Meme

So, it looks like I’m part of a blog-meme. I normally wouldn’t do this, but I have some time to kill what with all this flying I’m doing (visiting grad schools). So, here goes, slightly modified…

1. Link to the person who tagged you. Done.

2. List 7 a few random things currently on your mind.
- Where should I go for grad school? I have it narrowed down to a few institutions, each of which has its own particular strengths and weaknesses - in terms of the projects I’m very excited about, equipment/facilities, funding, location, the size of the groups, the intellectual culture, etc. The spreadsheet has them dead even to within uncertainty, which means that I’ll have to keep taking data…
- Some of the research groups I’m interested in joining are quite large. This is often cited as a disadvantage, since it could translate into less “face-time” with the advisor, although to be fair - isn’t the more relevant parameter the (postdoc + senior grad student)/new student ratio rather than the faculty/new student ratio?
- Research - just thinking through the details of a number of experiments and simulations that I’m working on. The annoying thing with all this traveling is that it really punches a hole in my productivity (as well as means I’ll be missing the first half of the APS March Meeting!); but then again, talking to all these fascinating people and finding out about all the cool work going on at these different places is invaluable.
- Another thing that traveling makes difficult is staying on top of the literature. I have several tens of papers waiting to be read, and while long flights are great for plowing through them, the rate at which the to-read list grows is impressive.
- I came across this interesting NYT book review on a recent book, Intern by Sandeep Jauhar. The gist is Scrubs-ian in nature - it’s the story of a medical intern trying to deal with the imperfections of day-to-day hospital culture, the meaning of life, etc. - but what really got me was his physics background (he has a Ph.D. from Berkeley) and the analogies he makes: “Life on the wards was like the plasmons I had studied in condensed matter physics… where individual electrons, moving randomly, coalesced into something greater than the sum of their parts. There was a sort of synchronized buzz. … In the midst of this collective excitation, I kept thinking, Why am I so lonely?” Alright, so it’s kind of a stretch, but still - it’s physics.

3. Tag more people at the end of your blog and link to theirs. I’ll suggest Rod, Sam and Travis.

4. Let the tagged people know by leaving a note on their site. Done.

Cool Papers 1: General

I’ve come across a number of pretty cool papers in the past few months. Some of them deal with particular phenomena (stay tuned for possible upcoming posts on molecules at surfaces, biomimetics, phononics, crystallization, nanoparticles, wetting phenomena, computational physics, etc. etc. - at some point), and so are probably better off getting their own blog posts. Here are a few papers that didn’t fall into specific categories…

1. Frictional Anisotropy on a Quasicrystal Surface
Along with ~10 other things, a subject that I’ve recently become interested in is nanoscale mechanics, broadly defined. A key experimental tool in this field is the use of local probes to push or pull on things controllably. Miquel Salmeron’s STM group at Berkeley does work on this and related subjects, and I finally got around to reading this paper of theirs from a few years back.

The idea is conceptually very simple: while friction unsurprisingly depends on commensurability (that is, if two surfaces in contact are structurally ‘complementary’, they will ‘lock in’ to each other and hence have high friction between them - an idea that apparently dates back to da Vinci), trying to think about friction using just this notion is unrealistic. For starters, most contacting surfaces are probably incommensurate, and other factors - such as periodicity(?) - contribute, as well.

This paper nicely singles out the role of periodicity by looking at different directions along Al-Ni-Co quasicrystal surfaces using STM (to image the surface and hence distinguish the periodic and aperiodic directions of atom ordering) and AFM (to measure the probe tip-surface friction along these directions) in ultra-high vacuum. The AFM friction data can be modeled using a classical model relevant to the experimental situation (the Derjaguin-Muller-Toporov or DMT model, which I need to learn more about), enabling key parameters to be derived from the measurements.

In particular, the authors find a larger friction force (8x) along the periodic direction than along the aperiodic direction. Unsurprisingly, they ascribe this to differences in energy dissipation via electron or phonon excitation+propagation along the different directions, although it is unclear to what extent each kind of excitation plays a role. Perhaps similar local-probe measurements of a different kind (e.g. ones sensitive to electrical versus mechanical properties) might be useful… At the end of the day, I like this paper because it is an elegant example of using a unique microstructure, in which just one variable (here periodicity) changes in ways that are well understood, to study something interesting as a function of just that variable.

2. Liquid Crystals and the Origins of Life
Noel Clark gave a great talk about this work here at Penn not too long ago. I won’t write too much about this since Randy has a nice description of it over at the condmat journal club.

