Prove that the eigenvalues of a real symmetric matrix are real.











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I am having a difficult time with the following question. Any help will be much appreciated.




Let $A$ be an $n×n$ real matrix such that $A^T = A$. We call such matrices “symmetric.” Prove that the eigenvalues of a real symmetric matrix are real (i.e. if $lambda$ is an eigenvalue of $A$, show that $lambda = overline{lambda}$ )











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  • A real $ntimes n$ matrix only can have real eigenvalues (every complex zero of the characteristic is no eigenvalue of the real matrix)
    – Dominic Michaelis
    Apr 7 '13 at 19:12






  • 1




    @Susan : see Dominic's answer. You will need to use the "complex inner product" $langle mathbf{x}, mathbf{y} rangle = sum_{i=1}^n {bar x_i}y_i$. Also see Lepidopterist's answer, where $C^*$ is the conjugate transpose of $C$, $C^* = {bar {C^T}}$.
    – Stefan Smith
    Apr 7 '13 at 19:13












  • @DominicMichaelis : do you really mean that (a real square matrix can have only real eigenvalues)? I'm afraid you might confuse Susan. What about $[0, 1;-1, 0]$ with eigenvalues $pm i$? (Sorry, I don't remember the $LaTeX$ for writing a matrix
    – Stefan Smith
    Apr 7 '13 at 19:45










  • @StefanSmith if you consider it as a real matrix, it doesn't have any eigenvalues.
    – Dominic Michaelis
    Apr 7 '13 at 19:49










  • Going Dominic's way or Lepidopterist's way, you will easily see that the (a priori complex) eigenvalues must be real. Note that the exact same proofs show that the eigenvalues of a hermitian $A^*=A$ matrix are real in the general complex case.
    – Julien
    Apr 7 '13 at 19:59

















up vote
8
down vote

favorite
4












I am having a difficult time with the following question. Any help will be much appreciated.




Let $A$ be an $n×n$ real matrix such that $A^T = A$. We call such matrices “symmetric.” Prove that the eigenvalues of a real symmetric matrix are real (i.e. if $lambda$ is an eigenvalue of $A$, show that $lambda = overline{lambda}$ )











share|cite|improve this question
























  • A real $ntimes n$ matrix only can have real eigenvalues (every complex zero of the characteristic is no eigenvalue of the real matrix)
    – Dominic Michaelis
    Apr 7 '13 at 19:12






  • 1




    @Susan : see Dominic's answer. You will need to use the "complex inner product" $langle mathbf{x}, mathbf{y} rangle = sum_{i=1}^n {bar x_i}y_i$. Also see Lepidopterist's answer, where $C^*$ is the conjugate transpose of $C$, $C^* = {bar {C^T}}$.
    – Stefan Smith
    Apr 7 '13 at 19:13












  • @DominicMichaelis : do you really mean that (a real square matrix can have only real eigenvalues)? I'm afraid you might confuse Susan. What about $[0, 1;-1, 0]$ with eigenvalues $pm i$? (Sorry, I don't remember the $LaTeX$ for writing a matrix
    – Stefan Smith
    Apr 7 '13 at 19:45










  • @StefanSmith if you consider it as a real matrix, it doesn't have any eigenvalues.
    – Dominic Michaelis
    Apr 7 '13 at 19:49










  • Going Dominic's way or Lepidopterist's way, you will easily see that the (a priori complex) eigenvalues must be real. Note that the exact same proofs show that the eigenvalues of a hermitian $A^*=A$ matrix are real in the general complex case.
    – Julien
    Apr 7 '13 at 19:59















up vote
8
down vote

favorite
4









up vote
8
down vote

favorite
4






4





I am having a difficult time with the following question. Any help will be much appreciated.




Let $A$ be an $n×n$ real matrix such that $A^T = A$. We call such matrices “symmetric.” Prove that the eigenvalues of a real symmetric matrix are real (i.e. if $lambda$ is an eigenvalue of $A$, show that $lambda = overline{lambda}$ )











share|cite|improve this question















I am having a difficult time with the following question. Any help will be much appreciated.




Let $A$ be an $n×n$ real matrix such that $A^T = A$. We call such matrices “symmetric.” Prove that the eigenvalues of a real symmetric matrix are real (i.e. if $lambda$ is an eigenvalue of $A$, show that $lambda = overline{lambda}$ )








linear-algebra matrices eigenvalues-eigenvectors inner-product-space






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edited Oct 10 '16 at 6:14









Irregular User

2,86251743




2,86251743










asked Apr 7 '13 at 18:58









Susan

3671311




3671311












  • A real $ntimes n$ matrix only can have real eigenvalues (every complex zero of the characteristic is no eigenvalue of the real matrix)
    – Dominic Michaelis
    Apr 7 '13 at 19:12






  • 1




    @Susan : see Dominic's answer. You will need to use the "complex inner product" $langle mathbf{x}, mathbf{y} rangle = sum_{i=1}^n {bar x_i}y_i$. Also see Lepidopterist's answer, where $C^*$ is the conjugate transpose of $C$, $C^* = {bar {C^T}}$.
    – Stefan Smith
    Apr 7 '13 at 19:13












  • @DominicMichaelis : do you really mean that (a real square matrix can have only real eigenvalues)? I'm afraid you might confuse Susan. What about $[0, 1;-1, 0]$ with eigenvalues $pm i$? (Sorry, I don't remember the $LaTeX$ for writing a matrix
    – Stefan Smith
    Apr 7 '13 at 19:45










  • @StefanSmith if you consider it as a real matrix, it doesn't have any eigenvalues.
    – Dominic Michaelis
    Apr 7 '13 at 19:49










  • Going Dominic's way or Lepidopterist's way, you will easily see that the (a priori complex) eigenvalues must be real. Note that the exact same proofs show that the eigenvalues of a hermitian $A^*=A$ matrix are real in the general complex case.
    – Julien
    Apr 7 '13 at 19:59




















  • A real $ntimes n$ matrix only can have real eigenvalues (every complex zero of the characteristic is no eigenvalue of the real matrix)
    – Dominic Michaelis
    Apr 7 '13 at 19:12






  • 1




    @Susan : see Dominic's answer. You will need to use the "complex inner product" $langle mathbf{x}, mathbf{y} rangle = sum_{i=1}^n {bar x_i}y_i$. Also see Lepidopterist's answer, where $C^*$ is the conjugate transpose of $C$, $C^* = {bar {C^T}}$.
    – Stefan Smith
    Apr 7 '13 at 19:13












  • @DominicMichaelis : do you really mean that (a real square matrix can have only real eigenvalues)? I'm afraid you might confuse Susan. What about $[0, 1;-1, 0]$ with eigenvalues $pm i$? (Sorry, I don't remember the $LaTeX$ for writing a matrix
    – Stefan Smith
    Apr 7 '13 at 19:45










  • @StefanSmith if you consider it as a real matrix, it doesn't have any eigenvalues.
    – Dominic Michaelis
    Apr 7 '13 at 19:49










  • Going Dominic's way or Lepidopterist's way, you will easily see that the (a priori complex) eigenvalues must be real. Note that the exact same proofs show that the eigenvalues of a hermitian $A^*=A$ matrix are real in the general complex case.
    – Julien
    Apr 7 '13 at 19:59


















A real $ntimes n$ matrix only can have real eigenvalues (every complex zero of the characteristic is no eigenvalue of the real matrix)
– Dominic Michaelis
Apr 7 '13 at 19:12




A real $ntimes n$ matrix only can have real eigenvalues (every complex zero of the characteristic is no eigenvalue of the real matrix)
– Dominic Michaelis
Apr 7 '13 at 19:12




1




1




@Susan : see Dominic's answer. You will need to use the "complex inner product" $langle mathbf{x}, mathbf{y} rangle = sum_{i=1}^n {bar x_i}y_i$. Also see Lepidopterist's answer, where $C^*$ is the conjugate transpose of $C$, $C^* = {bar {C^T}}$.
– Stefan Smith
Apr 7 '13 at 19:13






@Susan : see Dominic's answer. You will need to use the "complex inner product" $langle mathbf{x}, mathbf{y} rangle = sum_{i=1}^n {bar x_i}y_i$. Also see Lepidopterist's answer, where $C^*$ is the conjugate transpose of $C$, $C^* = {bar {C^T}}$.
– Stefan Smith
Apr 7 '13 at 19:13














@DominicMichaelis : do you really mean that (a real square matrix can have only real eigenvalues)? I'm afraid you might confuse Susan. What about $[0, 1;-1, 0]$ with eigenvalues $pm i$? (Sorry, I don't remember the $LaTeX$ for writing a matrix
– Stefan Smith
Apr 7 '13 at 19:45




@DominicMichaelis : do you really mean that (a real square matrix can have only real eigenvalues)? I'm afraid you might confuse Susan. What about $[0, 1;-1, 0]$ with eigenvalues $pm i$? (Sorry, I don't remember the $LaTeX$ for writing a matrix
– Stefan Smith
Apr 7 '13 at 19:45












