents' house (nobody else in the household had read these epic books), so I picked up Shōgun, which became an important part of my own personal history, even though I forgot so much of it.
I suppose that a new Nobel House miniseries may be possible? That one, too, was a particularly awesome book. (I also enjoyed the others, although I gave up on Tai-Pan the first time and started over and read it only a couple of years after, because I could put up with the rougher writing of that earlier work with the thoughts of it as a prequel to Nobel House.)
Friday, April 12, 2024
What Happens in San Francisco Stays in San Francisco (again)
I am heading to San Francisco for a cousin's wedding.
Thursday, April 11, 2024
RIP David Goodstein (1939–2024)
David Goodstein (an emeritus physics professor at Caltech) died yesterday. This is the end of an era.
I watched many of The Mechanical Universe videos in high school. The beginning and end of each video showed Goodstein lecturing to students in the big Caltech physics lecture hall. I had Goodstein for Physics 1a (mechanics) in fall of my frosh year in that same lecture hall, and I remember how surreal it felt. That was one of my big "Wow, I am now at Caltech." things. Also, I came out of lectures feeling that I understood the material — but then I tried the homework and saw that I didn't actually yet understand it.
(h/t Barry Simon)
I watched many of The Mechanical Universe videos in high school. The beginning and end of each video showed Goodstein lecturing to students in the big Caltech physics lecture hall. I had Goodstein for Physics 1a (mechanics) in fall of my frosh year in that same lecture hall, and I remember how surreal it felt. That was one of my big "Wow, I am now at Caltech." things. Also, I came out of lectures feeling that I understood the material — but then I tried the homework and saw that I didn't actually yet understand it.
(h/t Barry Simon)
Tuesday, March 26, 2024
What Happens in Hanover Stays in Hanover
I am heading to New Hampshire for the first time ever. I'll be in Hanover to give the mathematics colloquium at Dartmouth College.
Monday, March 18, 2024
What Happens in New York City Stays in New York City
I'm heading off to New York City for the first time in many years. I'll be giving a talk at The Rockefeller University.
Tuesday, February 27, 2024
"Complex Networks with Complex Weights"
The published version of one of my papers came out today. Its title is one of my favorites among all of the papers that I've ever written. Here are some details about the paper.
Title: Complex Networks with Complex Weights
Authors: Lucas Böttcher and Mason A. Porter
Abstract: In many studies, it is common to use binary (i.e., unweighted) edges to examine networks of entities that are either adjacent or not adjacent. Researchers have generalized such binary networks to incorporate edge weights, which allow one to encode node–node interactions with heterogeneous intensities or frequencies (e.g., in transportation networks, supply chains, and social networks). Most such studies have considered real-valued weights, despite the fact that networks with complex weights arise in fields as diverse as quantum information, quantum chemistry, electrodynamics, rheology, and machine learning. Many of the standard network-science approaches in the study of classical systems rely on the real-valued nature of edge weights, so it is necessary to generalize them if one seeks to use them to analyze networks with complex edge weights. In this paper, we examine how standard network-analysis methods fail to capture structural features of networks with complex edge weights. We then generalize several network measures to the complex domain and show that random-walk centralities provide a useful approach to examine node importances in networks with complex weights.
Title: Complex Networks with Complex Weights
Authors: Lucas Böttcher and Mason A. Porter
Abstract: In many studies, it is common to use binary (i.e., unweighted) edges to examine networks of entities that are either adjacent or not adjacent. Researchers have generalized such binary networks to incorporate edge weights, which allow one to encode node–node interactions with heterogeneous intensities or frequencies (e.g., in transportation networks, supply chains, and social networks). Most such studies have considered real-valued weights, despite the fact that networks with complex weights arise in fields as diverse as quantum information, quantum chemistry, electrodynamics, rheology, and machine learning. Many of the standard network-science approaches in the study of classical systems rely on the real-valued nature of edge weights, so it is necessary to generalize them if one seeks to use them to analyze networks with complex edge weights. In this paper, we examine how standard network-analysis methods fail to capture structural features of networks with complex edge weights. We then generalize several network measures to the complex domain and show that random-walk centralities provide a useful approach to examine node importances in networks with complex weights.
Tuesday, January 23, 2024
Adrián Beltré, Todd Helton, and Joe Mauer Elected to Baseball Hall of Fame!
Adrián Beltré, Todd Helton, and Joe Mauer have been elected to the Major Legaue Baseball Hall of Fame! I knew that Mauer would make the Hall of Fame eventually, but he far surpassed my prediction for how he was going to do this year. I am pleasantly surprised to see him make the Hall on the first ballot, as I thought that he would need to wait a year or two to be elected. Adrián Beltré obviously sailed into the Hall on the first ballot.
Billy Wagner, who was named on 73.8% of the ballots, missed election to the Hall by only 5 votes. He'll make it in 2025, which is his 10th and final year on the writers' ballot. Gary Sheffield was named on 63.9% of the ballots in his final year on the writers' ballot. His Hall case is now in the hands of the various small commitees, and I think (and hope) that he'll make it eventually. Andruw Jones had a small gain to 61.6% and Carlos Beltrán made a sizeable gain to 57.1%. Beltrán has an outside shot to be elected in 2025, but I think that 2026 is more likely. Andruw Jones could also ultimately make it through the writers' ballot, but I think that Beltrán will surpass Jones in the vote total in 2025. One way or another, they'll both eventually make the Hall of Fame. Chase Utley got 28.8% of the vote in his debut on the ballot. He did much better in the public ballots than in the private ones. I do think that Utley will eventually make it, but it's going to be a long road for the more sabermetrically-minded folks to convince others that Utley belongs in the Hall of Fame.
