Are these square matrices always diagonalisable? Announcing the arrival of Valued Associate...

What's parked in Mil Moscow helicopter plant?

What helicopter has the most rotor blades?

Processing ADC conversion result: DMA vs Processor Registers

Suing a Police Officer Instead of the Police Department

What *exactly* is electrical current, voltage, and resistance?

Feather, the Redeemed and Dire Fleet Daredevil

Does a Draconic Bloodline sorcerer's doubled proficiency bonus for Charisma checks against dragons apply to all dragon types or only the chosen one?

Was Objective-C really a hindrance to Apple software development?

Why did Israel vote against lifting the American embargo on Cuba?

Specify the range of GridLines

What's the difference between using dependency injection with a container and using a service locator?

Coin Game with infinite paradox

What is the purpose of the side handle on a hand ("eggbeater") drill?

Is there a possibility to generate a list dynamically in Latex?

What does こした mean?

Eigenvalues of the Laplacian of the directed De Bruijn graph

Why doesn't the university give past final exams' answers?

How to translate "red flag" into Spanish?

Variable does not exist: sObjectType (Task.sObjectType)

Are there existing rules/lore for MTG planeswalkers?

What to do with someone that cheated their way though university and a PhD program?

How did Elite on the NES work?

Why isn't everyone flabbergasted about Bran's "gift"?

Raising a bilingual kid. When should we introduce the majority language?



Are these square matrices always diagonalisable?



Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30 pm US/Eastern)Conditions for diagonalizability of $ntimes n$ anti-diagonal matricesFinding eigenvalues/vectors of a matrix and proving it is not diagonalisable.Finding if a linear transformation is diagonalisableThe diagonalisation of the two matricesIf $A in K^{n times n}$ is diagonalisable, the dimension of the subspace of its commuting matrices is $geq n$ nCalculating the eigenvalues of a diagonalisable linear operator $L$.How to find eigenvalues for mod 2 field?Find for which real parameter a matrix is diagonalisableSquare Roots of a Matrix: Diagonalisable Solutions.eigenvalues and eigenvectors of Diagonalisable matrices












1












$begingroup$


When trying to solve a physics problem on decoupling a system of ODEs, I found myself needing to address the following problem:




Let $A_nin M_n(mathbb R)$ be the matrix with all $1$s above its main diagonal, all $-1$s below its diagonal, and $0$s everywhere else. Is $A_n$ always diagonalisable? If so, what is its diagonalisation (equivalently: what are its eigenvalues and corresponding eigenvectors)?




For example,
$$A_3=begin{bmatrix}0&1&0\-1&0&1\0&-1&0end{bmatrix},quad A_5begin{bmatrix}0&1&0&0&0\-1&0&1&0&0\0&-1&0&1&0\0&0&-1&0&1\0&0&0&-1&0end{bmatrix}.$$





Assuming my code is correct, Mathematica has been able to verify that $A_n$ is always diagonalisable up to $n=1000$. If we use $chi_n(t)inmathbb Z[t]$ to denote the characteristic polynomial of $A_n$, a straightforward evaluation also shows that
$$chi_n(t)=-tchi_{n-1}(t)+chi_{n-2}(t)tag{1}$$
for all $ngeq4$. Furthermore, note that $A_n=-A_n^t$ so that, in the case where the dimension is even,
$$det(A_{2n}-lambda I)=det(A_{2n}^t-lambda I)=det(-A_{2n}-lambda I)=det(A_{2n}+lambda I).$$
This implies that whenever $lambda$ is an eigenvalue of $A_{2n}$, so is $-lambda$. In other words, $chi_{2n}(t)$ is always of the form $(t^2-lambda _1^2)(t^2-lambda_2^2)dotsm(t^2-lambda_n^2)$ for some $lambda_i$.



And this is where I am stuck. In order for $A_n$ to be diagonalisable, we must have that all the eigenvalues are distinct, but trying to use the recurrence $(1)$ and strong induction, or trying to use the formula for the even case have not helped at all. It seems like the most probable line of attack would be to somehow show that
$$chi_{2n}'(t)=2tsum_{k=1}^nfrac{chi_{2n}(t)}{t^2-lambda_k^2}$$
never shares a common zero with $chi_{2n}$ (which would resolve the even case), though I don't see how to make this work.





