Meaning of Delta Notation












2












$begingroup$


I was reading a paper (https://arxiv.org/pdf/1609.03891.pdf), and on the first page the author's write the following line:
$$
mu^sigma = frac{1}{n} sum_{i = 1}^n delta_{left(frac{2i}{n} - 1, frac{2sigma(i)}{n} -1right)}.
$$

Here, $sigma$ is in the symmetric group on $n$ letters. The authors write that $mu^sigma$ is supposed to be a probability measure on $[-1, 1]^2$. I'm having trouble parsing the expression. Is the delta supposed to be the Kroenecker delta? I don't think so, because the subscript ${left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}$ doesn't seem to make sense (it would be equivalent to saying $i = sigma(i)?$). Also, why is the domain $[-1, 1]^2$?



Could someone help me understand this expression?










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    2












    $begingroup$


    I was reading a paper (https://arxiv.org/pdf/1609.03891.pdf), and on the first page the author's write the following line:
    $$
    mu^sigma = frac{1}{n} sum_{i = 1}^n delta_{left(frac{2i}{n} - 1, frac{2sigma(i)}{n} -1right)}.
    $$

    Here, $sigma$ is in the symmetric group on $n$ letters. The authors write that $mu^sigma$ is supposed to be a probability measure on $[-1, 1]^2$. I'm having trouble parsing the expression. Is the delta supposed to be the Kroenecker delta? I don't think so, because the subscript ${left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}$ doesn't seem to make sense (it would be equivalent to saying $i = sigma(i)?$). Also, why is the domain $[-1, 1]^2$?



    Could someone help me understand this expression?










    share|cite|improve this question











    $endgroup$















      2












      2








      2





      $begingroup$


      I was reading a paper (https://arxiv.org/pdf/1609.03891.pdf), and on the first page the author's write the following line:
      $$
      mu^sigma = frac{1}{n} sum_{i = 1}^n delta_{left(frac{2i}{n} - 1, frac{2sigma(i)}{n} -1right)}.
      $$

      Here, $sigma$ is in the symmetric group on $n$ letters. The authors write that $mu^sigma$ is supposed to be a probability measure on $[-1, 1]^2$. I'm having trouble parsing the expression. Is the delta supposed to be the Kroenecker delta? I don't think so, because the subscript ${left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}$ doesn't seem to make sense (it would be equivalent to saying $i = sigma(i)?$). Also, why is the domain $[-1, 1]^2$?



      Could someone help me understand this expression?










      share|cite|improve this question











      $endgroup$




      I was reading a paper (https://arxiv.org/pdf/1609.03891.pdf), and on the first page the author's write the following line:
      $$
      mu^sigma = frac{1}{n} sum_{i = 1}^n delta_{left(frac{2i}{n} - 1, frac{2sigma(i)}{n} -1right)}.
      $$

      Here, $sigma$ is in the symmetric group on $n$ letters. The authors write that $mu^sigma$ is supposed to be a probability measure on $[-1, 1]^2$. I'm having trouble parsing the expression. Is the delta supposed to be the Kroenecker delta? I don't think so, because the subscript ${left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}$ doesn't seem to make sense (it would be equivalent to saying $i = sigma(i)?$). Also, why is the domain $[-1, 1]^2$?



      Could someone help me understand this expression?







      probability probability-theory notation






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Dec 26 '18 at 23:55









      MJD

      47.3k29213396




      47.3k29213396










      asked Dec 26 '18 at 23:47









      ProbablyProbably

      111




      111






















          1 Answer
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          $begingroup$

          Note that
          $$
          {left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}
          $$

          is a point in $[-1,1]^2$.

          So $delta$ with that subscript is a unit point mass at that point.

          Add $n$ point masses and divide by $n$, we get a probability measure.






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            That seems to be what the diagrams in the middle of page 4 are about; they are maps of where the point masses are.
            $endgroup$
            – MJD
            Dec 26 '18 at 23:58










          • $begingroup$
            @MJD So $mu^sigma$ places $n$ masses of $1/n$ in the square $[-1, 1]^2$ and assigns measure $0$ to every other point. Is that the right way to interpret the expression?
            $endgroup$
            – Probably
            Dec 27 '18 at 0:01












          • $begingroup$
            Yes. A measure is a function on sets. The pdf is a distribution. That's the Dirac delta in $mathbb{R}^2$ : $delta(x,y) = delta(x)delta(y)$ the latter being the usual Dirac delta in $mathbb{R}$ @Probably
            $endgroup$
            – reuns
            Dec 27 '18 at 1:00













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          1 Answer
          1






          active

          oldest

          votes








          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          3












          $begingroup$

          Note that
          $$
          {left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}
          $$

          is a point in $[-1,1]^2$.

          So $delta$ with that subscript is a unit point mass at that point.

          Add $n$ point masses and divide by $n$, we get a probability measure.






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            That seems to be what the diagrams in the middle of page 4 are about; they are maps of where the point masses are.
            $endgroup$
            – MJD
            Dec 26 '18 at 23:58










          • $begingroup$
            @MJD So $mu^sigma$ places $n$ masses of $1/n$ in the square $[-1, 1]^2$ and assigns measure $0$ to every other point. Is that the right way to interpret the expression?
            $endgroup$
            – Probably
            Dec 27 '18 at 0:01












          • $begingroup$
            Yes. A measure is a function on sets. The pdf is a distribution. That's the Dirac delta in $mathbb{R}^2$ : $delta(x,y) = delta(x)delta(y)$ the latter being the usual Dirac delta in $mathbb{R}$ @Probably
            $endgroup$
            – reuns
            Dec 27 '18 at 1:00


















          3












          $begingroup$

          Note that
          $$
          {left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}
          $$

          is a point in $[-1,1]^2$.

