ArticleslgStudy

mathematics

Rabinovich–Fabrikant equations

Rabinovich–Fabrikant equations is a mathematics 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 Rabinovich–Fabrikant equations rather than just read about it. In short: The Rabinovich–Fabrikant equations are a set of three coupled ordinary differential equations exhibiting chaotic behaviour for certain values of the parameters. They are named after Mikhail Rabinovich and Anatoly Fabrikant, who described them in 1979.

Rabinovich–Fabrikant equations — main illustration
Rabinovich–Fabrikant equations — illustration

Key takeaways

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

Reference excerpt

The Rabinovich–Fabrikant equations are a set of three coupled ordinary differential equations exhibiting chaotic behaviour for certain values of the parameters. They are named after Mikhail Rabinovich and Anatoly Fabrikant, who described them in 1979.

System description The equations are:

x ˙ = y ( z − 1 + x 2 ) + γ x {\displaystyle {\dot {x}}=y(z-1+x^{2})+\gamma x\,}

y ˙ = x ( 3 z + 1 − x 2 ) + γ y {\displaystyle {\dot {y}}=x(3z+1-x^{2})+\gamma y\,}

z ˙ = − 2 z ( α + x y ) , {\displaystyle {\dot {z}}=-2z(\alpha +xy),\,}

where α, γ are constants that control the evolution of the system. For some values of α and γ, the system is chaotic, but for others it tends to a stable periodic orbit. Danca and Chen note that the Rabinovich–Fabrikant system is difficult to analyse (due to the presence of quadratic and cubic terms) and that different attractors can be obtained for the same parameters by using different step sizes in the integration, see on the right an example of a solution obtained by two different solvers for the same parameter values and initial conditions. Also, recently, a hidden attractor was discovered in the Rabinovich–Fabrikant system.

Equilibrium points

The Rabinovich–Fabrikant system has five hyperbolic equilibrium points, one at the origin and four dependent on the system parameters α and γ:

x ~ 0 = ( 0 , 0 , 0 ) {\displaystyle {\tilde {\mathbf {x} }}_{0}=(0,0,0)}

x ~ 1 , 2 = ( ± q − , ∓ α q − , 1 − ( 1 − γ α ) q − 2 ) {\displaystyle {\tilde {\mathbf {x} }}_{1,2}=\left(\pm q_{-},\mp {\frac {\alpha }{q_{-}}},1-\left(1-{\frac {\gamma }{\alpha }}\right)q_{-}^{2}\right)}

x ~ 3 , 4 = ( ± q + , ∓ α q + , 1 − ( 1 − γ α ) q + 2 ) {\displaystyle {\tilde {\mathbf {x} }}_{3,4}=\left(\pm q_{+},\mp {\frac {\alpha }{q_{+}}},1-\left(1-{\frac {\gamma }{\alpha }}\right)q_{+}^{2}\right)}

where

… excerpt ends here. Continue reading the full article.

Illustrations

Rabinovich–Fabrikant equations: Trajectory of a solution with parameter values 
  
    
      
        α
        =
        0.05
      
    
    {\displaystyle \alpha =0.05}
  
 and 
  
    
      
        γ
        =
        0.1
      
    
    {\displaystyle \gamma =0.1}
  
 and initial conditions 
  
    
      
        
          x
          
            0
          
        
        =
        0.1
      
    
    {\displaystyle x_{0}=0.1}
  
, 
  
    
      
        
          y
          
            0
          
        
        =
        −
        0.1
      
    
    {\displaystyle y_{0}=-0.1}
  
, and 
  
    
      
        
          z
          
            0
          
        
        =
        0.1
      
    
    {\displaystyle z_{0}=0.1}
  
, using the default ODE solver in MATLAB. Colors vary from blue to yellow with time.
Trajectory of a solution with parameter values α = 0.05 {\displaystyle \alpha =0.05} and γ = 0.1 {\displaystyle \gamma =0.1} and initial conditions x 0 = 0.1 {\displaystyle x_{0}=0.1} , y 0 = − 0.1 {\displaystyle y_{0}=-0.1} , and z 0 = 0.1 {\displaystyle z_{0}=0.1} , using the default ODE solver in MATLAB. Colors vary from blue to yellow with time.
Rabinovich–Fabrikant equations: Trajectory of a solution with parameter values 
  
    
      
        α
        =
        0.05
      
    
    {\displaystyle \alpha =0.05}
  
 and 
  
    
      
