Why aren't primary tests easily linear in time complexity?
Why don't we consider them as linear? I don't understand. You just have to check for factorization up to sqrt of n. So it's even faster than linear.
I assume it's not linear only if we compare the number of operations relative to the input in terms of binary representation. But why would we do so?
It seems to me wrong. The growth in calculation should be calculated compared to the number itself. Why do we compare it to the binary representation?
algorithm-analysis time-complexity runtime-analysis
asked 3 hours ago
bilanush
193
add a comment |
Why don't we consider them as linear? I don't understand. You just have to check for factorization up to sqrt of n. So it's even faster than linear.
I assume it's not linear only if we compare the number of operations relative to the input in terms of binary representation. But why would we do so?
It seems to me wrong. The growth in calculation should be calculated compared to the number itself. Why do we compare it to the binary representation?
algorithm-analysis time-complexity runtime-analysis
asked 3 hours ago
bilanush
193
add a comment |
Why don't we consider them as linear? I don't understand. You just have to check for factorization up to sqrt of n. So it's even faster than linear.
I assume it's not linear only if we compare the number of operations relative to the input in terms of binary representation. But why would we do so?
It seems to me wrong. The growth in calculation should be calculated compared to the number itself. Why do we compare it to the binary representation?
algorithm-analysis time-complexity runtime-analysis
asked 3 hours ago
bilanush
193
Why don't we consider them as linear? I don't understand. You just have to check for factorization up to sqrt of n. So it's even faster than linear.
I assume it's not linear only if we compare the number of operations relative to the input in terms of binary representation. But why would we do so?
It seems to me wrong. The growth in calculation should be calculated compared to the number itself. Why do we compare it to the binary representation?
algorithm-analysis time-complexity runtime-analysis
algorithm-analysis time-complexity runtime-analysis
asked 3 hours ago
bilanush
193
asked 3 hours ago
bilanush
193
asked 3 hours ago
bilanush
193
asked 3 hours ago
bilanush
193
asked 3 hours ago
bilanush
193
193
add a comment |
add a comment |
1 Answer
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Simple. When you give the number one trillion as input to your algorithm, do you give it as 1'000'000'000'000, or as a terabyte large string of ones?
And by all means, you are free to choose whichever representation you feel comfortable with.
We analyze the runtime as a function of the size of the input, not as the magnitude of the number represented by the input were the input to be a number.
answered 2 hours ago
Pål GD
5,8871939
Sorry. But this is exactly what I don't understand. Why do we care about the binary representation ? It just looks like a manipulation of looking at it's binaric input and asking about the complexity of it. Why don't you look at the number itself which is what we truly care about. The whole point of complexity is to assess how fast the time grows as we move to greater numbers. So the most logical way of looking at it is by assessing how fast for example grow when we move from 10 to 100 . So it's 2^4 compared to 2^7 the growth is exactly linearly proportional to the input number
– bilanush
19 mins ago
We as humans deal with the number itself. Not with it's binaric shape. Why on Earth would it matter the complexity compared to binaric input? We are only trying to figure out how complicated the algorithm gets as we go to greater numbers. It doesn't matter at all the way computer choose to write it. Buttom line we should care only about the number of operations the computer does, and as well as the input. But of course, we should care about the magnitude of the number because this is what we are having in our heads , what is the rate in which the complexity grows as we go to great number
– bilanush
10 mins ago
@bilanush no, we as humans are incapable of doing math on "the number itself". Usually we use the base-10 representation. Which is the same size as the base-2 representation, within a constant factor.
– hobbs
3 mins ago
add a comment |
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1 Answer
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1 Answer
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Simple. When you give the number one trillion as input to your algorithm, do you give it as 1'000'000'000'000, or as a terabyte large string of ones?
And by all means, you are free to choose whichever representation you feel comfortable with.
