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 $n$--component spins ($n=2,3$) and associated with a $D$--dimensional lattice ($D=2,3$); 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 $\mu$. 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 $\mu=0$, 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 $\mu=-D/2$ was chosen for each of the four previously investigated counterparts, together with $\mu=-3D/4$ 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