        γ
        =
        0.1
      
    
    {\displaystyle \gamma =0.1}
  
 and initial conditions 
  
    
      
        
          x
          
            0
          
        
        =
        0.1
      
    
    {\displaystyle x_{0}=0.1}
  
, 
  
    
      
        
          y
          
            0
          
        
        =
        −
        0.1
      
    
    {\displaystyle y_{0}=-0.1}
  
, and 
  
    
      
        
          z
          
            0
          
        
        =
        0.1
      
    
    {\displaystyle z_{0}=0.1}
  
, using the default ODE solver in Mathematica. Colors vary from orange-red to magenta-red with time. Notice the drastic change in the solutions with respect to the solution obtained with MATLAB.
Trajectory of a solution with parameter values α = 0.05 {\displaystyle \alpha =0.05} and γ = 0.1 {\displaystyle \gamma =0.1} and initial conditions x 0 = 0.1 {\displaystyle x_{0}=0.1} , y 0 = − 0.1 {\displaystyle y_{0}=-0.1} , and z 0 = 0.1 {\displaystyle z_{0}=0.1} , using the default ODE solver in Mathematica. Colors vary from orange-red to magenta-red with time. Notice the drastic change in the solutions with respect to the solution obtained with MATLAB.
Rabinovich–Fabrikant equations: A chaotic attractor found with parameter values 
  
    
      
        α
        =
        1.1
      
    
    {\displaystyle \alpha =1.1}
  
 and 
  
    
      
        γ
        =
        0.87
      
    
    {\displaystyle \gamma =0.87}
  
 and initial conditions 
  
    
      
        
          x
          
            0
          
        
        =
        −
        1
      
    
    {\displaystyle x_{0}=-1}
  
, 
  
    
      
        
          y
          
            0
          
        
        =
        −
        0
      
    
    {\displaystyle y_{0}=-0}
  
, and 
  
    
      
        
          z
          
            0
          
        
        =
        0.5
      
    
    {\displaystyle z_{0}=0.5}
  
, using the default ODE solver in Mathematica. Colors vary from orange-red to magenta-red with time. Notice that colors do not follow any order, reflecting the chaotic dynamics of the solution.
A chaotic attractor found with parameter values α = 1.1 {\displaystyle \alpha =1.1} and γ = 0.87 {\displaystyle \gamma =0.87} and initial conditions x 0 = − 1 {\displaystyle x_{0}=-1} , y 0 = − 0 {\displaystyle y_{0}=-0} , and z 0 = 0.5 {\displaystyle z_{0}=0.5} , using the default ODE solver in Mathematica. Colors vary from orange-red to magenta-red with time. Notice that colors do not follow any order, reflecting the chaotic dynamics of the solution.
Rabinovich–Fabrikant equations: Graph of the regions for which equilibrium points 
  
    
      
        
          
            
              
                
                  x
                
                ~
              
            
          
          
            1
            ,
            2
            ,
            3
            ,
            4
          
        
      
    
    {\displaystyle {\tilde {\mathbf {x} }}_{1,2,3,4}}
  
 exist.
Graph of the regions for which equilibrium points x ~ 1 , 2 , 3 , 4 {\displaystyle {\tilde {\mathbf {x} }}_{1,2,3,4}} exist.
Rabinovich–Fabrikant equations: 3D parametric plot of the solution of the Rabinovich-Fabrikant equations for α=0.14 and γ=0.1 (limit cycle is shown by the red curve)
3D parametric plot of the solution of the Rabinovich-Fabrikant equations for α=0.14 and γ=0.1 (limit cycle is shown by the red curve)

Worked examples

Example 1 — a first encounter with Rabinovich–Fabrikant equations

Start with the simplest possible case. Write down what Rabinovich–Fabrikant equations claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, 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 Rabinovich–Fabrikant equations 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 Rabinovich–Fabrikant equations 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 Rabinovich–Fabrikant equations

In research
Rabinovich–Fabrikant equations appears in mathematics 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 Rabinovich–Fabrikant equations 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
Rabinovich–Fabrikant equations is common in secondary-school and first-year university syllabi. It links to neighbouring topics Chaotic maps, Equations, so understanding it makes those chapters shorter.
In everyday life
Look for Rabinovich–Fabrikant equations 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.
Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Rabinovich–Fabrikant equations” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Rabinovich–Fabrikant equations in 20 minutes

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

Frequently asked questions

What is Rabinovich–Fabrikant equations in simple terms?

The Rabinovich–Fabrikant equations are a set of three coupled ordinary differential equations exhibiting chaotic behaviour for certain values of the parameters. They are named after Mikhail Rabinovich and Anatoly Fabrikant, who described them in 1979.

Why does Rabinovich–Fabrikant equations matter?

Because it connects several mathematics 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 Rabinovich–Fabrikant equations?

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 Rabinovich–Fabrikant equations.

Tags

  • Chaotic maps
  • Equations

Keep exploring