Cauchy sequences and convergent sequences
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I am very confused with a little problem.
What is the difference between a Cauchy sequence and a convergent sequence?
functional-analysis
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add a comment |
$begingroup$
I am very confused with a little problem.
What is the difference between a Cauchy sequence and a convergent sequence?
functional-analysis
$endgroup$
$begingroup$
Every convergent sequence is a Cauchy sequence. The converse is not always true. If it is, we call such metric space complete.
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– APC89
Dec 22 '18 at 20:08
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Can you Give me an example which is Cauchy but not convergent an any space?
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– Masaud Khan
Dec 22 '18 at 20:10
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Consider the metric space $M := (0,1]subsettextbf{R}$. The sequence $a_{n} = 1/n$ is a Cauchy sequence, but it does not converge in $M$, since $lim a_{n} = 0$. Therefore $M$ is not complete.
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– APC89
Dec 22 '18 at 20:12
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Thanks. I was reading my real analysis book and get confused with the problem. And now i realized that real R is complete..
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– Masaud Khan
Dec 22 '18 at 20:16
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I think what makes it initially confusing is that we're already used to convergent sequences of real numbers before starting analysis, so it's instinctive to visualise Cauchy sequences as being exactly the same thing.
$endgroup$
– timtfj
Dec 22 '18 at 23:54
add a comment |
$begingroup$
I am very confused with a little problem.
What is the difference between a Cauchy sequence and a convergent sequence?
functional-analysis
$endgroup$
I am very confused with a little problem.
What is the difference between a Cauchy sequence and a convergent sequence?
functional-analysis
functional-analysis
edited Dec 22 '18 at 20:21
dantopa
6,58942244
6,58942244
asked Dec 22 '18 at 20:06
Masaud KhanMasaud Khan
162
162
$begingroup$
Every convergent sequence is a Cauchy sequence. The converse is not always true. If it is, we call such metric space complete.
$endgroup$
– APC89
Dec 22 '18 at 20:08
$begingroup$
Can you Give me an example which is Cauchy but not convergent an any space?
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:10
$begingroup$
Consider the metric space $M := (0,1]subsettextbf{R}$. The sequence $a_{n} = 1/n$ is a Cauchy sequence, but it does not converge in $M$, since $lim a_{n} = 0$. Therefore $M$ is not complete.
$endgroup$
– APC89
Dec 22 '18 at 20:12
$begingroup$
Thanks. I was reading my real analysis book and get confused with the problem. And now i realized that real R is complete..
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:16
$begingroup$
I think what makes it initially confusing is that we're already used to convergent sequences of real numbers before starting analysis, so it's instinctive to visualise Cauchy sequences as being exactly the same thing.
$endgroup$
– timtfj
Dec 22 '18 at 23:54
add a comment |
$begingroup$
Every convergent sequence is a Cauchy sequence. The converse is not always true. If it is, we call such metric space complete.
$endgroup$
– APC89
Dec 22 '18 at 20:08
$begingroup$
Can you Give me an example which is Cauchy but not convergent an any space?
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:10
$begingroup$
Consider the metric space $M := (0,1]subsettextbf{R}$. The sequence $a_{n} = 1/n$ is a Cauchy sequence, but it does not converge in $M$, since $lim a_{n} = 0$. Therefore $M$ is not complete.
$endgroup$
– APC89
Dec 22 '18 at 20:12
$begingroup$
Thanks. I was reading my real analysis book and get confused with the problem. And now i realized that real R is complete..
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:16
$begingroup$
I think what makes it initially confusing is that we're already used to convergent sequences of real numbers before starting analysis, so it's instinctive to visualise Cauchy sequences as being exactly the same thing.
$endgroup$
– timtfj
Dec 22 '18 at 23:54
$begingroup$
Every convergent sequence is a Cauchy sequence. The converse is not always true. If it is, we call such metric space complete.
$endgroup$
– APC89
Dec 22 '18 at 20:08
$begingroup$
Every convergent sequence is a Cauchy sequence. The converse is not always true. If it is, we call such metric space complete.
