We had a baby last month. I am really, really into this baby.

Like, the baby is so good.

I am one of those people who is prone to over-thinking simple things. The last time I bought a backpack, it took me more than a year to decide on bag evaluation criteria, develop a personal theory of backpack aesthetics, understand the environmental and ethical implications of buying from this or that company … I guess what I’m saying is that I am a dweeb.

But so the point is: if my feelings about a dumb ol’ backpack are complex to the point of unmanageable, please try to imagine what my brain does when confronted with questions of parenthood.

I wanted to start capturing some of these feelings somehow. Newborn babies don’t tend to let you sleep, and sleep deprivation messes with your ability to form memories. I feel sure that I won’t remember most of my thoughts tomorrow, let alone next year. And it turns out that this is a slightly scary way to feel when it’s in relation to a tiny, beautiful, fragile human I helped to make. I’m worried I’ll forget the small details this experience that all feel so important when they happen.

I’ve taken so many photos that my phone has run out of storage space. I’ve done some writing to try and capture the very personal stuff I don’t intend to share with internet strangers (no offense). For the stuff in between, a webcomic currently seems like a good idea. I already type too much for work and for fun, so blogging doesn’t appeal for this job. I like to draw and want more excuses to do it … There you go.

Reading webcomics has been a part of my morning routine for years. I wanted to call out a couple artists whose work has inspired me towards doing my own thing:

• Kate Beaton is brilliant and everybody knows it. Her site is not currently updating, but she occasionally posts new stuff to twitter (@beatonna) that I am finding extremely relatable.
• Kevin Budnik (@knittedsweater) makes a journal comic that is sometimes sad and often really thoughtful and poetic.

Lastly: I’m really just doing this comic for myself. If you get something out of reading it, that would make me very happy. But I’m a busy person with a growing family and a fulfilling job. While I aspire to write and post comics regularly for my own sake, I think it’s not responsible to make promises about a posting schedule.

Now I’ll try and sleep, although I may just stare at baby pictures on my phone instead. Good night!

We’re starting a new research program and I’m excited to tell you about it!

Let’s start with the big picture, and then we’ll use subsequent posts to zoom in on the details. The big picture goes like this:

1. 95% of the mass-energy in the universe is a huge mystery. Everything we see around us — pizza, dinosaur bones, galactic clusters — is made of atoms. But as best we can tell, atoms account for only 5% of the mass-energy in the observable universe. The rest is a big mystery that we call dark matter and dark energy. It would be fair to say that physicists are very interested in sorting out the remaining 95%. Aren’t you? If your everyday senses only reveal 5% of the known universe, what are you missing out on?
2. Dark matter is very probably made of particles, and we think a great candidate is a particle called the axion. The axion is cool because it solves other problems in physics in addition to dark matter. (We’ll talk about it later, but you can skip ahead and look up the “strong CP problem” if you want.) You may not have heard of axions yet, but the scrabble game on my telephone sure has.
3. Axions are hard to detect. They’re a bit like neutrinos, in that they’re (probably) all around us but they hardly ever interact with normal matter. You detect them by converting them into photons and then looking for the photons. (Physicists are pretty good at counting photons; we’ve had a century of practice at it.) To further complicate matters, our theorists have narrowed down the axion mass to a window that spans three orders of magnitude. We have to design an axion search that is sensitive to potential masses (or equivalently, photon energies) between meV and μeV.
4. So: a metaphor. Imagine you’re driving down a desert highway in an old car and you want to listen to the radio. Since you’re way out in the middle of nowhere, the radio is mostly static. How do you find a station? You’d probably tune the radio dial a little bit, listen for a while to see if you could pick out any signal in the noise, tune the dial, listen, tune, and so on. Eventually, if you started to pick out some faint music in the static, you’d know you were getting close. Same for us! In fact, our colleagues have an experiment called the Dark Matter Radio. The key point here is distinguishing signal from noise.
5. Reduce, reduce, reduce the noise that competes with the signal. If you give me $100M for a 30-tesla magnet, I can give you a real strong, healthy axion signal. If you don’t have that kind of magnet money laying around, I’ll have to figure out some way to keep noise out of my experiment. One way to do this is to use quantum bits. I’ll get into this in a later post, but the technology we borrow from quantum information science gives us the ability to suppress experimental noise by four orders of magnitude. Not bad!