Note: I do not have any clue how to actually find the eigenvalues/eigenvectors even in the case where the $A_n$ are diagonalisable. As such even if someone cannot answer the second part of the question, but can prove that the $A_n$ are diagonalisable, I would appreciate that as an answer as well. Above I tried to look at the special case where the dimension is even, though of course the proof for all odd and even $n$ is more valuable. Even if this is not possible, for my purposes I just need an unbounded subset $Ssubseteqmathbb Z$ for which the conclusion is proven for $nin S$, so any such approach is welcome too.



Thank you in advance!










share|cite|improve this question









$endgroup$

















    1












    $begingroup$


    When trying to solve a physics problem on decoupling a system of ODEs, I found myself needing to address the following problem:




    Let $A_nin M_n(mathbb R)$ be the matrix with all $1$s above its main diagonal, all $-1$s below its diagonal, and $0$s everywhere else. Is $A_n$ always diagonalisable? If so, what is its diagonalisation (equivalently: what are its eigenvalues and corresponding eigenvectors)?




    For example,
    $$A_3=begin{bmatrix}0&1&0\-1&0&1\0&-1&0end{bmatrix},quad A_5begin{bmatrix}0&1&0&0&0\-1&0&1&0&0\0&-1&0&1&0\0&0&-1&0&1\0&0&0&-1&0end{bmatrix}.$$





    Assuming my code is correct, Mathematica has been able to verify that $A_n$ is always diagonalisable up to $n=1000$. If we use $chi_n(t)inmathbb Z[t]$ to denote the characteristic polynomial of $A_n$, a straightforward evaluation also shows that
    $$chi_n(t)=-tchi_{n-1}(t)+chi_{n-2}(t)tag{1}$$
    for all $ngeq4$. Furthermore, note that $A_n=-A_n^t$ so that, in the case where the dimension is even,
    $$det(A_{2n}-lambda I)=det(A_{2n}^t-lambda I)=det(-A_{2n}-lambda I)=det(A_{2n}+lambda I).$$
    This implies that whenever $lambda$ is an eigenvalue of $A_{2n}$, so is $-lambda$. In other words, $chi_{2n}(t)$ is always of the form $(t^2-lambda _1^2)(t^2-lambda_2^2)dotsm(t^2-lambda_n^2)$ for some $lambda_i$.



    And this is where I am stuck. In order for $A_n$ to be diagonalisable, we must have that all the eigenvalues are distinct, but trying to use the recurrence $(1)$ and strong induction, or trying to use the formula for the even case have not helped at all. It seems like the most probable line of attack would be to somehow show that
    $$chi_{2n}'(t)=2tsum_{k=1}^nfrac{chi_{2n}(t)}{t^2-lambda_k^2}$$
    never shares a common zero with $chi_{2n}$ (which would resolve the even case), though I don't see how to make this work.





    Note: I do not have any clue how to actually find the eigenvalues/eigenvectors even in the case where the $A_n$ are diagonalisable. As such even if someone cannot answer the second part of the question, but can prove that the $A_n$ are diagonalisable, I would appreciate that as an answer as well. Above I tried to look at the special case where the dimension is even, though of course the proof for all odd and even $n$ is more valuable. Even if this is not possible, for my purposes I just need an unbounded subset $Ssubseteqmathbb Z$ for which the conclusion is proven for $nin S$, so any such approach is welcome too.



    Thank you in advance!










    share|cite|improve this question









    $endgroup$















      1












      1








      1





      $begingroup$


      When trying to solve a physics problem on decoupling a system of ODEs, I found myself needing to address the following problem:




      Let $A_nin M_n(mathbb R)$ be the matrix with all $1$s above its main diagonal, all $-1$s below its diagonal, and $0$s everywhere else. Is $A_n$ always diagonalisable? If so, what is its diagonalisation (equivalently: what are its eigenvalues and corresponding eigenvectors)?