Here’s the executive summary: according to extensions of Onsager’s rigid-rod model for the formation of liquid crystal phases, individual molecules must be sufficiently anisotropic (i.e. the aspect ratio has to be above a certain minimum) to form a liquid crystal (LC). Surprisingly, the authors of this paper observed LC phases consisting of single-stranded (ss) DNA molecules too short to satisfy this criterion. Optical and x-ray measurements indicate that this results from end-to-end stacking of duplexes of complementary short ss-DNA molecules (known as ‘living polymerization’) into larger rods that satisfy the Onsager criterion, even at low temperatures (in concentrated phases of duplexes separated from the isotropic phase of unpaired ss-DNA molecules).

This autocatalytic behavior is like positive feedback, in a sense, and is why this work is so interesting from a biological point of view: it provides a mechanism by which the right molecules can be ’selected’ out from a ’soup’, and ‘evolve’ into larger ones as part of an RNA world. It’s an interesting idea - definitely one that’s gotten a lot of press, it seems - and while this work doesn’t provide much hard evidence for it, I’ll be interested to see what it stimulates.

3. Suprafroth!
This is a very interesting paper out recently on the arxiv, I think to be published in Nature Physics. While I don’t understand all the details, I like this particularly because it’s a nice combination of ideas from soft- and hard-condensed matter physics, like electronic liquid crystals.

The authors used magneto-optical imaging, which I need to learn more about, to image the flux pattern of superconducting lead (a type-I superconductor). Turns out that the magnetic field on the edge of a disc-shaped sample of lead is larger than the actual applied field, and for large enough magnetic field some flux can penetrate the sample. This leads to a phase intermediate between the normal and superconducting phases, possessing a froth-like magnetic structure - specifically, the froth cell boundaries are superconducting, while the interiors are normal metal. This shows up very clearly in the magneto-optical images (see figures in the paper).

The nice thing is that, unlike ‘conventional’ froths, mass-transport processes like drying or drainage are not present here (as the authors point out, “this superconducting froth involves only electrons”). This means that the froth structure can be tuned reversibly using the applied magnetic field or temperature, and the nice magneto-optical images allow for quantitative analysis of the froth structure as a function of just these parameters.

This is philosophically similar (loosely speaking) to paper #1 - the friction measurements of quasicrystals: again, it is a very nice example of using a unique microstructure (here, a froth structure that doesn’t suffer from irreversible processes, and can be controlled by magnetic field or temperature) to study something interesting (here, the structure and dynamics of froths) as a function of just the variables that you can control.

4. Universality in Conference Registration
This is a cute correspondence recently sent to Nature Physics describing an intriguing social application of statistical mechanics.

The authors used registration data from two physics conferences (# of registrants as a function of time to the deadline), saw that they matched up remarkably well (after rescaling), and came up with a simple model to capture the observed phenomenon in which the ‘pressure’ felt by potential attendees to register varies inversely with respect to the time to the deadline. Also, incorporating a Boltzmann-like factor (instead of uniform probability to register over the period of time) leads to a prediction that agrees well with # of payments as a function of time to the deadline data.

Of course, there are a number of assumptions and fitting parameters floating around here, and I’m not entirely sure this work will change the world of physics, but I always find things like this fun.

Graduate School

It’s graduate admissions season, apparently. So far I’ve heard back from six institutions: four acceptances (including a number of my top choices) with fellowships at two of them, one we’ll-fly-you-out ‘interview’, and one phone interview that went rather well… so at the end of the day, figuring out where I want to end up may be nontrivial.

As I noted in a previous comment, my algorithm for deciding where to apply to was pretty simple: I spent a good deal of time soul-searching and deciding (roughly) what I want to do for the next five-ish years, made a list of all the people I thought would make good research advisors to that end, and applied to the n departments that contained the maximal number of the people on my list (where n was determined by how many applications I was willing to fill out; turned out to be thirteen in total - I’m not superstitious).

My algorithm for deciding where to go for grad school will probably be a variant of the algorithm I used to pick my undergrad institution, and again is not too complicated (Sean Carroll has a very nice post on this subject, btw, as does okham as I just discovered):

1. Make a list of all the factors that I care about: for example, number/quality of advisors who I’m interested in (based on various factors like personal interactions, reputation, publication record, how they place people…), how excited I am by current research efforts, intellectual environment, potential for interesting collaborations, other students, location, quality of the department/school/life, bureaucratic requirements, funding, etc.

2. Weight individual factors accordingly: pretty self-explanatory, although this requires a lot of thought.

3. Visit all the places I’m seriously considering/find out as much about them as possible: this is the data collection stage, so that I have a good idea of how various places shape up in terms of the factors I listed. I’m pretty much traveling every weekend from next Friday to the end of March, with a few days in between for the APS March meeting. That’ll be fun.