So there you go: the broad strokes for finding dark matter using quantum bits. Slowly but surely, we’ll take all those individual menu items above and expand on them in future posts. Exciting times!

Will I shock you, dear reader, if I tell you that physics has a gender problem? Women are underrepresented in physics at every career stratum. Whether you look at undergraduate students or faculty, it’s mostly dudes.

Since we’re talking about gender today, I’ll say right up front that with a few notable exceptions, lots of the data out there about STEM & gender assumes that there are only two genders. My nonbinary folks out there: we see you. Maybe one day the data will see you too.

Women make up about 50% of the population, so you don’t have to do much work to see how screwed up our ratios are. As of 2015, women made up 20% of all physics majors and only about 10% of all tenured physics faculty. You can look at other metrics and see the same story. Holman, Stuart-Fox, and Hauser just published a study in PLOS suggesting that at the rate we’re going, it will take 256 years before women in physics are published at parity with men.

There’s no shortage of work that tries to explain the sources of this imbalance, and the forefront of this research is an interesting place to watch. If you want to understand a complex problem though, it’s a good move to break it up into little sub-problems. So some folks study the role that family care plays in this imbalance, or overt sexism in the workplace. Today’s post is about gender bias in STEM hiring. A few meetings ago, our Inclusivity Journal Club read and discussed “Science faculty’s subtle gender biases favor male students” by Moss-Racusin et al. Here’s a link to the article and the supplemental material.

The authors put together a job application package for a fictional aspiring lab manager and sent it to 127 physics, biology, and chemistry professors. These application packages were all identical, except that for half of them the candidate was named John, and for half of them the candidate was named Jennifer. The professors were asked to rate the competence and hireability of this fictional candidate, to rate their own willingness to mentor this candidate, and to propose a starting salary for the position.
I bet you can guess what happened!

What happened was that the male version of this candidate was rated significantly better across all metrics, and the average proposed starting salary for male candidates was about $4k higher. Maybe a little more surprising: this bias towards male applicants was about the same, regardless of the gender of the person doing the evaluation.

This study gets a lot of play in the popular science press, and for good reason. It’s hard to do a double-blind study on gender bias! Or bias of any kind, really. It’s an interesting exercise to try and design a study like this in your head. Would you just give someone a survey asking whether they’re biased?

Since lots of people have written about this paper already, I’ll focus on our group’s reaction. I noticed the mood of the room move through a couple distinct phases; maybe you’ll recognize those phases in yourself when you read the paper, too. We started off feeling collectively angry and disappointed on behalf of all women scientists. Then, I’m not sure what motivated this, but the mood shifted and we all took turns being very critical. And then once that subsided, there was a self-reflective phase where we all did a little personal growth.

First phase: Sexism is stupid and dumb, and the paper shows its effects to you pretty clearly, with easy-to-understand graphs. It’s no wonder we started off feeling angry.

Next phase: the knives came out. Once we had a handle on the basics of the paper, we started picking at it in the way that physicists are famous and famously mocked for doing. Put more charitably, critical engagement is an important intellectual step and some nerds regard it as a way of showing respect. Our critical engagement looked kind of like this:

• The physicists in the room, used to using terabyte-scale data sets for high-energy collider analysis, were all a little scandalized that this study relied on so few data points. Only 127 respondents? To us, that seemed like too small a number to do anything really cool. (Our social scientist pal convinced us it was ok.)
  
• We took turns noticing that 78% of the respondents were male, and 81% were White. Did this further skew the results? Or is this just “the way it is” in the sciences, making the study actually more representative?
  
• In the real world, lots of hiring gets done by committees, in part to help reduce the effects of individual bias. How would the results change if, instead of individual professors doing this rating, it was done by groups?
  
