Microscopic calculation of symmetry projected nuclear level densities

We present a quantum Monte Carlo method with exact projection on parity and angular momentum that is free of a sign problem for seniority-conserving nuclear interactions. This technique allows the microscopic calculation of angular momentum and parity-projected nuclear level densities. We present results for the Fe-55, Fe-56, and Fe-57 isotopes. Signatures of the pairing phase transition are observed in the angular momentum distribution of the nuclear level density

The coexistence of superconductivity and ferromagnetism in nano-scale metallic grains

A nano-scale metallic grain in which the single-particle dynamics are chaotic is described by the so-called universal Hamiltonian. This Hamiltonian includes a superconducting pairing term and a ferromagnetic exchange term that compete with each other: pairing correlations favor minimal ground-state spin, while the exchange interaction favors maximal spin polarization. Of particular interest is the fluctuation-dominated regime where the bulk pairing gap is comparable to or smaller than the single-particle mean level spacing and the Bardeen-Cooper-Schrieffer theory of superconductivity breaks down. Superconductivity and ferromagnetism can coexist in this regime. We identify signatures of the competition between superconductivity and ferromagnetism in a number of quantities: ground-state spin, conductance fluctuations when the grain is weakly coupled to external leads and the thermodynamic properties of the grain, such as heat capacity and spin susceptibility.Comment: 13 pages, 13 figures, Proceedings of the Conference on the Frontiers of Quantum and Mesoscopic Thermodynamics (FQMT11

A quantum Monte-Carlo method for fermions, free of discretization errors

In this work we present a novel quantum Monte-Carlo method for fermions, based on an exact decomposition of the Boltzmann operator $exp(-\beta H)$. It can be seen as a synthesis of several related methods. It has the advantage that it is free of discretization errors, and applicable to general interactions, both for ground-state and finite-temperature calculations. The decomposition is based on low-rank matrices, which allows faster calculations. As an illustration, the method is applied to an analytically solvable model (pairing in a degenerate shell) and to the Hubbard model.Comment: 5 pages, 4 figures, submitted to Phys. Rev. Let

Continuous-time spike-based reinforcement learning for working memory tasks

As the brain purportedly employs on-policy reinforcement learning compatible with SARSA learning, and most interesting cognitive tasks require some form of memory while taking place in continuous-time, recent work has developed plausible reinforcement learning schemes that are compatible with these requirements. Lacking is a formulation of both computation and learning in terms of spiking neurons. Such a formulation creates both a closer mapping to biology, and also expresses such learning in terms of asynchronous and sparse neural computation. We present a spiking neural network with memory that learns cognitive tasks in continuous time. Learning is biologically plausibly implemented using the AuGMeNT framework, and we show how separate spiking forward and feedback networks suffice for learning the tasks just as fast the analog CT-AuGMeNT counterpart, while computing efficiently using very few spikes: 1–20 Hz on average

Continuous Time Quantum Monte Carlo Method for Fermions: Beyond Auxiliary Field Framework

Numerically exact continuous-time Quantum Monte Carlo algorithm for finite fermionic systems with non-local interactions is proposed. The scheme is particularly applicable for general multi-band time-dependent correlations since it does not invoke Hubbard-Stratonovich transformation. The present determinantal grand-canonical method is based on a stochastic series expansion for the partition function in the interaction representation. The results for the Green function and for the time-dependent susceptibility of multi-orbital super-symmetric impurity model with a spin-flip interaction are presented

TGF-β-driven reduction of cytoglobin leads to oxidative DNA damage in stellate cells during non-alcoholic steatohepatitis

