More specifically, let’s consider the case of a biological circuit.  These circuits regulate the state of a cell in response to a given set of input signals. The parts of the circuit are a wide variety of specific proteins, whose synthesis and function are modified by many different mechanisms.  One distinction of biological relative to engineered circuits is the fact that every protein is different so that there are no standardized parts. Proteins interact to modify one another’s function and eventually produce an output, i.e., change the state of the cell by changing its transcriptional program and thereby changing the concentrations of its constitutive proteins.

For a given circuit, it is still an open question as to how many genes could be legitimately considered to be involved. In yeast, genetic maps constructed with high-throughput robotics have identified literally millions of interactions; these are shown as the famous ‘hairball’ plots one frequently encounters. So, is that the answer? Do we need to know everything about everything to make sense of it all? Do we need a map whose legend states that 1 mile = 1 mile to understand the cell? If so, then what kind of understanding would that entail… a depressing prospect, being drowned in a sea of information.

So, we want and need reduced models to better understand the functions of a biological circuit. Intuitively, this is what the more classical cell biologists and biochemists have been constructing. Classical mutagenesis tends to focus on mutations to critical genes that severely hamper cell fitness. Thus, inadvertently, the community may have been studying the circuit elements containing the most information about the process. However, several questions arise. First, where do you draw the line and exclude more peripheral elements? And second, is this a legitimate endeavor?

Consider a simple example, where the dynamics of a circuit are dominated by a few interactions each of strength O(1). There is a second handful of interactions of strength O(epsilon), whose exclusion gives a negligible error of O(epsilon) << 1.  However, if the number of weaker interactions is larger, as threatened by the hairball, we could get into serious trouble. If the number is N ~ 1/epsilon, we would still probably be ok in our approximation due to the unexpected property of asymptotic analysis to give fundamental insight even when it shouldn’t. However, if N >> 1/epsilon things would start looking quite terrible from the point of view of dimensional reduction. The genetic tractability of circuits and the progress made argues against the later case, but the intermediate case is not yet ruled out and relatively few cases have been studied in sufficient detail (i.e., the drunk looking for his lost keys at night under the street lamp because that is where the light is). So, we are left with the following tentative definition of information – a sum of the relevant biochemical interactions multiplied by their relative impact on the output. Obvious issues left to be resolved regard the definition of ‘relative impact’ and how to quantitatively define the information content of a circuit output.

Further understanding of information transmission in biology will require new quantitative imaging tools to better measure chemistry on the level of single cells, where it really takes place. Integration of these techniques with the rapidly increasing amounts of cell biological and genetic knowledge promises rapid advances in our understanding of information transmission and generation in cellular systems. The rapid technical advancement in biology of the past decades leads one to expect significant progress on these fundamental issues over the next decade.

The experiments were carried out at the Advanced Photon Source synchrotron in Chicago, in collaboration with scientists from the University of Michigan and The Center for Advanced Radiation Sources, University of Chicago.

Image: Greg Stewart/SLAC

Harmonic generation (HHG) is a general feature of driven nonlinear systems and is well known to occur for strong field laser interactions with atomic systems. This is the basis for producing attosecond pulses in the VUV. The mechanism is well understood in terms of a simple three step model consisting of strong-field ionization, acceleration of the free electron in the laser field, and recombination upon returning to the parent atom. In solids, we expect the process to be fundamentally different due to the high density and periodicity of the system. We have observed for the first time nonperturbative HHG in a bulk crystalline solid. The results appeared in Nature Physics this week ( link to article ) and were the results of a collaboration between Stanford and the Ohio State University.

We measure harmonics up to the 25th order, well above the band-gap of the ZnO crystal we used. We observe several fundamental differences between the solid and atomic case.  For example, the scaling of the high-energy cutoff is linearly proportional to the electric field (as opposed to quadratic) and the lack of inversion symmetry gives rise to even and odd harmonics. The results can be understood at least qualitatively in terms of a two step process consisting of strong field ionization across the band gap, followed by radiation due to a nonlinear current driven by the strong field laser. This has important implications for the understanding of attosecond electron dynamics and other non-equilibrium band-structure-related phenomena in strongly driven bulk solids.

Looking to the future, it is hard to imagine that forefront technology and engineering could progress another ten or twenty years without experiencing some bombshell revolutions. Issues related to globalization and to the environment have recently flared onto our radar screens and are bound to remain there for the foreseeable future; businesses and universities are scrambling to anticipate and to adapt. But another broad class of challenges—which will likewise demand systemic response, yet are much harder to assess managerially—are beginning to come into focus as we contemplate the long term outlook for high-performance yet energy-efficient computation and communication, and as a growing list of industries get serious about grappling with nanotechnology. These challenges are purely intellectual in nature, fall squarely within the scope of academia’s educational mission, and are hallmarks of a major turning point in the modern development of engineering and applied science.

