Behold the power of good lab notebook practice!

I was just able to help out my postdoc by pulling an old Bell Labs notebook from 11.5 years ago off my bookshelf and showing him a schematic of an electrical measurement technique. This is an object lesson in why it is a good idea to keep a clear, complete lab notebook! I try very hard to impress upon undergrad and graduate students alike that it's critically important to keep good notes, even (perhaps especially) in these days of electronic data acquisition and analysis. I've never once looked back and regretted how much time I spent writing things down, or how much paper I used - good record keeping has saved my bacon (and lots of time) on multiple occasions. Unfortunately, with rare exceptions, students come in to the university (at the undergrad or grad levels) and seem determined to write as little as possible down using as few sheets of paper as they can manage. Somewhere along the way (before grad school, though my thesis advisor was outstanding about this), it got pounded into my brain: if you didn't document it, you didn't do it. Perhaps we should make a facebook-like or twitter-like application that would sucker student researchers into obsessively updating their work status....

Statistical mechanics: still work to be done!

Statistical mechanics, the physics of many-particle systems, is a profound intellectual achievement.  A statistical approach to systems with many degrees of freedom makes perfect sense.  It's ridiculous to think about solving Newton's laws (or the Schroedinger equation, for that matter) for all the gas molecules in this room.  Apart from being computationally intractable, it would be silly for the vast majority of issues we care about, since the macroscopic properties of the air in the room are approximately the same now as they were when you began reading this sentence.  Instead of worrying about every molecule and their interactions, we characterize the macroscopic properties of the air by a small number of parameters (the pressure, temperature, and density).  The remarkable achievement of statistical physics is that it places this on a firm footing, showing how one can go from the microscopic degrees of freedom, through a statistical analysis, and out the other side with the macroscopic parameters.  

However, there are still some tricky bits, and even equilibrium statistical mechanics continues to be an active topic of research.  For example, one key foundation of statistical mechanics is the idea of replacing time-averages with energy-averages.  When we teach stat mech to undergrads, we usually say something like, a system explores all of the microscopic states available to it (energetically, and within other constraints) with equal probability.  That is, if there are five ways to arrange the system's microscopic degrees of freedom, and all five of those ways have the same energy, then the system in equilibrium is equally likely to be found in any of those five "microstates".  How does this actually work, though?  Should we think of the system somehow bopping around (making transitions) between these microstates?  What guarantees that it would spend, on average, equal time in each?  These sorts of issues are the topic of papers like this one, from the University of Tokyo.  Study of these issues in classical statistical mechanics led to the development of ergodic theory (which I have always found opaque, even when described by the best in the business).  In the quantum limit, when one must worry about physics like entanglement, this is still a topic of active research, which is pretty cool. 

Science's Breakthrough of the Year for 2010

Science Magazine has named the work of a team at UCSB directed by Andrew Cleland and John Martinis as their scientific breakthrough of the year for 2010.  Their achievement:  the demonstration of a "quantum machine".  I'm writing about this for two reasons.  First, it is extremely cool stuff that has a nano+condensed matter focus.  Second, this article and this one in the media have so many things wrong with them that I don't even know where to begin, and upon reading them I felt compelled to try to give a better explanation of this impressive work.

One of the main points of quantum mechanics is that systems tend to take in or emit energy in "quanta" (chunks of a certain size) rather than in any old amount.  This quantization is the reason for the observation of spectral lines, and mathematically is rather analogous to the fact that a guitar string can ring at a discrete set of harmonics and not any arbitrary frequency.   The idea that a quantum system at low energies can have a very small number of states each corresponding to a certain specific energy is familiar (in slightly different language) to every high school chemistry student who has seen s, p, and d orbitals and talked about the Bohr model of the atom.  The quantization of energy shows up not just in the case of electronic transitions (that we've discussed so far), but also in mechanical motion.  Vibrations in quantum mechanics are quantized - in quantum mechanics, a perfect ball-on-a-spring mechanical oscillator with some mechanical frequency can only emit or absorb energy in amounts of size hf, where h is Planck's constant.  Furthermore, there is some lowest energy allowed state of the oscillator called the "ground state".  Again, this is all old news, and such vibrational quantization is clear as a bell in many spectroscopy techniques (infrared absorption; Raman spectroscopy). 

