Controlled dephasing of a quantum dot in the Kondo regime

Kondo correlation in a spin polarized quantum dot (QD) results from the dynamical formation of a spin singlet between the dot's net spin and a Kondo cloud of electrons in the leads, leading to enhanced coherent transport through the QD. We demonstrate here significant dephasing of such transport by coupling the QD and its leads to potential fluctuations in a near by 'potential detector'. The qualitative dephasing is similar to that of a QD in the Coulomb Blockade regime in spite of the fact that the mechanism of transport is quite different. A much stronger than expected suppression of coherent transport is measured, suggesting that dephasing is induced mostly in the 'Kondo cloud' of electrons within the leads and not in the QD.Comment: to be published in PR

People and networks: psychology, structure, and motivations

© 2005 Dr. Yuval KalishFrom title page: Submitted in total fulfillment of the requirements of the combined Masters of Psychology and Doctor of Philosophy degreesThis thesis argues that the anticategorical imperative (Emirbayer & Goodwin, 1994) limits our understanding of social networks. We suggest that the assumption that social network processes play out solely in terms of "self-organising" processes may not capture the complexity of network phenomenon, because similar types of network structures may arise under different actor motivations, with implications for how these structures are utilised and how the network continues to evolve. In a series of four studies, we examine how actors' psychological attributes, identity, values, and psychological strain enhance our understanding of network phenomena. In the first three studies, we examine the propensity of actors with specific psychological predispositions to structure their network in certain ways. In the Study 4, we examine how network structures affect the individuals occupying them. In Study 1 we develop a measurement instrument that we argue is better suited than the available network metrics to examine egocentric networks. We find using this instrument that psychological characteristics are related to the way 125 University of Melbourne students structure their local network. In Studies 2 and 3 we expand the notion of structural holes. Following Simmel (1955), we differentiate between two types of structural holes. Using two small case-studies conducted in Israel, we identify two network orientations (peace-building and entrepreneurial) that relate to individuals who seek and occupy structural holes. In study 4 we examine the psychological distress arising from occupying different triadic configurations of signed (and missing) ties. Using a community sample of 332 people, our results suggest that balance theory may be flawed. In the Discussion, we integrate the findings from the four Studies. We propose a classification of individuals who occupy structural holes based on characteristics of their alters and the network orientation of the broker. We examine the implications of this classification to the evolution of network structures, to identity formation and to leadership

An introduction to exponential random graph (p*) models for social networks

This article provides an introductory summary to the formulation and application of exponential random graph models for social networks. The possible ties among nodes of a network are regarded as random variables, and assumptions about dependencies among these random tie variables determine the general form of the exponential random graph model for the network. Examples of different dependence assumptions and their associated models are given, including Bernoulli, dyad-independent and Markov random graph models. The incorporation of actor attributes in social selection models is also reviewed. Newer, more complex dependence assumptions are briefly outlined. Estimation procedures are discussed, including new methods for Monte Carlo maximum likelihood estimation. We foreshadow the discussion taken up in other papers in this special edition: that the homogeneous Markov random graph models of Frank and Strauss [Frank, O., Strauss, D., 1986. Markov graphs. Journal of the American Statistical Association 81, 832-842] are not appropriate for many observed networks, whereas the new model specifications of Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handock, M. New specifications for exponential random graph models. Sociological Methodology, in press] offer substantial improvement

Megakaryocyte- and erythroblast-specific cell-free DNA patterns in plasma and platelets reflect thrombopoiesis and erythropoiesis levels

Abstract Circulating cell-free DNA (cfDNA) fragments are a biological analyte with extensive utility in diagnostic medicine. Understanding the source of cfDNA and mechanisms of release is crucial for designing and interpreting cfDNA-based liquid biopsy assays. Using cell type-specific methylation markers as well as genome-wide methylation analysis, we determine that megakaryocytes, the precursors of anuclear platelets, are major contributors to cfDNA (~26%), while erythroblasts contribute 1–4% of cfDNA in healthy individuals. Surprisingly, we discover that platelets contain genomic DNA fragments originating in megakaryocytes, contrary to the general understanding that platelets lack genomic DNA. Megakaryocyte-derived cfDNA is increased in pathologies involving increased platelet production (Essential Thrombocythemia, Idiopathic Thrombocytopenic Purpura) and decreased upon reduced platelet production due to chemotherapy-induced bone marrow suppression. Similarly, erythroblast cfDNA is reflective of erythrocyte production and is elevated in patients with thalassemia. Megakaryocyte- and erythroblast-specific DNA methylation patterns can thus serve as biomarkers for pathologies involving increased or decreased thrombopoiesis and erythropoiesis, which can aid in determining the etiology of aberrant levels of erythrocytes and platelets