Radiocarbon positive-ion mass spectrometry

Proof-of-principle of a new mass spectrometric technique for radiocarbon measurement is demonstrated. Interfering nitrogen and hydrocarbon molecules are largely eliminated in a charge-exchange cell operating on non-metallic gas. The positive-to-negative ion conversion is the reverse of that conventionally used in accelerator mass spectrometry (AMS) and is compatible with plasma ion sources that may be significantly more efficient and capable of greater output than are AMS sputter ion sources. The Nanogan electron cyclotron resonance (ECR) ion source employed exhibited no sample memory and the >50 kyrs age range of AMS was reproduced. A bespoke prototype new instrument is now required to optimise the plasma and cell physics and to realise hypothetical performance gains over AMS

MIMO In Vivo

We present the performance of MIMO for in vivo environments, using ANSYS HFSS and their complete human body model, to determine the maximum data rates that can be achieved using an IEEE 802.11n system. Due to the lossy nature of the in vivo medium, achieving high data rates with reliable performance will be a challenge, especially since the in vivo antenna performance is strongly affected by near field coupling to the lossy medium and the signals levels will be limited by specified specific absorption rate (SAR) levels. We analyzed the bit error rate (BER) of a MIMO system with one pair of antennas placed in vivo and the second pair placed inside and outside the body at various distances from the in vivo antennas. The results were compared to SISO simulations and showed that by using MIMO in vivo, significant performance gain can be achieved, and at least two times the data rate can be supported with SAR limited transmit power levels, making it possible to achieve target data rates in the 100 Mbps.Comment: WAMICON 201

Consistent Inversion of Noisy Non-Abelian X-Ray Transforms

For $M$ a simple surface, the non-linear statistical inverse problem of recovering a matrix field $\Phi: M \to \mathfrak{so}(n)$ from discrete, noisy measurements of the $SO(n)$-valued scattering data $C_\Phi$ of a solution of a matrix ODE is considered ($n\geq 2$). Injectivity of the map $\Phi \mapsto C_\Phi$ was established by [Paternain, Salo, Uhlmann; Geom.Funct.Anal. 2012]. A statistical algorithm for the solution of this inverse problem based on Gaussian process priors is proposed, and it is shown how it can be implemented by infinite-dimensional MCMC methods. It is further shown that as the number $N$ of measurements of point-evaluations of $C_\Phi$ increases, the statistical error in the recovery of $\Phi$ converges to zero in $L^2(M)$-distance at a rate that is algebraic in $1/N$, and approaches $1/\sqrt N$ for smooth matrix fields $\Phi$. The proof relies, among other things, on a new stability estimate for the inverse map $C_\Phi \to \Phi$. Key applications of our results are discussed in the case $n=3$ to polarimetric neutron tomography, see [Desai et al., Nature Sc.Rep. 2018] and [Hilger et al., Nature Comm. 2018