23,463 research outputs found
Nematic order by thermal disorder in a three-dimensional lattice-spin model with dipolar-like interactions
At low temperatures, some lattice spin models with simple ferromagnetic or
antiferromagnetic interactions (for example nearest-neighbour interaction being
isotropic in spin space on a bipartite three-dimensional lattice) produce
orientationally ordered phases exhibiting nematic (second--rank) order, in
addition to the primary first-rank one; on the other hand, in the Literature,
they have been rather seldom investigated in this respect. Here we study the
thermodynamic properties of a three-dimensional model with dipolar-like
interaction. Its ground state is found to exhibit full orientational order with
respect to a suitably defined staggered magnetization (polarization), but no
nematic second-rank order. Extensive Monte Carlo simulations, in conjunction
with Finite-Size Scaling analysis have been used for characterizing its
critical behaviour; on the other hand, it has been found that nematic order
does indeed set in at low temperatures, via a mechanism of order by disorder.Comment: 24 pages, 9 figure
First order phase transitions in classical lattice gas spin models
The present paper considers some classical ferromagnetic lattice--gas models,
consisting of particles that carry --component spins () and
associated with a --dimensional lattice (); each site can host one
particle at most, thus implicitly allowing for hard--core repulsion; the pair
interaction, restricted to nearest neighbors, is ferromagnetic, and site
occupation is also controlled by the chemical potential . The models had
previously been investigated by Mean Field and Two--Site Cluster treatments
(when D=3), as well as Grand--Canonical Monte Carlo simulation in the case
, for both D=2 and D=3; the obtained results showed the same kind of
critical behaviour as the one known for their saturated lattice counterparts,
corresponding to one particle per site. Here we addressed by Grand--Canonical
Monte Carlo simulation the case where the chemical potential is negative and
sufficiently large in magnitude; the value was chosen for each of
the four previously investigated counterparts, together with in an
additional instance. We mostly found evidence of first order transitions, both
for D=2 and D=3, and quantitatively characterized their behaviour. Comparisons
are also made with recent experimental results.Comment: 9 pages, 12 figure
Quantum and Superquantum Nonlocal Correlations
We present a simple hidden variable model for the singlet state of a pair of
qubits, characterized by two kinds, hierarchically ordered, of hidden
variables. We prove that, averaging over both types of variables, one
reproduces all the quantum mechanical correlations of the singlet state. On the
other hand, averaging only over the hidden variables of the lower level, one
obtains a general formal theoretical scheme exhibiting correlations stronger
than the quantum ones, but with faster-than-light communication forbidden. This
result is interesting by itself since it shows that a violation of the quantum
bound for nonlocal correlations can be implemented in a precise physical manner
and not only mathematically, and it suggests that resorting to two levels of
nonlocal hidden variables might led to a deeper understanding of the physical
principles at the basis of quantum nonlocality.Comment: 5 pages, 1 figure. Submitted for publicatio
Environment induced incoherent controllability
We prove that the environment induced entanglement between two non
interacting, two-dimensional quantum systems S and P can be used to control the
dynamics of S by means of the initial state of P. Using a simple, exactly
solvable model, we show that both accessibility and controllability of S can be
achieved under suitable conditions on the interaction of S and P with the
environment.Comment: revtex4, 5 page
Panel performance: Modelling variation in sensory profiling data by multiway analysis
Sensory profiling data is essentially three-way data where samples, attributes and assessors are the three dimensions of information. It is common practice to average over the assessors and focus the analysis on the relations between samples and sensory descriptors. However, since assessor reliability can not be controlled in advance, posthoc analysis on assessors is needed to assess performance of the individual and at the panel level. For this purpose, multiway analysis is a very efficient data method as it provides information on samples, attributes and assessors, simultaneously [1]. PARAllel FACtor (PARAFAC) analysis is one of the most used multiway methods in sensory analysis [2][3]. It is based on two basic assumptions: 1) there exist latent variables behind the identified sensory descriptors describing the variation among the products; 2) assessors have different sensitivities to these common latent variables. However, assessors may perceive the factors differently, so the assumption of “common latent variables” becomes questionable. This may happen when the panel is not well trained and/or the samples present subtle differences difficult to detect.
In this work a more flexible approach to the analysis of sensory data is presented. Specifically, the work proposes to use PARAFAC2 modelling [4] as it allows each assessor to have an individual idiosyncratic perceptive model. The data was obtained from a descriptive sensory analysis of organic milk samples. Results show that PARAFAC2 is very useful to highlight disagreement in the panel on specific attributes and to detect outlying assessors. In addition, by using PARAFAC2 an improvement in the description of samples is also achieved. On the other hand, PARAFAC has to be preferred to PARAFAC2 when a good panel agreement is observed, since it provides more stable solutions and no further gain in information is obtained from PARAFAC2. Finally, the work proposes an index to measure the performance of each assessor based on individual sensitivity and reproducibility
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