1,301 research outputs found
Thermal correlators of anyons in two dimensions
The anyon fields have trivial -commutator for not integer.
For integer the commutators become temperature-dependent operator
valued distributions. The -point functions do not factorize as for quasifree
states.Comment: 14 pages, LaTeX (misprints corrected, a reference added
Evolution Kernels of Twist-3 Light-Ray Operators in Polarized Deep Inelastic Scattering
The twist three contributions to the -evolution of the spin-dependent
structure function are considered in the non-local operator product
approach. Starting from the perturbative expansion of the T-product of two
electromagnetic currents, we introduce the nonlocal light-cone expansion proved
by Anikin and Zavialov and determine the physical relevant set of light-ray
operators of twist three. Using the equations of motion we show the equivalence
of these operators to the Shuryak-Vainshtein operators plus the mass operator,
and we determine their evolution kernels using the light-cone gauge with the
Leibbrandt-Mandelstam prescription. The result of Balitsky and Braun for the
twist three evolution kernel (nonsinglet case) is confirmed.Comment: 7 pages, LaTeX, Talk given at the workshop "QCD and QED in Higher
Order", Rheinsberg, April 21-26, 199
SiPM and front-end electronics development for Cherenkov light detection
The Italian Institute of Nuclear Physics (INFN) is involved in the
development of a demonstrator for a SiPM-based camera for the Cherenkov
Telescope Array (CTA) experiment, with a pixel size of 66 mm. The
camera houses about two thousands electronics channels and is both light and
compact. In this framework, a R&D program for the development of SiPMs suitable
for Cherenkov light detection (so called NUV SiPMs) is ongoing. Different
photosensors have been produced at Fondazione Bruno Kessler (FBK), with
different micro-cell dimensions and fill factors, in different geometrical
arrangements. At the same time, INFN is developing front-end electronics based
on the waveform sampling technique optimized for the new NUV SiPM. Measurements
on 11 mm, 33 mm, and 66 mm NUV SiPMs
coupled to the front-end electronics are presentedComment: In Proceedings of the 34th International Cosmic Ray Conference
(ICRC2015), The Hague, The Netherlands. All CTA contributions at
arXiv:1508.0589
Social facilitation on the development of foraging behaviors in a population of autonomous robots
Abstract. In this paper we propose an adaptive algorithm based on a combination of selective reproduction, individual learning, and social learning. Social learning consists of a simple facilitation process that regulates the strength of individual learning on the basis of the number of individuals located nearby. By testing this model in an experimental scenario, in which a population of 10 mobile robots has to develop a simple foraging behavior, we demonstrate how the model proposed produces effective results. By comparing the results obtained in different experimental conditions we also show how the method proposed outperforms other alternative algorithms based on genetic evolution or individual learning. Finally, we briefly discuss how the model proposed can help us to understand the role of social learning in biological organisms
Portfolio selection problems in practice: a comparison between linear and quadratic optimization models
Several portfolio selection models take into account practical limitations on
the number of assets to include and on their weights in the portfolio. We
present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset
Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional
Value-at-Risk (LACVaR) models, where the assets are limited with the
introduction of quantity and cardinality constraints. We propose a completely
new approach for solving the LAM model, based on reformulation as a Standard
Quadratic Program and on some recent theoretical results. With this approach we
obtain optimal solutions both for some well-known financial data sets used by
several other authors, and for some unsolved large size portfolio problems. We
also test our method on five new data sets involving real-world capital market
indices from major stock markets. Our computational experience shows that,
rather unexpectedly, it is easier to solve the quadratic LAM model with our
algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of
the best commercial codes for mixed integer linear programming (MILP) problems.
Finally, on the new data sets we have also compared, using out-of-sample
analysis, the performance of the portfolios obtained by the Limited Asset
models with the performance provided by the unconstrained models and with that
of the official capital market indices
Regularizing Portfolio Optimization
The optimization of large portfolios displays an inherent instability to
estimation error. This poses a fundamental problem, because solutions that are
not stable under sample fluctuations may look optimal for a given sample, but
are, in effect, very far from optimal with respect to the average risk. In this
paper, we approach the problem from the point of view of statistical learning
theory. The occurrence of the instability is intimately related to over-fitting
which can be avoided using known regularization methods. We show how
regularized portfolio optimization with the expected shortfall as a risk
measure is related to support vector regression. The budget constraint dictates
a modification. We present the resulting optimization problem and discuss the
solution. The L2 norm of the weight vector is used as a regularizer, which
corresponds to a diversification "pressure". This means that diversification,
besides counteracting downward fluctuations in some assets by upward
fluctuations in others, is also crucial because it improves the stability of
the solution. The approach we provide here allows for the simultaneous
treatment of optimization and diversification in one framework that enables the
investor to trade-off between the two, depending on the size of the available
data set
Anyons and the Bose-Fermi duality in the finite-temperature Thirring model
Solutions to the Thirring model are constructed in the framework of algebraic
QFT. It is shown that for all positive temperatures there are fermionic
solutions only if the coupling constant is . These fermions are inequivalent and only for they are canonical
fields. In the general case solutions are anyons. Different anyons (which are
uncountably many) live in orthogonal spaces and obey dynamical equations (of
the type of Heisenberg's "Urgleichung") characterized by the corresponding
values of the statistic parameter. Thus statistic parameter turns out to be
related to the coupling constant and the whole Hilbert space becomes
non-separable with a different "Urgleichung" satisfied in each of its sectors.
This feature certainly cannot be seen by any power expansion in .
Moreover, since the latter is tied to the statistic parameter, it is clear that
such an expansion is doomed to failure and will never reveal the true structure
of the theory.
The correlation functions in the temperature state for the canonical dressed
fermions are shown by us to coincide with the ones for bare fields, that is in
agreement with the uniqueness of the -KMS state over the CAR algebra
( being the shift automorphism). Also the -anyon two-point
function is evaluated and for scalar field it reproduces the result that is
known from the literature.Comment: 25 pages, LaTe
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