A comparison of physical random number generators

Winner, ScienceGood random number generators (RNGs) are required for many applications in science and industry. Random numbers can be created in two ways: with a computer algorithm known as a pseudo-random number generator (PRNG), or by measuring physical phenomena which behave randomly, such as quantum mechanical or chaotic systems. However, PRNGs are deterministic in nature and cannot produce truly random output, while physical RNGs can. Three physical RNGs were constructed: a Chua circuit, an electrical circuit which exhibits chaos; an avalanche circuit, which produces a noisy electrical signal; and a radioactive decay counter. Each RNG produced output in the form of ASCII files containing 0s and 1s. The randomness of the data was assessed using the open source statistical test suite rngtest

Magnetohydrodynamical simulations of the fragmentation of molecular cloud cores

1 online resource (vi, 59 p.) : ill. (chiefly col.).Includes abstract and appendices.Includes bibliographical references (p. 57-59).Multiple star systems are quite common throughout the universe, so it is of interest to know what physical process may promote and prevent the fragmentation of a collapsing gas cloud that leads to multiple star system formation. Protostars, condensed objects in which nuclear reactions have yet to begin, are predominantly formed in Molecular Cloud Cores, dense regions of Molecular clouds composed of mostly cold molecular hydrogen. The condition for fragmentation is described by the Jeans Length, the maximm radius a uniform spherical core can have, beyond which thermal pressure is insufficient to support the core against gravitational collapse. To simulate the formation of multiple star systems, a model was developed consisting of a sphere of uniform density with an azimuthal density perturbation to stimulate fragmentation, with some initial amount of rotation and a uniform magnetic field parallel to the rotation axis. The parameters tested were the ratios of the initial thermal, rotational, and magnetic energy to the gravitational potential energy of the sphere, and the ratio of specific heats, denoted by [alpha], [beta], [zeta subscript m], and [gamma] respectively. An [alpha]-[beta]-[zeta subscript m]-[gamma] parameter space survey was carried out using the magnetohydrodynamical computer code ZEUS-3D, augmented with a Fourier transform based gravity solver. The increase of the energy ratios [alpha], [beta], and [zeta subscript m] was found to generally provide more support against the collapse and result in the evolution of the cores to a lower density. Multiple dense fragments were produced primarily in the hydrodynamica simulations using adiabatic values of [gamma]. The addition of a magnetic field was found to homogenize the density distribution, suppess fragmentation, and prevent the movement of fluid perpendicular to field lines, resulting in a smaller collapsed core. Simulations using near-isothermal values of [gamma] were found to generally collapse to a higher density state than those with adiabatic values, and to produce a single central condensation rather than multiple fragments

Association between Physical and Motor Fitness with Cognition in Children

Background and objective: There is an increased interest in exploring the association between fitness components with cognitive development in children in recent years. One of the scopes is to find the best exercise prescription to enhance health and cognition. Most of the studies so far have focused on cardiorespiratory fitness with little evidence on other fitness components. The present study aimed to explore the association between physical fitness (PF) and motor fitness (MF) with cognitive performance in children. Methods: Two hundred and six schoolboys (11.0 ± 0.8 y) underwent a battery of tests to measure information processing speed (i.e., simple and choice reaction time) and inhibitory control (i.e., Simon task). PF components (i.e., flexibility, muscular strength, and endurance) and MF components (speed and agility) were measured. Results: Multiple linear regression analysis adjusted for potential confounders (i.e., age, socioeconomic status, %fat and physical activity) revealed no relationship between flexibility, speed, muscular strength, and endurance with either information processing tasks or inhibitory control tasks. However, a positive association was observed between agility with both congruent reaction time and incongruent reaction time. Conclusions: No relationship was observed between the underlying fitness components with either information processing or inhibitory control. However, an association was observed between agility with inhibitory control