Colour Confinement and Deformed Baryons in Quantum Chromodynamics

The confinement of coloured entities in Quantum Chromodynamics (QCD) is traced to colour singletness of the observed entities. This is believed to arise from colour singlet state of quark-antiquark for mesons and a fully colour antisymmetric state for baryons. This demands a spherically symmetric baryon in the ground state. However it is pointed out that a deformed baryon in the ground state has been found to be extremely successful phenomenology. There are convincing experimental supports for a deformed nucleon as well. This means that something has been missed in the fundamental theory. In this paper this problem is traced to a new colour singlet state for baryons which has been missed hitherto and incorporation of which provides a consistent justification of a deformed baryon in the ground state. Interestingly this new colour singlet state is global in nature.Comment: 5 pages, 1 figur

An information theory for preferences

Recent literature in the last Maximum Entropy workshop introduced an analogy between cumulative probability distributions and normalized utility functions. Based on this analogy, a utility density function can de defined as the derivative of a normalized utility function. A utility density function is non-negative and integrates to unity. These two properties form the basis of a correspondence between utility and probability. A natural application of this analogy is a maximum entropy principle to assign maximum entropy utility values. Maximum entropy utility interprets many of the common utility functions based on the preference information needed for their assignment, and helps assign utility values based on partial preference information. This paper reviews maximum entropy utility and introduces further results that stem from the duality between probability and utility

MOCCA-SURVEY database I. Accreting white dwarf binary systems in globular clusters -- IV. cataclysmic variables -- properties of bright and faint populations

We investigate here populations of cataclysmic variables (CVs) in a set of 288 globular cluster (GC) models evolved with the MOCCA code. This is by far the largest sample of GC models ever analysed with respect to CVs. Contrary to what has been argued for a long time, we found that dynamical destruction of primordial CV progenitors is much stronger in GCs than dynamical formation of CVs, and that dynamically formed CVs and CVs formed under no/weak influence of dynamics have similar white dwarf mass distributions. In addition, we found that, on average, the detectable CV population is predominantly composed of CVs formed via typical common envelope phase (CEP) ($\gtrsim70$ per cent), that only $\approx2-4$ per cent of all CVs in a GC is likely to be detectable, and that core-collapsed models tend to have higher fractions of bright CVs than non-core-collapsed ones. We also consistently show, for the first time, that the properties of bright and faint CVs can be understood by means of the pre-CV and CV formation rates, their properties at their formation times and cluster half-mass relaxation times. Finally, we show that models following the initial binary population proposed by Kroupa and set with low CEP efficiency better reproduce the observed amount of CVs and CV candidates in NGC 6397, NGC 6752 and 47 Tuc. To progress with comparisons, the essential next step is to properly characterize the candidates as CVs (e.g. by obtaining orbital periods and mass ratios).Comment: 18 pages, 13 figures; accepted for publication in MNRA

New control strategies for neuroprosthetic systems

The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with\ud neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to accomplish these tasks include feedforward (open-loop), feedback, and adaptive control. Feedforward control requires a great deal of information about the biomechanical behavior of the limb. For the upper extremity, an artificial motor program was developed to provide such movement program input to a neuroprosthesis. In lower extremity control, one group achieved their best results by attempting to meet naturally perceived gait objectives rather than to follow an exact joint angle trajectory. Adaptive feedforward control, as implemented in the cycleto-cycle controller, gave good compensation for the gradual decrease in performance observed with open-loop control. A neural network controller was able to control its system to customize stimulation parameters in order to generate a desired output trajectory in a given individual and to maintain tracking performance in the presence of muscle fatigue. The authors believe that practical FNS control systems must\ud exhibit many of these features of neurophysiological systems