In December, a small committee elected former manager Jim Leyland to the Hall of Fame.
As usual, I have been following the ballot tracker very closely these past couple of months.
A discussion of a few ESPN.com writers of this year's biggest winners and biggest losers, as well as an outlook on the 2025 ballot.
Of the players who can debut on the writers' ballot in 2025, the only plausible Hall of Fame candidates are Ichiro Suzuki and C.C. Sabathia. Ichiro will sail into the Hall of Fame in his ballot debut (and hopefully he'll be elected unanimously, but I am not holding my breath). Sabathia will eventually make it, but I think that it's going to take a few years (say, 4 years).
Update (which I forgot to include in the original text of this post): My prediction for the 2025 balloting is that Ichiro Suzuki and Billy Wagner will be the two players elected. I think that Carlos Beltrán will get around 70% of the vote next year and that Andruw Jones will be in the mid 60s (perhaps around 66%). I think that Chase Utley will probably end up at about 35%. Utley's candidacy appears to be the latest battle in the considerations of old-school versus new-school voters.
Update: Jay Jaffe has written a rundown of the results of this year's writers' ballot.
Update (1/24/24): Here is Jay Jaffe's candidate-by-candidate dissection of this year's writers' ballot.
Update (1/29/24): Here is Jay Jaffe's five-year forecast of Hall of Fame balloting.
Billy Wagner, who was named on 73.8% of the ballots, missed election to the Hall by only 5 votes. He'll make it in 2025, which is his 10th and final year on the writers' ballot. Gary Sheffield was named on 63.9% of the ballots in his final year on the writers' ballot. His Hall case is now in the hands of the various small commitees, and I think (and hope) that he'll make it eventually. Andruw Jones had a small gain to 61.6% and Carlos Beltrán made a sizeable gain to 57.1%. Beltrán has an outside shot to be elected in 2025, but I think that 2026 is more likely. Andruw Jones could also ultimately make it through the writers' ballot, but I think that Beltrán will surpass Jones in the vote total in 2025. One way or another, they'll both eventually make the Hall of Fame. Chase Utley got 28.8% of the vote in his debut on the ballot. He did much better in the public ballots than in the private ones. I do think that Utley will eventually make it, but it's going to be a long road for the more sabermetrically-minded folks to convince others that Utley belongs in the Hall of Fame.
In December, a small committee elected former manager Jim Leyland to the Hall of Fame.
As usual, I have been following the ballot tracker very closely these past couple of months.
A discussion of a few ESPN.com writers of this year's biggest winners and biggest losers, as well as an outlook on the 2025 ballot.
Of the players who can debut on the writers' ballot in 2025, the only plausible Hall of Fame candidates are Ichiro Suzuki and C.C. Sabathia. Ichiro will sail into the Hall of Fame in his ballot debut (and hopefully he'll be elected unanimously, but I am not holding my breath). Sabathia will eventually make it, but I think that it's going to take a few years (say, 4 years).
Update (which I forgot to include in the original text of this post): My prediction for the 2025 balloting is that Ichiro Suzuki and Billy Wagner will be the two players elected. I think that Carlos Beltrán will get around 70% of the vote next year and that Andruw Jones will be in the mid 60s (perhaps around 66%). I think that Chase Utley will probably end up at about 35%. Utley's candidacy appears to be the latest battle in the considerations of old-school versus new-school voters.
Update: Jay Jaffe has written a rundown of the results of this year's writers' ballot.
Update (1/24/24): Here is Jay Jaffe's candidate-by-candidate dissection of this year's writers' ballot.
Update (1/29/24): Here is Jay Jaffe's five-year forecast of Hall of Fame balloting.
Thursday, January 04, 2024
"Learning Low-Rank Latent Mesoscale Structures in Networks"
One of my papers came out in final form today. Here are some details.
Title: Learning Low-Rank Latent Mesoscale Structures in Networks
Authors: Hanbaek Lyu, Yacoub H. Kureh, Joshua Vendrow, and Mason A. Porter
Abstract: Researchers in many fields use networks to represent interactions between entities in complex systems. To study the large-scale behavior of complex systems, it is useful to examine mesoscale structures in networks as building blocks that influence such behavior. In this paper, we present an approach to describe low-rank mesoscale structures in networks. We find that many real-world networks possess a small set of latent motifs that effectively approximate most subgraphs at a fixed mesoscale. Such low-rank mesoscale structures allow one to reconstruct networks by approximating subgraphs of a network using combinations of latent motifs. Employing subgraph sampling and nonnegative matrix factorization enables the discovery of these latent motifs. The ability to encode and reconstruct networks using a small set of latent motifs has many applications in network analysis, including network comparison, network denoising, and edge inference.
Title: Learning Low-Rank Latent Mesoscale Structures in Networks
Authors: Hanbaek Lyu, Yacoub H. Kureh, Joshua Vendrow, and Mason A. Porter
Abstract: Researchers in many fields use networks to represent interactions between entities in complex systems. To study the large-scale behavior of complex systems, it is useful to examine mesoscale structures in networks as building blocks that influence such behavior. In this paper, we present an approach to describe low-rank mesoscale structures in networks. We find that many real-world networks possess a small set of latent motifs that effectively approximate most subgraphs at a fixed mesoscale. Such low-rank mesoscale structures allow one to reconstruct networks by approximating subgraphs of a network using combinations of latent motifs. Employing subgraph sampling and nonnegative matrix factorization enables the discovery of these latent motifs. The ability to encode and reconstruct networks using a small set of latent motifs has many applications in network analysis, including network comparison, network denoising, and edge inference.