In mathematics, the tent map with parameter μ is the real-valued function fμ defined by
f μ ( x ) := μ min { x , 1 − x } , {\displaystyle f_{\mu }(x):=\mu \min\{x,\,1-x\},}
the name being due to the tent-like shape of the graph of fμ. For the values of the parameter μ within 0 and 2, fμ maps the unit interval [0, 1] into itself, thus defining a discrete-time dynamical system on it (equivalently, a recurrence relation). In particular, iterating a point x0 in [0, 1] gives rise to a sequence x n {\displaystyle x_{n}} :
x n + 1 = f μ ( x n ) = { μ x n f o r x n < 1 2 μ ( 1 − x n ) f o r 1 2 ≤ x n {\displaystyle x_{n+1}=f_{\mu }(x_{n})={\begin{cases}\mu x_{n}&\mathrm {for} ~~x_{n}<{\frac {1}{2}}\\\mu (1-x_{n})&\mathrm {for} ~~{\frac {1}{2}}\leq x_{n}\end{cases}}}
where μ is a positive real constant. Choosing for instance the parameter μ = 2, the effect of the function fμ may be viewed as the result of the operation of folding the unit interval in two, then stretching the resulting interval [0, 1/2] to get again the interval [0, 1]. Iterating the procedure, any point x0 of the interval assumes new subsequent positions as described above, generating a sequence xn in [0, 1]. The μ = 2 {\displaystyle \mu =2} case of the tent map is a non-linear transformation of both the bit shift map and the r = 4 case of the logistic map.
Behaviour
The tent map with parameter μ = 2 and the logistic map with parameter r = 4 are topologically conjugate, and thus the behaviours of the two maps are in this sense identical under iteration. Depending on the value of μ, the tent map demonstrates a range of dynamical behaviour ranging from predictable to chaotic.
If μ is less than 1 the point x = 0 is an attractive fixed point of the system for all initial values of x i.e. the system will converge towards x = 0 from any initial value of x. If μ is 1 all values of x less than or equal to 1/2 are fixed points of the system. If μ is greater than 1 the system has two fixed points, one at 0, and the other at μ/(μ + 1). Both fixed points are unstable, i.e. a value of x close to either fixed point will move away from it, rather than towards it. For example, when μ is 1.5 there is a fixed point at x = 0.6 (since 1.5(1 − 0.6) = 0.6) but starting at x = 0.61 we get
0.61 → 0.585 → 0.6225 → 0.56625 → 0.650625 … {\displaystyle 0.61\to 0.585\to 0.6225\to 0.56625\to 0.650625\ldots }
If μ is between 1 and the square root of 2 the system maps a set of intervals between μ − μ2/2 and μ/2 to themselves. This set of intervals is the Julia set of the map – that is, it is the smallest invariant subset of the real line under this map. If μ is greater than the square root of 2, these intervals merge, and the Julia set is the whole interval from μ − μ2/2 to μ/2 (see bifurcation diagram). If μ is between 1 and 2 the interval [μ − μ2/2, μ/2] contains both periodic and non-periodic points, although all of the orbits are unstable (i.e. nearby points move away from the orbits rather than towards them). Orbits with longer lengths appear as μ increases. For example:
μ μ 2 + 1 → μ 2 μ 2 + 1 → μ μ 2 + 1 appears at μ = 1 {\displaystyle {\frac {\mu }{\mu ^{2}+1}}\to {\frac {\mu ^{2}}{\mu ^{2}+1}}\to {\frac {\mu }{\mu ^{2}+1}}{\mbox{ appears at }}\mu =1}
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