$endgroup$
– APC89
Dec 22 '18 at 20:08
$begingroup$
Can you Give me an example which is Cauchy but not convergent an any space?
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:10
$begingroup$
Can you Give me an example which is Cauchy but not convergent an any space?
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:10
$begingroup$
Consider the metric space $M := (0,1]subsettextbf{R}$. The sequence $a_{n} = 1/n$ is a Cauchy sequence, but it does not converge in $M$, since $lim a_{n} = 0$. Therefore $M$ is not complete.
$endgroup$
– APC89
Dec 22 '18 at 20:12
$begingroup$
Consider the metric space $M := (0,1]subsettextbf{R}$. The sequence $a_{n} = 1/n$ is a Cauchy sequence, but it does not converge in $M$, since $lim a_{n} = 0$. Therefore $M$ is not complete.
$endgroup$
– APC89
Dec 22 '18 at 20:12
$begingroup$
Thanks. I was reading my real analysis book and get confused with the problem. And now i realized that real R is complete..
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:16
$begingroup$
Thanks. I was reading my real analysis book and get confused with the problem. And now i realized that real R is complete..
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:16
$begingroup$
I think what makes it initially confusing is that we're already used to convergent sequences of real numbers before starting analysis, so it's instinctive to visualise Cauchy sequences as being exactly the same thing.
$endgroup$
– timtfj
Dec 22 '18 at 23:54
$begingroup$
I think what makes it initially confusing is that we're already used to convergent sequences of real numbers before starting analysis, so it's instinctive to visualise Cauchy sequences as being exactly the same thing.
$endgroup$
– timtfj
Dec 22 '18 at 23:54
add a comment |
3 Answers
3
active
oldest
votes
$begingroup$
Every convergent sequence is Cauchy but not every Cauchy sequence is convergent depending on which space you are considering.
A Cauchy sequence is a sequence where the terms of the sequence get arbitrarily close to each other after a while.
A convergent sequence is a sequence where the terms get arbitrarily close to a specific point.
Formally a convergent sequence ${x_n}_{n}$ converging to $x$ satisfies:
$$forall varepsilon>0, exists N>0, n>NRightarrow |x_n-x|<varepsilon.$$
A Cauchy sequence ${x_n}_n$ satisfies:
$$forall varepsilon>0, exists N>0, n,m>NRightarrow |x_n-x_m|<varepsilon.$$
For real numbers with the euclidean metric the properties are equivalent but not for every metric space. Consider for instance in $mathbf{Q}$ the sequence
$$x_1 = 3, x_2 = 3.1, x_3 = 3.14, x_4 = 3.141, x_5 = 3.1415 dotsc$$
whic gets arbitrarily close to the real number $pi$. Now $pinotin mathbf{Q}$ so the sequence does not converge in $mathbf{Q}$. It is however a Cauchy sequence
$endgroup$
add a comment |
$begingroup$
You can easily find the definitions. Every convergent sequence is necessarily Cauchy but not every Cauchy sequence converges. The notions can be defined in any metric space. The notions are tied to the notion of completeness: A space is complete if, and only if, a sequence converges precisely when it is Cauchy. Also, a sequence is Cauchy if, and only if, it converges in the completion of the space.
