Examine the singular points of the equation y'=(y)/(x)
Examine the singular points of the equation $$y'=\frac{y}{x}.$$
Explanation of Method
The singular points are located by solving P(x,y) = 0 and Q(x,y) = 0 simultaneously. The associated planar autonomous system is formed (linearising about the singular point where necessary), its coefficient/Jacobian matrix is written down, and the point is classified from the sign and nature of that matrix's eigenvalues, using the standard classification of planar linear systems into nodes, saddles, foci, and centres.
Step 1 · Symmetric form
Write the equation as $$P(x,y)\,dx - Q(x,y)\,dy = 0,$$ with $$P(x,y)=y,\qquad Q(x,y)=x.$$
Step 2 · Locating the singular point
Set $P=0$ and $Q=0$ simultaneously: $$\begin{cases} y=0,\\ x=0. \end{cases}$$ The unique singular point is $$(x^*,y^*)=(0,0).$$
Step 3 · Associated linear autonomous system
Since $P$ and $Q$ are homogeneous of degree 1, write the equivalent planar system $$\frac{dx}{dt}=P(x,y)=y,\qquad \frac{dy}{dt}=Q(x,y)=x,$$ with coefficient matrix $$A=\begin{pmatrix}0&1\\1&0\end{pmatrix}.$$
Step 4 · Eigenvalues of $A$
The characteristic equation is $$\det(A-\lambda I)=0 \implies (-\lambda)(-\lambda)-1=0 \implies \lambda^2-1=0 \implies (\lambda-1)(\lambda+1)=0.$$ Thus $$\lambda_1=-1,\qquad \lambda_2=1.$$
Step 5 · Classification of the singular point
The two eigenvalues are real, distinct, and of opposite sign: $$\lambda_1=-1<0<\lambda_2=1.$$ By the standard classification of linear autonomous systems, the origin is a saddle point.
Step 6 · Eigenvectors and separatrices
For $\lambda_1=-1$: $$(A+I)\mathbf{v}=0 \implies \begin{pmatrix}1&1\\1&1\end{pmatrix}\mathbf{v}=0.$$ Both rows give $v_1+v_2=0$, so $$\mathbf{v}^{(1)}=\begin{pmatrix}1\\-1\end{pmatrix}.$$ The stable separatrix is tangent at the origin to the line $\ell_1:\; y=-x$. For $\lambda_2=1$: $$(A-I)\mathbf{v}=0 \implies \begin{pmatrix}-1&1\\1&-1\end{pmatrix}\mathbf{v}=0.$$ Both rows give $v_1=v_2$, so $$\mathbf{v}^{(2)}=\begin{pmatrix}1\\1\end{pmatrix}.$$ The unstable separatrix is tangent at the origin to the line $\ell_2:\; y=x$.
Step 7 · Exact solution of the scalar ODE
The original equation $y'=y/x$ is separable. Separating variables: $$\frac{dy}{y}=\frac{dx}{x} \implies \ln|y|=\ln|x|+C \implies y=Kx,\quad K\in\mathbb{R}\setminus\{0\}.$$ The general solution consists of all straight lines through the origin: $y=Kx$, $K\in\mathbb{R}$. Every such line passes through the singular point $(0,0)$.
Step 8 · Verification of separatrices
Setting $K=-1$ gives $\ell_1:\,y=-x$, with slope $y/x=-1$: \checkmark. Setting $K=1$ gives $\ell_2:\,y=x$, with slope $y/x=1$: \checkmark. Both separatrices are exact straight-line solutions of the scalar ODE, consistent with the system analysis.
Step 9 · Nature of the singular point — degenerate case
While the eigenvalue analysis of the associated system classifies the origin as a saddle, the scalar ODE $y'=y/x$ presents a degenerate situation: its general solution $y=Kx$ is a one-parameter family of straight lines all passing through the origin. Every line through the origin is an integral curve, and uniqueness of solutions fails there because $y/x$ is homogeneous of degree zero. The singular point $(0,0)$ is an improper node (also called a stellar or isotropic node) of the scalar ODE, despite the saddle classification of the symmetrised system.
Step 10 · Conclusion
$$\boxed{ (x^*,y^*)=(0,0)\text{ is the unique singular point.} }$$ The general solution $y=Kx$ is a family of lines through the origin. Every integral curve passes through the singular point, and uniqueness of the initial-value problem fails there. The eigenvalues of the associated linear system are $\lambda_{1,2}=\pm1$ (real, opposite sign), giving a saddle for the system; however, for the scalar ODE the origin behaves as an improper (stellar) node through which every direction is a solution trajectory.
Summary Table
| Quantity | Value |
|---|---|
| Eigenvalues | $\det(A-\lambda I)=0 \implies (-\lambda)(-\lambda)-1=0 \implies \lambda^2-1=0 \implies (\lambda-1)(\lambda+1)=0.$ |
| Classification | — |
Additional Notes
- The classification follows from the standard theory of planar linear (or linearised) autonomous systems, based on the sign and nature of the eigenvalues of the coefficient/Jacobian matrix.
Result
The final classification is: