2 research outputs found
Electron Exchange Coupling for Single Donor Solid-State Qubits
Inter-valley interference between degenerate conduction band minima has been
shown to lead to oscillations in the exchange energy between neighbouring
phosphorus donor electron states in silicon \cite{Koiller02,Koiller02A}. These
same effects lead to an extreme sensitivity of the exchange energy on the
relative orientation of the donor atoms, an issue of crucial importance in the
construction silicon-based spin quantum computers. In this article we calculate
the donor electron exchange coupling as a function of donor position
incorporating the full Bloch structure of the Kohn-Luttinger electron
wavefunctions. It is found that due to the rapidly oscillating nature of the
terms they produce, the periodic part of the Bloch functions can be safely
ignored in the Heitler-London integrals as was done by Koiller et. al. [Phys.
Rev. Lett. 88,027903(2002),Phys. Rev. B. 66,115201(2002)], significantly
reducing the complexity of calculations.
We address issues of fabrication and calculate the expected exchange coupling
between neighbouring donors that have been implanted into the silicon substrate
using an 15keV ion beam in the so-called 'top down' fabrication scheme for a
Kane solid-state quantum computer. In addition we calculate the exchange
coupling as a function of the voltage bias on control gates used to manipulate
the electron wavefunctions and implement quantum logic operations in the Kane
proposal, and find that these gate biases can be used to both increase and
decrease the magnitude of the exchange coupling between neighbouring donor
electrons. The zero-bias results reconfirm those previously obtained by
Koiller.Comment: 10 Pages, 8 Figures. To appear in Physical Review
Medium-term environmental changes influence age-specific survival estimates in a salmonid population
Human-induced environmental change is a major stressor on freshwater habitats that has resulted in the population declines of many freshwater species. Ontogenetic shifts in habitat use and associated (st)age-specific requirements mean that impacts of environmental stressors can influence (st)ages in a population differently, and yet relatively few studies of freshwater fish populations account for their detail. We aimed to identify environmental and biotic factors affecting survival estimated for six age-classes of a European grayling population in the River Wylye, UK over a 17-year period. We used a Bayesian age-structured state space model to estimate survival of grayling cohorts between subsequent life stages (eggs to age 5 adults) for 16 annual transitions (2003–2004 to 2018–2019), whilst accounting for imperfect sampling of the population. We quantified the effects of seasonal water flow and temperature, in-stream habitat and prey resource, and potential competitors and predators on survival between subsequent life stages. We used Bayesian variable selection to gauge their relative importance on survival. Grayling abundances declined during the study period (>75% in all age-classes), predominately driven by a loss of mature adults. Changes to seasonal flows negatively influenced their survival: increased days of summer low flow related to decreased survival of subadults and mature adults, and lower winter flows related to reduced recruitment of juveniles from eggs. Higher summer macrophyte cover negatively influenced juvenile and subadult survival and increasing days of high temperature in summer appeared detrimental to juvenile survival. Abundance of brown trout (a potential competitor and predator) did not negatively influence grayling survival. Our results reveal the implications of environmental change on a salmonid population, where recent low summer flows and high temperatures, and below average winter flows, have negatively influenced grayling survival. These conditions appear to be becoming more frequent and persistent in our study river, which is towards the species’ southern range limit, which could render the population vulnerable to climate change. Our study demonstrates how careful analysis of long-term population monitoring and environmental datasets can identify factors affecting (st)age-specific fish population dynamics, and when combined with local expertise, results in realistic mitigation proposals to promote wildlife population persistence