$endgroup$
add a comment |
$begingroup$
Let $(X,d)$ be a metric space (or a normed vector space, if you want. In this case we define $d(x,y) := ||x-y||$). We call $(x_n)$ convergent with limit $x$ iff $forall varepsilon>0;exists Ninmathbb{N};forall ngeq N: d(x_n,x) < varepsilon$ (or, intuitively speaking, if the distance between $x_n$ and $x$ will eventually approach zero as $n rightarrow infty$). We say $(x_n)$ is a cauchy sequence iff $forall varepsilon > 0;exists Ninmathbb{N};forall m,ngeq N: d(x_m,x_n) < varepsilon$ (intuitively, if the distance between two arbitrary sequence elements will eventually approach zero as $n rightarrow infty$). One can show that any convergent sequence is a cauchy sequence (you can try to prove this, it's a very easy exercise). If for any metric space or normed vector space $X$ the converse holds true (i.e. every cauchy sequence converges to some limit $x$), we call that space complete. We can show that any normed vector space with finite dimension is complete (though this requires some work, you could start with proving the Bolzano Weierstraß theorem, first for $mathbb{R}$, then for $mathbb{R}^n$ via induction and then for $mathbb{C}^n$ via $mathbb{C}^n cong mathbb{R}^{2n}$, then by showing that cauchy sequences are bounded and that every cauchy sequence with a convergent subsequence is in fact convergent you can show that $mathbb{R}^n$ and $mathbb{C}^n$ are complete, then you can generalize this result for all normed vector spaces of finite dimension because all vector spaces of the same finite dimension are isomorphic to $mathbb{R}^n$ or $mathbb{C}^n$ and all norms are equivalent on $mathbb{R}^n$ and $mathbb{C}^n$ (the equivalence of norms part is really difficult to prove and requires some additional work so you should skip that if you really want to prove everything else).
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add a comment |
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3 Answers
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3 Answers
3
active
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$begingroup$
Every convergent sequence is Cauchy but not every Cauchy sequence is convergent depending on which space you are considering.
A Cauchy sequence is a sequence where the terms of the sequence get arbitrarily close to each other after a while.
A convergent sequence is a sequence where the terms get arbitrarily close to a specific point.
Formally a convergent sequence ${x_n}_{n}$ converging to $x$ satisfies:
$$forall varepsilon>0, exists N>0, n>NRightarrow |x_n-x|<varepsilon.$$
A Cauchy sequence ${x_n}_n$ satisfies:
$$forall varepsilon>0, exists N>0, n,m>NRightarrow |x_n-x_m|<varepsilon.$$
For real numbers with the euclidean metric the properties are equivalent but not for every metric space. Consider for instance in $mathbf{Q}$ the sequence
$$x_1 = 3, x_2 = 3.1, x_3 = 3.14, x_4 = 3.141, x_5 = 3.1415 dotsc$$
whic gets arbitrarily close to the real number $pi$. Now $pinotin mathbf{Q}$ so the sequence does not converge in $mathbf{Q}$. It is however a Cauchy sequence
$endgroup$
add a comment |
$begingroup$
Every convergent sequence is Cauchy but not every Cauchy sequence is convergent depending on which space you are considering.
A Cauchy sequence is a sequence where the terms of the sequence get arbitrarily close to each other after a while.
A convergent sequence is a sequence where the terms get arbitrarily close to a specific point.
Formally a convergent sequence ${x_n}_{n}$ converging to $x$ satisfies:
$$forall varepsilon>0, exists N>0, n>NRightarrow |x_n-x|<varepsilon.$$
A Cauchy sequence ${x_n}_n$ satisfies:
$$forall varepsilon>0, exists N>0, n,m>NRightarrow |x_n-x_m|<varepsilon.$$
For real numbers with the euclidean metric the properties are equivalent but not for every metric space. Consider for instance in $mathbf{Q}$ the sequence
$$x_1 = 3, x_2 = 3.1, x_3 = 3.14, x_4 = 3.141, x_5 = 3.1415 dotsc$$
whic gets arbitrarily close to the real number $pi$. Now $pinotin mathbf{Q}$ so the sequence does not converge in $mathbf{Q}$. It is however a Cauchy sequence
$endgroup$
add a comment |
$begingroup$
Every convergent sequence is Cauchy but not every Cauchy sequence is convergent depending on which space you are considering.
A Cauchy sequence is a sequence where the terms of the sequence get arbitrarily close to each other after a while.
A convergent sequence is a sequence where the terms get arbitrarily close to a specific point.
