A critical analysis of the hydrino model

Recently, spectroscopic and calorimetric observations of hydrogen plasmas and chemical reactions with them have been interpreted as evidence for the existence of electronic states of the hydrogen atom with a binding energy of more than 13.6 eV. The theoretical basis for such states, that have been dubbed hydrinos, is investigated. We discuss both, the novel deterministic model of the hydrogen atom, in which the existence of hydrinos was predicted, and standard quantum mechanics. Severe inconsistencies in the deterministic model are pointed out and the incompatibility of hydrino states with quantum mechanics is reviewed.Comment: 9 page

Optimisation in ‘Self-modelling’ Complex Adaptive Systems

When a dynamical system with multiple point attractors is released from an arbitrary initial condition it will relax into a configuration that locally resolves the constraints or opposing forces between interdependent state variables. However, when there are many conflicting interdependencies between variables, finding a configuration that globally optimises these constraints by this method is unlikely, or may take many attempts. Here we show that a simple distributed mechanism can incrementally alter a dynamical system such that it finds lower energy configurations, more reliably and more quickly. Specifically, when Hebbian learning is applied to the connections of a simple dynamical system undergoing repeated relaxation, the system will develop an associative memory that amplifies a subset of its own attractor states. This modifies the dynamics of the system such that its ability to find configurations that minimise total system energy, and globally resolve conflicts between interdependent variables, is enhanced. Moreover, we show that the system is not merely ‘recalling’ low energy states that have been previously visited but ‘predicting’ their location by generalising over local attractor states that have already been visited. This ‘self-modelling’ framework, i.e. a system that augments its behaviour with an associative memory of its own attractors, helps us better-understand the conditions under which a simple locally-mediated mechanism of self-organisation can promote significantly enhanced global resolution of conflicts between the components of a complex adaptive system. We illustrate this process in random and modular network constraint problems equivalent to graph colouring and distributed task allocation problems

Structural Assembly Demonstration Experiment (SADE)

The purpose of the Structural Assembly Demonstration Experiment (SADE) was to create a near-term Shuttle flight experiment focusing on the deployment and erection of structural truss elements. The activities of the MIT Space Systems Laboratory consist of three major areas: preparing and conducting neutral buoyancy simulation test series; producing a formal SADE Experiment plan; and studying the structural dynamics issues of the truss structure. Each of these areas is summarized

Macrospin Models of Spin Transfer Dynamics

The current-induced magnetization dynamics of a spin valve are studied using a macrospin (single domain) approximation and numerical solutions of a generalized Landau-Lifshitz-Gilbert equation. For the purpose of quantitative comparison with experiment [Kiselev {\it et al.} Nature {\bf 425}, 380 (2003)], we calculate the resistance and microwave power as a function of current and external field including the effects of anisotropies, damping, spin-transfer torque, thermal fluctuations, spin-pumping, and incomplete absorption of transverse spin current. While many features of experiment appear in the simulations, there are two significant discrepancies: the current dependence of the precession frequency and the presence/absence of a microwave quiet magnetic phase with a distinct magnetoresistance signature. Comparison is made with micromagnetic simulations designed to model the same experiment.Comment: 14 pages, 14 figures. Email [email protected] for a pdf with higher quality figure

Transformations in the Scale of Behaviour and the Global Optimisation of Constraints in Adaptive Networks

The natural energy minimisation behaviour of a dynamical system can be interpreted as a simple optimisation process, finding a locally optimal resolution of problem constraints. In human problem solving, high-dimensional problems are often made much easier by inferring a low-dimensional model of the system in which search is more effective. But this is an approach that seems to require top-down domain knowledge; not one amenable to the spontaneous energy minimisation behaviour of a natural dynamical system. However, in this paper we investigate the ability of distributed dynamical systems to improve their constraint resolution ability over time by self-organisation. We use a ‘self-modelling’ Hopfield network with a novel type of associative connection to illustrate how slowly changing relationships between system components can result in a transformation into a new system which is a low-dimensional caricature of the original system. The energy minimisation behaviour of this new system is significantly more effective at globally resolving the original system constraints. This model uses only very simple, and fully-distributed positive feedback mechanisms that are relevant to other ‘active linking’ and adaptive networks. We discuss how this neural network model helps us to understand transformations and emergent collective behaviour in various non-neural adaptive networks such as social, genetic and ecological networks

Theory of Local Dynamical Magnetic Susceptibilities from the Korringa-Kohn-Rostoker Green Function Method

Within the framework of time-dependent density functional theory combined with the Korringa-Kohn-Rostoker Green function formalism, we present a real space methodology to investigate dynamical magnetic excitations from first-principles. We set forth a scheme which enables one to deduce the correct effective Coulomb potential needed to preserve the spin-invariance signature in the dynamical susceptibilities, i.e. the Goldstone mode. We use our approach to explore the spin dynamics of 3d adatoms and different dimers deposited on a Cu(001) with emphasis on their decay to particle-hole pairs.Comment: 32 pages (preprint), 6 figures, one tabl

Spin Orbit Coupling and Spin Waves in Ultrathin Ferromagnets: The Spin Wave Rashba Effect

We present theoretical studies of the influence of spin orbit coupling on the spin wave excitations of the Fe monolayer and bilayer on the W(110) surface. The Dzyaloshinskii-Moriya interaction is active in such films, by virtue of the absence of reflection symmetry in the plane of the film. When the magnetization is in plane, this leads to a linear term in the spin wave dispersion relation for propagation across the magnetization. The dispersion relation thus assumes a form similar to that of an energy band of an electron trapped on a semiconductor surfaces with Rashba coupling active. We also show SPEELS response functions that illustrate the role of spin orbit coupling in such measurements. In addition to the modifications of the dispersion relations for spin waves, the presence of spin orbit coupling in the W substrate leads to a substantial increase in the linewidth of the spin wave modes. The formalism we have developed applies to a wide range of systems, and the particular system explored in the numerical calculations provides us with an illustration of phenomena which will be present in other ultrathin ferromagnet/substrate combinations