1,128 research outputs found
A systematic comparison of supervised classifiers
Pattern recognition techniques have been employed in a myriad of industrial,
medical, commercial and academic applications. To tackle such a diversity of
data, many techniques have been devised. However, despite the long tradition of
pattern recognition research, there is no technique that yields the best
classification in all scenarios. Therefore, the consideration of as many as
possible techniques presents itself as an fundamental practice in applications
aiming at high accuracy. Typical works comparing methods either emphasize the
performance of a given algorithm in validation tests or systematically compare
various algorithms, assuming that the practical use of these methods is done by
experts. In many occasions, however, researchers have to deal with their
practical classification tasks without an in-depth knowledge about the
underlying mechanisms behind parameters. Actually, the adequate choice of
classifiers and parameters alike in such practical circumstances constitutes a
long-standing problem and is the subject of the current paper. We carried out a
study on the performance of nine well-known classifiers implemented by the Weka
framework and compared the dependence of the accuracy with their configuration
parameter configurations. The analysis of performance with default parameters
revealed that the k-nearest neighbors method exceeds by a large margin the
other methods when high dimensional datasets are considered. When other
configuration of parameters were allowed, we found that it is possible to
improve the quality of SVM in more than 20% even if parameters are set
randomly. Taken together, the investigation conducted in this paper suggests
that, apart from the SVM implementation, Weka's default configuration of
parameters provides an performance close the one achieved with the optimal
configuration
Resolving the nature of electronic excitations in resonant inelastic x-ray scattering
The study of elementary bosonic excitations is essential toward a complete
description of quantum electronic solids. In this context, resonant inelastic
X-ray scattering (RIXS) has recently risen to becoming a versatile probe of
electronic excitations in strongly correlated electron systems. The nature of
the radiation-matter interaction endows RIXS with the ability to resolve the
charge, spin and orbital nature of individual excitations. However, this
capability has been only marginally explored to date. Here, we demonstrate a
systematic method for the extraction of the character of excitations as
imprinted in the azimuthal dependence of the RIXS signal. Using this novel
approach, we resolve the charge, spin, and orbital nature of elastic
scattering, (para-)magnon/bimagnon modes, and higher energy dd excitations in
magnetically-ordered and superconducting copper-oxide perovskites (Nd2CuO4 and
YBa2Cu3O6.75). Our method derives from a direct application of scattering
theory, enabling us to deconstruct the complex scattering tensor as a function
of energy loss. In particular, we use the characteristic tensorial nature of
each excitation to precisely and reliably disentangle the charge and spin
contributions to the low energy RIXS spectrum. This procedure enables to
separately track the evolution of spin and charge spectral distributions in
cuprates with doping. Our results demonstrate a new capability that can be
integrated into the RIXS toolset, and that promises to be widely applicable to
materials with intertwined spin, orbital, and charge excitations
The symmetry of charge order in cuprates
Charge-ordered ground states permeate the phenomenology of 3d-based
transition metal oxides, and more generally represent a distinctive hallmark of
strongly-correlated states of matter. The recent discovery of charge order in
various cuprate families fueled new interest into the role played by this
incipient broken symmetry within the complex phase diagram of high-Tc
superconductors. Here we use resonant X-ray scattering to resolve the main
characteristics of the charge-modulated state in two cuprate families: Bi2201
and YBCO. We detect no signatures of spatial modulations along the nodal
direction in Bi2201, thus clarifying the inter-unit-cell momentum-structure of
charge order. We also resolve the intra-unit-cell symmetry of the charge
ordered state, which is revealed to be best represented by a bond-order with
modulated charges on the O-2p orbitals and a prominent d-wave character. These
results provide insights on the microscopic description of charge order in
cuprates, and on its origin and interplay with superconductivity.Comment: A high-resolution version with supplementary material can be found
at:
http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Articles/CDW_symmetry.pd
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