Exploring out-of-equilibrium quantum magnetism and thermalization in a spin-3 many-body dipolar lattice system

Understanding quantum thermalization through entanglement build-up in isolated quantum systems addresses fundamental questions on how unitary dynamics connects to statistical physics. Here, we study the spin dynamics and approach towards local thermal equilibrium of a macroscopic ensemble of S = 3 spins prepared in a pure coherent spin state, tilted compared to the magnetic field, under the effect of magnetic dipole-dipole interactions. The experiment uses a unit filled array of 104 chromium atoms in a three dimensional optical lattice, realizing the spin-3 XXZ Heisenberg model. The buildup of quantum correlation during the dynamics, especially as the angle approaches pi/2, is supported by comparison with an improved numerical quantum phase-space method and further confirmed by the observation that our isolated system thermalizes under its own dynamics, reaching a steady state consistent with the one extracted from a thermal ensemble with a temperature dictated from the system's energy. This indicates a scenario of quantum thermalization which is tied to the growth of entanglement entropy. Although direct experimental measurements of the Renyi entropy in our macroscopic system are unfeasible, the excellent agreement with the theory, which can compute this entropy, does indicate entanglement build-up.Comment: 12 figure

Many-body localization in a quantum simulator with programmable random disorder

When a system thermalizes it loses all local memory of its initial conditions. This is a general feature of open systems and is well described by equilibrium statistical mechanics. Even within a closed (or reversible) quantum system, where unitary time evolution retains all information about its initial state, subsystems can still thermalize using the rest of the system as an effective heat bath. Exceptions to quantum thermalization have been predicted and observed, but typically require inherent symmetries or noninteracting particles in the presence of static disorder. The prediction of many-body localization (MBL), in which disordered quantum systems can fail to thermalize in spite of strong interactions and high excitation energy, was therefore surprising and has attracted considerable theoretical attention. Here we experimentally generate MBL states by applying an Ising Hamiltonian with long-range interactions and programmably random disorder to ten spins initialized far from equilibrium. We observe the essential signatures of MBL: memory retention of the initial state, a Poissonian distribution of energy level spacings, and entanglement growth in the system at long times. Our platform can be scaled to higher numbers of spins, where detailed modeling of MBL becomes impossible due to the complexity of representing such entangled quantum states. Moreover, the high degree of control in our experiment may guide the use of MBL states as potential quantum memories in naturally disordered quantum systems.Comment: 9 pages, 9 figure

Order of Magnitude Smaller Limit on the Electric Dipole Moment of the Electron

The Standard Model of particle physics is known to be incomplete. Extensions to the Standard Model, such as weak-scale supersymmetry, posit the existence of new particles and interactions that are asymmetric under time reversal (T) and nearly always predict a small yet potentially measurable electron electric dipole moment (EDM), d_e, in the range of 10^(−27) to 10^(−30) e·cm. The EDM is an asymmetric charge distribution along the electron spin (S) that is also asymmetric under T. Using the polar molecule thorium monoxide, we measured d_e = (–2.1±3.7_(stat)±2.5_(syst)) × 10−29 e·cm. This corresponds to an upper limit of ❘d_e❘ < 8.7 × 10^(−29) e·cm with 90% confidence, an order of magnitude improvement in sensitivity relative to the previous best limit. Our result constrains T-violating physics at the TeV energy scale

Coherent Control of Quantum Dynamics with Sequences of Unitary Phase-Kick Pulses

Coherent optical control schemes exploit the coherence of laser pulses to change the phases of interfering dynamical pathways in order to manipulate dynamical processes. These active control methods are closely related to dynamical decoupling techniques, popularized in the field of Quantum Information. Inspired by Nuclear Magnetic Resonance (NMR) spectroscopy, dynamical decoupling methods apply sequences of unitary operations to modify the interference phenomena responsible for the system dynamics thus also belonging to the general class of coherent control techniques. Here we review related developments in the fields of coherent optical control and dynamical decoupling, with emphasis on control of tunneling and decoherence in general model systems. Considering recent experimental breakthroughs in the demonstration of active control of a variety of systems, we anticipate that the reviewed coherent control scenarios and dynamical decoupling methods should raise significant experimental interest.Comment: 52 pages, 7 figure