The first remarkable thing done by the UCSB team is to manufacture a mechanical resonator containing millions of atoms, and to put that whole object into its quantum ground state (by cooling it so that the thermal energy scale is much smaller than hf for that resonator).  In fact, that's the comparatively easy part.  The second (and really) remarkable thing that the UCSB team did was to confirm experimentally that the resonator really was in its ground state, and to deliberately add and take away single quanta of energy from the resonator.  This is very challenging to do, because quantum states can be quite delicate - it's very easy to have your measurement setup mess with the quantum system you're trying to study!

What is the point?  Well, on the basic science side, it's of fundamental interest to understand just how complicated many particle systems behave when they are placed in highly quantum situations.  That's where much of the "spookiness" of quantum physics lurks.  On the practical side, the tools developed to do these kinds of experiments are one way that people like Martinis hope to build quantum computers.  I strongly encourage you to watch the video on the Science webpage (should be free access w/ registration); it's a thorough discussion of this impressive achievement.

Taking temperatures at the molecular scale

As discussed in my previous post, temperature may be associated with how energy is distributed among microscopic degrees of freedom (like the vibrational motion of atoms in a solid, or how electrons in a metal are placed into the allowed electronic energy levels).  Moreover, it takes time for energy to be transferred (via "inelastic" processes) among and between the microscopic degrees of freedom, and during that time electrons can actually move pretty far, on the nano scale of things.  This means that if energy is pumped into the microscopic degrees of freedom somehow, it is possible to drive those vibrations and electronic distributions way out of their thermal equilibrium configurations. 

So, how can you tell if you've done that?  With macroscopic objects, you can think about still describing the nonequilibrium situation with an effective temperature, and measuring that temperature with a thermometer.  For example, when cooking a pot roast in the oven (this example has a special place in the hearts of many Stanford graduate physics alumni), the roast is out of thermal equilibrium but in an approximate steady state.  The outside of the roast may be brown, crisp, and at 350 F, while the inside of the pot roast may be pink, rare, and 135 F.  You could find these effective temperatures (effective because strictly speaking temperature is an equilibrium parameter) by sticking a probe thermometer at different points on the roast, and as long as the thermometer is small (little heat capacity compared to the roast), you can measure the temperature distribution.

What about nanoscale systems?  How can you look at the effective temperature or how the energy is distributed in microscopic degrees of freedom, since you can't stick in a thermometer?  For electrons, one approach is to use tunneling (see here and here), which is a topic for another time. In our newest paper, we use a different technique, Raman spectroscopy. 

In Raman, incoming light hits a system under study, and comes out with either less energy than it had before (Stokes process, dumping energy into the system) or more energy than it had before (anti-Stokes process, taking energy out of the system).  By comparing how much anti-Stokes Raman you get vs. how much Stokes, you can back out info about how much energy was already in the system, and therefore an effective temperature (if that's how you want to describe the energy distribution).  You can imagine doing this while pushing current through a nanosystem, and watching how things heat up.  This has been done with the vibrational modes of nanotubes and graphene, as well as large ensembles of molecules.  In our case, through cool optical antenna physics, we are able to do Raman spectroscopy on nanoscale junctions, ideally involving one or two molecules.  We see that sometimes the energy input to molecular vibrations from the Raman process itself is enough to drive some of those vibrations very hard, up to enormous effective temperatures.  Further, we can clearly see vibrations get driven as current is ramped up through the junction, and we also see evidence (from Raman scattering off the electrons in the metal) that the electrons themselves can get warm at high current densities.  This is about as close as one can get to interrogating the energy distributions at the single nanometer scale in an electrically active junction, and that kind of information is important if we are worried about how dissipation happens in nanoelectronic systems. 

Temperature, thermal equilibrium, and nanoscale systems

In preparation for a post about a new paper from my group, I realized that it will be easier to explain why the result is cool if I first write a bit about temperature and thermal equilibrium in nanoscale systems.  I've tried to write about temperature before, and in hindsight I think I could have done better.  We all have a reasonably good intuition for what temperature means on the macroscopic scale:  temperature tells us which way heat flows when two systems are brought into "thermal contact".  A cool coin brought into contact with my warm hand will get warmer (its temperature will increase) as my hand cools down (its temperature will locally decrease).  Thermal contact here means that the two objects can exchange energy with each other via microscopic degrees of freedom, such as the vibrational jiggling of the atoms in a solid, or the particular energy levels occupied by the electrons in a metal.  (This is in contrast to energy in macroscopic degrees of freedom, such as the kinetic energy of the overall motion of the coin, or the potential energy of the coin in the gravitational field of the earth.)