Formally a convergent sequence ${x_n}_{n}$ converging to $x$ satisfies:
$$forall varepsilon>0, exists N>0, n>NRightarrow |x_n-x|<varepsilon.$$
A Cauchy sequence ${x_n}_n$ satisfies:
$$forall varepsilon>0, exists N>0, n,m>NRightarrow |x_n-x_m|<varepsilon.$$
For real numbers with the euclidean metric the properties are equivalent but not for every metric space. Consider for instance in $mathbf{Q}$ the sequence
$$x_1 = 3, x_2 = 3.1, x_3 = 3.14, x_4 = 3.141, x_5 = 3.1415 dotsc$$
whic gets arbitrarily close to the real number $pi$. Now $pinotin mathbf{Q}$ so the sequence does not converge in $mathbf{Q}$. It is however a Cauchy sequence
$endgroup$
Every convergent sequence is Cauchy but not every Cauchy sequence is convergent depending on which space you are considering.
A Cauchy sequence is a sequence where the terms of the sequence get arbitrarily close to each other after a while.
A convergent sequence is a sequence where the terms get arbitrarily close to a specific point.
Formally a convergent sequence ${x_n}_{n}$ converging to $x$ satisfies:
$$forall varepsilon>0, exists N>0, n>NRightarrow |x_n-x|<varepsilon.$$
A Cauchy sequence ${x_n}_n$ satisfies:
$$forall varepsilon>0, exists N>0, n,m>NRightarrow |x_n-x_m|<varepsilon.$$
For real numbers with the euclidean metric the properties are equivalent but not for every metric space. Consider for instance in $mathbf{Q}$ the sequence
$$x_1 = 3, x_2 = 3.1, x_3 = 3.14, x_4 = 3.141, x_5 = 3.1415 dotsc$$
whic gets arbitrarily close to the real number $pi$. Now $pinotin mathbf{Q}$ so the sequence does not converge in $mathbf{Q}$. It is however a Cauchy sequence
edited Dec 22 '18 at 20:17
answered Dec 22 '18 at 20:12
Olof RubinOlof Rubin
872317
872317
add a comment |
add a comment |
$begingroup$
You can easily find the definitions. Every convergent sequence is necessarily Cauchy but not every Cauchy sequence converges. The notions can be defined in any metric space. The notions are tied to the notion of completeness: A space is complete if, and only if, a sequence converges precisely when it is Cauchy. Also, a sequence is Cauchy if, and only if, it converges in the completion of the space.
$endgroup$
add a comment |
$begingroup$
You can easily find the definitions. Every convergent sequence is necessarily Cauchy but not every Cauchy sequence converges. The notions can be defined in any metric space. The notions are tied to the notion of completeness: A space is complete if, and only if, a sequence converges precisely when it is Cauchy. Also, a sequence is Cauchy if, and only if, it converges in the completion of the space.
$endgroup$
add a comment |
$begingroup$
You can easily find the definitions. Every convergent sequence is necessarily Cauchy but not every Cauchy sequence converges. The notions can be defined in any metric space. The notions are tied to the notion of completeness: A space is complete if, and only if, a sequence converges precisely when it is Cauchy. Also, a sequence is Cauchy if, and only if, it converges in the completion of the space.
$endgroup$
You can easily find the definitions. Every convergent sequence is necessarily Cauchy but not every Cauchy sequence converges. The notions can be defined in any metric space. The notions are tied to the notion of completeness: A space is complete if, and only if, a sequence converges precisely when it is Cauchy. Also, a sequence is Cauchy if, and only if, it converges in the completion of the space.
