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On page 48 of [Zill2022], there is an initial-value problem (IVP): $$ \frac{dy}{dx}=xy^{1/2}, y(0)=0. \tag{1} $$ I try to solve this IVP by myself. My solution is as follows:

Solution: First, it is easily seen that $y = 0$ is a solution to (1). Second, separating variables gives $$ y^{-1/2} dy = x dx. \tag{2} $$ Integrating (2), we have $$ \int y^{-1/2} dy = \int x dx, \tag{3} $$ then $$ 2 y^{1/2} = \frac{x^2}{2} + c. \tag{4} $$ Applying the initial condition $y(0) = 0$, we obtain $c = 0$. Then $$ 2 y^{1/2} = \frac{x^2}{2} \tag{5} $$ which implies $$ y = \frac{x^4}{16}. \tag{6} $$ Therefore, IVP (1) has two solutions: $y=0$ and $y = \frac{x^4}{16}$. $\blacksquare$

I thought I had found all the solutions. But [Zill2022] says:

The initial-value problem (1) actually possesses many more solutions, since for any choice of the parameter $a \geq 0$ the piecewise-defined function $$ y = \begin{cases} 0, & x < a \\ \frac{1}{16} (x^2 - a^2)^2, & x \geq a \end{cases} \tag{7}$$ satisfies both the differential equation and the initial condition.

Thus, my question is:

Question: How to solve (1) to get the solution in (7)?

Any comments and answers are welcome. Thanks in advance.

Reference

[Zill2022] D. G. Zill, Advanced Engineering Mathematics, Seventh Edition, International Student Edition, Jones & Bartlett Learning, 2022.

Joako
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6 Answers6

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A simpler question that illustrates the same concept is $y'=y^{1/2},y(0)=0$. This has a "trivial solution" $y \equiv 0$ and a "separable solution" $y=\begin{cases} x^2/4 & x>0 \\ 0 & \text{otherwise} \end{cases}$. But this problem is autonomous, so there is nothing special about it starting to increase at $0$ instead of somewhere else. You can just run the trivial solution up to some $a \geq 0$ and then view that $a$ like how the separable solution views $0$, resulting in $y=\begin{cases} (x-a)^2/4 & x>a \\ 0 & \text{otherwise} \end{cases}$ for any $a \geq 0$.

Your problem is basically the same, except that it isn't autonomous, so the various separable solutions that start increasing at various different $a$'s are not simply translates of one another. Nevertheless the idea is the same: you can run the trivial solution up to whatever $a \geq 0$ you like and then follow the separable solution starting at that $a$.

Getting to avoid doing this kind of analysis is why we like having an existence/uniqueness theorem to lean on. Picard-Lindelof is the usual one, but it requires the equation to be of the form $y'=f(x,y)$ where $f$ is locally Lipschitz in $y$. Your equation fails this condition ($f$ becomes too sensitive to changes in $y$ near $y=0$), which means Picard-Lindelof makes no guarantees of uniqueness.

