applications


➤ accurate instrumental calibration. An innovative new methodology, called IONONEST, for assessing the effect of space weather on radio signals in the ionosphere has been devised by researchers from the University of Manchester’s Jodrell Bank Centre for Astrophysics. Dr Anna Scaife, head of the Interferometry Centre of Excellence at Te University of Manchester, told Scientific Computing World: ‘When we started the IONONEST project, our thinking was ‘if our measurements are so sensitively affected by changes in the ionosphere, why don’t we turn things around and try to use the telescope to make measurements of the ionosphere instead?’ Te researchers decided to focus on frequency-


dependent absorption of radio waves as Scaife explained: ‘Tis could provide information on the height profile of the electron density through the lower ionosphere. Information on this height dependence is oſten lost by ionospheric probes, which predominantly focus on integrated electron density measurements. Te absorption technique we adopted is also sensitive to the lowest part of the ionosphere, the D-region, where again many other techniques are not.’ However, recovering height profiles from


frequency dependent absorption measurements is an ‘inverse problem’, where the measurement itself doesn’t provide the quantity of interest directly, but needs to be inverted. ‘Tere are different ways of tackling this kind of problem and we adopted a numerical approach, iteratively simulating our measurements from a model and comparing/ fitting them to the data,’ according to Scaife. One of the strengths of this approach is that


the fitted parameters of the model can then be used to track the time-dependent behaviour of the ionosphere, as Scaife added: ‘Characterisation such as this is key to understanding how different space weather events impact on the ionosphere and, consequently, how to predict and respond to them.’ Te IONONEST methodology used a ‘Bayesian approach’, where the ionospheric


Antennas of the front-end receiver system, part of the LOFAR array


THE SIMULATED RESPONSE IS COMPARED TO MEASURED DATA TO ASSESS ITS ACCURACY


electron density profile as a function of height based on an input model, as well as the instrument response to that profile, are iteratively simulated. Te simulated response is compared to measured data to assess its accuracy, the parameters of the model are updated and the process is repeated to improve the accuracy. Sciafe explained: ‘We do not measure absolute


accuracy, but rather the degree of similarity between our measurements and our simulations. We use this to characterise the allowable range


in our recovered parameters. Tere are lots of ways to do this. In the IONONEST code, we make an assumption of uncorrelated Gaussian noise on our measurements and use this to construct a likelihood function that tells us how well the measured data fit the model we are assuming. We use this likelihood, combined with prior information on our model parameters, to calculate the posterior probability – that is, how well the model fits the data. ‘Finally we calculate a quantity known as


the Bayesian evidence, which is the probability of the input model itself. We use the evidence value to make a relative assessment of different underlying input models, and decide which one is most likely to provide a true description of the data.’ Te team now hopes to compare more


detailed and physically motivated models of the ionospheric electron density, in order to further its understanding of this complex region. ‘Expanding these models to include not only height information, but also wider spatial volumes of the ionosphere, would be an excellent path forward. To do this would require measurements from an array of telescopes; our ambition in this area is to see this realised using the European LOFAR array and, potentially in the future, the SKA1-LOW telescope,’ Scaife added. As this last statement indicates, the fields of


Visualisations of the large scale outflows and small-scale star-forming clumps 28 SCIENTIFIC COMPUTING WORLD


observational and theoretical astronomy are interlinked. As one field improves, it opens the door for new observations or theories to feed the other field. And so the cycle of research continues until, eventually, the secrets of our universe may be unlocked. l


@scwmagazine l www.scientific-computing.com


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