4. Assign data values corresponding to each factor for each department: i.e. the results of step #3. These data values will obviously have error bars to reflect the subjectivity inherent to the data collection process, but the inverse relationship between error bar size and time spent on step #3 should enable a single-valued result.

5. Plug and chug: go wherever above algorithm says to go. Hey, it worked pretty well for my undergrad.

Speaking of which, I feel compelled to plug Penn. If anyone reading this happens to be a senior who got into Penn (terminology: I refer to UPenn, not Penn State) for something physics / materials science / nanoscience-related, I strongly urge you to think about coming here for grad school. There’s a lot of very exciting work going on here, and a lot of great people to work with - fantastic intellectual environment (I would say Penn does pretty highly on all the factors I mentioned above).

At this point I’m not really giving much thought to grad admissions anymore, although I know people who obsessively check their email/mail/online forums, like thegradcafe. I was looking through the posts there, and came across a few rather unconventional programs, if they’re real:

- Penn State has a Master’s program in “Recreation, Parks and Tourism Management”

- Fordham has a “School Psychology” program

- Someone posted about an “Applicable Math” program at UNC Chapel Hill, although I couldn’t find it, although apparently there’s one at Syracuse (did they decide not to go as far as to actually apply the math?)

- U Minnesota has a “Comparative Studies in Discourse and Society” program

- Quite a few places (I think I saw Syracuse and UC Berkeley) have programs in rhetoric.

…and so on.

Whew.

I realize that I pretty much dropped off the face of the earth for a while - the result of a crazy semester filled with endless problem sets, writing papers (both research and for classes), working on experiments/having equipment break down on me, the GREs, grad school apps, and random personal issues. Thankfully things are far less stressful nowadays what with the holidays + new semester and all…

One of the highlights was going to Boston to talk about some of my recent work at the Materials Research Society fall meeting. It was great - I had the chance to meet some very interesting people and go to quite a few exciting talks, both of relevance to my research or of personal interest. I might post about some of the ideas/papers I’ve been thinking about since then, some partly stimulated by some of the MRS talks or talks we’ve had here at Penn, some partly stimulated by my recent experiments.

Random thought: a service that I would love to have (I’ve found myself wishing for this kind of thing both when digging through the literature on a particular subject) is an online ’science network visualizer’ application. Basically an online service (maybe provided by ISI, Google scholar or something of that sort?) that would take a given researcher’s name - or perhaps an individual paper citation - as an input, and generate a ‘map’ of what people/groups of people/other papers cite them, and with what frequency. I know facebook has a few things like this (e.g. the many eyes friend network visualizer), and the awesome people at information esthetics created this map of science (of which I have a poster) using a similar algorithm. This kind of service would be invaluable for figuring out who is paying attention to a particular kind of research (and what else they pay attention to), what ‘cliques’ exist in various scientific communities, what the big results are/who the big players are, what connections are just waiting to happen… actually now that I think of it, this kind of thing probably already exists, hopefully in a more general framework that can be used to visualize other kinds of communities as well. I am an avid rss subscriber of visual complexity, a great site by Manuel Lima that documents various kinds of network visualization, but I don’t think I’ve ever come across something that fits this description.

In other news, I’ve started to write my senior/master’s thesis and have had to relearn . At the beginning the learning curve was incredibly frustrating, but things are finally starting to fall into place. After much experimenting, I’ve decided to go with BibDesk for managing citations, as suggested by Andrew Dawes (of The Daily Photon, a valuable new addition to the blogroll). It’s a wonderful program, and now that I’m doing more on the front it makes a lot of sense. Andrew has a post on some mac apps that he uses - similar to my previous post on the subject, and presumably with more to come.

Speaking of which, another new addition to the blogroll is confused at a higher level, an interesting “professional journal” by a physicist in Minnesota. He has a few posts that I thought were particularly interesting, for example documenting various aspects of the peer-review process (like ref comments) or collaborations that he’s working on. Also, he’s a Tufte fan (see my post from ages ago).

PC to Mac

Yup, I’ve caved. I’ve been a PC user all my life, but the one I’ve had for the past several years has been slowly and steadily grinding to a halt, while my digital work load has equally been consistently rising, so it was time for a change. While I get the impression that switching to Mac is the new ‘in’ thing these days - IP has noted that new converts often favor style over functionality (and Macs are pretty, without a doubt) - my main reason was much more simple: it’s true, Macs generally do tend to be more stable, secure, and easy to use, and now with Boot Camp, I’m running Windows as well. There’s nothing to lose and a whole lot to gain, and for people like me who treat life as one giant optimization problem, that’s a big deal. Indeed, making the transition, transferring data, getting comfortable with (mostly) everything, &c. took under a week. Here’s how I do my ‘basic’ tasks…

- Presentations/Word Processing: MS Powerpoint & MS Word 2004. while I’ve heard good things about iWork, I went with MS Office simply because, at the end of the day, most of the files I work with (e.g. in collaborations) are Office files, and I wanted to make sure that I was 100% compatible (even though from what I hear, there aren’t too many major compatibility issues). I’m slightly regretting this now on the Word front (Powerpoint I can live with) - it’s notoriously slow at times. I’m trying to wait it out until Office 2008 for Mac comes out, but I may end up shelling out some more and get Pages (or something free, like OpenOffice).

