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4.1: Big-O Notation

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    Show that the following functions of \(n\) are ranked in order from least to greatest eventual growth.

    \(1, \log_2 n, n, n\log_2 n, n^2, 2^n, n!, n^n\)

    For what integer values of \(n\) does a function in the list above surpass (or equal) the previous one?

    Big-O notation is commonly used to describe the growth of functions and, as we will see in subsequent sections, in estimating the number of operations an algorithm requires.

    Definition: Big-o notation

    Let \(f\) and \(g\) be real-valued functions (with domain \(\mathbb{R}\) or \(\mathbb{N}\)) and assume that \(g\) is eventually positive. We say that \(f(x)\) is \(O(g(x))\) if there are constants \(M\) and \(k\) so that

    \(|f(x)|\le Mg(x)\)

    for all \(x> k\). We read this as "\(f\) is big-O of \(g\)" and sometimes it is written as \(f(x)=O(g(x))\).

    To show that one function is big-O of another, we must produce the constants \(M\) and \(k\).

    Example \(\PageIndex{1}\)

    Show that \(f(x)=x^2+3x-2\) is \(O(x^3)\).


    We notice that as long as \(x> 1\), \(x^2\le x^3\) and \(3x-2\le x^3\). Therefore, when \(x> 1\), we have that \(|f(x)|=x^2+3x-2\le 2x^3\). So we choose \(k=1\) and \(M=2\). There are infinitely many other choices for pairs \(k,M\) that would work as well.

    Exercise \(\PageIndex{2}\)

    Suppose \(f(x)=x^2+2x+2\) and \(g(x)=x^2\). Prove that \(f(x)\) is \(O(g(x))\) and \(g(x)\) is \(O(f(x))\)


    For the first part, use \(k=2\) and \(M=3\). For the second, try \(k=0\) and \(M=1\).

    If two functions \(f\) and \(g\) are both big-O of the other one, we say that \(f\) and \(g\) have the same order.

    We can also use the definition to show that a function is not big-O of another.

    Exercise \(\PageIndex{3}\)

    Prove that \(f(x)=3x^5\) is not \(O(x^4)\).


    Assume that a \(k\) and \(M\) exist and then find a contradiction.

    In fact, we can prove a statement involving polynomials in general.

    Theorem \(\PageIndex{4}\)

    Let \(p(x)=a_nx^n+a_{n-1}x^{n-1}+\ldots+a_1x+a_0\) where the \(a_i\) are real numbers with \(a_n\neq 0\). Then \(p(x)\) is \(O(x^m)\) if and only if \(m\ge n\). [In particular, \(p(x)\) is of order \(x^n\).]

    Proof Idea

    First assume that \(m\ge n\) and use \(k=1\). (Think about what \(M\) should be.) Then assume \(m<n\) and show that it is not possible for \(p(x)\) to be \(O(x^m)\) similarly to how we did in the prior exercise.

    So far, we haven't considered any examples of functions with domain \(\mathbb{N}\).

    Example \(\PageIndex{5}\)

    Suppose \(f(n)=1^2+2^2+\cdots +n^2\). Show that \(f(n)\) is \(O(n^3)\).


    Notice that \(f(n)=1^2+2^2+\cdots+n^2\le n^2+n^2+\cdots +n^2=n^3\). Using \(k=M=1\) we see that \(f(n)\) is \(O(n^3)\).

    Some results for commonly-used functions are given below.

    Theorem \(\PageIndex{6}\)

    1. If \(1<a<b\), then \(x^a\) is \(O(x^b)\) but \(x^b\) is not \(O(x^a)\).
    2. If \(b>1\), then \(\log_b(x)\) is \(O(x)\) but \(x\) is not \(O(\log_b(x))\).
    3. If \(b>1\) and \(a\) is positive, then \(x^a\) is \(O(b^x)\) but \(b^x\) is not \(O(x^a)\)
    4. If \(1<a<b\), then \(a^x\) is \(O(b^x)\) but \(b^x\) is not \(O(a^x)\).

    You should be able to prove all of these.

    Theorem \(\PageIndex{7}\)

    Suppose that \(f_1(x)\) is \(O(g_1(x))\) and \(f_2(x)\) is \(O(g_2(x))\). Then \((f_1+f_2)(x)\) is \(O(\max(|g_1(x)|,|g_2(x)|)\) and \((f_1f_2)(x)\) is \(O(g_1(x)g_2(x))\).


    We will prove the second result here; the proof of the first is similar. We know that there exist constants \(M_1,M_2,k_1,k_2\) so that \(|f_1(x)|\le M_1|g_1(x)| \) for \(x> k_1\) and \(|f_2(x)|\le M_2|g_2(x)|\) for \(x> k_2\). Then, as long as \(x\) is bigger than both \(k_1\) and \(k_2\) we have that \(|f_1(x)f_2(x)|\le |f_1(x)||f_1(x)|\le M_1|g_1(x)| M_2|g_2(x)|\le M_1M_2|g_1(x)g_2(x)|\). In particular we use \(M=M_1M_2\) and \(k=\max(k_1,k_2)\).

    Now apply these prior results.

    Exercise \(\PageIndex{8}\)

    Show that \(h(x)=(x+1)^2\log(x^4-3)+2x^3\) is \(O(x^3)\).

    There are a few other definitions provided below, also related to growth of functions. Big-omega notation is used to when discussing lower bounds in much the same way that big-O is for upper bounds.

    Definition: Big-\(\Omega\) Notation

    Let \(f\) and \(g\) be real-valued functions (with domain \(\mathbb{R}\) or \(\mathbb{N}\)). We say that \(f(x)\) is \(\Omega(g(x))\) if there are constants \(M\) and \(k\) so that

    \(|f(x)|\ge M|g(x)|\)

    for all \(x> k\). We read this as "\(f\) is big-omega of \(g\)".

    Definition: BIG-\(\Theta\) Notation

    Let \(f\) and \(g\) be real-valued functions (with domain \(\mathbb{R}\) or \(\mathbb{N}\)). We say that \(f(x)\) is \(\Theta(g(x))\) if \(f(x)\) is both \(\Omega(g(x))\) and \(O(g(x))\). We read this as "\(f\) is big-theta of \(g\)" and that \(f\) and \(g\) have the same order.

    4.1: Big-O Notation is shared under a CC BY-NC-SA license and was authored, remixed, and/or curated by LibreTexts.

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