<s>[INST] AsymptoticNotation/O-notation gives us one way to analyze the performancelimitationsof an algorithm. However, there are two importantperformance limitations that can be looked at in terms of asymptoticnotation.Big-O notation only considers what is possible to achieve in terms of performance.Although it provides an upper-bound on an algorithm’s running-time, thatbound might not be at all typical of expectations. For instance, O(n!) doesnot have to grow as quickly as Omega(n!), even though often times it does.Besides exponential and factorial functions, polynomials form a huge classto observe performance. The two prominent asymptotic notations used inalgorithm analysis are as follows:1. Big Omega (Ω(n)) — a lower bound2. Big Theta (Θ(n)) — a tight boundLet’s elaborate on both of the notations.[/INST]