Relativistic BB84, relativistic errors, and how to correct them

The Bennett-Brassard cryptographic scheme (BB84) needs two bases, at least one of them linearly polarized. The problem is that linear polarization formulated in terms of helicities is not a relativistically covariant notion: State which is linearly polarized in one reference frame becomes depolarized in another one. We show that a relativistically moving receiver of information should define linear polarization with respect to projection of Pauli-Lubanski's vector in a principal null direction of the Lorentz transformation which defines the motion, and not with respect to the helicity basis. Such qubits do not depolarize.Comment: revtex

A topological characterization of the stable and minimal model classes of propositional logic programs

In terms of the arithmetic hierarchy, the complexity of the set of minimal models and of the set of stable models of a propositional general logic program has previously been described. However, not every set of interpretations of this level of complexity is obtained as such a set. In this paper we identify the sets of interpretations which are minimal or stable model classes by their properties in an appropriate topology on the space of interpretations. Closely connected with the topological characterization, in parallel with results previously known for stable model classes we obtain for minimal model classes both a normal-form representation as the set of minimal models of a prerequisite-free program and a logical description in terms of formulas. Our approach centers on the relation which we establish between stable and minimal model classes. We include examples of calculations which can be performed by these methods.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41770/1/10472_2005_Article_BF01536400.pd

Particle-Like Description in Quintessential Cosmology

Assuming equation of state for quintessential matter: $p=w(z)\rho$, we analyse dynamical behaviour of the scale factor in FRW cosmologies. It is shown that its dynamics is formally equivalent to that of a classical particle under the action of 1D potential $V(a)$. It is shown that Hamiltonian method can be easily implemented to obtain a classification of all cosmological solutions in the phase space as well as in the configurational space. Examples taken from modern cosmology illustrate the effectiveness of the presented approach. Advantages of representing dynamics as a 1D Hamiltonian flow, in the analysis of acceleration and horizon problems, are presented. The inverse problem of reconstructing the Hamiltonian dynamics (i.e. potential function) from the luminosity distance function $d_{L}(z)$ for supernovae is also considered.Comment: 35 pages, 26 figures, RevTeX4, some applications of our treatment to investigation of quintessence models were adde

Universal features of the order-parameter fluctuations : reversible and irreversible aggregation

We discuss the universal scaling laws of order parameter fluctuations in any system in which the second-order critical behaviour can be identified. These scaling laws can be derived rigorously for equilibrium systems when combined with the finite-size scaling analysis. The relation between order parameter, criticality and scaling law of fluctuations has been established and the connexion between the scaling function and the critical exponents has been found. We give examples in out-of-equilibrium aggregation models such as the Smoluchowski kinetic equations, or of at-equilibrium Ising and percolation models.Comment: 19 pages, 10 figure

Effects of Pore Walls and Randomness on Phase Transitions in Porous Media

We study spin models within the mean field approximation to elucidate the topology of the phase diagrams of systems modeling the liquid-vapor transition and the separation of He$^3$--He$^4$ mixtures in periodic porous media. These topologies are found to be identical to those of the corresponding random field and random anisotropy spin systems with a bimodal distribution of the randomness. Our results suggest that the presence of walls (periodic or otherwise) are a key factor determining the nature of the phase diagram in porous media.Comment: REVTeX, 11 eps figures, to appear in Phys. Rev.

Simple Dynamics on the Brane

We apply methods of dynamical systems to study the behaviour of the Randall-Sundrum models. We determine evolutionary paths for all possible initial conditions in a 2-dimensional phase space and we investigate the set of accelerated models. The simplicity of our formulation in comparison to some earlier studies is expressed in the following: our dynamical system is a 2-dimensional Hamiltonian system, and what is more advantageous, it is free from the degeneracy of critical points so that the system is structurally stable. The phase plane analysis of Randall-Sundrum models with isotropic Friedmann geometry clearly shows that qualitatively we deal with the same types of evolution as in general relativity, although quantitatively there are important differences.Comment: an improved version, 34 pages, 9 eps figure

Cosmological model with macroscopic spin fluid

We consider a Friedmann-Robertson-Walker cosmological model with some exotic perfect fluid with spin known as the Weyssenhoff fluid. The possibility that the dark energy may be described in part by the Weyssenhoff fluid is discussed. The observational constraint coming from supernovae type Ia observations is established. This result indicates that, whereas the cosmological constant is still needed to explain current observations, the model with spin fluid is admissible. For high redshifts $z > 1$ the differences between the model with spin fluid and the cold dark matter model with a cosmological constant become detectable observationally for the flat case with $\Omega_{\text{m},0}=0.3$. From the maximum likelihood method we obtain the value of $\Omega_{\text{s},0} = 0.004 \pm 0.016$. This gives us the limit $\Omega_{\text{s},0} > -0.012$ at the $1\sigma$ level. While the model with ``brane effects'' is preferred by the supernovae Ia data, the model with spin fluid is statistically admissible. For comparison, the limit on the spin fluid coming from cosmic microwave background anisotropies is also obtained. The uncertainties in the location of a first peak give the interval $-1.4 \times 10^{-10} < \Omega_{\text{s},0} < -10^{-10}$. From big bang nucleosynthesis we obtain the strongest limit $\Omega_{\text{s},0} \gtrsim -10^{-20}$. The interconnection between the model considered and brane models is also pointed out.Comment: RevTeX4, 15 pages, 10 figures; some minor change

The Effect of Convection on Disorder in Primary Cellular and Dendritic Arrays

Directional solidification studies have been carried out to characterize the spatial disorder in the arrays of cells and dendrites. Different factors that cause array disorder are investigated experimentally and analyzed numerically. In addition to the disorder resulting from the fundamental selection of a range of primary spacings under given experimental conditions, a significant variation in primary spacings is shown to occur in bulk samples due to convection effects, especially at low growth velocities. The effect of convection on array disorder is examined through directional solidification studies in two different alloy systems, Pb-Sn and Al-Cu. A detailed analysis of the spacing distribution is carried out, which shows that the disorder in the spacing distribution is greater in the Al-Cu system than in Pb-Sn system. Numerical models are developed which show that fluid motion can occur in both these systems due to the negative axial density gradient or due the radial temperature gradient which is always present in Bridgman growth. The modes of convection have been found to be significantly different in these systems, due to the solute being heavier than the solvent in the Al-Cu system and lighter than it in the Pb-Sn system. The results of the model have been shown to explain experimental observations of higher disorder and greater solute segregation in a weakly convective Al-Cu system than those in a highly convective Pb-Sn system

Dynamics of the Universe with global rotation

We analyze dynamics of the FRW models with global rotation in terms of dynamical system methods. We reduce dynamics of these models to the FRW models with some fictitious fluid which scales like radiation matter. This fluid mimics dynamically effects of global rotation. The significance of the global rotation of the Universe for the resolution of the acceleration and horizon problems in cosmology is investigated. It is found that dynamics of the Universe can be reduced to the two-dimensional Hamiltonian dynamical system. Then the construction of the Hamiltonian allows for full classification of evolution paths. On the phase portraits we find the domains of cosmic acceleration for the globally rotating universe as well as the trajectories for which the horizon problem is solved. We show that the FRW models with global rotation are structurally stable. This proves that the universe acceleration is due to the global rotation. It is also shown how global rotation gives a natural explanation of the empirical relation between angular momentum for clusters and superclusters of galaxies. The relation $J \sim M^2$ is obtained as a consequence of self similarity invariance of the dynamics of the FRW model with global rotation. In derivation of this relation we use the Lie group of symmetry analysis of differential equation.Comment: Revtex4, 22 pages, 5 figure

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations