1,616 research outputs found
Magnetic-film atom chip with 10 m period lattices of microtraps for quantum information science with Rydberg atoms
We describe the fabrication and construction of a setup for creating lattices
of magnetic microtraps for ultracold atoms on an atom chip. The lattice is
defined by lithographic patterning of a permanent magnetic film. Patterned
magnetic-film atom chips enable a large variety of trapping geometries over a
wide range of length scales. We demonstrate an atom chip with a lattice
constant of 10 m, suitable for experiments in quantum information science
employing the interaction between atoms in highly-excited Rydberg energy
levels. The active trapping region contains lattice regions with square and
hexagonal symmetry, with the two regions joined at an interface. A structure of
macroscopic wires, cut out of a silver foil, was mounted under the atom chip in
order to load ultracold Rb atoms into the microtraps. We demonstrate
loading of atoms into the square and hexagonal lattice sections simultaneously
and show resolved imaging of individual lattice sites. Magnetic-film lattices
on atom chips provide a versatile platform for experiments with ultracold
atoms, in particular for quantum information science and quantum simulation.Comment: 7 pages, 7 figure
Studying Paths of Participation in Viral Diffusion Process
Authors propose a conceptual model of participation in viral diffusion
process composed of four stages: awareness, infection, engagement and action.
To verify the model it has been applied and studied in the virtual social chat
environment settings. The study investigates the behavioral paths of actions
that reflect the stages of participation in the diffusion and presents
shortcuts, that lead to the final action, i.e. the attendance in a virtual
event. The results show that the participation in each stage of the process
increases the probability of reaching the final action. Nevertheless, the
majority of users involved in the virtual event did not go through each stage
of the process but followed the shortcuts. That suggests that the viral
diffusion process is not necessarily a linear sequence of human actions but
rather a dynamic system.Comment: In proceedings of the 4th International Conference on Social
Informatics, SocInfo 201
Semiring and semimodule issues in MV-algebras
In this paper we propose a semiring-theoretic approach to MV-algebras based
on the connection between such algebras and idempotent semirings - such an
approach naturally imposing the introduction and study of a suitable
corresponding class of semimodules, called MV-semimodules.
We present several results addressed toward a semiring theory for
MV-algebras. In particular we show a representation of MV-algebras as a
subsemiring of the endomorphism semiring of a semilattice, the construction of
the Grothendieck group of a semiring and its functorial nature, and the effect
of Mundici categorical equivalence between MV-algebras and lattice-ordered
Abelian groups with a distinguished strong order unit upon the relationship
between MV-semimodules and semimodules over idempotent semifields.Comment: This version contains some corrections to some results at the end of
Section
Activating Generalized Fuzzy Implications from Galois Connections
This paper deals with the relation between fuzzy implications and Galois connections, trying to raise the awareness that the fuzzy implications are indispensable to generalise Formal Concept Analysis. The concrete goal of the paper is to make evident that Galois connections, which are at the heart of some of the generalizations of Formal Concept Analysis, can be interpreted as fuzzy incidents. Thus knowledge processing, discovery, exploration and visualization as well as data mining are new research areas for fuzzy implications as they are areas where Formal Concept Analysis has a niche.F.J. Valverde-Albacete—was partially supported by EU FP7 project LiMoSINe, (contract 288024). C. Peláez-Moreno—was partially supported by the Spanish Government-CICYT project 2011-268007/TEC.Publicad
Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment
We present a simulation-based study using deep convolutional neural networks
(DCNNs) to identify neutrino interaction vertices in the MINERvA passive
targets region, and illustrate the application of domain adversarial neural
networks (DANNs) in this context. DANNs are designed to be trained in one
domain (simulated data) but tested in a second domain (physics data) and
utilize unlabeled data from the second domain so that during training only
features which are unable to discriminate between the domains are promoted.
MINERvA is a neutrino-nucleus scattering experiment using the NuMI beamline at
Fermilab. -dependent cross sections are an important part of the physics
program, and these measurements require vertex finding in complicated events.
To illustrate the impact of the DANN we used a modified set of simulation in
place of physics data during the training of the DANN and then used the label
of the modified simulation during the evaluation of the DANN. We find that deep
learning based methods offer significant advantages over our prior track-based
reconstruction for the task of vertex finding, and that DANNs are able to
improve the performance of deep networks by leveraging available unlabeled data
and by mitigating network performance degradation rooted in biases in the
physics models used for training.Comment: 41 page
First evidence of coherent meson production in neutrino-nucleus scattering
Neutrino-induced charged-current coherent kaon production,
, is a rare, inelastic electroweak process
that brings a on shell and leaves the target nucleus intact in its ground
state. This process is significantly lower in rate than neutrino-induced
charged-current coherent pion production, because of Cabibbo suppression and a
kinematic suppression due to the larger kaon mass. We search for such events in
the scintillator tracker of MINERvA by observing the final state ,
and no other detector activity, and by using the kinematics of the final state
particles to reconstruct the small momentum transfer to the nucleus, which is a
model-independent characteristic of coherent scattering. We find the first
experimental evidence for the process at significance.Comment: added ancillary file with information about the six kaon candidate
Measurement of Partonic Nuclear Effects in Deep-Inelastic Neutrino Scattering using MINERvA
The MINERvA collaboration reports a novel study of neutrino-nucleus
charged-current deep inelastic scattering (DIS) using the same neutrino beam
incident on targets of polystyrene, graphite, iron, and lead. Results are
presented as ratios of C, Fe, and Pb to CH. The ratios of total DIS cross
sections as a function of neutrino energy and flux-integrated differential
cross sections as a function of the Bjorken scaling variable x are presented in
the neutrino-energy range of 5 - 50 GeV. Good agreement is found between the
data and predicted ratios, based on charged-lepton nucleus scattering, at
medium x and low neutrino energies. However, the data rate appears depleted in
the vicinity of the nuclear shadowing region, x < 0.1. This apparent deficit,
reflected in the DIS cross-section ratio at high neutrino energy , is
consistent with previous MINERvA observations and with the predicted onset of
nuclear shadowing with the the axial-vector current in neutrino scattering
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