Cauchy Sequence in subset of a metric space











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True or False:
If E is a subset of a metric space X, then any sequence of points of E that is a Cauchy sequence in X is a Cauchy sequence in E.



I'm having difficulty understanding this language. What does it mean for a sequence to be Cauchy "in" X?










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    True or False:
    If E is a subset of a metric space X, then any sequence of points of E that is a Cauchy sequence in X is a Cauchy sequence in E.



    I'm having difficulty understanding this language. What does it mean for a sequence to be Cauchy "in" X?










    share|cite|improve this question


























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      True or False:
      If E is a subset of a metric space X, then any sequence of points of E that is a Cauchy sequence in X is a Cauchy sequence in E.



      I'm having difficulty understanding this language. What does it mean for a sequence to be Cauchy "in" X?










      share|cite|improve this question















      True or False:
      If E is a subset of a metric space X, then any sequence of points of E that is a Cauchy sequence in X is a Cauchy sequence in E.



      I'm having difficulty understanding this language. What does it mean for a sequence to be Cauchy "in" X?







      real-analysis sequences-and-series metric-spaces cauchy-sequences






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      edited Nov 13 at 8:02









      Henno Brandsma

      101k344107




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      asked Nov 13 at 6:45









      51n84d

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          Since $X$ is a metric space there is a distance $d:Xtimes Xto [0,+infty)$. Then ${x_n}_nsubset X$ is a Cauchy sequence in $X$ (or with respect to this distance $d$) if $$forallepsilon>0,; exists N;:; forall n,m>N, d(x_n,x_m)<epsilon.$$
          If $Esubset X$ and ${x_n}_nsubset E$ then we may say that if ${x_n}_n$ is a Cauchy sequence in $X$ then it also a Cauchy sequence in $E$. $E$ and $X$ share the same distance if nothing else has been specified.






          share|cite|improve this answer























          • Does E being a subset of X imply that E and X share the same distance function?
            – 51n84d
            Nov 13 at 6:56






          • 1




            Yes, $E$ and $X$ share the same distance.
            – Robert Z
            Nov 13 at 6:59










          • 51n84d.Given a metric d on X, and $E subset X$, $d_E(x,y) : =d(x,y)$, $x,y in E subset X$.
            – Peter Szilas
            Nov 13 at 7:13






          • 1




            To the proposer: Strictly speaking, a metric space is a pair $(X,d)$ where $d:Xtimes Xto Bbb R$ is a metric on a set $X$. When speaking of a Cauchy or convergent sequence in some $Esubset X$, it is usually assumed, without saying so, that we mean in the metric space $(E,d|_{Etimes E})$ where $d|_{Etimes E}$ is $d$ restricted to the domain $Etimes E$.
            – DanielWainfleet
            Nov 13 at 9:07




















          up vote
          1
          down vote













          The definition of Cauchy sequence is$$forall epsilon>0 exists Nin mathbb Ntext{ such that } d(a_n,a_m)<epsilon forall n,m>N$$
          Now, the existence of this N is dependent on the metric space(similar to the fact that limit points of a set may or may not be in a particular metric space).



          Coming back to the question, yes, the given statement is true.



          $because$We know that the sequence is in E, therefore, all of the terms of the sequence is in E. Hence, all the terms after the stage N are also in E and therefore the property satisfies.



          Hope it helps:)






          share|cite|improve this answer






























            up vote
            0
            down vote













            The same sequence may be Cauchy in one metric space but not Cauchy in another. For example, let $M =mathbb{Q}$ with the normal distance function, $d(x, y) = |x-y|$, and let $N = mathbb{Q}$ with $d(x, y) = 1$ if $x not = y$ and $d(x, x) = 0$ (this is called the discrete metric).



            Now notice that $M$ and $N$ have the same set, but they are different metric spaces since a metric space is the set together with the distance function.



            Now consider $x_n = dfrac 1n$. In $M$, this sequence is convergent and therefore Cauchy (the terms bunch up near $0$ and thus get closer and closer to each other).



            Now since the sequence never repeats terms, in $N$, every member of the sequence is at distance $1$ from every other member, so the terms do not get closer and closer.



            Thus $x_n$ is Cauchy in $M$ but not Cauchy in $N$.



            Now your exercise is one of those "so easy that's it's hard". There isn't really anything to do to solve it, but you do have to understand exactly what is going on to write a correct answer.






            share|cite|improve this answer





















              Your Answer





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              3 Answers
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              active

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              3 Answers
              3






              active

              oldest

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              active

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              up vote
              0
              down vote



              accepted










              Since $X$ is a metric space there is a distance $d:Xtimes Xto [0,+infty)$. Then ${x_n}_nsubset X$ is a Cauchy sequence in $X$ (or with respect to this distance $d$) if $$forallepsilon>0,; exists N;:; forall n,m>N, d(x_n,x_m)<epsilon.$$
              If $Esubset X$ and ${x_n}_nsubset E$ then we may say that if ${x_n}_n$ is a Cauchy sequence in $X$ then it also a Cauchy sequence in $E$. $E$ and $X$ share the same distance if nothing else has been specified.






              share|cite|improve this answer























              • Does E being a subset of X imply that E and X share the same distance function?
                – 51n84d
                Nov 13 at 6:56






              • 1




                Yes, $E$ and $X$ share the same distance.
                – Robert Z
                Nov 13 at 6:59










              • 51n84d.Given a metric d on X, and $E subset X$, $d_E(x,y) : =d(x,y)$, $x,y in E subset X$.
                – Peter Szilas
                Nov 13 at 7:13






              • 1




                To the proposer: Strictly speaking, a metric space is a pair $(X,d)$ where $d:Xtimes Xto Bbb R$ is a metric on a set $X$. When speaking of a Cauchy or convergent sequence in some $Esubset X$, it is usually assumed, without saying so, that we mean in the metric space $(E,d|_{Etimes E})$ where $d|_{Etimes E}$ is $d$ restricted to the domain $Etimes E$.
                – DanielWainfleet
                Nov 13 at 9:07

















              up vote
              0
              down vote



              accepted










              Since $X$ is a metric space there is a distance $d:Xtimes Xto [0,+infty)$. Then ${x_n}_nsubset X$ is a Cauchy sequence in $X$ (or with respect to this distance $d$) if $$forallepsilon>0,; exists N;:; forall n,m>N, d(x_n,x_m)<epsilon.$$
              If $Esubset X$ and ${x_n}_nsubset E$ then we may say that if ${x_n}_n$ is a Cauchy sequence in $X$ then it also a Cauchy sequence in $E$. $E$ and $X$ share the same distance if nothing else has been specified.






              share|cite|improve this answer























              • Does E being a subset of X imply that E and X share the same distance function?
                – 51n84d
                Nov 13 at 6:56






              • 1




                Yes, $E$ and $X$ share the same distance.
                – Robert Z
                Nov 13 at 6:59










              • 51n84d.Given a metric d on X, and $E subset X$, $d_E(x,y) : =d(x,y)$, $x,y in E subset X$.
                – Peter Szilas
                Nov 13 at 7:13






              • 1




                To the proposer: Strictly speaking, a metric space is a pair $(X,d)$ where $d:Xtimes Xto Bbb R$ is a metric on a set $X$. When speaking of a Cauchy or convergent sequence in some $Esubset X$, it is usually assumed, without saying so, that we mean in the metric space $(E,d|_{Etimes E})$ where $d|_{Etimes E}$ is $d$ restricted to the domain $Etimes E$.
                – DanielWainfleet
                Nov 13 at 9:07















              up vote
              0
              down vote



              accepted







              up vote
              0
              down vote



              accepted






              Since $X$ is a metric space there is a distance $d:Xtimes Xto [0,+infty)$. Then ${x_n}_nsubset X$ is a Cauchy sequence in $X$ (or with respect to this distance $d$) if $$forallepsilon>0,; exists N;:; forall n,m>N, d(x_n,x_m)<epsilon.$$
              If $Esubset X$ and ${x_n}_nsubset E$ then we may say that if ${x_n}_n$ is a Cauchy sequence in $X$ then it also a Cauchy sequence in $E$. $E$ and $X$ share the same distance if nothing else has been specified.






              share|cite|improve this answer














              Since $X$ is a metric space there is a distance $d:Xtimes Xto [0,+infty)$. Then ${x_n}_nsubset X$ is a Cauchy sequence in $X$ (or with respect to this distance $d$) if $$forallepsilon>0,; exists N;:; forall n,m>N, d(x_n,x_m)<epsilon.$$
              If $Esubset X$ and ${x_n}_nsubset E$ then we may say that if ${x_n}_n$ is a Cauchy sequence in $X$ then it also a Cauchy sequence in $E$. $E$ and $X$ share the same distance if nothing else has been specified.







              share|cite|improve this answer














              share|cite|improve this answer



              share|cite|improve this answer








              edited Nov 13 at 7:08

























              answered Nov 13 at 6:54









              Robert Z

              90.1k1056128




              90.1k1056128












              • Does E being a subset of X imply that E and X share the same distance function?
                – 51n84d
                Nov 13 at 6:56






              • 1




                Yes, $E$ and $X$ share the same distance.
                – Robert Z
                Nov 13 at 6:59










              • 51n84d.Given a metric d on X, and $E subset X$, $d_E(x,y) : =d(x,y)$, $x,y in E subset X$.
                – Peter Szilas
                Nov 13 at 7:13






              • 1




                To the proposer: Strictly speaking, a metric space is a pair $(X,d)$ where $d:Xtimes Xto Bbb R$ is a metric on a set $X$. When speaking of a Cauchy or convergent sequence in some $Esubset X$, it is usually assumed, without saying so, that we mean in the metric space $(E,d|_{Etimes E})$ where $d|_{Etimes E}$ is $d$ restricted to the domain $Etimes E$.
                – DanielWainfleet
                Nov 13 at 9:07




















              • Does E being a subset of X imply that E and X share the same distance function?
                – 51n84d
                Nov 13 at 6:56






              • 1




                Yes, $E$ and $X$ share the same distance.
                – Robert Z
                Nov 13 at 6:59










              • 51n84d.Given a metric d on X, and $E subset X$, $d_E(x,y) : =d(x,y)$, $x,y in E subset X$.
                – Peter Szilas
                Nov 13 at 7:13






              • 1




                To the proposer: Strictly speaking, a metric space is a pair $(X,d)$ where $d:Xtimes Xto Bbb R$ is a metric on a set $X$. When speaking of a Cauchy or convergent sequence in some $Esubset X$, it is usually assumed, without saying so, that we mean in the metric space $(E,d|_{Etimes E})$ where $d|_{Etimes E}$ is $d$ restricted to the domain $Etimes E$.
                – DanielWainfleet
                Nov 13 at 9:07


















              Does E being a subset of X imply that E and X share the same distance function?
              – 51n84d
              Nov 13 at 6:56




              Does E being a subset of X imply that E and X share the same distance function?
              – 51n84d
              Nov 13 at 6:56




              1




              1




              Yes, $E$ and $X$ share the same distance.
              – Robert Z
              Nov 13 at 6:59




              Yes, $E$ and $X$ share the same distance.
              – Robert Z
              Nov 13 at 6:59












              51n84d.Given a metric d on X, and $E subset X$, $d_E(x,y) : =d(x,y)$, $x,y in E subset X$.
              – Peter Szilas
              Nov 13 at 7:13




              51n84d.Given a metric d on X, and $E subset X$, $d_E(x,y) : =d(x,y)$, $x,y in E subset X$.
              – Peter Szilas
              Nov 13 at 7:13