@StefanSmith if you consider it as a real matrix, it doesn't have any eigenvalues.
– Dominic Michaelis
Apr 7 '13 at 19:49




@StefanSmith if you consider it as a real matrix, it doesn't have any eigenvalues.
– Dominic Michaelis
Apr 7 '13 at 19:49












Going Dominic's way or Lepidopterist's way, you will easily see that the (a priori complex) eigenvalues must be real. Note that the exact same proofs show that the eigenvalues of a hermitian $A^*=A$ matrix are real in the general complex case.
– Julien
Apr 7 '13 at 19:59






Going Dominic's way or Lepidopterist's way, you will easily see that the (a priori complex) eigenvalues must be real. Note that the exact same proofs show that the eigenvalues of a hermitian $A^*=A$ matrix are real in the general complex case.
– Julien
Apr 7 '13 at 19:59












5 Answers
5






active

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up vote
11
down vote













$Av=lambda v$ combined with $A=A^T$ gives $$langle Av,Avrangle=v^*A^*Av=v^*A^TAv=v^*A^2v=lambda^2||v||^2.$$



Now $lambda^2=frac{langle Av,Avrangle}{||v||^2}geq 0,$ as the quotient of a nonnegative real number by a positive one. So $lambda$ must be real.






share|cite|improve this answer























  • A quotient of non-negative real numbers? But the argument is very neat.
    – Chris Godsil
    Apr 7 '13 at 19:08










  • only because of $lambda^2$ is real $lambda$ is not real in general. and still you need non negative, because $Av=0$ will surely not be positive. and your equation is confusing
    – Dominic Michaelis
    Apr 7 '13 at 19:19








  • 1




    If $lambda^2$ is positive and real, then $lambda$ is real. What is confusing? And ok, we can assume $lambda$ is not zero! Zero is real obviously.
    – Lepidopterist
    Apr 7 '13 at 19:23






  • 1




    You don't need to bother about $lambda =0$. All you need is $|v|>0$, which is given as you take a (nonzero) eigenvector. So you do find $lambda^2geq 0$. Which is equivalent to $lambda $ being real.
    – Julien
    Apr 7 '13 at 19:44








  • 2




    I decided to edit your answer directly to avoid long chat discussions. I hope you don't mind. Just roll back to your version if you disagree and I will leave it alone.
    – Julien
    Apr 7 '13 at 19:51


















up vote
4
down vote













Let $Ax=lambda x$ with $xne 0$, with $lambdainmathbb{R}$, then
begin{align}
lambda bar x^T x &= bar x^T(lambda x)\
&=bar x^T A x \
&=(A^T bar{x})^T x \
&=(A bar x)^T x \
&=(bar A bar x)^T x \
&=(barlambdabar x)^T x\
&=bar lambda bar x^T x.\
end{align}

Because $xne 0$, then $bar{x}^T xne 0$ and $lambda=bar lambda$.






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    up vote
    3
    down vote













    Hint:
    Prove that $$x^ast A x=langle x , A xrangle = langle Ax, xrangle = x^ast A^ast x $$
    Where $A^ast=overline{A}^T$






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    • 1




      As $A^*=A$, you even get $x^*A^*x=x^*Ax$ directly without any intermediate step. ANd that's all you need for nonzero eigenvalues to be real. I have just seen you hint, by the way, +1.
      – Julien
      Apr 7 '13 at 19:56










    • It's homework so I thought i only give a hint. yeah the equation is pretty obvious but it's worth mentioning in homework i guess
      – Dominic Michaelis
      Apr 7 '13 at 19:59






    • 1




      I'm afraid you misunderstood my comment. It is great that you only gave a hint. I was just saying that the first two equalities are not necessary. But sure, it does not hurt either to include them.
      – Julien
      Apr 7 '13 at 20:01




















    up vote
    1
    down vote













    If $lambda$ is any eigenvalue of a Hermitian (in particular real symmetric) matrix $A$, then for some non-zero vector $x$,
    $$Ax = lambda x implies x^*Ax = lambda x^*x implies lambda = dfrac{x^*Ax}{x^*x}.$$



    Now $$lambda^* = dfrac{x^* A^* x}{x^*x} = dfrac{x^*Ax}{x^*x} = lambda.$$
    Therefore, $lambda$ is real.