We analyze the runtime as a function of the size of the input, not as the magnitude of the number represented by the input were the input to be a number.
answered 2 hours ago
Pål GD
5,8871939
Sorry. But this is exactly what I don't understand. Why do we care about the binary representation ? It just looks like a manipulation of looking at it's binaric input and asking about the complexity of it. Why don't you look at the number itself which is what we truly care about. The whole point of complexity is to assess how fast the time grows as we move to greater numbers. So the most logical way of looking at it is by assessing how fast for example grow when we move from 10 to 100 . So it's 2^4 compared to 2^7 the growth is exactly linearly proportional to the input number
– bilanush
19 mins ago
We as humans deal with the number itself. Not with it's binaric shape. Why on Earth would it matter the complexity compared to binaric input? We are only trying to figure out how complicated the algorithm gets as we go to greater numbers. It doesn't matter at all the way computer choose to write it. Buttom line we should care only about the number of operations the computer does, and as well as the input. But of course, we should care about the magnitude of the number because this is what we are having in our heads , what is the rate in which the complexity grows as we go to great number
– bilanush
10 mins ago
@bilanush no, we as humans are incapable of doing math on "the number itself". Usually we use the base-10 representation. Which is the same size as the base-2 representation, within a constant factor.
– hobbs
3 mins ago
add a comment |
Simple. When you give the number one trillion as input to your algorithm, do you give it as 1'000'000'000'000, or as a terabyte large string of ones?
And by all means, you are free to choose whichever representation you feel comfortable with.
We analyze the runtime as a function of the size of the input, not as the magnitude of the number represented by the input were the input to be a number.
answered 2 hours ago
Pål GD
5,8871939
Sorry. But this is exactly what I don't understand. Why do we care about the binary representation ? It just looks like a manipulation of looking at it's binaric input and asking about the complexity of it. Why don't you look at the number itself which is what we truly care about. The whole point of complexity is to assess how fast the time grows as we move to greater numbers. So the most logical way of looking at it is by assessing how fast for example grow when we move from 10 to 100 . So it's 2^4 compared to 2^7 the growth is exactly linearly proportional to the input number
– bilanush
19 mins ago
We as humans deal with the number itself. Not with it's binaric shape. Why on Earth would it matter the complexity compared to binaric input? We are only trying to figure out how complicated the algorithm gets as we go to greater numbers. It doesn't matter at all the way computer choose to write it. Buttom line we should care only about the number of operations the computer does, and as well as the input. But of course, we should care about the magnitude of the number because this is what we are having in our heads , what is the rate in which the complexity grows as we go to great number
– bilanush
10 mins ago
@bilanush no, we as humans are incapable of doing math on "the number itself". Usually we use the base-10 representation. Which is the same size as the base-2 representation, within a constant factor.
– hobbs
3 mins ago
add a comment |
Simple. When you give the number one trillion as input to your algorithm, do you give it as 1'000'000'000'000, or as a terabyte large string of ones?
And by all means, you are free to choose whichever representation you feel comfortable with.
We analyze the runtime as a function of the size of the input, not as the magnitude of the number represented by the input were the input to be a number.
answered 2 hours ago
Pål GD
5,8871939
Simple. When you give the number one trillion as input to your algorithm, do you give it as 1'000'000'000'000, or as a terabyte large string of ones?
And by all means, you are free to choose whichever representation you feel comfortable with.
We analyze the runtime as a function of the size of the input, not as the magnitude of the number represented by the input were the input to be a number.
answered 2 hours ago
Pål GD
5,8871939
answered 2 hours ago
Pål GD
5,8871939
answered 2 hours ago
Pål GD
5,8871939
answered 2 hours ago
Pål GD
5,8871939
5,8871939
Sorry. But this is exactly what I don't understand. Why do we care about the binary representation ? It just looks like a manipulation of looking at it's binaric input and asking about the complexity of it. Why don't you look at the number itself which is what we truly care about. The whole point of complexity is to assess how fast the time grows as we move to greater numbers. So the most logical way of looking at it is by assessing how fast for example grow when we move from 10 to 100 . So it's 2^4 compared to 2^7 the growth is exactly linearly proportional to the input number
– bilanush
19 mins ago
We as humans deal with the number itself. Not with it's binaric shape. Why on Earth would it matter the complexity compared to binaric input? We are only trying to figure out how complicated the algorithm gets as we go to greater numbers. It doesn't matter at all the way computer choose to write it. Buttom line we should care only about the number of operations the computer does, and as well as the input. But of course, we should care about the magnitude of the number because this is what we are having in our heads , what is the rate in which the complexity grows as we go to great number
– bilanush
10 mins ago
@bilanush no, we as humans are incapable of doing math on "the number itself". Usually we use the base-10 representation. Which is the same size as the base-2 representation, within a constant factor.
