# Questions tagged [landau-notation]

Questions about asymptotic notations such as Big-O, Omega, etc.

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### How do I simplify $O\left({n^2}/{\log{\frac{n(n+1)}{2}}}\right)$

I'm not very certain about how to deal with asymptotics when they are in the denominator. For $$O\left(\frac{n^2}{\log{\frac{n(n+1)}{2}}}\right)$$, my intuition tells me that it should be treated in a ...
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### Is O((n^2)*log(n)) greater than O(n^(2.5))?

I know that $O(n^2\times \log(n))$ is greater than $O(n^2)$, but is $O(n^2\times \log(n))$ greater than $O(n^{2.5})$?
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### When are log complexities considered equivalent?

Would we consider $O(\log_2(n))$ to be the same complexity as $O(\log_2(n-1))$? Why or why not? I'm specifically wondering about how the number we take the log of affects the time complexity.
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### Substitution for Landau's O notation formula

I found the following description when I was reading a paper on computational complexity theory. This can be done ... in time 2n･poly(logs,n)+2O(logs)c. For s≤2no(1), the runtime is 2n･poly(n). I ...
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### which rule can conduct this formula $\log n = O(n^{0.000001})$? [duplicate]

i am learning this post about Big O, which gives this formula $$\log n = O(n^{0.000001})$$ why is that?
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### Run time of pseudo code in big theta notation [duplicate]

I am looking for the run time of the following pseudo code. ...
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### How can i prove this asymptotic comparison? [duplicate]

This is an exercise that's part of my assignment, but it is optional and flagged as a "challenge". I would like to discuss its solution: Prove that: $$27\log{n} + \sqrt{n} = \theta(\sqrt{n})$$ ...
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### If my algorithm has complexity O(n!*n), can I just write O(n!), or do I have to keep it like O(n!*n)?

Just as I asked in the title: if my algorithm has complexity $O(n!\times n)$, can I just write $O(n!)$, or I have to keep it like $O(n!\times n)$?
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### O(·) is not a function, so how can a function be equal to it?

I totally understand what big $O$ notation means. My issue is when we say $T(n)=O(f(n))$ , where $T(n)$ is running time of an algorithm on input of size $n$. I understand semantics of it. But $T(n)$ ...
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### How come O(n) + O(logn) = O(logn)

How come O(n) + O(logn) = O(logn)? When talking for example about an algorithm that has two operations. One of them takes O(n) and the other O(logn) and in the end we say that the total complexity is ...
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### Is this a valid use of big-O notation?

Suppose that $m=O(n^{c+1/2})$ for some real $c>0$ and $x=O(\sqrt{\log m})$. Are the following two computations valid? I understand that I'm abusing notations a bit to get at the desired results. ...
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### Introductory explanation of the Big-Oh properties

I've noticed that Big-Oh notation actually has some properties such as summation, product but i couldn't find an introductory explanation for their use or how they can help to solve asymptotic ...
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### How to prove $\Theta(g(n))\cup o(g(n))\ne O(g(n))$

How to prove $\Theta(g(n))\cup o(g(n))\ne O(g(n))$ ? Is there a simple example for understanding? Seems there's a gap between $O(g(n))- \Theta(g(n))$ and $o(g(n))$ just from the definition. But I ...
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### Is this correct in term of big-oh notation: given $g = O(f)$ and $h = O(f)$ can we say $g = O(h)$?

We have two equations $g = O(f)$ and $h = O(f)$ , then can we derive that $g = O(h)$. I came up with following proof but i dont know it's correct or not. $$g = O(f)$$ $$g \le c_1*f$$ $$h \le c_2*f$$ ...
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### Asymptotic Notation Analysis

2^n=O(3^n) : This is true or it is false if n>=0 or if n>=1 since 2^n may or not be element of O(3^n) I need a hint to figure the problem
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### complexity class of functions [duplicate]

What would these statements mean if f(n) and g(n) are functions over natural numbers? g(n) is in Θ(f(n)). and An algorithm is in the complexity class Θ(f(n)).
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### how to interpret O(1) + O(2) + … + O(n)? [duplicate]

in the book "Introduction to algorithms"(CLRS) page 49 it says: "The number of anonymous functions in an expression is understood to be equal to the number of times the asymptotic notation ...
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### Can the following O(…) expression be simplified?

