Partition Functions of Non-Abelian Quantum Hall States

Partition functions of edge excitations are obtained for non-Abelian Hall states in the second Landau level, such as the anti-Read-Rezayi state, the Bonderson-Slingerland hierarchy and the Wen non-Abelian fluid, as well as for the non-Abelian spin-singlet state. The derivation is straightforward and unique starting from the non-Abelian conformal field theory data and solving the modular invariance conditions. The partition functions provide a complete account of the excitation spectrum and are used to describe experiments of Coulomb blockade and thermopower.Comment: 42 pages, 3 figures; published version; minor corrections to sect. 4.

Density Induced Interchange of Anisotropy Axes at Half-Filled High Landau Levels

We observe density induced 90$^{\circ}$ rotations of the anisotropy axes in transport measurements at half-filled high Landau levels in the two dimensional electron system, where stripe states are proposed ($\nu$=9/2, 11/2, etc). Using a field effect transistor, we find the transition density to be $2.9\times10^{11}$cm$^{-2}$ at $\nu$=9/2. Hysteresis is observed in the vicinity of the transition. We construct a phase boundary in the filling factor-magnetic field plane in the regime $4.4<\nu<4.6$. An in-plane magnetic field applied along either anisotropy axis always stabilizes the low density orientation of the stripes.Comment: 1 revtex file, 3 eps figure

Edge-State Velocity and Coherence in a Quantum Hall Fabry-Perot Interferometer

We investigate nonlinear transport in electronic Fabry-Perot interferometers in the integer quantum Hall regime. For interferometers sufficiently large that Coulomb blockade effects are absent, a checkerboard-like pattern of conductance oscillations as a function of dc bias and perpendicular magnetic field is observed. Edge-state velocities extracted from the checkerboard data are compared to model calculations and found to be consistent with a crossover from skipping orbits at low fields to E x B drift at high fields. Suppression of visibility as a function of bias and magnetic field is accounted for by including energy- and field-dependent dephasing of edge electrons.Comment: related papers at http://marcuslab.harvard.ed

Magnetic Gaps related to Spin Glass Order in Fermionic Systems

We provide evidence for spin glass related magnetic gaps in the fermionic density of states below the freezing temperature. Model calculations are presented and proposed to be relevant for explaining resistivity measurements which observe a crossover from variable-range- to activated behavior. The magnetic field dependence of a hardgap and the low temperature decay of the density of states are given. In models with fermion transport a new metal-insulator transition is predicted to occur due to the spin-glass gap, anteceding the spin glass to quantum paramagnet transition at smaller spin density. Important fluctuation effects due to finite range frustrated interactions are estimated and discussed.Comment: 4 pages, 1 Postscript figure, revised version accepted for publication in Physical Review Letter

Statistical pairwise interaction model of stock market

Financial markets are a classical example of complex systems as they comprise many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or others are agent-based models with rules designed in order to recover some empirical behaviours. Here we show that the pairwise model is actually a statistically consistent model with observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach based only on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviours, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.Comment: 11 pages, 8 figure

Open Database of Epileptic EEG with MRI and Postoperational Assessment of Foci—a Real World Verification for the EEG Inverse Solutions

This paper introduces a freely accessible database http://eeg.pl/epi, containing 23 datasets from patients diagnosed with and operated on for drug-resistant epilepsy. This was collected as part of the clinical routine at the Warsaw Memorial Child Hospital. Each record contains (1) pre-surgical electroencephalography (EEG) recording (10–20 system) with inter-ictal discharges marked separately by an expert, (2) a full set of magnetic resonance imaging (MRI) scans for calculations of the realistic forward models, (3) structural placement of the epileptogenic zone, recognized by electrocorticography (ECoG) and post-surgical results, plotted on pre-surgical MRI scans in transverse, sagittal and coronal projections, (4) brief clinical description of each case. The main goal of this project is evaluation of possible improvements of localization of epileptic foci from the surface EEG recordings. These datasets offer a unique possibility for evaluating different EEG inverse solutions. We present preliminary results from a subset of these cases, including comparison of different schemes for the EEG inverse solution and preprocessing. We report also a finding which relates to the selective parametrization of single waveforms by multivariate matching pursuit, which is used in the preprocessing for the inverse solutions. It seems to offer a possibility of tracing the spatial evolution of seizures in time

Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market

What are the dominant stocks which drive the correlations present among stocks traded in a stock market? Can a correlation analysis provide an answer to this question? In the past, correlation based networks have been proposed as a tool to uncover the underlying backbone of the market. Correlation based networks represent the stocks and their relationships, which are then investigated using different network theory methodologies. Here we introduce a new concept to tackle the above question—the partial correlation network. Partial correlation is a measure of how the correlation between two variables, e.g., stock returns, is affected by a third variable. By using it we define a proxy of stock influence, which is then used to construct partial correlation networks. The empirical part of this study is performed on a specific financial system, namely the set of 300 highly capitalized stocks traded at the New York Stock Exchange, in the time period 2001–2003. By constructing the partial correlation network, unlike the case of standard correlation based networks, we find that stocks belonging to the financial sector and, in particular, to the investment services sub-sector, are the most influential stocks affecting the correlation profile of the system. Using a moving window analysis, we find that the strong influence of the financial stocks is conserved across time for the investigated trading period. Our findings shed a new light on the underlying mechanisms and driving forces controlling the correlation profile observed in a financial market

Biallelic VARS variants cause developmental encephalopathy with microcephaly that is recapitulated in vars knockout zebrafish

Aminoacyl tRNA synthetases (ARSs) link specific amino acids with their cognate transfer RNAs in a critical early step of protein translation. Mutations in ARSs have emerged as a cause of recessive, often complex neurological disease traits. Here we report an allelic series consisting of seven novel and two previously reported biallelic variants in valyl-tRNA synthetase (VARS) in ten patients with a developmental encephalopathy with microcephaly, often associated with early-onset epilepsy. In silico, in vitro, and yeast complementation assays demonstrate that the underlying pathomechanism of these mutations is most likely a loss of protein function. Zebrafish modeling accurately recapitulated some of the key neurological disease traits. These results provide both genetic and biological insights into neurodevelopmental disease and pave the way for further in-depth research on ARS related recessive disorders and precision therapies