- E-mail/Calendar: Apple Mail/iCal. Like everything else that came along with this machine, these are wonderful. Plus I can sync the iCal to my iPod, which is great (although I really do hate all these ‘i-’ prefixes).

- RSS reader: Vienna. Open-source, freeware, sleek, built-in browser, and tons of functionality. Works great.

- Plotting data: OriginLab/Plot/Apple Grapher. I’ve always used OriginLab for data analysis, making figures, &c. so I decided to install it on my Windows partition (sadly, no Mac version). However, I recently discovered Plot (a freeware program) and the built-in Grapher app, both of which are wonderful for making high-quality figures, both 2d and 3d. They’re very bare bones, which is great for what I use them for (I fought with Origin for a half hour the other day trying to format a polar plot correctly, whereas Grapher took five minutes to do the same thing).

- General data analysis: OriginLab/Igor Pro. Our lab has a license for Origin, and it’s what I’ve always used, so I installed it - but I wanted something I could run on my Mac as well, without having to switch to the Windows partition. I’ve hear some good things about Igor, and their amazing student personal purchase deal made it economical enough to buy. Haven’t had much chance to play around with it, though.

- AFM/SPM image analysis: Gwyddion, sometimes Image SXM. I do a lot of AFM/SPM image processing and analysis, and have so far tended to use Veeco’s Nanoscope software (again, which isn’t supported on Mac). I’m happy about that though, because I don’t think I would’ve ever bothered to try out Gwyddion, which is a wonderful piece of software. It’s freeware, has just about every kind of functionality imaginable, and best of all: it tells you what it’s doing (with excellent supporting documentation). Installing it is somewhat involved, but not too difficult. (The only major point to note is that Gwyddion for Mac OS X needs X11, which comes on the Mac installer disk). Oh, and before I installed Gwyddion I played around with Image SXM a bit, too - pretty nice as well, but I’m far more impressed with Gwyddion.

- Graphics: GIMP (the GNU image manipulation program). I used to use Adobe Photoshop for all my graphics needs, but it’s ridiculously expensive. This program does, as far as I can tell, pretty much everything Photoshop does - for free. (Again, like Gwyddion, it uses X11, which is a tool OS X uses to run certain open source programs). The only issue is that it’s not that great with certain very simple tasks, like - of all things - drawing a circle.

- Lab Notebook: VoodooPad. Another great free program with a ton of functionality - basically like a personal wiki that I plan to use as a lab notebook, but I haven’t used it enough to pass judgement. Very easy to use, though.

- Organizing Papers: Zotero. I tried the much-raved about Papers for a bit, but soon quit, because they only supported PubMed (which only includes a fraction of the journals I read). Now that they include Web of Science I’d be more inclined to stick with them, but Zotero’s been serving me wonderfully. It’s a simple firefox plug-in that supports pretty much every publisher I’ve encountered. It downloads a paper’s metadata (author list, journal, abstract, etc.) with a click of a button, and lets you store the paper as an attachment, too. Only two issues are (i) integration with Word is poor, but I can easily export my Zotero citations as an endnote file and use endnote to put in citations, as I’ve done before; (ii) data is only stored on this computer, not on some central server somewhere (although they claim to be working on including this, which will be great).

- Windows-in-Mac: None at the moment. A number of programs exist that enable one to use the Windows partition while in conventional Mac mode. I tried CrossOver briefly, but it didn’t work all that great. I plan on giving Parallels Desktop a shot at some point, but frankly, I haven’t really needed Windows all that much. (Which is probably the take-home message from this experience…)

Of course, if anyone has suggestions for good software or simply personal favorites, I’d love to hear about them.

All in all, no complaints so far, except for one, which is a slightly big one that I’m not sure what I’ll do about: it turns out that my laptop doesn’t work with certain kinds of projectors, which sucks when I have to give a talk. Quick googling reveals that this is a problem with many MacBooks, and that not much has been done to acknowledge or fix the problem, which is ridiculous. Particularly since I have to give a talk at a conference in a week or so… I’ll probably have to pdf it and carry it on a USB drive just in case things don’t work out, which stinks (and is definitely not a long-term solution).