13,539 research outputs found
Opportunities for the development of organic data collection and processing based on Finnish experiences
The Plant Production Inspection Centre is one of the Finnish state authorities in charge of implementation of the inspection system laid down in Council Regulation 2092/91. It keeps the register of all organic farms and co-ordinates the inspection work managed by regional control bodies
Improved Estimates for the Parameters of the Heavy Quark Expansion
We give improved estimates for the non-perturbative parameters appearing in
the heavy quark expansion for inclusive decays. While the parameters appearing
in low orders of this expansion can be extracted from data, the number of
parameters in higher orders proliferates strongly, making a determination of
these parameters from data impossible. Thus, one has to rely on theoretical
estimates which may be obtained from an insertion of intermediate states. In
this paper we refine this method and attempt to estimate the uncertainties of
this approach.Comment: 18 pages (v2: Fixed sign error in section 3. conclusions unchanged
Topologically non-trivial magnon bands in artificial square spin ices subject to Dzyaloshinskii-Moriya interaction
Systems that exhibit topologically protected edge states are interesting both
from a fundamental point of view as well as for potential applications, the
latter because of the absence of back-scattering and robustness to
perturbations. It is desirable to be able to control and manipulate such edge
states. Here, we show that artificial square ices can incorporate both
features: an interfacial Dzyaloshinksii-Moriya gives rise to topologically
non-trivial magnon bands, and the equilibrium state of the spin ice is
reconfigurable with different configurations having different magnon
dispersions and topology. The topology is found to develop as odd-symmetry bulk
and edge magnon bands approach each other, so that constructive band inversion
occurs in reciprocal space. Our results show that topologically protected bands
are supported in square spin ices.Comment: 27 pages, 6 figure
Flat forms, bi-Lipschitz parametrizations, and smoothability of manifolds
We give a sufficient condition for a metric (homology) manifold to be locally
bi-Lipschitz equivalent to an open subset in \rn. The condition is a Sobolev
condition for a measurable coframe of flat 1-forms. In combination with an
earlier work of D. Sullivan, our methods also yield an analytic
characterization for smoothability of a Lipschitz manifold in terms of a
Sobolev regularity for frames in a cotangent structure. In the proofs, we
exploit the duality between flat chains and flat forms, and recently
established differential analysis on metric measure spaces. When specialized to
\rn, our result gives a kind of asymptotic and Lipschitz version of the
measurable Riemann mapping theorem as suggested by Sullivan
How sharp are PV measures?
Properties of sharp observables (normalized PV measures) in relation to
smearing by a Markov kernel are studied. It is shown that for a sharp
observable defined on a standard Borel space, and an arbitrary observable
, the following properties are equivalent: (a) the range of is contained
in the range of ; (b) is a function of ; (c) is a smearing of
.Comment: 9 page
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings
We introduce a novel kernel that models input-dependent couplings across
multiple latent processes. The pairwise joint kernel measures covariance along
inputs and across different latent signals in a mutually-dependent fashion. A
latent correlation Gaussian process (LCGP) model combines these non-stationary
latent components into multiple outputs by an input-dependent mixing matrix.
Probit classification and support for multiple observation sets are derived by
Variational Bayesian inference. Results on several datasets indicate that the
LCGP model can recover the correlations between latent signals while
simultaneously achieving state-of-the-art performance. We highlight the latent
covariances with an EEG classification dataset where latent brain processes and
their couplings simultaneously emerge from the model.Comment: 17 pages, 6 figures; accepted to ACML 201
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