      For example,
      $$A_3=begin{bmatrix}0&1&0\-1&0&1\0&-1&0end{bmatrix},quad A_5begin{bmatrix}0&1&0&0&0\-1&0&1&0&0\0&-1&0&1&0\0&0&-1&0&1\0&0&0&-1&0end{bmatrix}.$$





      Assuming my code is correct, Mathematica has been able to verify that $A_n$ is always diagonalisable up to $n=1000$. If we use $chi_n(t)inmathbb Z[t]$ to denote the characteristic polynomial of $A_n$, a straightforward evaluation also shows that
      $$chi_n(t)=-tchi_{n-1}(t)+chi_{n-2}(t)tag{1}$$
      for all $ngeq4$. Furthermore, note that $A_n=-A_n^t$ so that, in the case where the dimension is even,
      $$det(A_{2n}-lambda I)=det(A_{2n}^t-lambda I)=det(-A_{2n}-lambda I)=det(A_{2n}+lambda I).$$
      This implies that whenever $lambda$ is an eigenvalue of $A_{2n}$, so is $-lambda$. In other words, $chi_{2n}(t)$ is always of the form $(t^2-lambda _1^2)(t^2-lambda_2^2)dotsm(t^2-lambda_n^2)$ for some $lambda_i$.



      And this is where I am stuck. In order for $A_n$ to be diagonalisable, we must have that all the eigenvalues are distinct, but trying to use the recurrence $(1)$ and strong induction, or trying to use the formula for the even case have not helped at all. It seems like the most probable line of attack would be to somehow show that
      $$chi_{2n}'(t)=2tsum_{k=1}^nfrac{chi_{2n}(t)}{t^2-lambda_k^2}$$
      never shares a common zero with $chi_{2n}$ (which would resolve the even case), though I don't see how to make this work.





      Note: I do not have any clue how to actually find the eigenvalues/eigenvectors even in the case where the $A_n$ are diagonalisable. As such even if someone cannot answer the second part of the question, but can prove that the $A_n$ are diagonalisable, I would appreciate that as an answer as well. Above I tried to look at the special case where the dimension is even, though of course the proof for all odd and even $n$ is more valuable. Even if this is not possible, for my purposes I just need an unbounded subset $Ssubseteqmathbb Z$ for which the conclusion is proven for $nin S$, so any such approach is welcome too.



      Thank you in advance!










      share|cite|improve this question









      $endgroup$




      When trying to solve a physics problem on decoupling a system of ODEs, I found myself needing to address the following problem:




      Let $A_nin M_n(mathbb R)$ be the matrix with all $1$s above its main diagonal, all $-1$s below its diagonal, and $0$s everywhere else. Is $A_n$ always diagonalisable? If so, what is its diagonalisation (equivalently: what are its eigenvalues and corresponding eigenvectors)?




      For example,
      $$A_3=begin{bmatrix}0&1&0\-1&0&1\0&-1&0end{bmatrix},quad A_5begin{bmatrix}0&1&0&0&0\-1&0&1&0&0\0&-1&0&1&0\0&0&-1&0&1\0&0&0&-1&0end{bmatrix}.$$





      Assuming my code is correct, Mathematica has been able to verify that $A_n$ is always diagonalisable up to $n=1000$. If we use $chi_n(t)inmathbb Z[t]$ to denote the characteristic polynomial of $A_n$, a straightforward evaluation also shows that
      $$chi_n(t)=-tchi_{n-1}(t)+chi_{n-2}(t)tag{1}$$
      for all $ngeq4$. Furthermore, note that $A_n=-A_n^t$ so that, in the case where the dimension is even,
      $$det(A_{2n}-lambda I)=det(A_{2n}^t-lambda I)=det(-A_{2n}-lambda I)=det(A_{2n}+lambda I).$$
      This implies that whenever $lambda$ is an eigenvalue of $A_{2n}$, so is $-lambda$. In other words, $chi_{2n}(t)$ is always of the form $(t^2-lambda _1^2)(t^2-lambda_2^2)dotsm(t^2-lambda_n^2)$ for some $lambda_i$.