Functional Diversity and Structural Disorder in the Human Ubiquitination Pathway

The ubiquitin-proteasome system plays a central role in cellular regulation and protein quality control (PQC). The system is built as a pyramid of increasing complexity, with two E1 (ubiquitin activating), few dozen E2 (ubiquitin conjugating) and several hundred E3 (ubiquitin ligase) enzymes. By collecting and analyzing E3 sequences from the KEGG BRITE database and literature, we assembled a coherent dataset of 563 human E3s and analyzed their various physical features. We found an increase in structural disorder of the system with multiple disorder predictors (IUPred - E1: 5.97%, E2: 17.74%, E3: 20.03%). E3s that can bind E2 and substrate simultaneously (single subunit E3, ssE3) have significantly higher disorder (22.98%) than E3s in which E2 binding (multi RING-finger, mRF, 0.62%), scaffolding (6.01%) and substrate binding (adaptor/substrate recognition subunits, 17.33%) functions are separated. In ssE3s, the disorder was localized in the substrate/adaptor binding domains, whereas the E2-binding RING/HECT-domains were structured. To demonstrate the involvement of disorder in E3 function, we applied normal modes and molecular dynamics analyses to show how a disordered and highly flexible linker in human CBL (an E3 that acts as a regulator of several tyrosine kinase-mediated signalling pathways) facilitates long-range conformational changes bringing substrate and E2-binding domains towards each other and thus assisting in ubiquitin transfer. E3s with multiple interaction partners (as evidenced by data in STRING) also possess elevated levels of disorder (hubs, 22.90% vs. non-hubs, 18.36%). Furthermore, a search in PDB uncovered 21 distinct human E3 interactions, in 7 of which the disordered region of E3s undergoes induced folding (or mutual induced folding) in the presence of the partner. In conclusion, our data highlights the primary role of structural disorder in the functions of E3 ligases that manifests itself in the substrate/adaptor binding functions as well as the mechanism of ubiquitin transfer by long-range conformational transitions. © 2013 Bhowmick et al

Use of multi-trait and random regression models to identify genetic variation in tolerance to porcine reproductive and respiratory syndrome virus

Background: A host can adopt two response strategies to infection: resistance (reduce pathogen load) and tolerance (minimize impact of infection on performance). Both strategies may be under genetic control and could thus be targeted for genetic improvement. Although there is evidence that supports a genetic basis for resistance to porcine reproductive and respiratory syndrome (PRRS), it is not known whether pigs also differ genetically in tolerance. We determined to what extent pigs that have been shown to vary genetically in resistance to PRRS also exhibit genetic variation in tolerance. Multi-trait linear mixed models and random regression sire models were fitted to PRRS Host Genetics Consortium data from 1320 weaned pigs (offspring of 54 sires) that were experimentally infected with a virulent strain of PRRS virus to obtain genetic parameter estimates for resistance and tolerance. Resistance was defined as the inverse of within-host viral load (VL) from 0 to 21 (VL21) or 0 to 42 (VL42) days post-infection and tolerance as the slope of the reaction-norm of average daily gain (ADG21, ADG42) on VL21 or VL42. Results: Multi-trait analysis of ADG associated with either low or high VL was not indicative of genetic variation in tolerance. Similarly, random regression models for ADG21 and ADG42 with a tolerance slope fitted for each sire did not result in a better fit to the data than a model without genetic variation in tolerance. However, the distribution of data around average VL suggested possible confounding between level and slope estimates of the regression lines. Augmenting the data with simulated growth rates of non-infected half-sibs (ADG0) helped resolve this statistical confounding and indicated that genetic variation in tolerance to PRRS may exist if genetic correlations between ADG0 and ADG21 or ADG42 are low to moderate. Conclusions: Evidence for genetic variation in tolerance of pigs to PRRS was weak when based on data from infected piglets only. However, simulations indicated that genetic variance in tolerance may exist and could be detected if comparable data on uninfected relatives were available. In conclusion, of the two defense strategies, genetics of tolerance is more difficult to elucidate than genetics of resistance.</p

Self organising maps for visualising and modelling

The paper describes the motivation of SOMs (Self Organising Maps) and how they are generally more accessible due to the wider available modern, more powerful, cost-effective computers. Their advantages compared to Principal Components Analysis and Partial Least Squares are discussed. These allow application to non-linear data, are not so dependent on least squares solutions, normality of errors and less influenced by outliers. In addition there are a wide variety of intuitive methods for visualisation that allow full use of the map space. Modern problems in analytical chemistry include applications to cultural heritage studies, environmental, metabolomic and biological problems result in complex datasets. Methods for visualising maps are described including best matching units, hit histograms, unified distance matrices and component planes. Supervised SOMs for classification including multifactor data and variable selection are discussed as is their use in Quality Control. The paper is illustrated using four case studies, namely the Near Infrared of food, the thermal analysis of polymers, metabolomic analysis of saliva using NMR, and on-line HPLC for pharmaceutical process monitoring

Post hoc pattern matching: assigning significance to statistically defined expression patterns in single channel microarray data

