4,546 research outputs found
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
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
Development of conceptual groundwater flow model for Pali Area, India
Development of representative conceptual groundwater flow model is an important step before translating it into a numerical model. In this paper, a methodology for development of conceptual groundwater flow model has been presented in which spatially distributed values for groundwater recharge has been utilized instead of lump sum average values of recharge normally obtained by water budgeting method. The study also extensively uses GIS for preprocessing of hydrological, hydrogeological and geological data. In our view, the methodology presented here provides better tools for building a conceptual model for tackling groundwater modeling problems. Keywords: Groundwater flow model, conceptual model, groundwater recharge, spatial distribution, Geographical Information System
Bulk Viscosity of Magnetized Neutron Star Matter
We study the effect of magnetic field on the bulk viscosity of nuclear matter
in neutron stars. We employ the framework of relativistic mean field theory to
observe the dense nuclear matter in neutron stars. The effects are first
studied for the case when the magnetic field does not exceed the critical value
to confine the electrons to the lowest Landau levels. We then consider the case
of intense magnetic field to evaluate viscosity for the URCA processes and show
that the inequality is no longer required to
be satisfied for the URCA processes to proceed.Comment: Latex 2e file with four postscripts figure
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
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
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
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