I have always had two great interests: computers and fundamental physics. As I progressed through my undergraduate studies, I couldn’t seem to fully commit to either path. I thought I’d be either a software-savvy physicist or a physics-savvy software developer. I obtained B.S. degrees in both Computer Engineering and Physics.
When I graduated, I felt I had a pretty good handle on understanding computers and software, but still needed to learn things in physics. So I went on to grad school to get a Ph.D. in experimental High Energy Physics (HEP), thus tipping onto the software-savvy physicist career path. I truly enjoyed learning and doing physics in grad school, but where I stood out was by writing a lot of data acquisition and analysis software that I used for my thesis research, which was searching for proton decay (which led to my online moniker). This included getting a grant of supercomputer time (remember Cray computers?) to use neural networks for pattern recognition, long before neural networks were the thing that they have become these days.
Right out of grad school I landed my dream job at the Superconducting Super Collider (SSC) near Dallas, writing analysis software for HEP and maintaining scientific computing libraries. In the usual life-cycle for physicists, a newly Ph.D.’ed physicist usually gets a post-doc position for about 4 years, which is like a very low paying residency for medical doctors. If you managed to do outstanding research during your post-doc, you might then land a permanent position at either a university or a national lab. But I managed to skip that phase and get a permanent job at a national lab right out of grad school, thanks to my software skills and a job opening at the SSC that seemed tailor-made for a software-savvy physicist.
But, the SSC was cancelled, and I felt that the future of HEP in the US was cancelled with it. I couldn’t see going back to doing a post-doc in a field that had just been shot dead. So I went to Plan B, which was to be a physics-savvy software developer instead. So I spent about 6 years getting a Ph.D. (I enjoyed grad school so much that I was in no hurry to graduate) that kept me employed in my chosen field for about 18 months.
It didn’t work out so badly for me, I ended up having a pretty rewarding career in software development. I was able to find jobs in software development where I could at least leverage the problem solving skills that I developed by doing physics, if not the actual physics that I learned.
My short career in physics proper left me disillusioned regarding how our society chooses to fund and support physics (or not), but no disillusionment concerning physics itself - it still fascinates me. I saved all my physics textbooks through the years, thinking that I’d like to get back into physics at some point. Well, that never really happened until retirement, when I dusted off those textbooks and dove into them again. It was like going back to college for me, but maybe during a summer session where I was only taking a couple of classes and wasn’t working all that hard at it. I optimistically started out with my quantum field theory books because I found that subject to be absolutely fascinating when I learned it in grad school, and I had some unrequited hunger to learn more of it. But I had forgotten so much physics that I wasn’t understanding what I was reading at all. I had to set aside quantum field theory and go back to review basic quantum mechanics, and then go even further back to review classical mechanics, calculus, and linear algebra before enough old brain cells came back online to get some traction. I am in the process of gradually working my way back up this call stack.
In future posts, I will detail how this is going, what tools and resources I use, and maybe spout some thoughts on learning in modern times.