              1




              1




              To the proposer: Strictly speaking, a metric space is a pair $(X,d)$ where $d:Xtimes Xto Bbb R$ is a metric on a set $X$. When speaking of a Cauchy or convergent sequence in some $Esubset X$, it is usually assumed, without saying so, that we mean in the metric space $(E,d|_{Etimes E})$ where $d|_{Etimes E}$ is $d$ restricted to the domain $Etimes E$.
              – DanielWainfleet
              Nov 13 at 9:07






              To the proposer: Strictly speaking, a metric space is a pair $(X,d)$ where $d:Xtimes Xto Bbb R$ is a metric on a set $X$. When speaking of a Cauchy or convergent sequence in some $Esubset X$, it is usually assumed, without saying so, that we mean in the metric space $(E,d|_{Etimes E})$ where $d|_{Etimes E}$ is $d$ restricted to the domain $Etimes E$.
              – DanielWainfleet
              Nov 13 at 9:07












              up vote
              1
              down vote













              The definition of Cauchy sequence is$$forall epsilon>0 exists Nin mathbb Ntext{ such that } d(a_n,a_m)<epsilon forall n,m>N$$
              Now, the existence of this N is dependent on the metric space(similar to the fact that limit points of a set may or may not be in a particular metric space).



              Coming back to the question, yes, the given statement is true.



              $because$We know that the sequence is in E, therefore, all of the terms of the sequence is in E. Hence, all the terms after the stage N are also in E and therefore the property satisfies.



              Hope it helps:)






              share|cite|improve this answer



























                up vote
                1
                down vote













                The definition of Cauchy sequence is$$forall epsilon>0 exists Nin mathbb Ntext{ such that } d(a_n,a_m)<epsilon forall n,m>N$$
                Now, the existence of this N is dependent on the metric space(similar to the fact that limit points of a set may or may not be in a particular metric space).



                Coming back to the question, yes, the given statement is true.



                $because$We know that the sequence is in E, therefore, all of the terms of the sequence is in E. Hence, all the terms after the stage N are also in E and therefore the property satisfies.



                Hope it helps:)






                share|cite|improve this answer

























                  up vote
                  1
                  down vote










                  up vote
                  1
                  down vote









                  The definition of Cauchy sequence is$$forall epsilon>0 exists Nin mathbb Ntext{ such that } d(a_n,a_m)<epsilon forall n,m>N$$
                  Now, the existence of this N is dependent on the metric space(similar to the fact that limit points of a set may or may not be in a particular metric space).



                  Coming back to the question, yes, the given statement is true.



                  $because$We know that the sequence is in E, therefore, all of the terms of the sequence is in E. Hence, all the terms after the stage N are also in E and therefore the property satisfies.



                  Hope it helps:)






                  share|cite|improve this answer














                  The definition of Cauchy sequence is$$forall epsilon>0 exists Nin mathbb Ntext{ such that } d(a_n,a_m)<epsilon forall n,m>N$$
                  Now, the existence of this N is dependent on the metric space(similar to the fact that limit points of a set may or may not be in a particular metric space).



                  Coming back to the question, yes, the given statement is true.



                  $because$We know that the sequence is in E, therefore, all of the terms of the sequence is in E. Hence, all the terms after the stage N are also in E and therefore the property satisfies.



                  Hope it helps:)







                  share|cite|improve this answer














                  share|cite|improve this answer



                  share|cite|improve this answer








                  edited Nov 13 at 7:23









                  Henno Brandsma

                  101k344107




                  101k344107










                  answered Nov 13 at 7:04









                  Crazy for maths

                  5089




                  5089






















                      up vote
                      0
                      down vote













                      The same sequence may be Cauchy in one metric space but not Cauchy in another. For example, let $M =mathbb{Q}$ with the normal distance function, $d(x, y) = |x-y|$, and let $N = mathbb{Q}$ with $d(x, y) = 1$ if $x not = y$ and $d(x, x) = 0$ (this is called the discrete metric).



                      Now notice that $M$ and $N$ have the same set, but they are different metric spaces since a metric space is the set together with the distance function.



                      Now consider $x_n = dfrac 1n$. In $M$, this sequence is convergent and therefore Cauchy (the terms bunch up near $0$ and thus get closer and closer to each other).



                      Now since the sequence never repeats terms, in $N$, every member of the sequence is at distance $1$ from every other member, so the terms do not get closer and closer.



                      Thus $x_n$ is Cauchy in $M$ but not Cauchy in $N$.



                      Now your exercise is one of those "so easy that's it's hard". There isn't really anything to do to solve it, but you do have to understand exactly what is going on to write a correct answer.






                      share|cite|improve this answer

























                        up vote
                        0
                        down vote













                        The same sequence may be Cauchy in one metric space but not Cauchy in another. For example, let $M =mathbb{Q}$ with the normal distance function, $d(x, y) = |x-y|$, and let $N = mathbb{Q}$ with $d(x, y) = 1$ if $x not = y$ and $d(x, x) = 0$ (this is called the discrete metric).



                        Now notice that $M$ and $N$ have the same set, but they are different metric spaces since a metric space is the set together with the distance function.



                        Now consider $x_n = dfrac 1n$. In $M$, this sequence is convergent and therefore Cauchy (the terms bunch up near $0$ and thus get closer and closer to each other).



                        Now since the sequence never repeats terms, in $N$, every member of the sequence is at distance $1$ from every other member, so the terms do not get closer and closer.



                        Thus $x_n$ is Cauchy in $M$ but not Cauchy in $N$.



                        Now your exercise is one of those "so easy that's it's hard". There isn't really anything to do to solve it, but you do have to understand exactly what is going on to write a correct answer.






                        share|cite|improve this answer























                          up vote
                          0
                          down vote










                          up vote
                          0
                          down vote









                          The same sequence may be Cauchy in one metric space but not Cauchy in another. For example, let $M =mathbb{Q}$ with the normal distance function, $d(x, y) = |x-y|$, and let $N = mathbb{Q}$ with $d(x, y) = 1$ if $x not = y$ and $d(x, x) = 0$ (this is called the discrete metric).



                          Now notice that $M$ and $N$ have the same set, but they are different metric spaces since a metric space is the set together with the distance function.



                          Now consider $x_n = dfrac 1n$. In $M$, this sequence is convergent and therefore Cauchy (the terms bunch up near $0$ and thus get closer and closer to each other).



                          Now since the sequence never repeats terms, in $N$, every member of the sequence is at distance $1$ from every other member, so the terms do not get closer and closer.



                          Thus $x_n$ is Cauchy in $M$ but not Cauchy in $N$.



                          Now your exercise is one of those "so easy that's it's hard". There isn't really anything to do to solve it, but you do have to understand exactly what is going on to write a correct answer.






                          share|cite|improve this answer












                          The same sequence may be Cauchy in one metric space but not Cauchy in another. For example, let $M =mathbb{Q}$ with the normal distance function, $d(x, y) = |x-y|$, and let $N = mathbb{Q}$ with $d(x, y) = 1$ if $x not = y$ and $d(x, x) = 0$ (this is called the discrete metric).



                          Now notice that $M$ and $N$ have the same set, but they are different metric spaces since a metric space is the set together with the distance function.



                          Now consider $x_n = dfrac 1n$. In $M$, this sequence is convergent and therefore Cauchy (the terms bunch up near $0$ and thus get closer and closer to each other).



                          Now since the sequence never repeats terms, in $N$, every member of the sequence is at distance $1$ from every other member, so the terms do not get closer and closer.



                          Thus $x_n$ is Cauchy in $M$ but not Cauchy in $N$.



                          Now your exercise is one of those "so easy that's it's hard". There isn't really anything to do to solve it, but you do have to understand exactly what is going on to write a correct answer.







                          share|cite|improve this answer












                          share|cite|improve this answer



                          share|cite|improve this answer










                          answered Nov 13 at 7:16









                          Ovi

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