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Newton fractal

Newton fractal is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Newton fractal rather than just read about it. In short: The Newton fractal is a boundary set in the complex plane which is characterized by Newton's method applied to a fixed polynomial p(z) ∈ C {\displaystyle \mathbb {C} } [z] or transcendental function. It is the Julia set of the meromorphic function z ↦ z − ⁠p(z)/p′(z)⁠ which is given by Newton's method.

Newton fractal — main illustration
Newton fractal — illustration

Key takeaways

  • Newton fractal belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Newton fractal to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Newton fractal from memory before moving on to harder problems.

Reference excerpt

The Newton fractal is a boundary set in the complex plane which is characterized by Newton's method applied to a fixed polynomial p(z) ∈ C {\displaystyle \mathbb {C} } [z] or transcendental function. It is the Julia set of the meromorphic function z ↦ z − ⁠p(z)/p′(z)⁠ which is given by Newton's method. When there are no attractive cycles (of order greater than 1), it divides the complex plane into regions Gk, each of which is associated with a root ζk of the polynomial, k = 1, …, deg(p). In this way the Newton fractal is similar to the Mandelbrot set, and like other fractals it exhibits an intricate appearance arising from a simple description. It is relevant to numerical analysis because it shows that (outside the region of quadratic convergence) the Newton method can be very sensitive to its choice of start point. Almost all points of the complex plane are associated with one of the deg(p) roots of a given polynomial in the following way: the point is used as starting value z0 for Newton's iteration zn + 1 := zn − ⁠p(zn)/p'(zn)⁠, yielding a sequence of points z1, z2, …, If the sequence converges to the root ζk, then z0 was an element of the region Gk. However, for every polynomial of degree at least 2 there are points for which the Newton iteration does not converge to any root: examples are the boundaries of the basins of attraction of the various roots. There are even polynomials for which open sets of starting points fail to converge to any root: a simple example is z3 − 2z + 2, where some points are attracted by the cycle 0, 1, 0, 1… rather than by a root. An open set for which the iterations converge towards a given root or cycle (that is not a fixed point), is a Fatou set for the iteration. The complementary set to the union of all these, is the Julia set. The Fatou sets have common boundary, namely the Julia set. Therefore, each point of the Julia set is a point of accumulation for each of the Fatou sets. It is this property that causes the fractal structure of the Julia set (when the degree of the polynomial is larger than 2). To plot images of the fractal, one may first choose a specified number d of complex points (ζ1, …, ζd) and compute the coefficients (p1, …, pd) of the polynomial

p ( z ) = z d + p 1 z d − 1 + ⋯ + p d − 1 z + p d := ( z − ζ 1 ) ( z − ζ 2 ) ⋯ ( z − ζ d ) {\displaystyle p(z)=z^{d}+p_{1}z^{d-1}+\cdots +p_{d-1}z+p_{d}:=(z-\zeta _{1})(z-\zeta _{2})\cdots (z-\zeta _{d})} . Then for a rectangular lattice

z m n = z 00 + m Δ x + i n Δ y ; m = 0 , … , M − 1 ; n = 0 , … , N − 1 {\displaystyle z_{mn}=z_{00}+m\,\Delta x+in\,\Delta y;\quad m=0,\ldots ,M-1;\quad n=0,\ldots ,N-1}

of points in C {\displaystyle \mathbb {C} } , one finds the index k(m,n) of the corresponding root ζk(m,n) and uses this to fill an M × N raster grid by assigning to each point (m,n) a color fk(m,n). Additionally or alternatively the colors may be dependent on the distance D(m,n), which is defined to be the first value D such that |zD − ζk(m,n)| < ε for some previously fixed small ε > 0.

Generalization of Newton fractals A generalization of Newton's iteration is

z n + 1 = z n − a p ( z n ) p ′ ( z n ) {\displaystyle z_{n+1}=z_{n}-a{\frac {p(z_{n})}{p'(z_{n})}}}

where a is any complex number. The special choice a = 1 corresponds to the Newton fractal. The fixed points of this map are stable when a lies inside the disk of radius 1 centered at 1. When a is outside this disk, the fixed points are locally unstable, however the map still exhibits a fractal structure in the sense of Julia set. If p is a polynomial of degree d, then the sequence zn is bounded provided that a is inside a disk of radius d centered at d. More generally, Newton's fractal is a special case of a Julia set.

Series : p(z) = zn- 1

Other fractals where potential and trigonometric functions are multiplied. p(z) = zn*Sin(z) - 1

Nova fractal The Nova fractal invented in the mid 1990s by Paul Derbyshire, is a generalization of the Newton fractal with the addition of a value c at each step:

… excerpt ends here. Continue reading the full article.

Illustrations

Newton fractal: Fatou sets (blue, red and green) and Julia set (their boundary) for the rational function associated to Newton's method for f(z) = z3 − 1
Fatou sets (blue, red and green) and Julia set (their boundary) for the rational function associated to Newton's method for f(z) = z3 − 1
Newton fractal illustration
Newton fractal illustration
Newton fractal illustration
Newton fractal illustration

Worked examples

Example 1 — a first encounter with Newton fractal

Start with the simplest possible case. Write down what Newton fractal claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Newton fractal before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Newton fractal ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Newton fractal

In research
Newton fractal appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Newton fractal in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Newton fractal is common in secondary-school and first-year university syllabi. It links to neighbouring topics Fractals, Numerical analysis, so understanding it makes those chapters shorter.
In everyday life
Look for Newton fractal outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Newton fractal in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Newton fractal means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Newton fractal out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Newton fractal in simple terms?

The Newton fractal is a boundary set in the complex plane which is characterized by Newton's method applied to a fixed polynomial p(z) ∈ C {\displaystyle \mathbb {C} } [z] or transcendental function. It is the Julia set of the meromorphic function z ↦ z − ⁠p(z)/p′(z)⁠ which is given by Newton's met…

Why does Newton fractal matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Newton fractal?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Newton fractal.

Tags

  • Fractals
  • Numerical analysis

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