I have an algorithm with three variables affecting the time complexity: $k$, $L$, and $n$. I have come up with the following that expresses the complexity: $O(kn + k^2L + k^2nL + knL)$ I think I ...
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### Asymptotic notation? [duplicate]

can someone pls help How do I prove 2⌊lg n⌋ = Θ(2⌈lg n⌉) 2 ⌈lg n⌉+⌊lg n⌋ = Θ(n2) I'm not too good at maths. I know, lim ( n -> infinty) = f(x)/g(x) if we get a real constant the statement ...
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### What does the $O^*$ notation mean?

I'm recently reading some papers on the maximum independent set problem, all the algorithms' time complexity is donated by $O^*()$ notation, like $O^*(1.0836^n)$. One paper says "the $O^*$notation ...
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### Question regarding $O(n^2)$ efficiency

I'm going through a video of EDX course which talks about Big O notation. At the end of the video they have some questions but the $O(n^2)$ answer is confusing me. It feels like a mistake, but I just ...
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### What $O$ -symbol supresses?

I am reading this book Asymptotic Methods in Analysis by N. G. de Bruijn. It describes the definition of $O$ symbol as A weaker form of suppression of information is given by the Bachmann-Landau ...
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### Why base of log is insignificant while considering time complexity? [duplicate]

If so, then $O(log_2 n)$ = $O(log_{10} n)$ = $O(log_e n)$. It is very wired that computer scientist treat them equally. Considering, $(log_2 n)$ = $m$, meaning $n$ = $2^m$ $(log_{10} n)$ = $m$, ...
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### Proving asymptotic notations for functions

I recently started learning about asymptotic notations. While I was doing practice questions (not HW) I found various question that stumped me totally. So I just want some pointers on how to go by ...
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### Why is $3^{\log_2 n}$ the same as $n^{\log_2 3}$? [closed]

I am reading about divide and conquer algorithm at following link on page on 57 in this link. The document analyzes the running time of the algorithm. At the very top level, when $k = 0$, this works ...
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### Theta Manipulation to show $N = \Theta(n/\log N)=\Theta(n/\log n)$

I am studying different models of computation and how algorithms can be interpreted under different models. Here is a math(?) question that has been bugging me. Suppose we have $n = \Theta(N\log N)$ ...
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### If $f(n)=\Omega(g(n))$ and $h(n)=\theta (g(n))$ then does this implies $f(n).g(n)=\Omega(g(n).h(n))$?

If $f(n)=\Omega(g(n))$ and $h(n)=\theta (g(n))$ then does this implies $f(n).g(n)=\Omega(g(n).h(n))$ I saw a proof where they have proved If $f(n)=O(g(n))$ and $h(n)=\theta (g(n))$ then this implies ...
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### When it is said an algorithm runs in exponential time, is it meant it has complexity $O(2^n)$, or $2^{O(n)}$?

Also, are they equivalent or are they different? Examples of algorithms/Turing Machines that run in complexity of one but not the other would be much appreciated.
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### Can I use Θ if tightest lower and upper bound are not the same?

When analyzing the asymptotic running time of an algorithm where the tightest lower bound and upper bound are not the same, is it bad to denote the running time in theta notation? If an algorithm has ...
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### f(n) and g(n) are monotonically increasing functions. h(n) = max(f,g) => h = O(f) or h = O(g)?

All functions are from naturals to naturals. Let f(n) and g(n) be monotonically increasing functions. prove or disprove h(n) = max(f(n),g(n)) => h = O(f) or h = O(g) I've found close questions ...
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### Complexity calculus: O(log(n-1) * log(n)) = O(log(n))? [duplicate]

I have a question about calculating the complexity. If i need to do log(n-1) times O(log(n)), will this give me a complexity of O(log(n))? My intuition says yes however I am not sure.
Is next time complexity sub-exponential? $O(2^{N^{LOG2(1.5)}}/8)$ unformatted: O((2^N)^LOG2(1.5))/8) just in case I didn't format it properly.