Someone claims that the big O notation does not make sense at all, and they give the following example. An algorithm A that processes an input set of N elements takes time, in seconds, given by T(N) = 10000*N + 0.00001*N^3. They say that the large constant (10000) associated with the N will always dominate over the small constant (0.00001) associated with the N^3. You say that this algorithm A is:

Write a program that performs a simple n-body simulation, called "jumping leprechauns." this simulation involves n leprechauns, numberd 1 to n. it maintains a gold value g_i for each leprechaun i, which begins with each leprechaun starting out with a million dollars worth of gold, that is, g_i = 1000000 for each i = 1,. in addition, the simulation also maintains, for each leprachaun,i, a place on the horizon, which is represented as a double-precision floating point number, x_i. in each iteration of the simulation, the simulation processes the leprachauns in order. processing a leprachaun i during its iteration begins by computing a new place on the horizon for i, which is determined by the assignment: