Exact Differential Equation GeometryHelp with an Ordinary Differential EquationWhy aren't exact differential equations considered PDE?“Division” of an inexact differential form by an exact differential formFinding integrating factor for non-exact differential equation $(4y-10x)dx+(4x-6x^2y^-1)dy=0$.When is an ordinary differential equation truly inexact?Transform an inexact differential into an exact differential using an integrating factorSpecial integrating factor for non-exact DE that depends on two varibles?Exact solution for a first order autonomous algebraic ordinary differential equationdetermine whether differential equation is exact or not and solve itExact Differential Equation Integrating Factor

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Exact Differential Equation Geometry


Help with an Ordinary Differential EquationWhy aren't exact differential equations considered PDE?“Division” of an inexact differential form by an exact differential formFinding integrating factor for non-exact differential equation $(4y-10x)dx+(4x-6x^2y^-1)dy=0$.When is an ordinary differential equation truly inexact?Transform an inexact differential into an exact differential using an integrating factorSpecial integrating factor for non-exact DE that depends on two varibles?Exact solution for a first order autonomous algebraic ordinary differential equationdetermine whether differential equation is exact or not and solve itExact Differential Equation Integrating Factor













1












$begingroup$


In a variety of contexts, I have noticed hints of a strong connection between exact differential equations and machinery from multivariable calculus.



From another question, I have gathered that the geometry of finding the general solution to an exact differential equation $M(x, y) dx + N(x, y) dy = 0$ includes finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, that is, every surface in $mathbbR^3$ whose gradient is the vector field $beginbmatrixM(x, y) \ N(x, y)endbmatrix$. What is missing from this description? For example, we can write the LHS of a not-necessarily-exact $M(x, y) dx + N(x, y) dy = 0$ as $beginbmatrixM(x, y) \ N(x, y) endbmatrix cdot beginbmatrixdx \ dyendbmatrix$, which expresses the differential of work done by $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, and thus shows promise for extending the above geometric picture. In fact, since work is a path function, I suspect the Wikipedia quote




In mathematics, an integrating factor is a function that is chosen to
facilitate the solving of a given equation involving differentials. It
is commonly used to solve ordinary differential equations, but is also
used within multivariable calculus when multiplying through by an
integrating factor allows an inexact differential to be made into an
exact differential (which can then be integrated to give a scalar
field). This is especially useful in thermodynamics where temperature
becomes the integrating factor that makes entropy an exact
differential.




is misleading, in that the ordinary differential equations and multivariable calculus uses are actually identical, which if correct, might allow geometry from other path functions (such as the referenced thermodynamics example) to be leveraged.



A big part of what I'm trying to remedy is that it's not clear to me why finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$ should solve the ODE. I understand the algebraic rationale that the solution technique undoes the multivariable chain rule (multiply through by $dx$ then integrate both sides), but is the geometric picture just an afterthought, or does it offer its own independent rationale for the solution technique?










share|cite|improve this question









$endgroup$
















    1












    $begingroup$


    In a variety of contexts, I have noticed hints of a strong connection between exact differential equations and machinery from multivariable calculus.



    From another question, I have gathered that the geometry of finding the general solution to an exact differential equation $M(x, y) dx + N(x, y) dy = 0$ includes finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, that is, every surface in $mathbbR^3$ whose gradient is the vector field $beginbmatrixM(x, y) \ N(x, y)endbmatrix$. What is missing from this description? For example, we can write the LHS of a not-necessarily-exact $M(x, y) dx + N(x, y) dy = 0$ as $beginbmatrixM(x, y) \ N(x, y) endbmatrix cdot beginbmatrixdx \ dyendbmatrix$, which expresses the differential of work done by $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, and thus shows promise for extending the above geometric picture. In fact, since work is a path function, I suspect the Wikipedia quote




    In mathematics, an integrating factor is a function that is chosen to
    facilitate the solving of a given equation involving differentials. It
    is commonly used to solve ordinary differential equations, but is also
    used within multivariable calculus when multiplying through by an
    integrating factor allows an inexact differential to be made into an
    exact differential (which can then be integrated to give a scalar
    field). This is especially useful in thermodynamics where temperature
    becomes the integrating factor that makes entropy an exact
    differential.




    is misleading, in that the ordinary differential equations and multivariable calculus uses are actually identical, which if correct, might allow geometry from other path functions (such as the referenced thermodynamics example) to be leveraged.



    A big part of what I'm trying to remedy is that it's not clear to me why finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$ should solve the ODE. I understand the algebraic rationale that the solution technique undoes the multivariable chain rule (multiply through by $dx$ then integrate both sides), but is the geometric picture just an afterthought, or does it offer its own independent rationale for the solution technique?










    share|cite|improve this question









    $endgroup$














      1












      1








      1





      $begingroup$


      In a variety of contexts, I have noticed hints of a strong connection between exact differential equations and machinery from multivariable calculus.



      From another question, I have gathered that the geometry of finding the general solution to an exact differential equation $M(x, y) dx + N(x, y) dy = 0$ includes finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, that is, every surface in $mathbbR^3$ whose gradient is the vector field $beginbmatrixM(x, y) \ N(x, y)endbmatrix$. What is missing from this description? For example, we can write the LHS of a not-necessarily-exact $M(x, y) dx + N(x, y) dy = 0$ as $beginbmatrixM(x, y) \ N(x, y) endbmatrix cdot beginbmatrixdx \ dyendbmatrix$, which expresses the differential of work done by $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, and thus shows promise for extending the above geometric picture. In fact, since work is a path function, I suspect the Wikipedia quote




      In mathematics, an integrating factor is a function that is chosen to
      facilitate the solving of a given equation involving differentials. It
      is commonly used to solve ordinary differential equations, but is also
      used within multivariable calculus when multiplying through by an
      integrating factor allows an inexact differential to be made into an
      exact differential (which can then be integrated to give a scalar
      field). This is especially useful in thermodynamics where temperature
      becomes the integrating factor that makes entropy an exact
      differential.




      is misleading, in that the ordinary differential equations and multivariable calculus uses are actually identical, which if correct, might allow geometry from other path functions (such as the referenced thermodynamics example) to be leveraged.



      A big part of what I'm trying to remedy is that it's not clear to me why finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$ should solve the ODE. I understand the algebraic rationale that the solution technique undoes the multivariable chain rule (multiply through by $dx$ then integrate both sides), but is the geometric picture just an afterthought, or does it offer its own independent rationale for the solution technique?










      share|cite|improve this question









      $endgroup$




      In a variety of contexts, I have noticed hints of a strong connection between exact differential equations and machinery from multivariable calculus.



      From another question, I have gathered that the geometry of finding the general solution to an exact differential equation $M(x, y) dx + N(x, y) dy = 0$ includes finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, that is, every surface in $mathbbR^3$ whose gradient is the vector field $beginbmatrixM(x, y) \ N(x, y)endbmatrix$. What is missing from this description? For example, we can write the LHS of a not-necessarily-exact $M(x, y) dx + N(x, y) dy = 0$ as $beginbmatrixM(x, y) \ N(x, y) endbmatrix cdot beginbmatrixdx \ dyendbmatrix$, which expresses the differential of work done by $beginbmatrixM(x, y) \ N(x, y)endbmatrix$, and thus shows promise for extending the above geometric picture. In fact, since work is a path function, I suspect the Wikipedia quote




      In mathematics, an integrating factor is a function that is chosen to
      facilitate the solving of a given equation involving differentials. It
      is commonly used to solve ordinary differential equations, but is also
      used within multivariable calculus when multiplying through by an
      integrating factor allows an inexact differential to be made into an
      exact differential (which can then be integrated to give a scalar
      field). This is especially useful in thermodynamics where temperature
      becomes the integrating factor that makes entropy an exact
      differential.




      is misleading, in that the ordinary differential equations and multivariable calculus uses are actually identical, which if correct, might allow geometry from other path functions (such as the referenced thermodynamics example) to be leveraged.



      A big part of what I'm trying to remedy is that it's not clear to me why finding the potential function of $beginbmatrixM(x, y) \ N(x, y)endbmatrix$ should solve the ODE. I understand the algebraic rationale that the solution technique undoes the multivariable chain rule (multiply through by $dx$ then integrate both sides), but is the geometric picture just an afterthought, or does it offer its own independent rationale for the solution technique?







      geometry ordinary-differential-equations multivariable-calculus vector-fields differential






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