answered Dec 22 '18 at 20:09
Ittay WeissIttay Weiss
64.2k7102184
64.2k7102184
add a comment |
add a comment |
$begingroup$
Let $(X,d)$ be a metric space (or a normed vector space, if you want. In this case we define $d(x,y) := ||x-y||$). We call $(x_n)$ convergent with limit $x$ iff $forall varepsilon>0;exists Ninmathbb{N};forall ngeq N: d(x_n,x) < varepsilon$ (or, intuitively speaking, if the distance between $x_n$ and $x$ will eventually approach zero as $n rightarrow infty$). We say $(x_n)$ is a cauchy sequence iff $forall varepsilon > 0;exists Ninmathbb{N};forall m,ngeq N: d(x_m,x_n) < varepsilon$ (intuitively, if the distance between two arbitrary sequence elements will eventually approach zero as $n rightarrow infty$). One can show that any convergent sequence is a cauchy sequence (you can try to prove this, it's a very easy exercise). If for any metric space or normed vector space $X$ the converse holds true (i.e. every cauchy sequence converges to some limit $x$), we call that space complete. We can show that any normed vector space with finite dimension is complete (though this requires some work, you could start with proving the Bolzano Weierstraß theorem, first for $mathbb{R}$, then for $mathbb{R}^n$ via induction and then for $mathbb{C}^n$ via $mathbb{C}^n cong mathbb{R}^{2n}$, then by showing that cauchy sequences are bounded and that every cauchy sequence with a convergent subsequence is in fact convergent you can show that $mathbb{R}^n$ and $mathbb{C}^n$ are complete, then you can generalize this result for all normed vector spaces of finite dimension because all vector spaces of the same finite dimension are isomorphic to $mathbb{R}^n$ or $mathbb{C}^n$ and all norms are equivalent on $mathbb{R}^n$ and $mathbb{C}^n$ (the equivalence of norms part is really difficult to prove and requires some additional work so you should skip that if you really want to prove everything else).
$endgroup$
add a comment |
$begingroup$
Let $(X,d)$ be a metric space (or a normed vector space, if you want. In this case we define $d(x,y) := ||x-y||$). We call $(x_n)$ convergent with limit $x$ iff $forall varepsilon>0;exists Ninmathbb{N};forall ngeq N: d(x_n,x) < varepsilon$ (or, intuitively speaking, if the distance between $x_n$ and $x$ will eventually approach zero as $n rightarrow infty$). We say $(x_n)$ is a cauchy sequence iff $forall varepsilon > 0;exists Ninmathbb{N};forall m,ngeq N: d(x_m,x_n) < varepsilon$ (intuitively, if the distance between two arbitrary sequence elements will eventually approach zero as $n rightarrow infty$). One can show that any convergent sequence is a cauchy sequence (you can try to prove this, it's a very easy exercise). If for any metric space or normed vector space $X$ the converse holds true (i.e. every cauchy sequence converges to some limit $x$), we call that space complete. We can show that any normed vector space with finite dimension is complete (though this requires some work, you could start with proving the Bolzano Weierstraß theorem, first for $mathbb{R}$, then for $mathbb{R}^n$ via induction and then for $mathbb{C}^n$ via $mathbb{C}^n cong mathbb{R}^{2n}$, then by showing that cauchy sequences are bounded and that every cauchy sequence with a convergent subsequence is in fact convergent you can show that $mathbb{R}^n$ and $mathbb{C}^n$ are complete, then you can generalize this result for all normed vector spaces of finite dimension because all vector spaces of the same finite dimension are isomorphic to $mathbb{R}^n$ or $mathbb{C}^n$ and all norms are equivalent on $mathbb{R}^n$ and $mathbb{C}^n$ (the equivalence of norms part is really difficult to prove and requires some additional work so you should skip that if you really want to prove everything else).