    Note: $(AB)^* = B^*A^*$.






    share|cite|improve this answer




























      up vote
      0
      down vote













      Hint: for every $ntimes n$ matrix $M$
      $$
      langle Mv , wrangle
      ~=~
      langle v , M^H wrangle
      $$
      where $M^H$ is the conjugate transpose of $M$ and $langle,cdot,,,cdot,rangle$ is the complex inner product (i.e. $langle v,wrangle=v^Hw$).




      1. Think about how the eigenvalues of $M^H$ and those of $M$ are related

      2. Let $v$ be a $lambda$-eigenvector of $M$ and try what happens choosing $v=w$ in the above equation

      3. Now, if $A$ is real valued and symmetric then $A^H=A$; try again the second point with $M=A$...






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        5 Answers
        5






        active

        oldest

        votes








        5 Answers
        5






        active

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        active

        oldest

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        active

        oldest

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        up vote
        11
        down vote













        $Av=lambda v$ combined with $A=A^T$ gives $$langle Av,Avrangle=v^*A^*Av=v^*A^TAv=v^*A^2v=lambda^2||v||^2.$$



        Now $lambda^2=frac{langle Av,Avrangle}{||v||^2}geq 0,$ as the quotient of a nonnegative real number by a positive one. So $lambda$ must be real.






        share|cite|improve this answer























        • A quotient of non-negative real numbers? But the argument is very neat.
          – Chris Godsil
          Apr 7 '13 at 19:08










        • only because of $lambda^2$ is real $lambda$ is not real in general. and still you need non negative, because $Av=0$ will surely not be positive. and your equation is confusing
          – Dominic Michaelis
          Apr 7 '13 at 19:19








        • 1




          If $lambda^2$ is positive and real, then $lambda$ is real. What is confusing? And ok, we can assume $lambda$ is not zero! Zero is real obviously.
          – Lepidopterist
          Apr 7 '13 at 19:23






        • 1




          You don't need to bother about $lambda =0$. All you need is $|v|>0$, which is given as you take a (nonzero) eigenvector. So you do find $lambda^2geq 0$. Which is equivalent to $lambda $ being real.
          – Julien
          Apr 7 '13 at 19:44








        • 2




          I decided to edit your answer directly to avoid long chat discussions. I hope you don't mind. Just roll back to your version if you disagree and I will leave it alone.
          – Julien
          Apr 7 '13 at 19:51















        up vote
        11
        down vote













        $Av=lambda v$ combined with $A=A^T$ gives $$langle Av,Avrangle=v^*A^*Av=v^*A^TAv=v^*A^2v=lambda^2||v||^2.$$



        Now $lambda^2=frac{langle Av,Avrangle}{||v||^2}geq 0,$ as the quotient of a nonnegative real number by a positive one. So $lambda$ must be real.






        share|cite|improve this answer























        • A quotient of non-negative real numbers? But the argument is very neat.
          – Chris Godsil
          Apr 7 '13 at 19:08










        • only because of $lambda^2$ is real $lambda$ is not real in general. and still you need non negative, because $Av=0$ will surely not be positive. and your equation is confusing
          – Dominic Michaelis
          Apr 7 '13 at 19:19








        • 1




          If $lambda^2$ is positive and real, then $lambda$ is real. What is confusing? And ok, we can assume $lambda$ is not zero! Zero is real obviously.
          – Lepidopterist
          Apr 7 '13 at 19:23






        • 1




          You don't need to bother about $lambda =0$. All you need is $|v|>0$, which is given as you take a (nonzero) eigenvector. So you do find $lambda^2geq 0$. Which is equivalent to $lambda $ being real.
          – Julien
          Apr 7 '13 at 19:44








        • 2




          I decided to edit your answer directly to avoid long chat discussions. I hope you don't mind. Just roll back to your version if you disagree and I will leave it alone.
          – Julien
          Apr 7 '13 at 19:51













        up vote
        11
        down vote










        up vote
        11
        down vote









        $Av=lambda v$ combined with $A=A^T$ gives $$langle Av,Avrangle=v^*A^*Av=v^*A^TAv=v^*A^2v=lambda^2||v||^2.$$



        Now $lambda^2=frac{langle Av,Avrangle}{||v||^2}geq 0,$ as the quotient of a nonnegative real number by a positive one. So $lambda$ must be real.






        share|cite|improve this answer














        $Av=lambda v$ combined with $A=A^T$ gives $$langle Av,Avrangle=v^*A^*Av=v^*A^TAv=v^*A^2v=lambda^2||v||^2.$$