Ian
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  • Hi Ian, thanks again for your detailed explanation! I come from an electrical and communications engineering background, so I haven’t studied the Picard–Lindelöf theorem or the concept of locally Lipschitz functions before. While I appreciate the theoretical insights, I’m currently trying to understand the concrete steps that lead from equation (1) to equation (7). Would you mind walking me through the actual derivation? That would really help me connect the theory with the computation. – Wei-Cheng Liu Nov 01 '25 at 11:12
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    @Wei-ChengLiu There are not really concrete steps to be shown beyond what you already did. You see that $y \equiv 0$ is a solution; you have to check this because the derivation of the separable solution has a singularity unless $y$ starts increasing immediately. You compute the separable solutions to the same ODE started with $y(a)=0$ for any $a \geq 0$. Then you notice that you can glue $y \equiv 0$ to any of these separable solutions and get another solution to the original IVP. To finish proving that there are no other solutions besides these, you can arrange to invoke Picard-Lindelof. – Ian Nov 01 '25 at 12:57
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    @Wei-ChengLiu A tip for those with a bit less real analysis background for how to see this coming is to take $\frac{\partial f}{\partial y}$ where the equation is $y'=f(x,y)$. If that derivative blows up at some $(x,y)$ (both finite), then you may see non-uniqueness for solutions to the IVP that pass through that $(x,y)$. In your problem, the issue is basically the entire line $y=0$. But this is not a guarantee of non-uniqueness nor does it really give you a recipe for how to find all the solutions. – Ian Nov 01 '25 at 13:24
  • Thank you for your thoughtful comments, Ian. I really appreciate the insights — I’ll take some time to digest everything and reflect on it carefully. I’ve taken Real Analysis I and II, but I’m still working on connecting some of these ideas to differential equations and uniqueness results like Picard–Lindelöf. Your explanation is very helpful. – Wei-Cheng Liu Nov 01 '25 at 13:50
  • Hi Ian, I want to emphasize that equation (7) does not appear out of nowhere. Zill must have used some method to derive it from the initial-value problem (1), even though he did not include the derivation in his book. What I’m trying to understand is the process or technique Zill used to arrive at equation (7) from (1). – Wei-Cheng Liu Nov 03 '25 at 01:26
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    @Wei-ChengLiu Unless you want intuition, I'm really not sure what to tell you. It really is as simple as: let $y_a : [a,\infty) \to \mathbb{R}$ be the separable solution with $y_a(a)=0$, then notice that $y(x)=\begin{cases} 0 & x<a \ y_a(x) & x \geq a \end{cases}$ is a solution to the original IVP as long as $a \geq 0$. – Ian Nov 03 '25 at 16:24
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    @Wei-ChengLiu On the intuition side, you can look at it like this. If I just want the solution to be zero somewhere, I can imagine starting at $(-\infty,0)$ and advancing time. At each time, I can either decide to start increasing now or not; either way the differential equation is still satisfied at the time, because $y'$ is actually zero when these solutions start increasing. So now, if I want to satisfy some IVP with a zero condition, all I need to do is to start increasing at a later time, but it doesn't matter which later time. – Ian Nov 03 '25 at 16:30
  • To Ian: OK, I understand. Thank you for your intuition. – Wei-Cheng Liu Nov 04 '25 at 01:42
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By integration assuming either $y=0$ or $y\ne0$, the general solution is

$$y=c_0\text{ or }\sqrt y=\frac{x^2}4+c_1.$$

The second part requires $\dfrac{x^2}4+c_1\ge0$, or $x^2\ge-4c_1$.

So even if $y(0)=0$, a nonzero solution remains possible in the positive $x$, with some negative $c_1$.

Due to the singular nature of the equation, the nonzero solution does not depend on the initial condition.

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If $f(x,y)$ is Lipschitz with respect to $y$ in the interior of a domain $D\subset\mathbb{R}^{n+1}$, the solution of the ODE $$ y'=f(x,y),y(x_0)=y_0$$ for $(x_0,y_0)\in D$ is unique (see https://en.wikipedia.org/wiki/Picard%E2%80%93Lindel%C3%B6f_theorem). In your case, $f(x,y)=xy^\frac12$ is not Lipschitz near $(0,0)$ and hence it is not guaranteed that it has a unique solution.

Update: You already give two solutions $y\equiv0$ and $y=\frac1{16}x^2$. To seek other solutions, first solving the following IVP $$ y'=xy^\frac12, y(a)=0$$ for $a>0$ gives $y=\frac1{16}(x^2-a^2)^2$. Define the piecewise function $$y=\begin{cases} \frac1{16}(x^2-a^2)^2 & x>a, \\ 0 & \text{otherwise}. \end{cases}$$ It is easy to see that $y(0)=0$ and $$ \lim_{x\to a^-}y'(x)=\lim_{x\to a^+}y'(x)=0$$ which means that the piecewise function is differentiable. So the IVP has infinite many solutions.

xpaul
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    Picard-Lindelof is not a necessary+sufficient theorem, so your wording should be softened a little bit. – Ian Oct 31 '25 at 13:28
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    See the update. – xpaul Oct 31 '25 at 13:30
  • Hi xpaul, thanks for your response! I appreciate your effort in explaining the general behavior of the differential equation. However, I was specifically trying to understand how to solve the initial-value problem in (1) and arrive at the expression given in equation (7). I feel that part wasn't fully addressed in your answer. Could you possibly elaborate on the steps that lead from (1) to (7)? That would be really helpful! – Wei-Cheng Liu Nov 01 '25 at 11:08
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    @Wei-ChengLiu, see the update. – xpaul Nov 03 '25 at 19:11
  • Hi xpaul, thank you for sharing your solution — I appreciate the clarity of your steps. I was working through the same differential equation and noticed a potential discrepancy in the final expression for $y$. From my calculations, the correct form should be: $y=\frac{1}{16}(x^2-a^2)^2$ rather than $y=\frac{1}{16}(x^2-a^2)$. This comes from integrating the separable form carefully and squaring the result after solving for $y^{1/2}$. I might be missing something, so please let me know if there's a step I overlooked in your derivation. – Wei-Cheng Liu Nov 04 '25 at 01:49
  • Hi xpaul, thanks again for your detailed response. I was reviewing the piecewise function you proposed: $y(x)=(x-a)^2/4, x>a; 0, \text{otherwise}$. I tried plugging it back into the original differential equation, and the derivative doesn't quite match the right-hand side. I wonder if the correct form should be: $y(x)=(x-a)^4/16, x>a; 0, \text{otherwise}$. This way, $y^{1/2}=(x-a)^2/4$, and the derivative aligns with $xy^{1/2}$. Let me know what you think — I might be missing something subtle. – Wei-Cheng Liu Nov 04 '25 at 01:55
  • You are welcome. – Wei-Cheng Liu Nov 05 '25 at 07:57
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Square equation (4) to get:

$$4y = \frac{1}{4}x^4 + cx^2 + c^2$$ $$y = \frac{1}{16}\left(x^4 + 4cx^2 + 4c^2\right)$$ $$y = \frac{1}{16}\left(x^2 + 2c\right)^2$$

But since $c$ is an arbitrary constant, we can replace it with a different constant expression, so let $c = -\frac{a^2}{2}$.

$$y = \frac{1}{16}\left(x^2 - a^2\right)^2 \tag{1}$$

It can easily be shown that:

$$\frac{dy}{dx} = \frac{1}{4}x(x^2 - a^2)$$ $$xy^{1/2} = \frac{1}{4}x(x^2 - a^2)$$

And thus the differential equation $\frac{dy}{dx} = xy^{1/2}$ is satisfied. But, we haven't done anything with the initial value $y(0) = 0$. The “natural” thing to do is to just plug $x = 0$ and $y = 0$ into equation (1), giving: $0 = \frac{1}{16}\left(0-a^2\right)^2$, from which $a = 0$. This gives the solution $y = \frac{1}{16}x^4$, as you found.

But what if we “cheat” by just defining $y = 0$ on some interval near $x = 0$? Pick some $b > 0$ and let:

$$y(x) = \begin{cases} 0 & x < b \\ \frac{1}{16}(x^2 - a^2)^2 & x > b \end{cases}$$

Then this trivially satisfies the condition $y(0) = 0$. And both cases satisfy the differential equation (without the initial condition). All we need to do is ensure that the equation is still satisfied at $x = b$.

In order for $y$ to be differentiable at $x = b$, it must be continuous, so

$$0 = \frac{1}{16}(b^2 - a^2)^2$$ $$0 = \frac{1}{16}(b + a)^2(b - a)^2$$ $$b = \pm a$$

So, just choose $b = a$, giving:

$$y(x) = \begin{cases} 0 & x \le a \\ \frac{1}{16}(x^2 - a^2)^2 & x \ge a \end{cases}$$

And then $y'(a) = 0$, thus satisfying $\frac{dy}{dx}=xy^{1/2}$ with $0 = a\sqrt{0}$ at the point $(a, 0)$.

So that's how you get the solution in Zill's equation (7).

Yeah, it's contrary to the “normal” approach, but that's kind of the point. There's technically no constraint in the problem that $y$ can't be piecewise-defined, and $xy^{1/2}$ breaks the separable equation assumption of being Lipschitz near $y = 0$. Hence this “extra” class of solutions that you didn't consider.

Dan
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  • This is a brilliant and elegant approach! I really appreciate the creativity in how you handled the initial condition. Well done! – Wei-Cheng Liu Nov 05 '25 at 07:56
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Apparently $y\equiv 0$ is a solution to the IVP. If $y(x_0)\not=0$ (hence $y(x_0)>0$ due to the presence of $y^{1/2}$ in the ODE) for some $x_0>0$, then by differentiability hence continuity of $y$, $y$ is nonzero around $x_0$, then the derivation (2)-(4) are completely justified. And note that since $y'=xy^{1/2}\ge0$ for $x\ge 0$, $y$ is increasing, hence $y(x)>0$ for all $x\ge x_0$. This means that once (2)-(4) kicks in, they will always be valid.

This proves that the solution over the interval $[0, \infty)$ can be separated into two pieces, one is just constantly $0$ and the other is of the form (4). But their connection has to be continuous and this will give us (7), with an arbitrary separation point $a$. $^{[1]}$

The same argument works for $(-\infty, 0]$, so the more general solution is $$y=\begin{cases} \frac{1}{16}(x^2-b^2)^2 & x<-b \\ 0 & -b\le x \le a \\ \frac{1}{16}(x^2-a^2)^2 & x>a \end{cases}$$

where $a,b$ are non-negative and allowed to be $\infty$.

