A stable Algebraic Spin Liquid in a Hubbard model

We show the existence of a stable Algebraic Spin Liquid (ASL) phase in a Hubbard model defined on a honeycomb lattice with spin-dependent hopping that breaks time-reversal symmetry. The effective spin model is the Kitaev model for large on-site repulsion. The gaplessness of the emergent Majorana fermions is protected by the time reversal (TR) invariance of this model. We prove that the effective spin model is TR invariant in the entire Mott phase thus ensuring the stability of the ASL. The model can be physically realized in cold atom systems and we propose experimental signals of the ASL.Comment: Published in PR

Self-Organization in Communication Networks

We develop a dynamic model to study the formation of communication networks. In this model, individuals periodically make decisions concerning the continuation of existing information links and the formation of new information links, with their cohorts. These decisions trade off the costs of forming and maintaining links against the potential rewards from doing so. We analyze the long run behavior of this process of link formation and dissolution. Our results establish that this process always self-organizes, i.e., irrespective of the number of agents, and the initial network, the dynamic process converges to a limit social communication network with probability one. Furthermore, we prove that the limiting network is invariably either a wheel network or the empty network. We show in the (corresponding) static network formation game that, while a variety of architectures can be sustained in equilibrium, the wheel is the unique efficient architecture for the interesting class of parameters. Thus, our results imply that the dynamics have strong equilibrium selection properties

Learning from Neighbors

When payoffs from different actions are unknown, agents use their own past experience as well as the experience of their neighbors to guide their current decision making. This paper develops a general framework to study the relationship between the structure of information flows and the process of social learning. We show that in a connected society, local learning ensures that all agents obtain the same utility, in the long run. We develop conditions under which this utility is the maximal attainable, i.e. optimal actions are adopted. This analysis identifies a structural property of information structures -- local independence -- which greatly facilitates social learning. Our analysis also suggests that there exists a negative relationship between the degree of social integration and the likelihood of diversity. Simulations of the model generate spatial and temporal patterns of adoption that are consistent with empirical work

Self-Organization in Communication Networks

We develop a dynamic model to study the formation of communication networks. In this model, individuals periodically make decisions concerning the continuation of existing information links and the formation of new information links, with their cohorts. These decisions trade off the costs of forming and maintaining links against the potential rewards from doing so. We analyze the long run behavior of this process of link formation and dissolution. Our results establish that this process always self-organizes, i.e., irrespective of the number of agents, and the initial network, the dynamic process converges to a limit social communication network with probability one. Furthermore, we prove that the limiting network is invariably either a wheel network or the empty network. We show in the (corresponding) static network formation game that, while a variety of architectures can be sustained in equilibrium, the wheel is the unique efficient architecture for the interesting class of parameters. Thus, our results imply that the dynamics have strong equilibrium selection properties.networks;learning;coordination;self-organization;path-dependence

Specific heat of robust Nb2PdS5 superconductor

We report specific heat under different magnetic fields for recently discovered quasi-one dimensional Nb2PdS5 superconductor. The studied compound is superconducting below 6 K. Nb2PdS5 is quite robust against magnetic field with dHc/dT of -42 kOe/K. The estimated upper critical field [Hc2(0)] is 190 kOe, clearly surpassing the Pauli-paramagnetic limit of 1.84Tc. Low temperature heat capacity in superconducting state of Nb2PdS5 under different magnetic fields showed s-wave superconductivity with two different gaps. Two quasi-linear slopes in Somerfield-coefficient as a function of applied magnetic field and two band behavior of the electronic heat capacity demonstrate that Nb2PdS5 is a multiband su-perconductor in weak coupling limit with deltagamma/deltaTc=0.9.Comment: 4 pages text Figs. Short Letter MS. Letter-J. Sup. & Novel Ma

Validating Network Value of Influencers by means of Explanations

Recently, there has been significant interest in social influence analysis. One of the central problems in this area is the problem of identifying influencers, such that by convincing these users to perform a certain action (like buying a new product), a large number of other users get influenced to follow the action. The client of such an application is a marketer who would target these influencers for marketing a given new product, say by providing free samples or discounts. It is natural that before committing resources for targeting an influencer the marketer would be interested in validating the influence (or network value) of influencers returned. This requires digging deeper into such analytical questions as: who are their followers, on what actions (or products) they are influential, etc. However, the current approaches to identifying influencers largely work as a black box in this respect. The goal of this paper is to open up the black box, address these questions and provide informative and crisp explanations for validating the network value of influencers. We formulate the problem of providing explanations (called PROXI) as a discrete optimization problem of feature selection. We show that PROXI is not only NP-hard to solve exactly, it is NP-hard to approximate within any reasonable factor. Nevertheless, we show interesting properties of the objective function and develop an intuitive greedy heuristic. We perform detailed experimental analysis on two real world datasets - Twitter and Flixster, and show that our approach is useful in generating concise and insightful explanations of the influence distribution of users and that our greedy algorithm is effective and efficient with respect to several baselines

Learning from Neighbors

When payoffs from different actions are unknown, agents use their own past experience as well as the experience of their neighbors to guide their current decision making. This paper develops a general framework to study the relationship between the structure of information flows and the process of social learning.We show that in a connected society, local learning ensures that all agents obtain the same utility, in the long run. We develop conditions under which this utility is the maximal attainable, i.e. optimal actions are adopted.This analysis identifies a structural property of information structures -- local independence -- which greatly facilitates social learning. Our analysis also suggests that there exists a negative relationship between the degree of social integration and the likelihood of diversity.Simulations of the model generate spatial and temporal patterns of adoption that are consistent with empirical work.diversity;diffusion;social integration;Royal Family;conformism;connected societies;locally independent agents

Nuclear Matter in Intense Magnetic Field and Weak Processes

We study the effect of magnetic field on the dominant neutrino emission processes in neutron stars.The processes are first calculated for the case when the magnetic field does not exceed the critical value to confine electrons to the lowest Landau state.We then consider the more important case of intense magnetic field to evaluate the direct URCA and the neutronisation processes. In order to estimate the effect we derive the composition of cold nuclear matter at high densities and in beta equilibrium, a situation appropriate for neutron stars. The hadronic interactions are incorporated through the exchange of scalar and vector mesons in the frame work of relativistic mean field theory. In addition the effects of anomalous magnetic moments of nucleons are also considered.Comment: 29 pages (LaTeX) including 7 figure

PdTe a 4.5K Type II BCS Superconductor

We report on the structure and physical properties of bulk Palladium Tellurium superconductor, which is synthesized via quartz vacuum encapsulation technique at 750 C. The as synthesized compound is crystallized in hexagonal crystal structure. Magnetization and Magneto-transport measurements provided the values of lower and upper critical field to be 250 and 1200 Gauss respectively at 2 Kelvin. The Coherence length and GL parameter are estimated from the experimentally determined upper and lower critical fields, which are 45 nm and 1.48 respectively. The jump in Cp(T) at Tc is found to be 1.33 and the Debye temperature and electronic specific heat constant are 203 Kelvin and 6.01mJ/mole-K2 respectively.Comment: 13 pages Text + Figs: Accepted in Sup. Sci. and Tec