        Now $lambda^2=frac{langle Av,Avrangle}{||v||^2}geq 0,$ as the quotient of a nonnegative real number by a positive one. So $lambda$ must be real.







        share|cite|improve this answer














        share|cite|improve this answer



        share|cite|improve this answer








        edited Apr 7 '13 at 19:51









        Julien

        38.2k355124




        38.2k355124










        answered Apr 7 '13 at 19:06









        Lepidopterist

        9771026




        9771026












        • A quotient of non-negative real numbers? But the argument is very neat.
          – Chris Godsil
          Apr 7 '13 at 19:08










        • only because of $lambda^2$ is real $lambda$ is not real in general. and still you need non negative, because $Av=0$ will surely not be positive. and your equation is confusing
          – Dominic Michaelis
          Apr 7 '13 at 19:19








        • 1




          If $lambda^2$ is positive and real, then $lambda$ is real. What is confusing? And ok, we can assume $lambda$ is not zero! Zero is real obviously.
          – Lepidopterist
          Apr 7 '13 at 19:23






        • 1




          You don't need to bother about $lambda =0$. All you need is $|v|>0$, which is given as you take a (nonzero) eigenvector. So you do find $lambda^2geq 0$. Which is equivalent to $lambda $ being real.
          – Julien
          Apr 7 '13 at 19:44








        • 2




          I decided to edit your answer directly to avoid long chat discussions. I hope you don't mind. Just roll back to your version if you disagree and I will leave it alone.
          – Julien
          Apr 7 '13 at 19:51


















        • A quotient of non-negative real numbers? But the argument is very neat.
          – Chris Godsil
          Apr 7 '13 at 19:08










        • only because of $lambda^2$ is real $lambda$ is not real in general. and still you need non negative, because $Av=0$ will surely not be positive. and your equation is confusing
          – Dominic Michaelis
          Apr 7 '13 at 19:19








        • 1




          If $lambda^2$ is positive and real, then $lambda$ is real. What is confusing? And ok, we can assume $lambda$ is not zero! Zero is real obviously.
          – Lepidopterist
          Apr 7 '13 at 19:23






        • 1




          You don't need to bother about $lambda =0$. All you need is $|v|>0$, which is given as you take a (nonzero) eigenvector. So you do find $lambda^2geq 0$. Which is equivalent to $lambda $ being real.
          – Julien
          Apr 7 '13 at 19:44








        • 2




          I decided to edit your answer directly to avoid long chat discussions. I hope you don't mind. Just roll back to your version if you disagree and I will leave it alone.
          – Julien
          Apr 7 '13 at 19:51
















        A quotient of non-negative real numbers? But the argument is very neat.
        – Chris Godsil
        Apr 7 '13 at 19:08




        A quotient of non-negative real numbers? But the argument is very neat.
        – Chris Godsil
        Apr 7 '13 at 19:08












        only because of $lambda^2$ is real $lambda$ is not real in general. and still you need non negative, because $Av=0$ will surely not be positive. and your equation is confusing
        – Dominic Michaelis
        Apr 7 '13 at 19:19






        only because of $lambda^2$ is real $lambda$ is not real in general. and still you need non negative, because $Av=0$ will surely not be positive. and your equation is confusing
        – Dominic Michaelis
        Apr 7 '13 at 19:19






        1




        1




        If $lambda^2$ is positive and real, then $lambda$ is real. What is confusing? And ok, we can assume $lambda$ is not zero! Zero is real obviously.
        – Lepidopterist
        Apr 7 '13 at 19:23




        If $lambda^2$ is positive and real, then $lambda$ is real. What is confusing? And ok, we can assume $lambda$ is not zero! Zero is real obviously.
        – Lepidopterist
        Apr 7 '13 at 19:23




        1




        1




        You don't need to bother about $lambda =0$. All you need is $|v|>0$, which is given as you take a (nonzero) eigenvector. So you do find $lambda^2geq 0$. Which is equivalent to $lambda $ being real.
        – Julien
        Apr 7 '13 at 19:44






        You don't need to bother about $lambda =0$. All you need is $|v|>0$, which is given as you take a (nonzero) eigenvector. So you do find $lambda^2geq 0$. Which is equivalent to $lambda $ being real.
        – Julien
        Apr 7 '13 at 19:44






        2




        2




        I decided to edit your answer directly to avoid long chat discussions. I hope you don't mind. Just roll back to your version if you disagree and I will leave it alone.
        – Julien
        Apr 7 '13 at 19:51