      And this is where I am stuck. In order for $A_n$ to be diagonalisable, we must have that all the eigenvalues are distinct, but trying to use the recurrence $(1)$ and strong induction, or trying to use the formula for the even case have not helped at all. It seems like the most probable line of attack would be to somehow show that
      $$chi_{2n}'(t)=2tsum_{k=1}^nfrac{chi_{2n}(t)}{t^2-lambda_k^2}$$
      never shares a common zero with $chi_{2n}$ (which would resolve the even case), though I don't see how to make this work.





      Note: I do not have any clue how to actually find the eigenvalues/eigenvectors even in the case where the $A_n$ are diagonalisable. As such even if someone cannot answer the second part of the question, but can prove that the $A_n$ are diagonalisable, I would appreciate that as an answer as well. Above I tried to look at the special case where the dimension is even, though of course the proof for all odd and even $n$ is more valuable. Even if this is not possible, for my purposes I just need an unbounded subset $Ssubseteqmathbb Z$ for which the conclusion is proven for $nin S$, so any such approach is welcome too.



      Thank you in advance!







      linear-algebra eigenvalues-eigenvectors determinant diagonalization






      share|cite|improve this question













      share|cite|improve this question











      share|cite|improve this question




      share|cite|improve this question










      asked 41 mins ago









      YiFanYiFan

      5,6102829




      5,6102829






















          3 Answers
          3






          active

          oldest

          votes


















          4












          $begingroup$

          The matrix $A_n$ is a tridiagonal Toeplitz matrix with diagonal entries $delta = 0$ and off-diagonal entries $tau = 1$ and $sigma = -1$. Hence, we can use the formula in this paper to show that the eigenvalues are $$lambda_k = 2icosleft(dfrac{kpi}{n+1}right),$$ for $k = 1,ldots,n$, and the corresponding eigenvectors $v_1,ldots,v_n$ have entries $$v_k[m] = i^msinleft(dfrac{mkpi}{n+1}right).$$






          share|cite|improve this answer











          $endgroup$





















            2












            $begingroup$

            All those matrices are anti-symmetric and therefore they are normal matrices. And every normal matrix is diagonalizable over $mathbb C$, by the spectral theorem.






            share|cite|improve this answer









            $endgroup$













            • $begingroup$
              Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
              $endgroup$
              – YiFan
              18 mins ago






            • 1




              $begingroup$
              I would have been surprised if you had not accepted that answer, since it provides more information than mine.
              $endgroup$
              – José Carlos Santos
              16 mins ago



















            2












            $begingroup$

            Using that your matrices are skew symmetric, you get that these matrices are diagonalizable. See the section spectral theory on this Wikipedia article.






            share|cite|improve this answer








            New contributor




            gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
            Check out our Code of Conduct.






            $endgroup$













            • $begingroup$
              Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
              $endgroup$
              – YiFan
              18 mins ago












            Your Answer








            StackExchange.ready(function() {
            var channelOptions = {
            tags: "".split(" "),
            id: "69"
            };
            initTagRenderer("".split(" "), "".split(" "), channelOptions);

            StackExchange.using("externalEditor", function() {
            // Have to fire editor after snippets, if snippets enabled
            if (StackExchange.settings.snippets.snippetsEnabled) {
            StackExchange.using("snippets", function() {
            createEditor();
            });
            }
            else {
            createEditor();
            }
            });

            function createEditor() {
            StackExchange.prepareEditor({
            heartbeatType: 'answer',
            autoActivateHeartbeat: false,
            convertImagesToLinks: true,
            noModals: true,
            showLowRepImageUploadWarning: true,
            reputationToPostImages: 10,
            bindNavPrevention: true,
            postfix: "",
            imageUploader: {
            brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
            contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
            allowUrls: true
            },
            noCode: true, onDemand: true,
            discardSelector: ".discard-answer"
            ,immediatelyShowMarkdownHelp:true
            });