BACKGROUND: Cytoglobin (CYGB) is a respiratory protein that acts as a scavenger of reactive oxygen species. Although CYGB is expressed uniquely in hepatic stellate cells (HSCs) in the liver, the molecular role of CYGB in human HSC activation and human liver disease remains uncharacterised. The aim of this study was to reveal the mechanism by which TGF-β1/SMAD2 pathway regulates human CYGB promoter and the pathophysiological function of CYGB in human non-alcoholic steatohepatitis (NASH). METHODS: Immunohistochemical staining was performed using human NASH biopsy specimens. Molecular and biochemical analysis were performed by western blotting, quantitative PCR, and luciferase and immunoprecipitation assays. Hydroxyl radicals (•OH) and oxidative DNA damage were measured using an •OH-detectable probe and 8-hydroxy-2’-deoxyguanosine (8-OHdG) ELISA. RESULTS: In culture, TGF-β1-pretreated human hepatic stellate cells (HHSteCs) exhibited lowered CYGB levels together with increased NADPH oxidase 4 (NOX4) expression and were primed for H_{2}O_{2}-triggered OH production and 8-OHdG generation. Overexpression of human CYGB in HHSteCs cancelled out those effects of TGF-β1. Electron spin resonance demonstrated direct •OH-scavenging activity of recombinant human CYGB. Mechanistically, pSMAD2 reduced CYGB transcription by recruiting the M1 repressor isoform of SP3 to the human CYGB promoter at nucleotide positions +2–{+}^13 from the transcription start site. The same repression did not occur on the mouse Cygb promoter. TGF-β1/SMAD3 mediated αSMA and collagen expression. Consistent with those observations in cultured HHSteCs, CYGB expression was negligible, but 8-OHdG was abundant, in activated αSMA^{+}pSMAD2^{+}- and αSMA^{+}NOX4^{+}-positive hepatic stellate cells from human NASH patients with advanced fibrosis. CONCLUSIONS: Downregulation of CYGB by the TGF-β1/pSMAD2/SP3-M1 pathway brings about •OH-dependent oxidative DNA damage in activated hepatic stellate cells from human patients with NASH

Test your surrogate data before you test for nonlinearity

The schemes for the generation of surrogate data in order to test the null hypothesis of linear stochastic process undergoing nonlinear static transform are investigated as to their consistency in representing the null hypothesis. In particular, we pinpoint some important caveats of the prominent algorithm of amplitude adjusted Fourier transform surrogates (AAFT) and compare it to the iterated AAFT (IAAFT), which is more consistent in representing the null hypothesis. It turns out that in many applications with real data the inferences of nonlinearity after marginal rejection of the null hypothesis were premature and have to be re-investigated taken into account the inaccuracies in the AAFT algorithm, mainly concerning the mismatching of the linear correlations. In order to deal with such inaccuracies we propose the use of linear together with nonlinear polynomials as discriminating statistics. The application of this setup to some well-known real data sets cautions against the use of the AAFT algorithm.Comment: 14 pages, 15 figures, submitted to Physical Review

Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient

Background: Investigation of the functioning of the brain in living systems has been a major effort amongst scientists and medical practitioners. Amongst the various disorder of the brain, epilepsy has drawn the most attention because this disorder can affect the quality of life of a person. In this paper we have reinvestigated the EEGs for normal and epileptic patients using surrogate analysis, probability distribution function and Hurst exponent. Results: Using random shuffled surrogate analysis, we have obtained some of the nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys Rev E 2001, 64:061907], for the epileptic patients during seizure. Probability distribution function shows that the activity of an epileptic brain is nongaussian in nature. Hurst exponent has been shown to be useful to characterize a normal and an epileptic brain and it shows that the epileptic brain is long term anticorrelated whereas, the normal brain is more or less stochastic. Among all the techniques, used here, Hurst exponent is found very useful for characterization different cases. Conclusions: In this article, differences in characteristics for normal subjects with eyes open and closed, epileptic subjects during seizure and seizure free intervals have been shown mainly using Hurst exponent. The H shows that the brain activity of a normal man is uncorrelated in nature whereas, epileptic brain activity shows long range anticorrelation.Comment: Keywords:EEG, epilepsy, Correlation dimension, Surrogate analysis, Hurst exponent. 9 page