Wavelet analysis of atmospheric turbulence over a coral reef flat

The world’s tropical coral reefs are at risk of severe bleaching episodes and species decline in response to global climate variability. The ecological and economic value of reef ecosystems is enormous, yet very little is known of the physical interactions that take place at the coral–ocean–atmosphere interfaces. This paper introduces and validates a novel technique for the acquisition of surface energy balance measurements over Heron Reef, part of the Capricorn Bunker Group of the southern Great Barrier Reef, Australia. Measurements of surface energy and radiation exchanges were made using a Campbell Scientific eddy covariance (EC) measurement system mounted on a floating pontoon anchored to the reef flat. A Nortek Vector velocimeter was positioned next to the pontoon to record wave motion. Wavelet analysis techniques were used to decompose the turbulent exchange of sensible heat measured by the EC unit and to compare vertical velocity measurements with wave-induced motion recorded by the velocimeter. The results indicate that although the EC system and the velocimeter share intermittent periods of high common power in their respective wavelet variance spectra, these regions are not coherent and differ in strength by more than an order of magnitude. It was concluded that over a standard averaging period of 30 min the wave-induced motion of the pontoon would not significantly interfere with the acquisition and calculation of turbulent fluxes of sensible and latent heat, thereby confirming the robustness of this method of obtaining surface energy balance measurements over coral reefs

Variations in the Freshwater Snail, Goniobasis Livescens

Author Institution: Bluffton College, Bluffton, Ohi

Higher Order Decompositions of Ordered Operator Exponentials

We present a decomposition scheme based on Lie-Trotter-Suzuki product formulae to represent an ordered operator exponential as a product of ordinary operator exponentials. We provide a rigorous proof that does not use a time-displacement superoperator, and can be applied to non-analytic functions. Our proof provides explicit bounds on the error and includes cases where the functions are not infinitely differentiable. We show that Lie-Trotter-Suzuki product formulae can still be used for functions that are not infinitely differentiable, but that arbitrary order scaling may not be achieved.Comment: 16 pages, 1 figur

Diurnal Variations in the Amount of Dissolved Oxygen, Alkalinity, and Free Ammonia in Certain Fish Ponds at Fairport, (Iowa)

Author Institution: U. S. Bureau of Fisheries, Fairport, Iow

The Effect of High Concentrations of Dissolved Oxygen on Several Species of Pond Fishes

Author Institution: U. S. Bureau of Fisheries Laboratory, Fairport, Iow

Dissolved Oxygen Profiles at Norris Dam and in the Big Creek Sector of Norris Reservoir (1937), with a Note on the Oxygen Demand of the Water (1938)

Author Institution: Biological Readjustment Division, Department of Forestry Relations (T.V.A.

Two inequivalent sublattices and orbital ordering in MnV2O4 studied by 51V NMR

We report detailed 51V NMR spectra in a single crystal of MnV2O4. The vanadium spectrum reveals two peaks in the orbitally ordered state, which arise from different internal hyperfine fields at two different V sublattices. These internal fields evolve smoothly with externally applied field, and show no change in structure that would suggest a change of the orbital ordering. The result is consistent with the orbital ordering model recently proposed by Sarkar et al. [Phys. Rev. Lett. 102, 216405 (2009)] in which the same orbital that is a mixture of t_2g orbitals rotates by about 45$^\circ$ alternately within and between orbital chains in the I4_1/a tetragonal space group.Comment: 4 pages, 4 figures, title changed, published in PRB as a rapid com

Experimental Quantum Hamiltonian Learning

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of foundational physics. Machine-learning enhanced by quantum simulators has been proposed as a route to improve the computational cost of performing these studies. Here we interface two different quantum systems through a classical channel - a silicon-photonics quantum simulator and an electron spin in a diamond nitrogen-vacancy centre - and use the former to learn the latter's Hamiltonian via Bayesian inference. We learn the salient Hamiltonian parameter with an uncertainty of approximately $10^{-5}$. Furthermore, an observed saturation in the learning algorithm suggests deficiencies in the underlying Hamiltonian model, which we exploit to further improve the model itself. We go on to implement an interactive version of the protocol and experimentally show its ability to characterise the operation of the quantum photonic device. This work demonstrates powerful new quantum-enhanced techniques for investigating foundational physical models and characterising quantum technologies