        I decided to edit your answer directly to avoid long chat discussions. I hope you don't mind. Just roll back to your version if you disagree and I will leave it alone.
        – Julien
        Apr 7 '13 at 19:51










        up vote
        4
        down vote













        Let $Ax=lambda x$ with $xne 0$, with $lambdainmathbb{R}$, then
        begin{align}
        lambda bar x^T x &= bar x^T(lambda x)\
        &=bar x^T A x \
        &=(A^T bar{x})^T x \
        &=(A bar x)^T x \
        &=(bar A bar x)^T x \
        &=(barlambdabar x)^T x\
        &=bar lambda bar x^T x.\
        end{align}

        Because $xne 0$, then $bar{x}^T xne 0$ and $lambda=bar lambda$.






        share|cite|improve this answer



























          up vote
          4
          down vote













          Let $Ax=lambda x$ with $xne 0$, with $lambdainmathbb{R}$, then
          begin{align}
          lambda bar x^T x &= bar x^T(lambda x)\
          &=bar x^T A x \
          &=(A^T bar{x})^T x \
          &=(A bar x)^T x \
          &=(bar A bar x)^T x \
          &=(barlambdabar x)^T x\
          &=bar lambda bar x^T x.\
          end{align}

          Because $xne 0$, then $bar{x}^T xne 0$ and $lambda=bar lambda$.






          share|cite|improve this answer

























            up vote
            4
            down vote










            up vote
            4
            down vote









            Let $Ax=lambda x$ with $xne 0$, with $lambdainmathbb{R}$, then
            begin{align}
            lambda bar x^T x &= bar x^T(lambda x)\
            &=bar x^T A x \
            &=(A^T bar{x})^T x \
            &=(A bar x)^T x \
            &=(bar A bar x)^T x \
            &=(barlambdabar x)^T x\
            &=bar lambda bar x^T x.\
            end{align}

            Because $xne 0$, then $bar{x}^T xne 0$ and $lambda=bar lambda$.






            share|cite|improve this answer














            Let $Ax=lambda x$ with $xne 0$, with $lambdainmathbb{R}$, then
            begin{align}
            lambda bar x^T x &= bar x^T(lambda x)\
            &=bar x^T A x \
            &=(A^T bar{x})^T x \
            &=(A bar x)^T x \
            &=(bar A bar x)^T x \
            &=(barlambdabar x)^T x\
            &=bar lambda bar x^T x.\
            end{align}

            Because $xne 0$, then $bar{x}^T xne 0$ and $lambda=bar lambda$.







            share|cite|improve this answer














            share|cite|improve this answer



            share|cite|improve this answer








            edited Oct 24 at 13:14









            amWhy

            191k27223437




            191k27223437










            answered Oct 10 '16 at 7:27









            naturer

            491




            491






















                up vote
                3
                down vote













                Hint:
                Prove that $$x^ast A x=langle x , A xrangle = langle Ax, xrangle = x^ast A^ast x $$
                Where $A^ast=overline{A}^T$






                share|cite|improve this answer

















                • 1




                  As $A^*=A$, you even get $x^*A^*x=x^*Ax$ directly without any intermediate step. ANd that's all you need for nonzero eigenvalues to be real. I have just seen you hint, by the way, +1.
                  – Julien
                  Apr 7 '13 at 19:56










                • It's homework so I thought i only give a hint. yeah the equation is pretty obvious but it's worth mentioning in homework i guess
                  – Dominic Michaelis
                  Apr 7 '13 at 19:59






                • 1




                  I'm afraid you misunderstood my comment. It is great that you only gave a hint. I was just saying that the first two equalities are not necessary. But sure, it does not hurt either to include them.
                  – Julien
                  Apr 7 '13 at 20:01

















                up vote
                3
                down vote













                Hint:
                Prove that $$x^ast A x=langle x , A xrangle = langle Ax, xrangle = x^ast A^ast x $$
                Where $A^ast=overline{A}^T$






                share|cite|improve this answer

















                • 1




                  As $A^*=A$, you even get $x^*A^*x=x^*Ax$ directly without any intermediate step. ANd that's all you need for nonzero eigenvalues to be real. I have just seen you hint, by the way, +1.
                  – Julien
                  Apr 7 '13 at 19:56










                • It's homework so I thought i only give a hint. yeah the equation is pretty obvious but it's worth mentioning in homework i guess
                  – Dominic Michaelis
                  Apr 7 '13 at 19:59






