Rheology is the science of deformation and flow, with a focus on materials that do not exhibit simple linear elastic or viscous Newtonian behaviours. Rheology plays an important role in the characterisation of soft viscoelastic materials commonly found in the food and cosmetics industries, as well as in biology and bioengineering. Empirical and theoretical approaches are commonly used to identify and quantify material behaviours based on experimental data. RHEOS (RHEology, Open-Source) is a software package designed to make the analysis of rheological data simpler, faster, and more reproducible. RHEOS is currently limited to the broad family of linear viscoelastic models. A particular strength of the library is its ability to handle rheological models containing fractional derivatives, which have demonstrable utility for the modelling of biological materials [1,2,3,4], but have hitherto remained in relative obscurity -possibly due to their mathematical and computational complexity. RHEOS is written in Julia [5], which provides excellent computational efficiency and approachable syntax. RHEOS is fully documented and has extensive testing coverage.To our knowledge, there is to this date no other software package that offers RHEOS' broad selection of rheology analysis tools and extensive library of both traditional and fractional models. It has been used to process data and validate a model in [3], and is currently in use for several ongoing projects.It should be noted that RHEOS is not an optimisation package. It builds on another optimisation package, NLopt [6], by adding a large number of abstractions and functionality specific to the exploration of viscoelastic data. Statement of NeedArbitrary stress-strain curves and broad relaxation spectra require advanced software Many scientists and engineers who undertake rheological experiments would fit their data with one or several viscoelastic models in order to classify materials, quantify their behaviour, and predict their response to external perturbations.Standard linear viscoelastic models take the form of an ordinary differential equation between stress σ and strain . Under simple perturbations (step or ramp in stress or strain, or frequency sweep), it is relatively straight-forward to extract time-scales and identify asymptotic behaviours required to identify parameter values. However, data often involves complex stress and strain signals, and materials whose behaviour involves a broad distribution of time-scales, including power law behaviours. Fitting models and predicting their response in the time domain then requires computing viscoelastic hereditary integrals such as:τ ) dτ dτ * J L Kaplan, email: jlk49@cam.ac.uk † A Bonfanti, email: ab2425@cam.ac.uk ‡ A Kabla,

Material failure is ubiquitous, with implications from geology to everyday life and material science. It often involves sudden, unpredictable events, with little or no macroscopically detectable precursors. A deeper understanding of the microscopic mechanisms eventually leading to failure is clearly required, but experiments remain scarce. Here, we show that the microscopic dynamics of a colloidal gel, a model network-forming system, exhibit dramatic changes that precede its macroscopic failure by thousands of seconds. Using an original setup coupling light scattering and rheology, we simultaneously measure the macroscopic deformation and the microscopic dynamics of the gel, while applying a constant shear stress. We show that the network failure is preceded by qualitative and quantitative changes of the dynamics, from reversible particle displacements to a burst of irreversible plastic rearrangements.