          So $delta$ with that subscript is a unit point mass at that point.

          Add $n$ point masses and divide by $n$, we get a probability measure.






          share|cite|improve this answer











          $endgroup$













          • $begingroup$
            That seems to be what the diagrams in the middle of page 4 are about; they are maps of where the point masses are.
            $endgroup$
            – MJD
            Dec 26 '18 at 23:58










          • $begingroup$
            @MJD So $mu^sigma$ places $n$ masses of $1/n$ in the square $[-1, 1]^2$ and assigns measure $0$ to every other point. Is that the right way to interpret the expression?
            $endgroup$
            – Probably
            Dec 27 '18 at 0:01












          • $begingroup$
            Yes. A measure is a function on sets. The pdf is a distribution. That's the Dirac delta in $mathbb{R}^2$ : $delta(x,y) = delta(x)delta(y)$ the latter being the usual Dirac delta in $mathbb{R}$ @Probably
            $endgroup$
            – reuns
            Dec 27 '18 at 1:00
















          3












          3








          3





          $begingroup$

          Note that
          $$
          {left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}
          $$

          is a point in $[-1,1]^2$.

          So $delta$ with that subscript is a unit point mass at that point.

          Add $n$ point masses and divide by $n$, we get a probability measure.






          share|cite|improve this answer











          $endgroup$



          Note that
          $$
          {left(frac{2i}{n} - 1, frac{2sigma(i) }{n} -1right)}
          $$

          is a point in $[-1,1]^2$.

          So $delta$ with that subscript is a unit point mass at that point.

          Add $n$ point masses and divide by $n$, we get a probability measure.







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited Dec 26 '18 at 23:59









          MJD

          47.3k29213396




          47.3k29213396










          answered Dec 26 '18 at 23:55









          GEdgarGEdgar

          62.5k267171




          62.5k267171












          • $begingroup$
            That seems to be what the diagrams in the middle of page 4 are about; they are maps of where the point masses are.
            $endgroup$
            – MJD
            Dec 26 '18 at 23:58










          • $begingroup$
            @MJD So $mu^sigma$ places $n$ masses of $1/n$ in the square $[-1, 1]^2$ and assigns measure $0$ to every other point. Is that the right way to interpret the expression?
            $endgroup$
            – Probably
            Dec 27 '18 at 0:01












          • $begingroup$
            Yes. A measure is a function on sets. The pdf is a distribution. That's the Dirac delta in $mathbb{R}^2$ : $delta(x,y) = delta(x)delta(y)$ the latter being the usual Dirac delta in $mathbb{R}$ @Probably
            $endgroup$
            – reuns
            Dec 27 '18 at 1:00




















          • $begingroup$
            That seems to be what the diagrams in the middle of page 4 are about; they are maps of where the point masses are.
            $endgroup$
            – MJD
            Dec 26 '18 at 23:58










          • $begingroup$
            @MJD So $mu^sigma$ places $n$ masses of $1/n$ in the square $[-1, 1]^2$ and assigns measure $0$ to every other point. Is that the right way to interpret the expression?
            $endgroup$
            – Probably
            Dec 27 '18 at 0:01












          • $begingroup$
            Yes. A measure is a function on sets. The pdf is a distribution. That's the Dirac delta in $mathbb{R}^2$ : $delta(x,y) = delta(x)delta(y)$ the latter being the usual Dirac delta in $mathbb{R}$ @Probably
            $endgroup$
            – reuns
            Dec 27 '18 at 1:00


















          $begingroup$
          That seems to be what the diagrams in the middle of page 4 are about; they are maps of where the point masses are.
          $endgroup$
          – MJD
          Dec 26 '18 at 23:58




          $begingroup$
          That seems to be what the diagrams in the middle of page 4 are about; they are maps of where the point masses are.
          $endgroup$
          – MJD
          Dec 26 '18 at 23:58












          $begingroup$
          @MJD So $mu^sigma$ places $n$ masses of $1/n$ in the square $[-1, 1]^2$ and assigns measure $0$ to every other point. Is that the right way to interpret the expression?
          $endgroup$
          – Probably
          Dec 27 '18 at 0:01






          $begingroup$
          @MJD So $mu^sigma$ places $n$ masses of $1/n$ in the square $[-1, 1]^2$ and assigns measure $0$ to every other point. Is that the right way to interpret the expression?
          $endgroup$
          – Probably
          Dec 27 '18 at 0:01














          $begingroup$
          Yes. A measure is a function on sets. The pdf is a distribution. That's the Dirac delta in $mathbb{R}^2$ : $delta(x,y) = delta(x)delta(y)$ the latter being the usual Dirac delta in $mathbb{R}$ @Probably
          $endgroup$
          – reuns
          Dec 27 '18 at 1:00






          $begingroup$
          Yes. A measure is a function on sets. The pdf is a distribution. That's the Dirac delta in $mathbb{R}^2$ : $delta(x,y) = delta(x)delta(y)$ the latter being the usual Dirac delta in $mathbb{R}$ @Probably
          $endgroup$
          – reuns
          Dec 27 '18 at 1:00




















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