                • 1




                  I'm afraid you misunderstood my comment. It is great that you only gave a hint. I was just saying that the first two equalities are not necessary. But sure, it does not hurt either to include them.
                  – Julien
                  Apr 7 '13 at 20:01















                up vote
                3
                down vote










                up vote
                3
                down vote









                Hint:
                Prove that $$x^ast A x=langle x , A xrangle = langle Ax, xrangle = x^ast A^ast x $$
                Where $A^ast=overline{A}^T$






                share|cite|improve this answer












                Hint:
                Prove that $$x^ast A x=langle x , A xrangle = langle Ax, xrangle = x^ast A^ast x $$
                Where $A^ast=overline{A}^T$







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered Apr 7 '13 at 19:06









                Dominic Michaelis

                17.6k43570




                17.6k43570








                • 1




                  As $A^*=A$, you even get $x^*A^*x=x^*Ax$ directly without any intermediate step. ANd that's all you need for nonzero eigenvalues to be real. I have just seen you hint, by the way, +1.
                  – Julien
                  Apr 7 '13 at 19:56










                • It's homework so I thought i only give a hint. yeah the equation is pretty obvious but it's worth mentioning in homework i guess
                  – Dominic Michaelis
                  Apr 7 '13 at 19:59






                • 1




                  I'm afraid you misunderstood my comment. It is great that you only gave a hint. I was just saying that the first two equalities are not necessary. But sure, it does not hurt either to include them.
                  – Julien
                  Apr 7 '13 at 20:01
















                • 1




                  As $A^*=A$, you even get $x^*A^*x=x^*Ax$ directly without any intermediate step. ANd that's all you need for nonzero eigenvalues to be real. I have just seen you hint, by the way, +1.
                  – Julien
                  Apr 7 '13 at 19:56










                • It's homework so I thought i only give a hint. yeah the equation is pretty obvious but it's worth mentioning in homework i guess
                  – Dominic Michaelis
                  Apr 7 '13 at 19:59






                • 1




                  I'm afraid you misunderstood my comment. It is great that you only gave a hint. I was just saying that the first two equalities are not necessary. But sure, it does not hurt either to include them.
                  – Julien
                  Apr 7 '13 at 20:01










                1




                1




                As $A^*=A$, you even get $x^*A^*x=x^*Ax$ directly without any intermediate step. ANd that's all you need for nonzero eigenvalues to be real. I have just seen you hint, by the way, +1.
                – Julien
                Apr 7 '13 at 19:56




                As $A^*=A$, you even get $x^*A^*x=x^*Ax$ directly without any intermediate step. ANd that's all you need for nonzero eigenvalues to be real. I have just seen you hint, by the way, +1.
                – Julien
                Apr 7 '13 at 19:56












                It's homework so I thought i only give a hint. yeah the equation is pretty obvious but it's worth mentioning in homework i guess
                – Dominic Michaelis
                Apr 7 '13 at 19:59




                It's homework so I thought i only give a hint. yeah the equation is pretty obvious but it's worth mentioning in homework i guess
                – Dominic Michaelis
                Apr 7 '13 at 19:59




                1




                1




                I'm afraid you misunderstood my comment. It is great that you only gave a hint. I was just saying that the first two equalities are not necessary. But sure, it does not hurt either to include them.
                – Julien
                Apr 7 '13 at 20:01






                I'm afraid you misunderstood my comment. It is great that you only gave a hint. I was just saying that the first two equalities are not necessary. But sure, it does not hurt either to include them.
                – Julien
                Apr 7 '13 at 20:01












                up vote
                1
                down vote













                If $lambda$ is any eigenvalue of a Hermitian (in particular real symmetric) matrix $A$, then for some non-zero vector $x$,
                $$Ax = lambda x implies x^*Ax = lambda x^*x implies lambda = dfrac{x^*Ax}{x^*x}.$$



                Now $$lambda^* = dfrac{x^* A^* x}{x^*x} = dfrac{x^*Ax}{x^*x} = lambda.$$
                Therefore, $lambda$ is real.



                Note: $(AB)^* = B^*A^*$.






                share|cite|improve this answer

























                  up vote
                  1
                  down vote













                  If $lambda$ is any eigenvalue of a Hermitian (in particular real symmetric) matrix $A$, then for some non-zero vector $x$,
                  $$Ax = lambda x implies x^*Ax = lambda x^*x implies lambda = dfrac{x^*Ax}{x^*x}.$$



                  Now $$lambda^* = dfrac{x^* A^* x}{x^*x} = dfrac{x^*Ax}{x^*x} = lambda.$$
                  Therefore, $lambda$ is real.



