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Newton's Method Root Finder

Find a root of f(x)=0 with Newton–Raphson iteration from a starting guess, showing every iterate, the residual f(xₖ), and the convergence path.

Enter f(x) using x as the variable and a starting guess. The derivative is computed numerically.

About this tool

The Newton's Method Root Finder is a free, in-browser calculator that solves f(x) = 0 numerically using the Newton–Raphson iteration x_{k+1} = x_k − f(x_k)/f′(x_k). Starting from a seed value x₀, each step follows the tangent line at the current point down to where it crosses the x-axis, and that crossing becomes the next estimate. The derivative f′ is evaluated numerically with a symmetric difference, so any expression you type — polynomials, roots, trig, exponentials, logs — works without you supplying the derivative.

Everything runs locally in your browser with a small expression parser, so nothing you enter is uploaded. Type f(x) using x as the variable (for example x^2 - 2, cos(x) - x, or exp(x) - 3*x), set a starting guess, and optionally adjust the tolerance and the maximum number of iterations. The tool iterates until the step size |x_{k+1} − x_k| or the residual |f(x_k)| falls below the tolerance, or until the iteration cap is reached, and it stops safely if the derivative goes flat (near zero) so it never returns a bogus number.

The result panel reports the converged root, the residual f(root) at that root, and how many iterations were needed, alongside a full iteration table listing k, x_k, f(x_k), and the error at each step. Newton's method converges quadratically near a simple root — the number of correct digits roughly doubles each step — which is why x² − 2 from x₀ = 1.5 nails √2 ≈ 1.414214 in just a handful of iterations.

Frequently asked questions

What is Newton's method formula?
It is the iteration x_{k+1} = x_k − f(x_k)/f′(x_k). Geometrically each step follows the tangent line at x_k to where it meets the x-axis. Repeated from a good starting guess it converges rapidly to a root of f(x) = 0.
How is the derivative computed?
Numerically, with a symmetric (central) difference f′(x) ≈ (f(x+h) − f(x−h)) / (2h) using a small h scaled to x. This means you only enter f(x) — no need to type the derivative — and any supported function works.
Why did it fail to converge?
Newton's method can fail if the starting guess is poor, if the iterate lands where f′(x) ≈ 0 (a flat tangent), or if the function has no real root nearby. Try a different seed closer to where you expect the root, or increase the maximum iterations.
What do the tolerance and max iterations control?
The tolerance is the stopping threshold: iteration ends when the step size or |f(x_k)| drops below it (default 1e-10). Max iterations caps the loop so it always terminates; the default is 50 and it is limited to 200.

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