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

噪声是信号中明显的随机波动，就像未调谐的收音机上的静电一样，是实验科学的一个普遍方面。我们常说“在噪音中寻找信号”；事实上，科学家们通常会竭尽全力降低其发病率。然而，噪声来自系统内部的微观波动，其性质敏感地取决于该系统的基本特征。就像降噪耳机屏蔽掉我们周围的环境一样，如果只看信号而不看噪音，我们就有可能忽略有关实验系统如何真正工作的重要信息。事实上，正是对天线上残余噪声的仔细解读，为宇宙微波背景辐射提供了第一个实验证据——这是宇宙大爆炸的关键特征，也是诺贝尔物理学奖的得主。然而，噪声作为一种信息来源常常被忽视，因为很难解释实验数据中的波动。解开造成噪声的许多因素并理解它们各自的噪声产生特性是具有挑战性的，特别是在微观波动仍然知之甚少的非平衡系统中。此外，虽然人们越来越认识到分子系统中波动的重要性，但从技术上来说，获得理解这种噪音所需的详细定量实验数据是不可能的，因为这里的波动复杂、快速，而且太小，无法用常规显微镜观察到。我的研究旨在通过研究实验模型中的波动来揭示这种噪音的起源，这些模型显示出类似的物理化学行为，但这些行为是直接可观察的，高度可调且易于操作，关键是使每个单独的贡献因素能够被隔离，识别和理解。物理化学系统波动的不同方面将通过三个研究目标来解决。第一种是考虑相互作用的粒子在通道中移动的电流。至关重要的是，这些粒子足够大，可以直接看到电流的波动，从而使我们能够探索系统的不同特征如何产生特定的噪声特性。这在理解在自然现象中观察到的特定形式的噪声方面有潜在的应用，例如潮汐模式或神经元的放电，目前人们对这些现象知之甚少。目标二考虑柔性模型聚合物的波动如何控制它们通过狭窄孔隙的传输；这一过程对细胞膜运输和新兴的dna测序技术都至关重要。目标三解决了由DNA构建的更复杂、更灵活的纳米级结构所产生的噪声，这些结构在规模上与细胞机制相似。这些结构可以用已知的特征来设计，但由于它们的体积小，它们的波动不能直接观察到。然而，我们可以看到这些波动对流经系统的分子电流的影响。至关重要的是，这些数据可以使用我们在目标一中了解到的可观察电流来解释，从而提供对这些纳米结构的特性和波动的见解。每个目标都阐明了物理化学系统中产生噪声的单个因素，并提供了测试和指导理论预测所需的详细实验数据。综上所述，我的综合结果相互迭代，形成了物理化学过程中噪声的综合图景，这些过程支撑着从技术到生物的复杂系统。更广泛地说，我的工作将促进分析噪声的新方法的发展，支持具有更好噪声特性的工程技术的努力，并为围绕这一实验科学普遍方面的基本问题提供新的见解。

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.