Multi-wavelength analysis of the Galactic supernova remnant MSH 11-61A

Due to its centrally bright X-ray morphology and limb brightened radio profile, MSH 11-61A (G290.1-0.8) is classified as a mixed morphology supernova remnant (SNR). H\textsc{i} and CO observations determined that the SNR is interacting with molecular clouds found toward the north and southwest regions of the remnant. In this paper we report on the detection of $\gamma$-ray emission coincident with MSH 11-61A, using 70 months of data from the Large Area Telescope on board the \textit{Fermi Gamma-ray Space Telescope}. To investigate the origin of this emission, we perform broadband modelling of its non-thermal emission considering both leptonic and hadronic cases and concluding that the $\gamma$-ray emission is most likely hadronic in nature. Additionally we present our analysis of a 111 ks archival \textit{Suzaku} observation of this remnant. Our investigation shows that the X-ray emission from MSH 11-61A arises from shock-heated ejecta with the bulk of the X-ray emission arising from a recombining plasma, while the emission towards the east arises from an ionising plasma.Comment: 12 Pages, 8 figures. Accepted for publication in the Astrophysical Journa

Chemical Identification of Ions in Doped NaCl by Scanning Force Microscopy

A quantitative comparison between experiment and theory is presented, which shows that all ions of the Suzuki structure on (001) surfaces of Mg2+ or Cd2+ doped NaCl crystals can be identified despite the tip-surface distance, differences in impurity chemistry, and surface termination. The identification can be used to calibrate the potential of the tip's last atom, and it is proposed to use these surfaces for better characterization of deposited nano-objects.Peer reviewe

Sublattice identification in noncontact atomic force microscopy of the NaCl(001) surface

We compare the three-dimensional force field obtained from frequency-distance measurements above the NaCl(001) surface to atomistic calculations using various tip models. In the experiments, long-range forces cause a total attractive force even on the similarly charged site. Taking force differences between two sites minimizes the influence of such long-range forces. The magnitude of the measured force differences are by a factor of 6.5–10 smaller than the calculated forces. This is an indication that for the particular tip used in this experiment several atoms of the tip interact with the surface atoms at close tip-sample distances. The interaction of these additional atoms with the surface is small at the imaging distance, because symmetric images are obtained. The force distance characteristics resemble those of a negative tip apex ion which could be explained, e.g., by a neutral Si tip.Peer reviewe

Efficient Real-world Testing of Causal Decision Making via Bayesian Experimental Design for Contextual Optimisation

The real-world testing of decisions made using causal machine learning models is an essential prerequisite for their successful application. We focus on evaluating and improving contextual treatment assignment decisions: these are personalised treatments applied to e.g. customers, each with their own contextual information, with the aim of maximising a reward. In this paper we introduce a model-agnostic framework for gathering data to evaluate and improve contextual decision making through Bayesian Experimental Design. Specifically, our method is used for the data-efficient evaluation of the regret of past treatment assignments. Unlike approaches such as A/B testing, our method avoids assigning treatments that are known to be highly sub-optimal, whilst engaging in some exploration to gather pertinent information. We achieve this by introducing an information-based design objective, which we optimise end-to-end. Our method applies to discrete and continuous treatments. Comparing our information-theoretic approach to baselines in several simulation studies demonstrates the superior performance of our proposed approach.Comment: ICML 2022 Workshop on Adaptive Experimental Design and Active Learning in the Real World. 16 pages, 5 figure