• We all had a hard time understanding how these results would translate into actual hiring outcomes. (Maybe you can tell that we started asking quite a lot from this one little five-page paper.)
  
• Why weren’t the respondents given any open-ended questions?
  
• How would the results change if the fictional applicant was going for a tenure-track job? Would prospective long-term colleagues be evaluated differently from low-level, more transient positions?
  
• It would have been interesting to see how geography influenced responses. For example, $25k per year goes a lot farther in St. Louis than it does in San Francisco. Tying the proposed salary to local cost-of-living would have been a neat addition with maybe some explanatory power.

So we went through the phases of appreciating and then being critical of the paper. After we’d gotten all that “critical engagement” out of our systems, we got a little self-aware. Physicists’ papers are built around very specific, narrow arguments. Why should we expect anything different from sociologists? Maybe this paper is not iron-clad proof of pan-institutional sexism, but why should we expect it to be? Moss-Racusin et al. asked a very narrow question, and gave us a very specific answer. That’s why the study is compelling.

There’s even scholarship on the way people react to papers about bias. It’s fascinating! The argument goes like this: Objectivity is a culturally desirable trait in STEM. Studies that discuss bias are very triggering for a particular kind of person who enjoys thinking of themselves as an ice-cold rational scholar. Such people (men more often than women) tend to work extra-hard to trash studies about bias in STEM. Were we all collectively doing this?

Real talk: I caught myself getting a little mentally defensive during this discussion. “I would do better than these other respondents. I’m much more aware of my own biases.” That kind of defensive thinking is part of the problem. So this is one of the reasons I ended up liking this paper so much. I learned something about bias in STEM and about they way social scientists roll, sure. But I also got pushed into being a little more self-aware. Not bad for an hour’s work, huh?

Stay tuned as I get caught up on these blog posts! Next up: Devine et al.‘s “Long-term reduction in implicit race bias: A prejudice habit-breaking intervention”.

Larry Phillips is one of the most interesting people I have ever met. I consider him a role model, and I learned today that we lost him to cancer. He was my PhD advisor.

Larry was and is well-regarded in the field of particle accelerator technology. I worked with him on problems related to thin-film superconductivity for accelerating cavities, but he was one of those smart, versatile people who ends up getting involved in all sorts of fun problems. You’ll find that he’s made contributions to the design of cryomodules, RF windows, electropolishing of niobium accelerator components, plasma surface treatments, … it’s a long list. He also had an encyclopedic knowledge of how to actually get things built. He “played against type” that way; he could keep up with condensed matter theorists, metallurgists, machinists, and grad students. In recent years he had gotten involved in the design of accelerator-driven nuclear reactors, and novel methods for detecting dark matter.

This diversity of interests and competence is maybe not surprising if you know anything about his life. Larry lived in New York in the 60s, partying with bohemians and working as a motorcycle courier. He blew glass professionally; he got his PhD working with Hans Meissner (son of Walther Meissner, who discovered the eponymous Meissner effect); he lived on a sailboat for a while; he not only designed his own house, but the construction methods used to build it; he was a devoted husband and father; and he was an excellent mentor for young physicists.

This is the part of the essay where I talk about gratitude. Larry took me on as a student at a time when I was feeling very unsure about myself, academically. I couldn’t have been luckier, in retrospect. He was always available when I needed support, and he also seemed to know when I needed to be left alone to sort things out for myself.

He went out of his way to make opportunities for me. There were the kinds of things you’d expect from a PhD advisor, like professional networking or experimental support. But he also made sure I didn’t graduate without learning how to weld, braze, run the hydraulic press, and how to talk to a machinist. (You’d be surprised how many scientists are not good at this.) And he set an example for me and all the people in our group with his positive attitude. He was always getting enthusiastic for new projects, and declaring that they would be fun. (He would also declare that new projects would be “easy”, but we all knew that when he said “easy” he meant “probably not impossible”.) I had a great time with him.