We can turn that around, and try to use temperature as a single number to describe how much energy is distributed in the (microscopic) degrees of freedom.  This is not always a good strategy.  In the coin I was using as an example, you can conceive of many ways to distribute vibrational energy.  Number all the atoms in the coin, and have the even numbered atoms moving to the right and the odd numbered atoms moving to the left at some speed at a given instant.  That certainly would have a bunch of energy tied up in vibrational motion.  However, that weird and highly artificial arrangement of atomic motion is not what one would expect in thermal equilibrium. Likewise, you could imagine looking at all the electronic energy levels possible for the electrons in the coin, and popping every third electron each up to some high unoccupied energy level.   That distribution of energy in the electrons is allowed, but not the sort of thing that would be common in thermal equilibrium.  There are certain vibrational and electronic distributions of energy that are expected in thermal equilibrium (when the system has sat long enough that it has reached steady-state as far as its statistical properties are concerned).

How long does it take a system to reach thermal equilibrium?  That depends on the system, and this is where nanoscale systems can be particularly interesting.  For example, there is some characteristic timescale for electrons to scatter off each other and redistribute energy.  If you could directly dump in electrons with an energy 1 eV (one electron volt) above the highest occupied electronic level of a piece of metal, it would take time, probably tens of femtoseconds, before those electrons redistributed their energy by sharing it with the other electrons.  During that time period, those energetic electrons can actually travel rather far.  A typical (classical) electron velocity in a metal is around 10⁶ m/s, meaning that the electrons could travel tens of nanometers before losing their energy to their surroundings.  The scattering processes that transfer energy from electrons into the vibrations of the atoms can be considerably slower than that! 

The take-home messages: 

1) It takes time for electrons and vibrations arrive at a thermal distribution of energy described by a single temperature number.

2) During that time, electrons and vibrations can have energy distributed in a way that can be complicated and very different from thermal distributions.

3) Electrons can travel quite far during that time, meaning that it's comparatively easy for nanoscale systems to have very non-thermal energy distributions, if driven somehow out of thermal equilibrium.

More tomorrow.

NSF grants and "wasteful spending"

Hat tip to David Bacon for highlighting this.  Republican whip Eric Cantor has apparently decided that the best way to start cutting government spending is to have the general public search through NSF awards and highlight "wasteful" grants that are a poor use of taxpayer dollars.

Look, I like the idea of cutting government spending, but I just spent two days in Washington DC sitting around a table with a dozen other PhD scientists and engineers arguing about which 12% of a large group of NSF proposals were worth trying to fund.  I'm sure Cantor would brand me as an elitist for what I'm about to write, but there is NO WAY that the lay public is capable of making a reasoned critical judgment about the relative merits of 98% of NSF grants - they simply don't have the needed contextual information.  Bear in mind, too, that the DOD budget is ONE HUNDRED TIMES larger than the NSF budget.  Is NSF really the poster child of government waste?  Seriously?

The tyranny of reciprocal space

I was again thinking about why it can be difficult to explain some solid-state physics ideas to the lay public, and I think part of the problem is what I call the tyranny of reciprocal space.  Here's an attempt to explain the issue in accessible language.  If you want to describe where the atoms are in a crystalline solid and you're not a condensed matter physicist, you'd either draw a picture, or say in words that the atoms are, for example, arranged in a periodic way in space (e.g., "stacked like cannonballs", "arranged on a square grid", etc.).  Basically, you'd describe their layout in what a condensed matter physicist would call real space.  However, physicists look at this and realize that you could be much more compact in your description.  For example, for a 1d chain of atoms a distance a apart from each other, a condensed matter physicist might describe the chain by a "wavevector" k = 2 \pi/a instead.  This k describes a spatial frequency; a wave (quantum matter has wavelike properties) described by cos kr would go through a complete period (peak of wave to peak of wave, say) and start repeating itself over a distance a.   Because k has units of 1/length, this wavevector way of describing spatially periodic things is often called reciprocal space.  A given point in reciprocal space (k_x, k_y, k_z) implies particular spatial periodicities in the x, y, and z directions.

