I’m thrilled to tell you all that I’m a candidate for the Chair line of the APS Forum for Early Career Scientists! This is a three year position consisting of one year each as chair elect, chair and past chair. I’ve serving as a member of the FECS Executive Committee for the past two years and I’m excited to be able to continue my service with FECS. If you’re a member of FECS, please vote for me! Polls close on November 20; you should have an email in your inbox now with the subject line “APS FECS Election”. I’ve included my bio and candidate statement below.
If you’re a member of APS and not a member of FECS, you should sign up! I don’t know if you would be able to vote, but it’s free and it’s a way to encourage APS to support postdocs other early career scientists (and to get support yourself)!
I’m thrilled to announce that my first single-author paper has just been published in Physical Review E:
Field-induced freezing in the unfrustrated Ising antiferromagnet
Physical Review E 102, 032112 (2020) [paywall]
[free PDF] [arXiv]
This paper is a continuation of the theme of my research career, which could be loosely described: “try adding a magnetic field to an antiferromagnet and see if something interesting happens.” In this case, I added a magnetic field to the classical 2D Ising antiferromagnet and studied it with the simplest implementation of Monte Carlo: the Metropolis(-Rosenbluth-Teller) algorithm. At low temperatures I found that simulations never reached the ground state. Instead, they get trapped in local energy minima from which they never escape: frozen states with finite magnetization. There are so many of these frozen states available that you are effectively guaranteed to cross one before you can reach the correct ground state. These frozen states can be described by simple rules based on stable local configurations.
I developed these notes and exercises as part of a tutorial on how to use the Kao Group’s computing cluster. Although some of the details are specific to this specific cluster, much of the material could be useful for anyone getting started in computational physics, so I thought I would share it here. The materials are posted on github.com/adazi/bootCampEx and the best place to start is by reading README.md
Friday was my last day as a postdoc at NTU. My next step isn’t another postdoc or even a faculty position; instead, I’ll be learning about public policy as a AAAS Science & Technology Policy Fellow (STPF)! My placement is in the Department of Energy, where I’ll be working on the diplomatic and legal arrangements that support international scientific collaboration.
I was flipping through the fourth edition Landau and Binder’s excellent book on Monte Carlo for statistical physics and I came across this gem on p. 139:
We end this chapter by summarizing a few procedures which in our experience can be useful for reducing errors and making simulations studies more effective. These thoughts are quite general and widely applicable. While these ‘rules’ provide no ‘money-back’ guarantee that the results will be correct, they do provide a prudent guideline of steps to follow.
(1) In the very beginning, think.
What problem do you really want to solve and what method and strategy is best suited to the study. You may not always choose the best approach to begin with, but a little thought may reduce the number of false starts.
(2) In the beginning think small.
Work with small lattices and short runs. This is useful for obtaining rapid turnaround of results and for checking the correctness of a program. This also allows us to search rather rapidly through a wide range of parameter space to determine ranges with physically interesting behavior.
(3) Test the random number generator.
Find some limiting cases where accurate, or exact values of certain properties can be calculated, and compare your results of your algorithm with different random number sequences and/or different random number generators.
(4) Look at systematic variations with system size and run length.
Use a wide range of sizes and run lengths and then use scaling forms to analyze data.
(5) Calculate error bars.
Search for and estimate both statistical and systematic errors. This enables both you and other researchers to evaluate the correctness of the conclusions which are drawn from the data.
(6) Make a few very long runs.
Do this to ensure that there is not some hidden time scale which is much longer than anticipated.
The discovery of nuclear weapons might be the most consequential discovery that physicists will ever make. If you disagree, you will certainly agree with my hope that this discovery does not become any more important. I believe physicists have a special responsibility to both understand the legacy of nuclear weapons and help society to prevent them from ever being used again.
Last September, I visited the Hiroshima Peace Memorial Museum, a deeply moving testament to the horrifying consequences of war. While I was there, I purchased this book. It’s short and excellent telling of the human impact of the bombing. I highly recommend it, especially for my fellow physicists.
Hiroshima by John Hersey
My Goodreads rating: 5 of 5 stars
“A short and beautiful book focusing on the human tragedy of people affected by the atomic bombing of Hiroshima and the lives they built in the aftermath.”
Today, June 10, 2020, scientists around the world are joining the #strike4BlackLives with #ShutdownSTEM. Both APS and AAAS have released statements condemning racism and have also announced their support for the strike.
I always look forward to the APS Office of Government Affairs’ monthly Signal Boost video. This month’s update was full of great stuff!