If you have never been a graduate student, you might not see this last statement as an appropriately big deal. Some of my grad school pals had advisors who worked them like dogs, or completely ignored them, or (in a few terrible cases) were outright emotionally abusive. This sort of thing is unfortunately not uncommon. And while I could never claim that the process of graduating wasn’t stressful, I came out of it feeling like a “real” scientist, with an appreciation for the state of my field and the ways I might contribute to it. I came out feeling positive and ready to go.

That’s why I’m talking about gratitude right now. It’s hard to overstate the enormity of the gift that Larry gave me. And not just me. We threw a surprise party for his 80th birthday just a few months ago, and the crowd there was full of people who will tell you the same things I’ve been telling you now.

Thanks, Larry, from all of us.

Let’s start with some numbers. According to the International Coffee Organization, the USA bought enough coffee beans in 2014 to brew something like 100 billion cups of coffee. That’s roughly one cup of coffee per day for every single US resident. Including babies. Coffee is everywhere, all the time.

So here’s a perfectly reasonable question: is coffee good for you? Humans have been drinking coffee for at least 600 years — plenty of time to come up with an answer.

The answer is a resounding “maybe”. Consider:

• A 1985 article in the New York Times suggested that 5 or more cups a day increases risk of heart disease. Specifically, it described a study which concluded that drinking that much coffee will triple the risk of heart disease, relative to people who drink none. (Coffee bad.)
• A 2012 article in the New England Journal of Medicine reported a correlation between increased coffee consumption and a decrease in “all-cause mortality” rates, essentially a measure of the likelihood of death. (Coffee good!)
• A 2013 study by the Mayo Clinic concluded that 4 cups per day increases the likelihood of all-cause mortality. (Coffee bad.) They recommend that young people limit their consumption of coffee to less than 4 cups per day.
• A 2014 study in The Annals of Internal Medicine concluded that “Regular coffee consumption was not associated with an increased mortality rate in either men or women. The possibility of a modest benefit of coffee consumption on all-cause and CVD mortality needs to be further investigated.” (Coffee good?)

I could go on. And on. And on. There’s an overwhelming supply of studies that will support either side of this argument. We haven’t even started talking about coffee’s effect on specific medical conditions; there are studies out there addressing coffee’s effect on the incidence and/or severity of Parkinson’s, liver disease, diabetes, Alzheimer’s, anemia, depression, dementia, athletic performance …

Superficially, this is bonkers. Coffee is everywhere. If you are not currently drinking coffee, you probably could be five minutes from now if you put your mind to it. I’m writing this post while sitting in a coffee shop. How can we still have so much uncertainty about something so ubiquitous?

The answer is typically science-y, of course. Coffee’s effect on the human body is complex because the human body is complex. These confusing and contradictory experimental results can motivate scientists to seek deeper, more complete answers to difficult questions. In the case of coffee, some very recent work suggests that your genes determine whether “coffee good” or “coffee bad”. Brave readers with lots of free time might want to stick around for the epilogue.

Anyway, I assert that coffee is hard to understand, despite its ubiquity. Do you know what else is ubiquitous and hard to understand?

Did you just yell “NEUTRINOS!” at the top of your lungs? Yeah, that’s the answer I was going for.

Subatomic particles, generally, are so, so far outside our everyday experience as human beings. Chances are, you’ve never had any reason to care about muons in your daily life. The subject just doesn’t come up, right? What about cosmic ray flux? Or neutrino oscillation rates? Not as often as you drink coffee, amirite?

So here you are, minding your own business, when a physicist starts blogging at you about neutrinos. They’re all around you, he says. Trillions of them pass through your body every second, he says. What are you supposed to do with that? To be blunt, how are you supposed to believe something so far outside your daily experience, when you don’t even know whether “coffee bad”?

Here, I don’t mean “believe” in the sense of truth vs. lies. I mean, how can you know that your body is permeated by neutrinos in the same way you know that gravity pulls you down to Earth, or that snow is made of frozen water, or that Daniel is handsome? You have direct, personal experience, through your senses, that these things are true. There are no intermediate steps. You don’t have to consult a scientific instrument to know that things fall down — you can feel the pull of gravity and you can see its effects on everything around you. Likewise, you don’t need to read a book in a library to know that coffee tastes amazing at 8 am.

