Discriminating spin through quantum interference

Many of the proposed solutions to the hierarchy and naturalness problems postulate new `partner' fields to the standard model particles. Determining the spins of these new particles will be critical in distinguishing among the various possible SM extensions, yet proposed methods rely on the underlying models. We propose a new model-independent method for spin measurements which takes advantage of quantum interference among helicity states. We demonstrate that this method will be able to discriminate scalar particles from higher spin states at the ILC, and discuss application to higher spins and possible uses at the LHC.Comment: 11 pages, 11 figure

Quantum Interference Effects Among Helicities at LEP-II and Tevatron

A completely model-independent method of obtaining information on the spin using the quantum interference effect among various helicity states was proposed in a recent paper. Here we point out that this effect should be demonstrable in the existing data on e^-e^+ \to W^+ W^- at LEP-II and p \bar{p} \to Z^0 + j at Tevatron.Comment: 6 pages, 5 figures, 7 table

Neural representations of the sense of self

The brain constructs representations of what is sensed and thought about in the form of nerve impulses that propagate in circuits and network assemblies (Circuit Impulse Patterns, CIPs). CIP representations of which humans are consciously aware occur in the context of a sense of self. Thus, research on mechanisms of consciousness might benefit from a focus on how a conscious sense of self is represented in brain. Like all senses, the sense of self must be contained in patterns of nerve impulses. Unlike the traditional senses that are registered by impulse flow in relatively simple, pauci-synaptic projection pathways, the sense of self is a system- level phenomenon that may be generated by impulse patterns in widely distributed complex and interacting circuits. The problem for researchers then is to identify the CIPs that are unique to conscious experience. Also likely to be of great relevance to constructing the representation of self are the coherence shifts in activity timing relations among the circuits. Consider that an embodied sense of self is generated and contained as unique combinatorial temporal patterns across multiple neurons in each circuit that contributes to constructing the sense of self. As with other kinds of CIPs, those representing the sense of self can be learned from experience, stored in memory, modified by subsequent experiences, and expressed in the form of decisions, choices, and commands. These CIPs are proposed here to be the actual physical basis for conscious thought and the sense of self. When active in wakefulness or dream states, the CIP representations of self act as an agent of the brain, metaphorically as an avatar. Because the selfhood CIP patterns may only have to represent the self and not directly represent the inner and outer worlds of embodied brain, the self representation should have more degrees of freedom than subconscious mind and may therefore have some capacity for a free-will mind of its own. S everal lines of evidence for this theory are reviewed. Suggested new research includes identifying distinct combinatorially coded impulse patterns and their temporal coherence shifts in defined circuitry, such as neocortical microcolumns. This task might be facilitated by identifying the micro-topography of field-potential oscillatory coherences among various regions and between different frequencies associated with specific conscious mentation. Other approaches can include identifying the changes in discrete conscious operations produced by focal trans-cranial magnetic stimulation

Inflation: flow, fixed points and observables to arbitrary order in slow roll

I generalize the inflationary flow equations of Hoffman and Turner to arbitrary order in slow roll. This makes it possible to study the predictions of slow roll inflation in the full observable parameter space of tensor/scalar ratio $r$, spectral index $n$, and running $d n / d \ln k$. It also becomes possible to identify exact fixed points in the parameter flow. I numerically evaluate the flow equations to fifth order in slow roll for a set of randomly chosen initial conditions and find that the models cluster strongly in the observable parameter space, indicating a ``generic'' set of predictions for slow roll inflation. I comment briefly on the the interesting proposed correspondence between flow in inflationary parameter space and renormalization group flow in a boundary conformal field theory.Comment: 16 pages, 7 figures. LaTeX. V4: Fixed important error in numerical constant in the second-order slow roll expressions for the observables r, n, and dn/dlog(k). See footnote after Eq. (48). New figures, minor changes to conclusions. Supersedes version published in Phys. Rev.

Current and emerging developments in subseasonal to decadal prediction

Weather and climate variations of subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus remains broadly similar (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correct, calibration and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Prograame (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis