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Ulam–Warburton automaton

Ulam–Warburton automaton is a biology 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 Ulam–Warburton automaton rather than just read about it. In short: The Ulam–Warburton cellular automaton (UWCA) is a 2-dimensional fractal pattern that grows on a regular grid of cells consisting of squares. Starting with one square initially ON and all others OFF, successive iterations are generated by turning ON all squares that share precisely one edge with an ON square.

Ulam–Warburton automaton — main illustration
Ulam–Warburton automaton — illustration

Key takeaways

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

Reference excerpt

The Ulam–Warburton cellular automaton (UWCA) is a 2-dimensional fractal pattern that grows on a regular grid of cells consisting of squares. Starting with one square initially ON and all others OFF, successive iterations are generated by turning ON all squares that share precisely one edge with an ON square. This is the von Neumann neighborhood. The automaton is named after the Polish-American mathematician and scientist Stanislaw Ulam and the Scottish engineer, inventor and amateur mathematician Mike Warburton.

Properties and relations The UWCA is a 2D 5-neighbor outer totalistic cellular automaton using rule 686. The number of cells turned ON in each iteration is denoted u ( n ) , {\displaystyle u(n),} with an explicit formula:

u ( 0 ) = 0 , u ( 1 ) = 1 , {\displaystyle u(0)=0,u(1)=1,} and for n ≥ 2 {\displaystyle n\geq 2}

u ( n ) = 4 ⋅ 3 w t ( n − 1 ) − 1 {\displaystyle u(n)=4\cdot 3^{wt(n-1)-1}}

where w t ( n ) {\displaystyle wt(n)} is the Hamming weight function which counts the number of 1's in the binary expansion of n {\displaystyle n}

w t ( n ) = n − ∑ k = 1 ∞ ⌊ n 2 k ⌋ {\displaystyle wt(n)=n-\sum _{k=1}^{\infty }\left\lfloor {\frac {n}{2^{k}}}\right\rfloor }

The minimum upper bound of summation for k {\displaystyle k} is such that 2 k ≥ n {\displaystyle 2^{k}\geq n}

The total number of cells turned ON is denoted U ( n ) {\displaystyle U(n)}

U ( n ) = ∑ i = ⁡ 0 n u ( i ) = 4 3 ∑ i = ⁡ 0 n − 1 3 w t ( i ) − 1 3 {\displaystyle U(n)=\sum _{i\mathop {=} 0}^{n}u(i)={\frac {4}{3}}\sum _{i\mathop {=} 0}^{n-1}3^{wt(i)}-{\frac {1}{3}}}

Table of wt(n), u(n) and U(n) The table shows that different inputs to w t ( n ) {\displaystyle wt(n)} can lead to the same output. This surjective property emerges from the simple rule of growth – a new cell is born if it shares only one-edge with an existing ON cell - the process appears disorderly and is modeled by functions involving w t ( n ) {\displaystyle wt(n)} but within the chaos there is regularity.

U ( n ) {\displaystyle U(n)} is OEIS sequence A147562 and u ( n ) {\displaystyle u(n)} is OEIS sequence A147582

Counting cells with quadratics

For all integer sequences of the form n m = m ⋅ 2 k {\displaystyle n_{m}=m\cdot 2^{k}} where m ≥ 1 {\displaystyle m\geq 1} and k ≥ 0 {\displaystyle k\geq 0}

Let

a m = ∑ i = ⁡ 0 m − 1 3 w t ( i ) {\displaystyle a_{m}=\sum _{i\mathop {=} 0}^{m-1}3^{wt(i)}}

( a m {\displaystyle a_{m}} is OEIS sequence A130665) Then the total number of ON cells in the integer sequence n m {\displaystyle n_{m}} is given by

U m ( n m ) = a m m 2 4 3 n m 2 − 1 3 {\displaystyle U_{m}(n_{m})={\frac {a_{m}}{m^{2}}}{\frac {4}{3}}n_{m}^{2}-{\frac {1}{3}}}

… excerpt ends here. Continue reading the full article.

Illustrations

Ulam–Warburton automaton: The first twenty iterations of the Ulam-Warburton cellular automaton
The first twenty iterations of the Ulam-Warburton cellular automaton
Ulam–Warburton automaton: Total number of ON cells 
  
    
      
        U
        (
        n
        )
      
    
    {\displaystyle U(n)}
  
 in the Ulam–Warburton CA and quadratics 
  
    
      
        
          U
          
            1
          
        
        ,
        
          U
          
            3
          
        
      
    
    {\displaystyle U_{1},U_{3}}
  
  and 
  
    
      
        
          U
          
            17
          
        
      
    
    {\displaystyle U_{17}}
Total number of ON cells U ( n ) {\displaystyle U(n)} in the Ulam–Warburton CA and quadratics U 1 , U 3 {\displaystyle U_{1},U_{3}} and U 17 {\displaystyle U_{17}}
Ulam–Warburton automaton: Total number of ON cells in the Ulam–Warburton cellular automaton
Total number of ON cells in the Ulam–Warburton cellular automaton
Ulam–Warburton automaton: Upper and lower bounds of 
  
    
      
        U
        (
        n
        )
        
          /
        
        
          n
          
            2
          
        
      
    
    {\displaystyle U(n)/n^{2}}
Upper and lower bounds of U ( n ) / n 2 {\displaystyle U(n)/n^{2}}
Ulam–Warburton automaton: Hex-Ulam-Warburton cellular automaton - generation 11
Hex-Ulam-Warburton cellular automaton - generation 11

Worked examples

Example 1 — a first encounter with Ulam–Warburton automaton

Start with the simplest possible case. Write down what Ulam–Warburton automaton claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In biology, 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 Ulam–Warburton automaton 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 Ulam–Warburton automaton 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 Ulam–Warburton automaton

In research
Ulam–Warburton automaton appears in biology 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 Ulam–Warburton automaton 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
Ulam–Warburton automaton is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cellular automaton rules, Fractals, so understanding it makes those chapters shorter.
In everyday life
Look for Ulam–Warburton automaton 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 Ulam–Warburton automaton in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Ulam–Warburton automaton 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 Ulam–Warburton automaton out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Ulam–Warburton automaton in simple terms?

The Ulam–Warburton cellular automaton (UWCA) is a 2-dimensional fractal pattern that grows on a regular grid of cells consisting of squares. Starting with one square initially ON and all others OFF, successive iterations are generated by turning ON all squares that share precisely one edge with an…

Why does Ulam–Warburton automaton matter?

Because it connects several biology 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 Ulam–Warburton automaton?

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 Ulam–Warburton automaton.

Tags

  • Cellular automaton rules
  • Fractals

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