But are your senses the only reliable source of truth? Are you skeptical about neutrinos because you can’t see them? You haven’t seen live dinosaurs either, and your day-to-day experience suggests that the Earth is flat, not round. Maybe you should limit your appreciation of truth to what you can sense for yourself.

More than two thousand years ago, the ancient Greeks kicked that idea right in its butt. This is a long discussion and I can’t do it justice in an already-long blog post. Essentially, your perception can change depending on circumstances. For example, maybe a fig tastes sweet to you. But if you eat honey before you eat figs, maybe those figs won’t seem so sweet anymore. What can you say that you know (like, really really know) about the taste of figs?

Your perceptions can be unreliable. Just think about the last time you got hangry. You skipped breakfast, maybe, and then right around 11 am the world started to suck, right? The line at the coffee shop started to seem unreasonably long, or the barista’s haircut seemed unreasonably annoying, or the guy behind you in line was talking unreasonably loud on his phone. In that moment, are you really perceiving an objective reality? Do you have well-deserved, righteous indignation about the barista’s haircut? Maybe you should get a muffin with that coffee.

Our senses, by themselves, are not the sole arbiters of truth. They are vital, beautiful, and useful, but they are not the whole story. Humans reach for truth in ways besides immediate sensory experience. One of those ways is called science. We have built tools and systems of thought in order to help us reliably, repeatably demonstrate complex and obscure phenomena.

Leon Lederman is a Nobel laureate, a former director of Fermilab, and the co-author of a truly enjoyable book with an admittedly silly name: The God Particle: If the Universe is the Answer, What Is the Question? (1993, Bantam Press). Here’s a particularly relevant excerpt. (Note for young people: TVs used to be bulky vacuum tubes with electron beams inside.)

The lady in the audience was stubborn. “Have you ever seen an atom?” she insisted.  … My attempts to answer this thorny question always begin with trying to generalize the word “see”. Do you “see” this page if you are wearing glasses? … If you are reading the text on a computer screen? Finally, in desperation, I ask, “Have you ever seen the pope?”

“Well, of course,” is the usual response. “I saw him on television.” Oh, really? What she saw was an electron beam striking phosphorous painted on the inside of a glass screen. My evidence for the atom, or the quark, is just as good.

Sometimes, you need to reach for truth through a pair of glasses. Or a television. Or a particle accelerator.

I’ll be talking about these ideas in more depth on December 6th at an event called Ask A Scientist. It should be fun! Hope to see you there.

Epilogue for Sticklers

For those of you still reading, I should admit to being a little glib for rhetorical reasons. As I said before, the human body is an incredibly complex system. To pose a binary question about whether coffee is categorically good or bad is to be ridiculously reductive.

Sometimes, the questions worth asking have complex answers. The questions we ask should allow for answers complex enough to be correct. As they say on Twitter, you should want better for yourself.
Arguments about all-cause mortality are statistical in nature and difficult to apply to a specific individual with her own specific physiology, metabolism, gut flora, lifestyle, etc. And in fact, there are a couple studies I’ve seen recently that bear this out.

• Does coffee increase your risk of heart disease? Well, you’ve got a gene called CYP1A2 that tells your liver how to make enzymes that help to metabolize caffeine. If you’ve got the CYP1A21A allele, your liver will make enzymes that help you to metabolize caffeine quickly; in that case, “coffee good”. But if you’ve got the CYP1A21F allele instead, you metabolize caffeine slowly and coffee might increase your risk of a heart attack. (Coffee bad.) This is hard to summarize in a paragraph-friendly way. Check out the article for better information.
• Likewise, there seem to be genetic factors that influence the effect of coffee on the risk of Parkinson’s disease.

Probably, then, the question “is coffee healthy” is a bad question to ask since the answer depends so much on individual factors. Perhaps a better question would be, “will I personally benefit from drinking coffee?” And perhaps you can’t answer that question without doing some of your own research, listening to your body, … I’ve even heard of people ordering genetic tests for themselves so that they can have some certainty about this.

Tip your baristas, ladies & gentlemen.