Why would condensed matter physicists do this - purely to be cryptic?  No, not just that.  It turns out that a particle's momentum (classically, the product of mass and velocity) in quantum mechanics is proportional to k for the wavelike description of the particle.  Larger k (shorter spatial periodicity), higher momentum.  Moreover, trying to describe the interaction of, e.g., a wave-like electron with the atoms in a periodic lattice is done very neatly by worrying about the wavevector of the electron and the wavevectors describing the lattice's periodicity.  The math is very nice and elegant.  I'm always blown away when scattering experts (those who use x-rays or neutrons as probes of material structure) can glance at some insanely complex diffraction pattern, and immediately identify particular peaks with obscure (to me) points in reciprocal space, thus establishing the symmetry of some underlying lattice.

The problem is, from the point of view of the lay public (and even most other branches of physics), essentially no one thinks in reciprocal space.  One of the hardest things you (as a condensed matter physicist) can do to an audience in a general (public or colloquium) talk is to start throwing around reciprocal space without some preamble or roadmap.  It just shuts down many nonexperts' ability to follow the talk, no matter how pretty the viewgraphs are.  Extreme caution should be used in talking about reciprocal space to a general audience!  Far better to have some real-space description for people to hang onto. 

A seasonal abstract

On the anomalous combustion of oleic and linoleic acid mixtures

J. Maccabeus et al., Hebrew University, Jerusalem, Judea

Olive-derived oils, composed primarily of oleic and linoleic fatty acids, have long been used as fuels, with well characterized combustion rates.  We report an observation of anomalously slow combustion of such a mixture, with a burn rate suppressed relative to the standard expectations by more than a factor of eight.  Candidate explanations for these unexpectedly slow exothermic reaction kinetics are considered, including the possibility of supernatural agencies intervening to alter the local passage of time in the vicinity of the combustion vessel.

(Happy Hanukkah, everyone.)
(Come on, admit it, this is at least as credible as either this or this.) 

Writing exams.

Writing (or perhaps I should say "creating", for the benefit of UK/Canada/Australia/NZ grammarians) good exams is not a trivial task.  You want very much to test certain concepts, and you don't want the exam to measure thing you consider comparatively unimportant.  For example, the first exam I ever took in college was in honors mechanics; out of a possible 30 points, the mean was a 9 (!), and I got a 6 (!!).  Apart from being a real wake-up call about how hard I would have to apply myself to succeed academically, that test was a classic example of an exam that did not do its job.  The reason the scores were so low is that the test was considerably too long for the time allotted.  Rather than measuring knowledge of mechanics or problem solving ability, the test largely measured people's speed of work - not an unimportant indicator (brilliant, well-prepared people do often work relatively quickly), but surely not what the instructor cared most about, since there usually isn't a need for raw speed in real physics or engineering.  

Ideally, the exam will have enough "dynamic range" that you can get a good idea of the spread of knowledge in the students.  If the test is too easy, you end up with a grade distribution that is very top-heavy, and you can't distinguish between the good and the excellent.  If the test is too difficult, the distribution is soul-crushingly bottom-heavy (leading to great angst among the students), and again you can't tell between those who really don't know what's going on and those who just slipped up.  Along these lines, you also need the test to be comparatively straightforward to take (step-by-step multipart problems, where there are still paths forward even if one part is wrong) and to grade.

Finally, in an ideal world, you'd actually like students to learn something from the test, not just have it act purely as a hurdle to be overcome.  This last goal is almost impossible to achieve in classes so large that multiple choice exams are the only real option.  It is where exam writing can be educational for the instructor as well, though - nothing quite like starting out to write a problem, only to realize partway through that the situation is more subtle than you'd first thought!  Ahh well.  Back to working on my test questions.

Memristors - how fundamental, and how useful?

You may have heard about an electronic device called a memristor, a term originally coined by Leon Chua back in 1971, and billed as the "missing fourth fundamental circuit element".  It's worth taking a look at what that means, and whether memristors are fundamental in the physics sense that resistors, capacitors, and inductors are.  Note that this is an entirely separate question from whether such devices and their relatives are technologically useful! 

