Effect of vibration in diffusion coefficient determination

<p>In [<a class="litnote tooltip" href="/literature/@catipovic2013">@catipovic2013<span class="tooltiptext">Improving the quantification of Brownian motion</span></a>], the authors added a drift of 200nm/s and vibrational noise with a standard deviation of 100nm to estimate whether it has any effect on the quality of the measurement of the diffusion coefficient. When <a class="wikilink" href="/calculating_diffusion_coefficient_from_jump_statistics/">calculating diffusion coefficient from jump statistics</a> it gives a $D$ 11% larger, while <a class="wikilink" href="/calculating_diffusion_coefficient_from_mean_squared_displacement_data/">Calculating diffusion coefficient from mean squared displacement data</a> gives a $D$ 18% larger. When the drift is increased to around $1\mu m/s$ then the result <strong>can be off by a factor 10 or more!</strong> </p> <p>Therefore, the most important source of uncertainty that people must consider is the drift, which is hard to remove if there is evaporation, or any other kind of fluid flow. </p> <p>Regarding vibration, in [<a class="litnote tooltip" href="/literature/@ernst2013">@ernst2013<span class="tooltiptext">Measuring a diffusion coefficient by single-particle tracking: statistical analysis of experimental mean squared displacement curves</span></a>], they observed that the residual vibration of their piezos was generating errors when calculating the <a class="wikilink" href="/mean_squared_displacement/">mean squared displacement</a> at the minimal time-delay, which forced them to disregard the data with the shortest time-delay.</p>