                  Note: $(AB)^* = B^*A^*$.






                  share|cite|improve this answer























                    up vote
                    1
                    down vote










                    up vote
                    1
                    down vote









                    If $lambda$ is any eigenvalue of a Hermitian (in particular real symmetric) matrix $A$, then for some non-zero vector $x$,
                    $$Ax = lambda x implies x^*Ax = lambda x^*x implies lambda = dfrac{x^*Ax}{x^*x}.$$



                    Now $$lambda^* = dfrac{x^* A^* x}{x^*x} = dfrac{x^*Ax}{x^*x} = lambda.$$
                    Therefore, $lambda$ is real.



                    Note: $(AB)^* = B^*A^*$.






                    share|cite|improve this answer












                    If $lambda$ is any eigenvalue of a Hermitian (in particular real symmetric) matrix $A$, then for some non-zero vector $x$,
                    $$Ax = lambda x implies x^*Ax = lambda x^*x implies lambda = dfrac{x^*Ax}{x^*x}.$$



                    Now $$lambda^* = dfrac{x^* A^* x}{x^*x} = dfrac{x^*Ax}{x^*x} = lambda.$$
                    Therefore, $lambda$ is real.



                    Note: $(AB)^* = B^*A^*$.







                    share|cite|improve this answer












                    share|cite|improve this answer



                    share|cite|improve this answer










                    answered 2 days ago









                    M. Vinay

                    6,75822035




                    6,75822035






















                        up vote
                        0
                        down vote













                        Hint: for every $ntimes n$ matrix $M$
                        $$
                        langle Mv , wrangle
                        ~=~
                        langle v , M^H wrangle
                        $$
                        where $M^H$ is the conjugate transpose of $M$ and $langle,cdot,,,cdot,rangle$ is the complex inner product (i.e. $langle v,wrangle=v^Hw$).




                        1. Think about how the eigenvalues of $M^H$ and those of $M$ are related

                        2. Let $v$ be a $lambda$-eigenvector of $M$ and try what happens choosing $v=w$ in the above equation

                        3. Now, if $A$ is real valued and symmetric then $A^H=A$; try again the second point with $M=A$...






                        share|cite|improve this answer

























                          up vote
                          0
                          down vote













                          Hint: for every $ntimes n$ matrix $M$
                          $$
                          langle Mv , wrangle
                          ~=~
                          langle v , M^H wrangle
                          $$
                          where $M^H$ is the conjugate transpose of $M$ and $langle,cdot,,,cdot,rangle$ is the complex inner product (i.e. $langle v,wrangle=v^Hw$).




                          1. Think about how the eigenvalues of $M^H$ and those of $M$ are related

                          2. Let $v$ be a $lambda$-eigenvector of $M$ and try what happens choosing $v=w$ in the above equation

                          3. Now, if $A$ is real valued and symmetric then $A^H=A$; try again the second point with $M=A$...






                          share|cite|improve this answer























                            up vote
                            0
                            down vote










                            up vote
                            0
                            down vote









                            Hint: for every $ntimes n$ matrix $M$
                            $$
                            langle Mv , wrangle
                            ~=~
                            langle v , M^H wrangle
                            $$
                            where $M^H$ is the conjugate transpose of $M$ and $langle,cdot,,,cdot,rangle$ is the complex inner product (i.e. $langle v,wrangle=v^Hw$).




                            1. Think about how the eigenvalues of $M^H$ and those of $M$ are related

                            2. Let $v$ be a $lambda$-eigenvector of $M$ and try what happens choosing $v=w$ in the above equation

                            3. Now, if $A$ is real valued and symmetric then $A^H=A$; try again the second point with $M=A$...






                            share|cite|improve this answer












                            Hint: for every $ntimes n$ matrix $M$
                            $$
                            langle Mv , wrangle
                            ~=~
                            langle v , M^H wrangle
                            $$
                            where $M^H$ is the conjugate transpose of $M$ and $langle,cdot,,,cdot,rangle$ is the complex inner product (i.e. $langle v,wrangle=v^Hw$).




                            1. Think about how the eigenvalues of $M^H$ and those of $M$ are related

                            2. Let $v$ be a $lambda$-eigenvector of $M$ and try what happens choosing $v=w$ in the above equation

                            3. Now, if $A$ is real valued and symmetric then $A^H=A$; try again the second point with $M=A$...







                            share|cite|improve this answer












                            share|cite|improve this answer



                            share|cite|improve this answer










                            answered Apr 7 '13 at 19:13









                            AndreasT

                            3,2811224




                            3,2811224






























                                 

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