In a resistor, electronic current flows in phase with the voltage drop across the resistor (assuming the voltage is cycled in an ac fashion).  In the dc limit, current flows in steady state proportional to the voltage, and power is dissipated.  In a capacitor, in contrast, the flow of current builds up charge (in the usual parallel plate concept, charge on the plates) that leads to the formation of an electric field between conducting parts, and hence a voltage difference.  The current leads the voltage (current is proportional to the rate of change of the voltage); when a constant voltage is specified, the current decreases to zero once that voltage is achieved, and energy is stored in the electric field of the capacitor.  In an inductor, the voltage leads the current - the voltage across an inductor, through Faraday's law, is proportional to the rate at which the current is changing.  Note that in a standard inductor (usually drawn as a coil of wire), the magnetic flux through the inductor is proportional to the current (flux = L I, where L is the inductance).  That means that if a certain current is specified through the inductor, the voltage drops to zero (in the ideal, zero-resistance case), and there is energy stored in the magnetic field of the inductor.  Notice that there is a duality between the inductor and capacitor cases (current and voltage swapping roles; energy stored in either electric or magnetic field).

Prof. Chua said that one could think of things a bit differently, and consider a circuit element where the magnetic flux (remember, in an inductor this would be proportional to the time integral of the voltage) is proportional to the charge that has passed through the device (the time integral of the current (rather than the current itself in an inductor)).  No one has actually made such a device, in terms of magnetic flux.  However, what people have made are any number of devices where the relationship between current and voltage depends on the past history of the current flow through the device.  One special case of this is the gadget marketed by HP as a memristor, consisting of two metal electrodes separated by a titanium oxide film.  In that particular example, at sufficiently high bias voltage, the flow of current through the device performs electrochemistry on the titanium oxide, either reducing it to titanium metal, or oxidizing it further, depending on the polarity of the flow.  The result is that the resistance (the proportionality between voltage and current; in the memristor language, the proportionality between the time integral of the voltage and the time integral of the current) depends on how much charge has flowed through the device.  Voila, a memristor.

I would maintain that this is conceptually very different and less fundamental than the resistor, capacitor, or inductor elements.  The resistor is the simplest possible relationship between current and voltage; the capacitor and inductor have a dual relationship and each involve energy storage in electromagnetic fields.  The memristor does not have a deep connection to electromagnetism - it is one particular example of the general "mem"device, which has a complex electrical impedance that depends on the current/voltage history of the device.  Indeed, my friend Max di Ventra has, with a colleague, written a review of the general case, which can be said to include "memcapacitors" and "meminductors".  The various memgizmos are certainly fun to think about, and in their simplest implementation have great potential for certain applications, such as nonvolatile memory.

Great moments in consumer electronics

It's been an extremely busy time of the semester, and there appears to be no end in sight.  There will be more physics posts soon, but in the meantime, I have a question for those of you out there that have Nintendo Wii consoles.  (The Wii is a great example of micromachining technology, by the way, since the controller contains a 3-axis MEMS accelerometer, and the Wii Motion Plus also contains a micromachined gyroscope.)  Apparently, if there is a power glitch, it is necessary to "reset your AC adapter" in order to power on the console.  The AC adapter looks for all the world like an ordinary "brick" power supply, which I would think should contain a transformer, some diodes, capacitors, and probably voltage regulators.  Resetting it involves unplugging it from both ends (the Wii and the power strip), letting it sit for two solid minutes, and then plugging it back directly into a wall outlet (not a power strip).  What the heck did Nintendo put in this thing, and why does that procedure work, when plugging it back into a power strip does not?!  Does Nintendo rely on poorly conditioned power to keep the adapter happy?  Is this all some scheme so that they can make sure you're not trying to use a gray-market adapter?  This is so odd that it seemed like the only natural way to try to get to the bottom of it (without following my physicist's inclination of ripping the adapter apart) was to ask the internet.

Paul Barbara

I was shocked and saddened to learn of the death of Paul Barbara, a tremendous physical chemist and National Academy of Sciences member at the University of Texas.  Prof. Barbara's research focused largely on electron transfer and single-molecule spectroscopy, and I met him originally because of a mutual interest in organic semiconductors.  He was very smart, funny, and a class act all the way, happy to talk science with me even when I was a brand new assistant professor just getting into our field of mutual interest.  He will be missed.

