The absorption spectrum around nu=1: evidence for a small size Skyrmion

We measure the absorption spectrum of a two-dimensional electron system (2DES) in a GaAs quantum well in the presence of a perpendicular magnetic field. We focus on the absorption spectrum into the lowest Landau Level around nu=1. We find that the spectrum consists of bound electron-hole complexes, trion and exciton like. We show that their oscillator strength is a powerful probe of the 2DES spatial correlations. We find that near nu=1 the 2DES ground state consists of Skyrmions of small size (a few magnetic lengths).Comment: To be published in Phys Rev Lett. To be presented in ICSP2004, Flagstaff, Arizona. 4 figures (1 of them in color). 5 page

The Fermi edge singularity of spin polarized electrons

We study the absorption spectrum of a two-dimensional electron gas (2DEG) in a magnetic field. We find that that at low temperatures, when the 2DEG is spin polarized, the absorption spectra, which correspond to the creation of spin up or spin down electron, differ in magnitude, linewidth and filling factor dependence. We show that these differences can be explained as resulting from creation of a Mahan exciton in one case, and of a power law Fermi edge singularity in the other.Comment: 4 pages, 4 figures, published in Phys. Rev. Let

Optical absorption to probe the quantum Hall ferromagnet at filling factor ν=1\nu=1

Optical absorption measurements are used to probe the spin polarization in the integer and fractional quantum Hall effect regimes. The system is fully spin polarized only at filling factor $\nu=1$ and at very low temperatures($\sim40$ mK). A small change in filling factor ($\delta\nu\approx\pm0.01$) leads to a significant depolarization. This suggests that the itinerant quantum Hall ferromagnet at $\nu=1$ is surprisingly fragile against increasing temperature, or against small changes in filling factor.Comment: 4 pages, 2 figure

Absorption in the fractional quantum Hall regime: trion dichroism and spin polarization

We present measurements of optical interband absorption in the fractional quantum Hall regime in a GaAs quantum well in the range 0 < nu < 1. We investigate the mechanism of singlet trion absorption, and show that its circular dichroism can be used as a probe of the spin polarization of the ground state of the two-dimensional electron system (2DES). We find that at nu = 1/3 the 2DES is fully spin-polarized. Increasing the filling factor results in a gradual depolarization, with a sharp minimum in the dichroism near nu = 2/3. We find that in the range 0.5 < nu < 0.85 the 2DES remains partially polarized for the broad range of magnetic fields from 2.75 to 11 Tesla. This is consistent with the presence of a mixture of polarized and depolarized regions.Comment: 4 pages, 4 figures (Fig 4 is in color

Chaotic flow and efficient mixing in a micro-channel with a polymer solution

Microscopic flows are almost universally linear, laminar and stationary because Reynolds number, $Re$, is usually very small. That impedes mixing in micro-fluidic devices, which sometimes limits their performance. Here we show that truly chaotic flow can be generated in a smooth micro-channel of a uniform width at arbitrarily low $Re$, if a small amount of flexible polymers is added to the working liquid. The chaotic flow regime is characterized by randomly fluctuating three-dimensional velocity field and significant growth of the flow resistance. Although the size of the polymer molecules extended in the flow may become comparable with the micro-channel width, the flow behavior is fully compatible with that in a table-top channel in the regime of elastic turbulence. The chaotic flow leads to quite efficient mixing, which is almost diffusion independent. For macromolecules, mixing time in this microscopic flow can be three to four orders of magnitude shorter than due to molecular diffusion.Comment: 8 pages,7 figure

pGQL: A probabilistic graphical query language for gene expression time courses

<p>Abstract</p> <p>Background</p> <p>Timeboxes are graphical user interface widgets that were proposed to specify queries on time course data. As queries can be very easily defined, an exploratory analysis of time course data is greatly facilitated. While timeboxes are effective, they have no provisions for dealing with noisy data or data with fluctuations along the time axis, which is very common in many applications. In particular, this is true for the analysis of gene expression time courses, which are mostly derived from noisy microarray measurements at few unevenly sampled time points. From a data mining point of view the robust handling of data through a sound statistical model is of great importance.</p> <p>Results</p> <p>We propose probabilistic timeboxes, which correspond to a specific class of Hidden Markov Models, that constitutes an established method in data mining. Since HMMs are a particular class of probabilistic graphical models we call our method Probabilistic Graphical Query Language. Its implementation was realized in the free software package pGQL. We evaluate its effectiveness in exploratory analysis on a yeast sporulation data set.</p> <p>Conclusions</p> <p>We introduce a new approach to define dynamic, statistical queries on time course data. It supports an interactive exploration of reasonably large amounts of data and enables users without expert knowledge to specify fairly complex statistical models with ease. The expressivity of our approach is by its statistical nature greater and more robust with respect to amplitude and frequency fluctuation than the prior, deterministic timeboxes.</p

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/

Anisotropy and periodicity in the density distribution of electrons in a quantum-well

We use low temperature near-field optical spectroscopy to image the electron density distribution in the plane of a high mobility GaAs quantum well. We find that the electrons are not randomly distributed in the plane, but rather form narrow stripes (width smaller than 150 nm) of higher electron density. The stripes are oriented along the [1-10 ] crystal direction, and are arranged in a quasi-periodic structure. We show that elongated structural mounds, which are intrinsic to molecular beam epitaxy, are responsible for the creation of this electron density texture.Comment: 10 pages, 3 figure