            }
            });














            draft saved

            draft discarded


















            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3198918%2fare-these-square-matrices-always-diagonalisable%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown

























            3 Answers
            3






            active

            oldest

            votes








            3 Answers
            3






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            4












            $begingroup$

            The matrix $A_n$ is a tridiagonal Toeplitz matrix with diagonal entries $delta = 0$ and off-diagonal entries $tau = 1$ and $sigma = -1$. Hence, we can use the formula in this paper to show that the eigenvalues are $$lambda_k = 2icosleft(dfrac{kpi}{n+1}right),$$ for $k = 1,ldots,n$, and the corresponding eigenvectors $v_1,ldots,v_n$ have entries $$v_k[m] = i^msinleft(dfrac{mkpi}{n+1}right).$$






            share|cite|improve this answer











            $endgroup$


















              4












              $begingroup$

              The matrix $A_n$ is a tridiagonal Toeplitz matrix with diagonal entries $delta = 0$ and off-diagonal entries $tau = 1$ and $sigma = -1$. Hence, we can use the formula in this paper to show that the eigenvalues are $$lambda_k = 2icosleft(dfrac{kpi}{n+1}right),$$ for $k = 1,ldots,n$, and the corresponding eigenvectors $v_1,ldots,v_n$ have entries $$v_k[m] = i^msinleft(dfrac{mkpi}{n+1}right).$$






              share|cite|improve this answer











              $endgroup$
















                4












                4








                4





                $begingroup$

                The matrix $A_n$ is a tridiagonal Toeplitz matrix with diagonal entries $delta = 0$ and off-diagonal entries $tau = 1$ and $sigma = -1$. Hence, we can use the formula in this paper to show that the eigenvalues are $$lambda_k = 2icosleft(dfrac{kpi}{n+1}right),$$ for $k = 1,ldots,n$, and the corresponding eigenvectors $v_1,ldots,v_n$ have entries $$v_k[m] = i^msinleft(dfrac{mkpi}{n+1}right).$$






                share|cite|improve this answer











                $endgroup$



                The matrix $A_n$ is a tridiagonal Toeplitz matrix with diagonal entries $delta = 0$ and off-diagonal entries $tau = 1$ and $sigma = -1$. Hence, we can use the formula in this paper to show that the eigenvalues are $$lambda_k = 2icosleft(dfrac{kpi}{n+1}right),$$ for $k = 1,ldots,n$, and the corresponding eigenvectors $v_1,ldots,v_n$ have entries $$v_k[m] = i^msinleft(dfrac{mkpi}{n+1}right).$$







                share|cite|improve this answer














                share|cite|improve this answer



                share|cite|improve this answer








                edited 26 mins ago

























                answered 32 mins ago









                JimmyK4542JimmyK4542

                41.5k246108




                41.5k246108























                    2












                    $begingroup$

                    All those matrices are anti-symmetric and therefore they are normal matrices. And every normal matrix is diagonalizable over $mathbb C$, by the spectral theorem.






                    share|cite|improve this answer









                    $endgroup$













                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago






                    • 1




                      $begingroup$
                      I would have been surprised if you had not accepted that answer, since it provides more information than mine.
                      $endgroup$
                      – José Carlos Santos
                      16 mins ago
















                    2












                    $begingroup$

                    All those matrices are anti-symmetric and therefore they are normal matrices. And every normal matrix is diagonalizable over $mathbb C$, by the spectral theorem.






                    share|cite|improve this answer









                    $endgroup$













                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago






                    • 1




                      $begingroup$
                      I would have been surprised if you had not accepted that answer, since it provides more information than mine.
                      $endgroup$
                      – José Carlos Santos
                      16 mins ago














                    2












                    2








                    2





                    $begingroup$

                    All those matrices are anti-symmetric and therefore they are normal matrices. And every normal matrix is diagonalizable over $mathbb C$, by the spectral theorem.






                    share|cite|improve this answer









                    $endgroup$



                    All those matrices are anti-symmetric and therefore they are normal matrices. And every normal matrix is diagonalizable over $mathbb C$, by the spectral theorem.