That said, these are examples that are designed to show IVPs doesn't necessarily have unique solutions without further constraints. They are not very relevant in applications (though a more knowledgeable person would almost certainly disagree). In reality, the zero solution is apparently very unstable hence coudln't last for long, i.e. ubiquitious random noise can easily push the system to evolve (diverge to infinity).


$^{[1]}$ To add a bit more details, multiply $2$ on both sides of (4), replace $2c$ by $c$, we have $4y^{1/2} = x^2+c$, and $y=\frac{1}{16}(x^2+c)^2$. Assume $a$ is the separation point between the zero solution and the above solution, then $$y(a)=\lim_{x\rightarrow a^-} y(x)=0$$ $$y(a)=\lim_{x\rightarrow a^+}y(x)=\lim_{x\rightarrow a^+}\frac{1}{16}(x^2+c)^2=\frac{1}{16}(a^2+c)^2$$ hence $$c=-a^2$$

Similar analysis can be done for $x\le 0$.

Just a user
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  • How do you get the solutions $y=\frac{1}{16}(x^2-b^2)^2$ for $x<-b$ and $y=\frac{1}{16}(x^2-a^2)$ for $x>a$? Moreover, according to (7), I think the correct solution for $x>a$ should be $y=\frac{1}{16}(x^2-a^2)^2$. – Wei-Cheng Liu Nov 03 '25 at 03:55
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    @Wei-ChengLiu I add more details in the answer on how to obtain the solution. And you're absolutely there was a typo, now fixed. – Just a user Nov 03 '25 at 05:39
  • Adding zero to zero is very stable numerically. If you do not add random noise explicitly, a numerical method for this IVP will not branch out from the zero solution. Now if you were to apply a non-linear coordinate transformation to the ODE, so that the zero solution would map to something curved, then numerical methods will indeed accumulate floating point noise and method errors that provide enough perturbation to branch away. – Lutz Lehmann Nov 03 '25 at 11:40
  • @LutzLehmann Thanks for the comment. However, of course, I'm not talking about numerical stability, but Lyapunov stability. – Just a user Nov 03 '25 at 14:54
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For intuition's sake, consider $x$ as a "time" variable and let's look at how the function changes as time increases from $0$. There are essentially two cases to consider:

  1. When $y=0$, then $\frac{dy}{dx}=0$. Hence, the function stays flat whenever it is on the $x$-axis.
  2. When $y>0$, then $\frac{dy}{dx}>0$ (when $x>0$), so the function must strictly increase.

We can now think about the problem as follows: at time $x=0$, the function is on the $x$-axis, so it stays flat. But it's also possible at some point in time the function curves up away from $0$ (while maintaining a derivative of $0$ at its last point on the $x$-axis, which works as long as the derivative is continuous). Once this happens, the derivative $\frac{dy}{dx}>0$, and the function continually increases.

When $y(x)\not\equiv 0$, we can set $x=a$ as our "last point" that lies on the $x$-axis (or technically speaking, the supremum of the $x$-values of all points that lie on the $x$-axis). Once the function goes past $a$, the differential equation becomes "nice"—that is, $xy^{1/2}$ comes Lipschitz continuous, so by Picard-Lindelöf, there is a unique solution now. Your work in steps (2)-(4) apply, so we can conclude that when the differential equation is bounded by $x>a$, there is a unique solution of the form $2y^{1/2}=\frac{x^2}{2}+c$ for some constant $c$. Since $y$ is positive, this can be rewritten as $y=\left(\frac{x^2}{4}+\frac{c}{2}\right)^2$.

But we also know that $y(x)$ must be continuous, so the right limit as $x$ approaches $a$ must be $0$. Hence, $\frac{a^2}{4}+\frac{c}{2}=0\implies c=-\frac{a^2}{2}$. So for $x\geq a$, we have $y=\frac{1}{16}(x^2-a^2)^2$. And in order for $y(a)=0$, all points before $a$ must also lie on the $x$-axis. Hence, this gives

$$y=\begin{cases}0 & \text{if } x<a\\ \frac{1}{16}(x^2-a^2)^2&\text{if }x\geq a\end{cases},$$

as one of the possible families of solutions to this differential equation, which Zill describes. Note that this solution assumes the differential equation is on the interval $[0,\infty)$. We can apply the same logic to the negative case to completely characterize all solutions.