That turning point will be the transition, in certain key sectors, from classical to quantum technologies. This shift may well be gradual and might not begin in earnest for ten or twenty years, but current expert opinion already deems it inevitable. The underlying quantum nature of the physical carriers of information in computers and communication networks—electrons and photons—cannot remain hidden forever as our relentless demand for speed drives engineers to deploy ever-smaller transistors, and to exploit ever-fainter and more fleeting blips of light in fiber-optic networks. We can already count the number of dopant atoms in a state-of-the-art transistor and the number of photons required to represent a bit of information in an optical communication link (a few dozen in both cases). Unfortunately, such extreme frugality in the physical resource allotment per information-processing element generally comes at the price of increased fluctuations and a propensity for soft defects. From a classical-engineering perspective this is a significant obstacle of fundamentally quantum-mechanical origin that signposts the technology roadmap right where Moore’s Law falls by the wayside.

But from the perspective of quantum engineering, the advent of such small-is-different complexities marks the opening of avenues toward radically new paradigms of functionalizing matter and energy with atomic resolution. New engineering concepts and methodology are possible, and indeed required at atomic scale because the physical dynamics of isolated microscopic systems are so qualitatively different from those upon which our macroscopic inventions have relied. Forerunners of true quantum engineering can be seen in the now-ubiquitous laser and in the atomic clock, which plays a key role in enabling modern systems for navigation and geodesy. We have seen our first hints regarding the long-term promise of quantum engineering in the celebrated theoretical results of quantum computation, which show that fundamentally different and superior algorithms can be posited for critical tasks such as factoring. This last revelation has already found its way into best-selling works of science fiction.

Within academia, the revolutionary ideas emerging from early research in quantum engineering have inspired the creation of numerous centers and faculty groups at leading universities; all this in an era when the actual construction of a sizeable quantum information processor remains a futuristic dream. Indeed, in practical terms the path forward is still rather murky as pure quantum behavior is quite difficult to achieve in the rudimentary constructs within reach of current technical capabilities in fabrication and control. The devices we can so-far produce tend to exhibit a gray mix of quantum and classical dynamics, with non-classical phenomena prominent only on very short timescales or over very short length-scales. The development of broadly applicable strategies for promoting and stabilizing pure quantum behavior in devices of useful size is a daunting technical challenge that could require decades of intensive work. As a result, despite the highly disruptive impact that the quantum revolution will ultimately have, companies in high-tech industries have generally adopted a wait-and-see attitude rather than rushing into any major immediate investments. But scientifically we know that the classical-quantum technology transition is there, a manifest destiny just waiting to be reached.

Universities and foundations that can afford to take a long-term view have recognized this, and quantum engineering activities are growing increasingly prominent in worldwide basic research. We believe that Stanford, as a leading institution of higher learning that upholds the integration of education and research as a guiding principle, can take a pioneering role in leveraging such visionary inquiry to inform the way we train our graduate students in participating fields. As the engineers and scientists we are educating today will drive technology development for the next thirty years, they will almost certainly be main players in actualizing the transition to quantum technologies.

Applied Physics is a graduate department in the Stanford University School of Humanities and Sciences.  Our Ph.D. students pursue research and coursework in the physical, information, life, and energy sciences.  Many work on engineering-oriented projects and on practical applications.  They find dissertation research advisors in a wide range of academic departments on campus and at SLAC.  After graduating they go on to careers in academia and in industry, in public service and in the non-profit sector.  Here at Stanford we have a world-class hospital, we have the world’s first x-ray laser, and we are steeped in the culture of Silicon Valley.  All of our basic science departments are at the tops of their fields, and we have a special set of “independent laboratories” that foster cutting-edge interdisciplinary research in areas ranging from the development of advanced materials to preserving the environment.

The Department of Applied Physics sits at the center of all this, and our Ph.D. program is structured to ensure that you receive a solid grounding in basic and applied physics, to give you the opportunity to explore research projects with our excellent core faculty, and to allow you the freedom to reach beyond our own Department in search of the best thesis project for you.

In order to help guide your exploration of Stanford research in applied physics and related areas, we have created a suite of four theme pages that provide overviews of Stanford/SLAC faculty, facilities, and courses in Nanoscience & Quantum Engineering, Lasers & Accelerators, Condensed Matter Physics, and Experimental & Theoretical Biophysics.  Although some prominent content on these pages comes from outside our Department proper, we like to think of these as Applied Physics themes, and we like to think of the people involved as members of the greater Applied Physics community.  None of this is meant to be exclusionary—many other Stanford departments and programs stake their claims in these areas, and there are certainly some important activities in Applied Physics that don’t fall neatly within any of the four presentation themes.  But we hope you’ll find these pages a good place to start as you get to know more about the general shape and structure of applied physics at Stanford.
Want to see a complete listing of our faculty, and our faculty only?  Want to filter the site content with categories other than the four major themes?  Have a look at the alternative browsing links that can be accessed through the “Navigate” pop-up menu; click on the “Faculty” link if that’s what you’re after, or try the “Browse all topic tags” option.  Or use the search box.  Our goal for the new site is to help you find the things here that really interest you.

Finally convinced?  Use the “Apply” pop-up menu to read about the requirements and then click through to Stanford University’s online application site! Deadline is January 4, 2011…

Hideo Mabuchi, Professor and Chair