Two cool videos, + science funding

Here are two extremely interesting videos related to physics topics.  Both combine two things I enjoy in life:  physics and coffee.  Here is a video made by scientists at the Institut Laue-Langevin, a neutron science laboratory in Grenoble funded by the EU.  The scientists decided to use a neutron beam to image through a little espresso maker as it brews.  They did this partly for fun, and partly to demonstrate how neutrons may be used to examine materials - for example, one could use this sort of imaging to look for flaws or cracks in turbine blades.  The cross-section for absorbing neutrons varies quite strongly from element to element, giving good material contrast.  The aluminum housing for the espresso maker shows up as very light gray, while the water (and resulting espresso, which is still mostly water, even when my old friend Sven makes it) shows up as very dark.  This is because the hydrogen in the water has a relatively large cross-section for capturing a neutron and becoming deuterium.

The second video I saw thanks to Charles Day's blog.  To me, a former mechanical engineer, this is rather jaw-dropping.  Hod Lipson and his graduate students at Cornell have managed to leverage a great piece of physics called the jamming transition.  Many physics students are surprised to learn that some "simple" problems of classical statistical physics can exhibit complex phenomenon and remain active subjects of research, even though they seem on the surface like they should have been solved by 19th century French mathematician whose name started with L.  The jamming transition is one of these problems.  Take a bunch of dry grains (in this case, ground coffee).  When there is a bit of air mixed in with the grains, the grains can slide over and past each other relatively easily.  A latex balloon filled with this mixture is squishy.  If the air is removed, however, the grains jam up, and the grain-filled balloon becomes very hard (as if the effective viscosity of the blob of grains diverges).  The Cornell researchers have used this phenomenon to make a universal "gripper" for picking up objects.  Just watch the movie.  It's very impressive.

Finally, a tidbit about science funding.  Well, it didn't take long.  The Heritage Foundation (a US conservative think-tank) is already proposing cutting the research budgets of NSF, DOE, and NIST, as well as eliminating NSF support for K12 education.  This isn't a surprise - they do this all the time - though it's interesting that they propose absolutely zero cuts to the Department of Defense (though they have no problem suggesting cuts for veterans benefits).   

Data and backups

I don't talk too much on here about the university service stuff that I do - frankly, much of it wouldn't be very interesting to most of my readers.  However, this year I'm chairing Rice University's Committee on Research, and we're discussing an issue that many of you may care about:  data management and preservation.   Generally, principal investigators are assumed to be "responsible custodians" of data taken during research.  Note that "data" can mean many things in this context - see here, for example.   US federal agencies that sponsor research typically expect the PIs to hold on to their data for several years following the conclusion of a project, and that PIs will make their data available if requested.  The university is legally responsible to ensure that the data is retained, in fact.  There are many issues that crop up here, but the particular one on which I'd like some feedback is university storage of electronic data.  If you're at a university, does your institution provide electronic (or physical, for that matter) storage space for the retention of research data?  Do they charge the investigators for that storage?  What kind of storage is it, and is the transfer of data from a PI's lab, say, to that storage automated?  I'd be very interested in hearing either success stories about university or institutional data management, or alternately horror stories. 

Wrap-up, Osheroff-fest

The symposium in honor of Doug Osheroff was great fun. It was great to see old friends again, to hear some stories that I didn't know, and to find out what other former group members are up to. The actual talks were generally pretty good, with a number of speakers focusing on how exciting and vibrant the whole field of low temperature physics was in its heyday. There were a total of seven Nobel Laureates there (DDO, Steve Chu, Bob Laughlin, Bob Richardson, Dave Lee, Phil Anderson, and Tony Leggett), and a bunch of other luminaries (Michael Fisher, Daniel Fisher, Bill Brinkman, Ted Geballe, and even a special and unexpected (by me, at least) appearance by Ed Witten). Steve Chu's talk was remarkable in part because he so clearly loved the chance to give an actual technical talk about some of his research, which you get the feeling he doesn't do so much at the DOE. Fun stuff, even when Bob Laughlin was giving me a hard time :-)

Osheroff-fest

I am currently visiting Stanford for my thesis advisor's big birthday bash/retirement festivities. It's really great to see so many former students, postdocs, and collaborators, and it's more than a little surreal to be back here after so long. It's a shame taht a few couldn't make it - they're sorely missed. There is going to be a day-long symposium tomorrow in his honor that should be very interesting. I'll post some brief description of some of the talks, if they seem like they are of general interest.

Excellent talk today + the point of colloquia.

