2,097 research outputs found
Neutrino-electron scattering in noncommutative space
Neutral particles can couple with the gauge field in the adjoint
representation at the tree level if the space-time coordinates are
noncommutative (NC). Considering neutrino-photon coupling in the NC QED
framework, we obtain the differential cross section of neutrino-electron
scattering. Similar to the magnetic moment effect, one of the NC terms is
proportional to , where is the electron recoil energy.
Therefore, this scattering provides a chance to achieve a stringent bound on
the NC scale in low energy by improving the sensitivity to the smaller electron
recoil energy.Comment: 12 pages, 2 figure
Direct Integration and Non-Perturbative Effects in Matrix Models
We show how direct integration can be used to solve the closed amplitudes of
multi-cut matrix models with polynomial potentials. In the case of the cubic
matrix model, we give explicit expressions for the ring of non-holomorphic
modular objects that are needed to express all closed matrix model amplitudes.
This allows us to integrate the holomorphic anomaly equation up to holomorphic
modular terms that we fix by the gap condition up to genus four. There is an
one-dimensional submanifold of the moduli space in which the spectral curve
becomes the Seiberg--Witten curve and the ring reduces to the non-holomorphic
modular ring of the group . On that submanifold, the gap conditions
completely fix the holomorphic ambiguity and the model can be solved explicitly
to very high genus. We use these results to make precision tests of the
connection between the large order behavior of the 1/N expansion and
non-perturbative effects due to instantons. Finally, we argue that a full
understanding of the large genus asymptotics in the multi-cut case requires a
new class of non-perturbative sectors in the matrix model.Comment: 51 pages, 8 figure
Constraining noncommutative field theories with holography
An important window to quantum gravity phenomena in low energy noncommutative
(NC) quantum field theories (QFTs) gets represented by a specific form of UV/IR
mixing. Yet another important window to quantum gravity, a holography,
manifests itself in effective QFTs as a distinct UV/IR connection. In matching
these two principles, a useful relationship connecting the UV cutoff
, the IR cutoff and the scale of
noncommutativity , can be obtained. We show that an effective
QFT endowed with both principles may not be capable to fit disparate
experimental bounds simultaneously, like the muon and the masslessness of
the photon. Also, the constraints from the muon preclude any possibility
to observe the birefringence of the vacuum coming from objects at cosmological
distances. On the other hand, in NC theories without the UV completion, where
the perturbative aspect of the theory (obtained by truncating a power series in
) becomes important, a heuristic estimate of the region
where the perturbative expansion is well-defined , gets affected when holography is applied by providing the energy of the
system a -dependent lower limit. This may affect models
which try to infer the scale by using data from low-energy
experiments.Comment: 4 pages, version to be published in JHE
Multi-view Brain Network Prediction from a Source View Using Sample Selection via CCA-Based Multi-kernel Connectomic Manifold Learning
Several challenges emerged from the dataclysm of neuroimaging datasets spanning both healthy and disordered brain spectrum. In particular, samples with missing data views (e.g., functional imaging modality) constitute a hurdle to conventional big data learning techniques which ideally would be trained using a maximum number of samples across all views. Existing works on predicting target data views from a source data view mainly used brain images such as predicting PET image from MRI image. However, to the best of our knowledge, predicting a set of target brain networks from a source network remains unexplored. To ll this gap, a multi-kernel manifold learning (MKML) framework is proposed to learn how to predict multi-view brain networks from a source network to impute missing views in a connectomic dataset. Prior to performing multiple kernel learning of multi-view data, it is typically assumed that the source and target data come from the same distribution. However, multi-view connectomic data can be drawn from different distributions. In order to build robust predictors for predicting target multi-view networks from a source network view, it is necessary to take into account the shift between the source and target domains. Hence, we first estimate a mapping function that transforms the source and the target domains into a shared space where their correlation is maximized using canonical correlation analysis (CCA). Next, we nest the projected training and testing source samples into a connectomic manifold using multiple kernel learning, where we identify the most similar training samples to the testing source network. Given a testing subject, we introduce a cross-domain trust score to assess the reliability of each selected training sample for the target prediction task. Our model outperformed both conventional MKML technique and the proposed CCA-based MKMLtechnique without enhancement by trust scores
Solving the Topological String on K3 Fibrations
We present solutions of the holomorphic anomaly equations for compact
two-parameter Calabi-Yau manifolds which are hypersurfaces in weighted
projective space. In particular we focus on K3-fibrations where due to
heterotic type II duality the topological invariants in the fibre direction are
encoded in certain modular forms. The formalism employed provides holomorphic
expansions of topological string amplitudes everywhere in moduli space.Comment: 60 pages, 1 figure, With an appendix by Sheldon Kat
Polynomial Structure of Topological String Partition Functions
We review the polynomial structure of the topological string partition
functions as solutions to the holomorphic anomaly equations. We also explain
the connection between the ring of propagators defined from special K\"ahler
geometry and the ring of almost-holomorphic modular forms defined on modular
curves.Comment: version 2: references fixe
A Hybrid (Monte-Carlo/Deterministic) Approach for Multi-Dimensional Radiation Transport
A novel hybrid Monte Carlo transport scheme is demonstrated in a scene with
solar illumination, scattering and absorbing 2D atmosphere, a textured
reflecting mountain, and a small detector located in the sky (mounted on a
satellite or a airplane). It uses a deterministic approximation of an adjoint
transport solution to reduce variance, computed quickly by ignoring atmospheric
interactions. This allows significant variance and computational cost
reductions when the atmospheric scattering and absorption coefficient are
small. When combined with an atmospheric photon-redirection scheme, significant
variance reduction (equivalently acceleration) is achieved in the presence of
atmospheric interactions
TeV Scale Implications of Non Commutative Space time in Laboratory Frame with Polarized Beams
We analyze , and processes within the
Seiberg-Witten expanded noncommutative scenario using polarized beams. With
unpolarized beams the leading order effects of non commutativity starts from
second order in non commutative(NC) parameter i.e. , while with
polarized beams these corrections appear at first order () in cross
section. The corrections in Compton case can probe the magnetic
component() while in Pair production and Pair annihilation
probe the electric component() of NC parameter. We include the
effects of earth rotation in our analysis. This study is done by investigating
the effects of non commutativity on different time averaged cross section
observables. The results which also depends on the position of the collider,
can provide clear and distinct signatures of the model testable at the
International Linear Collider(ILC).Comment: 22 pages, 19 figures, new comments and references added, few typos
corrected, Published in JHE
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