$endgroup$
add a comment |
$begingroup$
Let $(X,d)$ be a metric space (or a normed vector space, if you want. In this case we define $d(x,y) := ||x-y||$). We call $(x_n)$ convergent with limit $x$ iff $forall varepsilon>0;exists Ninmathbb{N};forall ngeq N: d(x_n,x) < varepsilon$ (or, intuitively speaking, if the distance between $x_n$ and $x$ will eventually approach zero as $n rightarrow infty$). We say $(x_n)$ is a cauchy sequence iff $forall varepsilon > 0;exists Ninmathbb{N};forall m,ngeq N: d(x_m,x_n) < varepsilon$ (intuitively, if the distance between two arbitrary sequence elements will eventually approach zero as $n rightarrow infty$). One can show that any convergent sequence is a cauchy sequence (you can try to prove this, it's a very easy exercise). If for any metric space or normed vector space $X$ the converse holds true (i.e. every cauchy sequence converges to some limit $x$), we call that space complete. We can show that any normed vector space with finite dimension is complete (though this requires some work, you could start with proving the Bolzano Weierstraß theorem, first for $mathbb{R}$, then for $mathbb{R}^n$ via induction and then for $mathbb{C}^n$ via $mathbb{C}^n cong mathbb{R}^{2n}$, then by showing that cauchy sequences are bounded and that every cauchy sequence with a convergent subsequence is in fact convergent you can show that $mathbb{R}^n$ and $mathbb{C}^n$ are complete, then you can generalize this result for all normed vector spaces of finite dimension because all vector spaces of the same finite dimension are isomorphic to $mathbb{R}^n$ or $mathbb{C}^n$ and all norms are equivalent on $mathbb{R}^n$ and $mathbb{C}^n$ (the equivalence of norms part is really difficult to prove and requires some additional work so you should skip that if you really want to prove everything else).
$endgroup$
Let $(X,d)$ be a metric space (or a normed vector space, if you want. In this case we define $d(x,y) := ||x-y||$). We call $(x_n)$ convergent with limit $x$ iff $forall varepsilon>0;exists Ninmathbb{N};forall ngeq N: d(x_n,x) < varepsilon$ (or, intuitively speaking, if the distance between $x_n$ and $x$ will eventually approach zero as $n rightarrow infty$). We say $(x_n)$ is a cauchy sequence iff $forall varepsilon > 0;exists Ninmathbb{N};forall m,ngeq N: d(x_m,x_n) < varepsilon$ (intuitively, if the distance between two arbitrary sequence elements will eventually approach zero as $n rightarrow infty$). One can show that any convergent sequence is a cauchy sequence (you can try to prove this, it's a very easy exercise). If for any metric space or normed vector space $X$ the converse holds true (i.e. every cauchy sequence converges to some limit $x$), we call that space complete. We can show that any normed vector space with finite dimension is complete (though this requires some work, you could start with proving the Bolzano Weierstraß theorem, first for $mathbb{R}$, then for $mathbb{R}^n$ via induction and then for $mathbb{C}^n$ via $mathbb{C}^n cong mathbb{R}^{2n}$, then by showing that cauchy sequences are bounded and that every cauchy sequence with a convergent subsequence is in fact convergent you can show that $mathbb{R}^n$ and $mathbb{C}^n$ are complete, then you can generalize this result for all normed vector spaces of finite dimension because all vector spaces of the same finite dimension are isomorphic to $mathbb{R}^n$ or $mathbb{C}^n$ and all norms are equivalent on $mathbb{R}^n$ and $mathbb{C}^n$ (the equivalence of norms part is really difficult to prove and requires some additional work so you should skip that if you really want to prove everything else).
answered Dec 22 '18 at 23:09
NicolasNicolas
767
767
add a comment |
add a comment |
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$begingroup$
Every convergent sequence is a Cauchy sequence. The converse is not always true. If it is, we call such metric space complete.
$endgroup$
– APC89
Dec 22 '18 at 20:08
$begingroup$
Can you Give me an example which is Cauchy but not convergent an any space?
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:10
$begingroup$
Consider the metric space $M := (0,1]subsettextbf{R}$. The sequence $a_{n} = 1/n$ is a Cauchy sequence, but it does not converge in $M$, since $lim a_{n} = 0$. Therefore $M$ is not complete.
$endgroup$
– APC89
Dec 22 '18 at 20:12
$begingroup$
Thanks. I was reading my real analysis book and get confused with the problem. And now i realized that real R is complete..
$endgroup$
– Masaud Khan
Dec 22 '18 at 20:16
$begingroup$
I think what makes it initially confusing is that we're already used to convergent sequences of real numbers before starting analysis, so it's instinctive to visualise Cauchy sequences as being exactly the same thing.
$endgroup$
– timtfj
Dec 22 '18 at 23:54