103,754 research outputs found
Standard Model Contributions to the Neutrino Index of Refraction in the Early Universe
With the standard electroweak interactions, the lowest-order coherent forward
scattering amplitudes of neutrinos in a CP symmetric medium (such as the early
universe) are zero, and the index of refraction of a propagating neutrino can
only arise from the expansion of gauge boson propagators, from radiative
corrections, and from new physics interactions. Motivated by nucleosynthesis
constraints on a possible sterile neutrino (suggested by the solar neutrino
deficit and a possible neutrino), we calculate the standard model
contributions to the neutrino index of refraction in the early universe,
focusing on the period when the temperature was of the order of a few . We
find sizable radiative corrections to the tree level result obtained by the
expansion of the gauge boson propagator. For the leading log correction is about , while for
the correction is about
. Depending on the family mixing (if any), effects from different family
scattering can be dominated by radiative corrections. The result for
is zero at one-loop level, even if neutrinos are
massive. The cancellation of infrared divergence in a coherent process is also
discussed.Comment: 46pp, 13 figures (not included), UPR-0495
Stimulated Raman adiabatic passage-like protocols for amplitude transfer generalize to many bipartite graphs
Adiabatic passage techniques, used to drive a system from one quantum state
into another, find widespread application in physics and chemistry. We focus on
techniques to spatially transport a quantum amplitude over a strongly coupled
system, such as STImulated Raman Adiabatic Passage (STIRAP) and Coherent
Tunnelling by Adiabatic Passage (CTAP). Previous results were shown to work on
certain graphs, such as linear chains, square and triangular lattices, and
branched chains. We prove that similar protocols work much more generally, in a
large class of (semi-)bipartite graphs. In particular, under random couplings,
adiabatic transfer is possible on graphs that admit a perfect matching both
when the sender is removed and when the receiver is removed. Many of the
favorable stability properties of STIRAP/CTAP are inherited, and our results
readily apply to transfer between multiple potential senders and receivers. We
numerically test transfer between the leaves of a tree, and find surprisingly
accurate transfer, especially when straddling is used. Our results may find
applications in short-distance communication between multiple quantum
computers, and open up a new question in graph theory about the spectral gap
around the value 0.Comment: 17 pages, 3 figures. v2 is made more mathematical and precise than v
Quantum gas-liquid condensation in an attractive Bose gas
Gas-liquid condensation (GLC) in an attractive Bose gas is studied on the
basis of statistical mechanics. Using some results in combinatorial
mathematics, the following are derived: (1) With decreasing temperature, the
Bose-statistical coherence grows in the many-body wave function, which gives
rise to the divergence of the grand partition function prior to Bose-Einstein
condensation. It is a quantum-mechanical analogue to the GLC in a classical gas
(quantum GLC). (2) This GLC is triggered by the bosons with zero momentum.
Compared with the classical GLC, an incomparably weaker attractive force
creates it. For the system showing the quantum GLC, we discuss a cold helium 4
gas at sufficiently low pressure.Comment: 12 pages, 8 figure
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Common mortality modeling and coherent forecasts. An empirical analysis of worldwide mortality data
A new common mortality modeling structure is presented for analyzing mortality dynamics for a pool of countries, under the framework of generalized linear models (GLM). The countries are first classified by fuzzy c-means cluster analysis in order to construct the common sparse age-period model structure for the mortality experience. Next, we propose a method to create the common sex difference age-period model structure and then use this to produce the residual age-periodmodel structure for each country and sex. The time related principal components are extrapolated using dynamic linear regression (DLR) models and coherent mortality forecasts are investigated. We make use of mortality data from the “Human Mortality Database”
Group field theories
Group field theories are particular quantum field theories defined on D
copies of a group which reproduce spin foam amplitudes on a space-time of
dimension D. In these lecture notes, we present the general construction of
group field theories, merging ideas from tensor models and loop quantum
gravity. This lecture is organized as follows. In the first section, we present
basic aspects of quantum field theory and matrix models. The second section is
devoted to general aspects of tensor models and group field theory and in the
last section we examine properties of the group field formulation of BF theory
and the EPRL model. We conclude with a few possible research topics, like the
construction of a continuum limit based on the double scaling limit or the
relation to loop quantum gravity through Schwinger-Dyson equationsComment: Lectures given at the "3rd Quantum Gravity and Quantum Geometry
School", march 2011, Zakopan
From data towards knowledge: Revealing the architecture of signaling systems by unifying knowledge mining and data mining of systematic perturbation data
Genetic and pharmacological perturbation experiments, such as deleting a gene
and monitoring gene expression responses, are powerful tools for studying
cellular signal transduction pathways. However, it remains a challenge to
automatically derive knowledge of a cellular signaling system at a conceptual
level from systematic perturbation-response data. In this study, we explored a
framework that unifies knowledge mining and data mining approaches towards the
goal. The framework consists of the following automated processes: 1) applying
an ontology-driven knowledge mining approach to identify functional modules
among the genes responding to a perturbation in order to reveal potential
signals affected by the perturbation; 2) applying a graph-based data mining
approach to search for perturbations that affect a common signal with respect
to a functional module, and 3) revealing the architecture of a signaling system
organize signaling units into a hierarchy based on their relationships.
Applying this framework to a compendium of yeast perturbation-response data, we
have successfully recovered many well-known signal transduction pathways; in
addition, our analysis have led to many hypotheses regarding the yeast signal
transduction system; finally, our analysis automatically organized perturbed
genes as a graph reflecting the architect of the yeast signaling system.
Importantly, this framework transformed molecular findings from a gene level to
a conceptual level, which readily can be translated into computable knowledge
in the form of rules regarding the yeast signaling system, such as "if genes
involved in MAPK signaling are perturbed, genes involved in pheromone responses
will be differentially expressed"
How to Suppress Dark States in Quantum Networks and Bio-Engineered Structures
Transport across quantum networks underlies many problems, from state
transfer on a spin network to energy transport in photosynthetic complexes.
However, networks can contain dark subspaces that block the transportation, and
various methods used to enhance transfer on quantum networks can be viewed as
equivalently avoiding, modifying, or destroying the dark subspace. Here, we
exploit graph theoretical tools to identify the dark subspaces and show that
asymptotically almost surely they do not exist for large networks, while for
small ones they can be suppressed by properly perturbing the coupling rates
between the network nodes. More specifically, we apply these results to
describe the recently experimentally observed and robust transport behaviour of
the electronic excitation travelling on a genetically-engineered
light-harvesting cylinder (M13 virus) structure. We believe that these mainly
topological tools may allow us to better infer which network structures and
dynamics are more favourable to enhance transfer of energy and information
towards novel quantum technologies.Comment: 9 pages, 6 figure
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