<p>Abstract</p> <p>Background</p> <p>Researchers using RNA expression microarrays in experimental designs with more than two treatment groups often identify statistically significant genes with ANOVA approaches. However, the ANOVA test does not discriminate which of the multiple treatment groups differ from one another. Thus, <it>post hoc </it>tests, such as linear contrasts, template correlations, and pairwise comparisons are used. Linear contrasts and template correlations work extremely well, especially when the researcher has <it>a priori </it>information pointing to a particular pattern/template among the different treatment groups. Further, all pairwise comparisons can be used to identify particular, treatment group-dependent patterns of gene expression. However, these approaches are biased by the researcher's assumptions, and some treatment-based patterns may fail to be detected using these approaches. Finally, different patterns may have different probabilities of occurring by chance, importantly influencing researchers' conclusions about a pattern and its constituent genes.</p> <p>Results</p> <p>We developed a four step, <it>post hoc </it>pattern matching (PPM) algorithm to automate single channel gene expression pattern identification/significance. First, 1-Way Analysis of Variance (ANOVA), coupled with <it>post hoc </it>'all pairwise' comparisons are calculated for all genes. Second, for each ANOVA-significant gene, all pairwise contrast results are encoded to create unique pattern ID numbers. The # genes found in each pattern in the data is identified as that pattern's 'actual' frequency. Third, using Monte Carlo simulations, those patterns' frequencies are estimated in random data ('random' gene pattern frequency). Fourth, a Z-score for overrepresentation of the pattern is calculated ('actual' against 'random' gene pattern frequencies). We wrote a Visual Basic program (StatiGen) that automates PPM procedure, constructs an Excel workbook with standardized graphs of overrepresented patterns, and lists of the genes comprising each pattern. The visual basic code, installation files for StatiGen, and sample data are available as supplementary material.</p> <p>Conclusion</p> <p>The PPM procedure is designed to augment current microarray analysis procedures by allowing researchers to incorporate all of the information from post hoc tests to establish unique, overarching gene expression patterns in which there is no overlap in gene membership. In our hands, PPM works well for studies using from three to six treatment groups in which the researcher is interested in treatment-related patterns of gene expression. Hardware/software limitations and extreme number of theoretical expression patterns limit utility for larger numbers of treatment groups. Applied to a published microarray experiment, the StatiGen program successfully flagged patterns that had been manually assigned in prior work, and further identified other gene expression patterns that may be of interest. Thus, over a moderate range of treatment groups, PPM appears to work well. It allows researchers to assign statistical probabilities to patterns of gene expression that fit <it>a priori </it>expectations/hypotheses, it preserves the data's ability to show the researcher interesting, yet unanticipated gene expression patterns, and assigns the majority of ANOVA-significant genes to non-overlapping patterns.</p

The Effect of Sensory Uncertainty Due to Amblyopia (Lazy Eye) on the Planning and Execution of Visually-Guided 3D Reaching Movements

Background: Impairment of spatiotemporal visual processing in amblyopia has been studied extensively, but its effects on visuomotor tasks have rarely been examined. Here, we investigate how visual deficits in amblyopia affect motor planning and online control of visually-guided, unconstrained reaching movements. Methods: Thirteen patients with mild amblyopia, 13 with severe amblyopia and 13 visually-normal participants were recruited. Participants reached and touched a visual target during binocular and monocular viewing. Motor planning was assessed by examining spatial variability of the trajectory at 50–100 ms after movement onset. Online control was assessed by examining the endpoint variability and by calculating the coefficient of determination (R 2) which correlates the spatial position of the limb during the movement to endpoint position. Results: Patients with amblyopia had reduced precision of the motor plan in all viewing conditions as evidenced by increased variability of the reach early in the trajectory. Endpoint precision was comparable between patients with mild amblyopia and control participants. Patients with severe amblyopia had reduced endpoint precision along azimuth and elevation during amblyopic eye viewing only, and along the depth axis in all viewing conditions. In addition, they had significantly higher R 2 values at 70 % of movement time along the elevation and depth axes during amblyopic eye viewing. Conclusion: Sensory uncertainty due to amblyopia leads to reduced precision of the motor plan. The ability to implemen

The Role of the p38 MAPK Signaling Pathway in High Glucose-Induced Epithelial-Mesenchymal Transition of Cultured Human Renal Tubular Epithelial Cells

Epithelial-mesenchymal transition of tubular epithelial cells, which is characterized by a loss of epithelial cell characteristics and a gain of ECM-producing myofibroblast characteristics, is an essential mechanism that is involved in tubulointerstitial fibrosis, an important component of the renal injury that is associated with diabetic nephropathy. Under diabetic conditions, p38 MAPK activation has been reported in glomeruli and mesangial cells; however, studies on p38 MAPK in TECs are lacking. In this study, the role of p38 MAPK in AP-1 activation and in the EMT in the human proximal tubular epithelial cell line (HK-2) under high glucose concentration conditions is investigated.A vector for small interfering RNA that targets p38 MAPK was constructed; the cells were then either transfected with p38 siRNA or pretreated with a chemical inhibitor of AP-1 and incubated with low glucose plus TGF-β1 or high glucose for 48 h. Cells that were not transfected or pretreated and were exposed to low glucose with or without TGF-β1 or high glucose for 48 h were considered to be the controls. We found that high glucose induced an increase in TGF-β1. And high glucose-induced p38 MAPK activation was inhibited by p38 siRNA (P<0.05). A significant decline in E-cadherin and CK expression and a notable increase in vimentin and α-SMA were detected when exposed to low glucose with TGF-β1 or high glucose, and a significant raise of secreted fibronectin were detected when exposed to high glucose; whereas these changes were reversed when the cells were treated with p38 siRNA or AP-1 inhibitor (P<0.05). AP-1 activity levels and Snail expression were up-regulated under high glucose conditions but were markedly down-regulated through knockdown of p38 MAPK with p38 siRNA or pretreatment with AP-1 inhibitor (P<0.05).This study suggests that p38 MAPK may play an important role in the high glucose-induced EMT by activating AP-1 in tubular epithelial cells