Galactic masers and the Milky Way circular velocity

Masers found in massive star-forming regions can be located precisely in six-dimensional phase space and therefore serve as a tool for studying Milky Way dynamics. The non-random orbital phases at which the masers are found and the sparseness of current samples require modeling. Here we model the phase-space distribution function of 18 precisely measured Galactic masers, permitting a mean velocity offset and a general velocity dispersion tensor relative to their local standards of rest, and accounting for different pieces of prior information. With priors only on the Sun's distance from the Galactic Center and on its motion with respect to the local standard of rest, the maser data provide a weak constraint on the circular velocity at the Sun of V_c = 246 +/- 30 km/s. Including prior information on the proper motion of Sgr A* leads to V_c = 244 +/- 13 km/s. We do not confirm the value of V_c \approx 254 km/s found in more restrictive models. This analysis shows that there is no conflict between recent determinations of V_c from Galactic Center analyses, orbital fitting of the GD-1 stellar stream, and the kinematics of Galactic masers; a combined estimate is V_c = 236 +/- 11 km/s. Apart from the dynamical parameters, we find that masers tend to occur at post-apocenter, circular-velocity-lagging phases of their orbits.Comment: ApJ in pres

Quantum processes, space-time representation and brain dynamics

The recent controversy of applicability of quantum formalism to brain dynamics has been critically analysed. The prerequisites for any type of quantum formalism or quantum field theory is to investigate whether the anatomical structure of brain permits any kind of smooth geometric notion like Hilbert structure or four dimensional Minkowskian structure for quantum field theory. The present understanding of brain function clearly denies any kind of space-time representation in Minkowskian sense. However, three dimensional space and one time can be assigned to the neuromanifold and the concept of probabilistic geometry is shown to be appropriate framework to understand the brain dynamics. The possibility of quantum structure is also discussed in this framework.Comment: Latex, 28 page

Interactions within the turbulent boundary layer at high Reynolds number

Simultaneous streamwise velocity measurements across the vertical direction obtained in the atmospheric surface layer (Re_τ ≃ 5 × 10^5) under near thermally neutral conditions are used to outline and quantify interactions between the scales of turbulence, from the very-large-scale motions to the dissipative scales. Results from conditioned spectra, joint probability density functions and conditional averages show that the signature of very-large-scale oscillations can be found across the whole wall region and that these scales interact with the near-wall turbulence from the energy-containing eddies to the dissipative scales, most strongly in a layer close to the wall, z^+ ≲ 10^3. The scale separation achievable in the atmospheric surface layer appears to be a key difference from the low-Reynolds-number picture, in which structures attached to the wall are known to extend through the full wall-normal extent of the boundary layer. A phenomenological picture of very-large-scale motions coexisting and interacting with structures from the hairpin paradigm is provided here for the high-Reynolds-number case. In particular, it is inferred that the hairpin-packet conceptual model may not be exhaustively representative of the whole wall region, but only of a near-wall layer of z^+ = O(10^3), where scale interactions are mostly confined