Today I was fortunate to host my department's weekly colloquium, with Prof. Wilson Ho from UC Irvine as the speaker.  He gave a great talk about "Visualizing Quantum Mechanics", in which he showed (using experiments from his own group) how scanning tunneling microscopy can be a great teaching tool for illustrating concepts from undergraduate quantum mechanics.  He covered the exponential dependence of tunneling on distance, imaging of molecular orbitals, the crossover between classical (activated) diffusion and quantum (tunneling-based) diffusion, particle-in-a-box physics in 1d atomic chains, visualization of Fermi's Golden Rule via light emission experiments, and other neat results.  The audience included not just the usual collection of faculty and grad students, but also a bunch of the current undergrad quantum students as well.  

The talk was pretty much a letter-perfect example of what a colloquium is supposed to be.  It was accessible to a general audience, was genuinely educational, had appealing visuals, and contained enough intellectual "meat" to be satisfying for experts, including some not-yet published stuff.  It would be nice if every speaker realized the difference between a colloquium and a seminar....

On an unrelated note, I can't resist commenting on this awful article from Reuters hyping the LHC.  I'm as happy as anyone that the accelerator is running well, but does the CERN press office really need to keep churning out this kind of garbage?  Can't they just have a nice release/article talking about how nicely the experiment is running, and how they're hitting their targets, without making just laughable statements?  I think we can be pretty damned sure that the LHC is not about to discover incontrovertible evidence for parallel universes.   

Buckyball celebration/symposium

In honor of the 25th anniversary of the discovery of C₆₀ at Rice, the university is holding a symposium to celebrate.  In addition to the surviving members of the discovery team (laureates Curl and Kroto; Prof. Heath, Dr. O'Brien), there are many big names in the business (Millie Dresselhaus, Marvin Cohen, Phaedon Avouris, Hongjie Dai).  Andre Geim is going to skype in, apparently, since getting the Nobel Prize this past week has understandably scrambled his travel plans.  Unfortunately I'm flying to Washington, DC later this morning, so I will miss most of the fun, but I'm sure it will be a very interesting and lively event.

2010 Physics Nobel for graphene

The 2010 Nobel Prize in Physics has been awarded to Andre Geim and Konstantin Novoselov for graphene.  Congratulations to them!  Graphene, the single-atomic-layer limit of graphite, has been a very hot topic in consensed matter physics since late 2004, and I've posted about it here and here.  There is no question that graphene is a very interesting material, and the possibility of serious technological applications looms large, but as Joerg Haber points out, overhype is a real danger.  The prize is somewhat unusual in that it was very fast on the scale of these things.  I also find it interesting that only the Manchester group was given the prize, given the impact of the work going on in this area at other places at around the same time (for example, take a look at the first few talks in this session I put together at the 2005 APS March Meeting).  I do hope that those in the British scientific funding establishment take note that future prizes and innovations like this are at severe risk if research and educational funding cuts continue.

"Definitively inaccurate": One more comment about NRC rankings

One last post before the Nobel in physics is announced tomorrow.... As many people in the academic blogosphere have reported, there are some serious issues with the NRC rankings of graduate programs.  Some of these seem to be related to data entry, and others to nonuniform or overly simplistic interpretations of answers to survey questions.  Let me give a couple of examples.  I'm in the physics and astronomy department at Rice, and for several years I've helped oversee the interdisciplinary applied physics graduate program here (not a department - applied physics does not have faculty billets or its own courses, for example).  I filled out faculty NRC paperwork, and I was also in charge (with a colleague) of filling out the "department"-level NRC paperwork for the applied physics program.  I know, with certainty, that some of the stats for the two programs are very very similar, including the allocation of work space to graduate students and the approximate completion rates of the PhD program.  However, while these seem to show up correctly in the applied physics NRC data, they are both skewed bizarrely wrong (and very unfavorably, like the completion rate in the NRC data is too low when compared with reality by at least a factor of two!) in the physics & astronomy departmental NRC data.  Now, overall the department did reasonably well in the rankings, and if one looks particularly at just the research stuff per faculty member, physics and astronomy did quite well.  However, this issue with student data really stinks, because that's what some sites geared toward prospective students emphasize.  It's wrong, there's no fixing it, and it looks like it will be "definitively inaccurate" (to borrow a phrase from Douglas Adams) for at least a decade.