– hobbs
3 mins ago
add a comment |
Sorry. But this is exactly what I don't understand. Why do we care about the binary representation ? It just looks like a manipulation of looking at it's binaric input and asking about the complexity of it. Why don't you look at the number itself which is what we truly care about. The whole point of complexity is to assess how fast the time grows as we move to greater numbers. So the most logical way of looking at it is by assessing how fast for example grow when we move from 10 to 100 . So it's 2^4 compared to 2^7 the growth is exactly linearly proportional to the input number
– bilanush
19 mins ago
We as humans deal with the number itself. Not with it's binaric shape. Why on Earth would it matter the complexity compared to binaric input? We are only trying to figure out how complicated the algorithm gets as we go to greater numbers. It doesn't matter at all the way computer choose to write it. Buttom line we should care only about the number of operations the computer does, and as well as the input. But of course, we should care about the magnitude of the number because this is what we are having in our heads , what is the rate in which the complexity grows as we go to great number
– bilanush
10 mins ago
@bilanush no, we as humans are incapable of doing math on "the number itself". Usually we use the base-10 representation. Which is the same size as the base-2 representation, within a constant factor.
– hobbs
3 mins ago
Sorry. But this is exactly what I don't understand. Why do we care about the binary representation ? It just looks like a manipulation of looking at it's binaric input and asking about the complexity of it. Why don't you look at the number itself which is what we truly care about. The whole point of complexity is to assess how fast the time grows as we move to greater numbers. So the most logical way of looking at it is by assessing how fast for example grow when we move from 10 to 100 . So it's 2^4 compared to 2^7 the growth is exactly linearly proportional to the input number
– bilanush
19 mins ago
Sorry. But this is exactly what I don't understand. Why do we care about the binary representation ? It just looks like a manipulation of looking at it's binaric input and asking about the complexity of it. Why don't you look at the number itself which is what we truly care about. The whole point of complexity is to assess how fast the time grows as we move to greater numbers. So the most logical way of looking at it is by assessing how fast for example grow when we move from 10 to 100 . So it's 2^4 compared to 2^7 the growth is exactly linearly proportional to the input number
– bilanush
19 mins ago
We as humans deal with the number itself. Not with it's binaric shape. Why on Earth would it matter the complexity compared to binaric input? We are only trying to figure out how complicated the algorithm gets as we go to greater numbers. It doesn't matter at all the way computer choose to write it. Buttom line we should care only about the number of operations the computer does, and as well as the input. But of course, we should care about the magnitude of the number because this is what we are having in our heads , what is the rate in which the complexity grows as we go to great number
– bilanush
10 mins ago
We as humans deal with the number itself. Not with it's binaric shape. Why on Earth would it matter the complexity compared to binaric input? We are only trying to figure out how complicated the algorithm gets as we go to greater numbers. It doesn't matter at all the way computer choose to write it. Buttom line we should care only about the number of operations the computer does, and as well as the input. But of course, we should care about the magnitude of the number because this is what we are having in our heads , what is the rate in which the complexity grows as we go to great number
– bilanush
10 mins ago
@bilanush no, we as humans are incapable of doing math on "the number itself". Usually we use the base-10 representation. Which is the same size as the base-2 representation, within a constant factor.
– hobbs
3 mins ago
@bilanush no, we as humans are incapable of doing math on "the number itself". Usually we use the base-10 representation. Which is the same size as the base-2 representation, within a constant factor.
– hobbs
3 mins ago
add a comment |
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