The noise is the signal: exploring physico-chemical fluctuations with multiscale experimental models

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Noise is the apparently random fluctuation in a signal, like static on an untuned radio, and is a universal aspect of experimental science. We often talk about finding 'the signal in the noise'; indeed, scientists typically go to great lengths to reduce its incidence. Yet noise arises from the microscopic fluctuations within a system, the nature of which depend sensitively upon that system's underlying features. Just as noise-cancelling headphones screen out our surroundings, by looking only at the signal and not at the noise we risk ignoring significant information about how an experimental system really works. In fact, it was careful interpretation of residual noise on an antenna that provided the first experimental evidence for cosmic microwave background radiation - a key signature of the Big Bang and an observation which resulted in the Nobel Prize in Physics.Noise is often overlooked as a source of information, however, because it is difficult to interpret fluctuations in experimental data. Disentangling the many factors that contribute to noise and understanding their individual noise-creating characteristics is challenging, especially in non-equilibrium systems where microscopic fluctuations remain poorly understood. Moreover, while the importance of fluctuations in molecular systems is increasingly recognised, obtaining the detailed quantitative experimental data needed to understand this noise is technically prohibitive, as here fluctuations are complex, rapid and too small to observe by conventional microscopy. My research aims to unravel the origins of this noise by studying fluctuations in experimental models that display analogous physico-chemical behaviour, but which are directly observable, highly tuneable and easily manipulable, crucially enabling each individual contributing factor to be isolated, identified and understood.Differing aspects of fluctuations in physico-chemical systems will be addressed via three research objectives. The first considers currents of interacting particles moving through channels. Crucially these particles are large enough for fluctuations in the current to be directly visualised, allowing us to explore how different features of a system give rise to particular noise characteristics. This has potential applications in understanding particular forms of noise observed in natural phenomena, e.g. tidal patterns or the firing of neurons, that are currently poorly understood. Objective two considers how the fluctuations of flexible model polymers govern their transport through narrow pores; a process of key importance both to cell membrane transport and emerging DNA-sequencing technologies. Objective three addresses noise arising from more complex, flexible nanoscale structures built from DNA and similar in scale to cellular machinery. These structures can be designed with known features, but their fluctuations cannot be directly observed due to their small size. We can, however, see the effect these fluctuations have on a molecular current running through the system. Crucially, this data can be interpreted using what we have learnt about observable currents in Objective one, thus providing insights into the properties and fluctuations of these nanostructures.Each objective elucidates an individual factor contributing to noise in physico-chemical systems and provides the detailed experimental data required to test and guide theoretical predictions. Taken together, my combined results feed iteratively into one another to forge a comprehensive picture of noise in the physico-chemical processes which underpin complex systems from technology to biology. More broadly, my work will facilitate the development of new approaches to analysing noise, support efforts to engineer technologies with better noise characteristics, and shed new light on fundamental questions surrounding this universal aspect of experimental science.