                    share|cite|improve this answer












                    share|cite|improve this answer



                    share|cite|improve this answer










                    answered 29 mins ago









                    José Carlos SantosJosé Carlos Santos

                    177k24138250




                    177k24138250












                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago






                    • 1




                      $begingroup$
                      I would have been surprised if you had not accepted that answer, since it provides more information than mine.
                      $endgroup$
                      – José Carlos Santos
                      16 mins ago


















                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago






                    • 1




                      $begingroup$
                      I would have been surprised if you had not accepted that answer, since it provides more information than mine.
                      $endgroup$
                      – José Carlos Santos
                      16 mins ago
















                    $begingroup$
                    Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                    $endgroup$
                    – YiFan
                    18 mins ago




                    $begingroup$
                    Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                    $endgroup$
                    – YiFan
                    18 mins ago




                    1




                    1




                    $begingroup$
                    I would have been surprised if you had not accepted that answer, since it provides more information than mine.
                    $endgroup$
                    – José Carlos Santos
                    16 mins ago




                    $begingroup$
                    I would have been surprised if you had not accepted that answer, since it provides more information than mine.
                    $endgroup$
                    – José Carlos Santos
                    16 mins ago











                    2












                    $begingroup$

                    Using that your matrices are skew symmetric, you get that these matrices are diagonalizable. See the section spectral theory on this Wikipedia article.






                    share|cite|improve this answer








                    New contributor




                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.






                    $endgroup$













                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago
















                    2












                    $begingroup$

                    Using that your matrices are skew symmetric, you get that these matrices are diagonalizable. See the section spectral theory on this Wikipedia article.






                    share|cite|improve this answer








                    New contributor




                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.






                    $endgroup$













                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago














                    2












                    2








                    2





                    $begingroup$

                    Using that your matrices are skew symmetric, you get that these matrices are diagonalizable. See the section spectral theory on this Wikipedia article.






                    share|cite|improve this answer








                    New contributor




                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.






                    $endgroup$



                    Using that your matrices are skew symmetric, you get that these matrices are diagonalizable. See the section spectral theory on this Wikipedia article.







                    share|cite|improve this answer








                    New contributor




                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.









                    share|cite|improve this answer



                    share|cite|improve this answer






                    New contributor




                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.









                    answered 27 mins ago









                    gcousingcousin

                    1012




                    1012




                    New contributor




                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.





                    New contributor





                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.






                    gcousin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                    Check out our Code of Conduct.












                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago


















                    • $begingroup$
                      Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                      $endgroup$
                      – YiFan
                      18 mins ago
















                    $begingroup$
                    Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                    $endgroup$
                    – YiFan
                    18 mins ago




                    $begingroup$
                    Thank you very much for the quick response! I hope you don't mind that I accepted JimmyK4542's answer, since it also gives explicitly the eigenvectors and eigenvalues.
                    $endgroup$
                    – YiFan
                    18 mins ago


















                    draft saved

                    draft discarded




















































                    Thanks for contributing an answer to Mathematics Stack Exchange!


                    • Please be sure to answer the question. Provide details and share your research!

                    But avoid



                    • Asking for help, clarification, or responding to other answers.

                    • Making statements based on opinion; back them up with references or personal experience.


                    Use MathJax to format equations. MathJax reference.


                    To learn more, see our tips on writing great answers.




                    draft saved


                    draft discarded














                    StackExchange.ready(
                    function () {
                    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3198918%2fare-these-square-matrices-always-diagonalisable%23new-answer', 'question_page');
                    }
                    );

                    Post as a guest















                    Required, but never shown





















































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown

































                    Required, but never shown














                    Required, but never shown












                    Required, but never shown







                    Required, but never shown







                    Popular posts from this blog

                    El tren de la libertad Índice Antecedentes "Porque yo decido" Desarrollo de la...

                    Castillo d'Acher Características Menú de navegación

                    Connecting two nodes from the same mother node horizontallyTikZ: What EXACTLY does the the |- notation for...