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Accurate estimation of focal length ($f$) and its associated uncertainty is a cornerstone of experimental physics and optical engineering. When performing bench measurements using convex or concave lenses, various random and systematic uncertainties inevitably affect data acquisition. Error propagation mathematics provides a rigorous statistical framework to combine individual measurement tolerances into a reliable composite uncertainty metric.
For the standard thin lens configuration, the relationship between object distance ($d_o$), image distance ($d_i$), and focal length ($f$) is governed by the thin lens equation:
To evaluate the combined random error ($\Delta f$), partial derivatives with respect to each independent variable are computed using standard Gaussian error propagation:
Where the partial derivatives resolve analytically to $\frac{\partial f}{\partial d_o} = \frac{d_i^2}{(d_o + d_i)^2}$ and $\frac{\partial f}{\partial d_i} = \frac{d_o^2}{(d_o + d_i)^2}$.
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