IB Mathematics: Analysis & Approaches HL · 鼎睿学苑

Unit E5: Differential
Equations
单元 E5:微分方程

A differential equation is an equation whose unknown is a function and which involves that function together with one or more of its derivatives. E5 covers the AHL-only toolkit for first-order DEs: verify a candidate solution, separate variables, multiply by an integrating factor, march numerically with Euler's method, read a slope field, and model the standard applications (growth, decay, Newton's law of cooling).微分方程是以函数为未知量、并把该函数与其若干阶导数联系起来的方程。E5 涵盖 AHL 专属的一阶微分方程工具集:验证候选解、分离变量、乘以积分因子、用欧拉法数值推进、读懂斜率场,以及标准建模应用(增长、衰减、牛顿冷却律)。

IB AA HL · AHL 5.17 Papers 1 · 2 · 3 HL HL only · 6 sectionsHL 专属 · 共 6 节

How to use this guide本指南使用说明

Differential equations are AHL-only territory. The IB Paper 3 exploration regularly opens with a DE that has to be classified (separable or linear), solved by hand for a particular initial condition, and then either compared against an Euler approximation or interpreted as a real-world model. Each section of E5 isolates one of those steps.微分方程是 AHL 专属内容。IB Paper 3 的探究题常以一个微分方程开篇:先分类(可分离或线性),用初始条件手解出特定解,再与欧拉近似比较或解读为实际模型。E5 各节分别聚焦其中一步。

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If you are cramming如果你在临阵磨枪

Memorise two recipes. Separable: if $\tfrac{dy}{dx} = f(x) g(y)$, rearrange to $\tfrac{dy}{g(y)} = f(x) \, dx$ and integrate both sides. Linear: if $\tfrac{dy}{dx} + P(x) y = Q(x)$, the integrating factor is $\mu = e^{\int P \, dx}$ and $\tfrac{d}{dx}(\mu y) = \mu Q$. Do one worked problem of each end to end.

背两个套路。可分离:若 $\tfrac{dy}{dx} = f(x) g(y)$,整理为 $\tfrac{dy}{g(y)} = f(x) \, dx$ 两边积分。线性:若 $\tfrac{dy}{dx} + P(x) y = Q(x)$,积分因子 $\mu = e^{\int P \, dx}$ 且 $\tfrac{d}{dx}(\mu y) = \mu Q$。每类完整做一道例题。

If you are going for a 7如果你目标是 7 分

Cleanly separate general solution (one arbitrary constant) from particular solution (constant fixed by an initial condition). Run Euler's method by hand for at least two steps and recognise that smaller step size $h$ improves accuracy but multiplies arithmetic. For applications, derive the cooling and logistic models from first principles instead of citing them.

把通解(含一个任意常数)与特解(由初始条件确定常数)严格区分。手算欧拉法至少两步,并理解步长 $h$ 越小精度越高、但运算量增加。应用题中由第一性原理推导冷却与逻辑斯蒂模型,不要直接背公式。

HL flagHL 标记说明 Every section of E5 is HL content (AHL 5.17). SL students do not see differential equations at all.E5 全部章节均为 HL 内容(AHL 5.17)。SL 学生完全不接触微分方程。

What is a Differential Equation何谓微分方程 HL AHL 5.17

The vocabulary set.
  • A differential equation (DE) is an equation involving an unknown function $y(x)$ together with one or more of its derivatives.
  • The order of a DE is the order of the highest derivative that appears. First-order means only $\tfrac{dy}{dx}$ shows up.
  • To solve a DE is to find an explicit formula $y = $ (expression in $x$), or an implicit relation $F(x, y) = 0$, that satisfies the equation.
  • The general solution contains one arbitrary constant (for a first-order DE). A particular solution is the general solution with that constant fixed by an initial condition, such as $y(0) = 1$.
  • To verify a candidate $y(x)$, substitute it into both sides of the DE and check that the two sides agree as functions of $x$.
术语表。
  • 微分方程(DE)是把未知函数 $y(x)$ 与其若干阶导数联系起来的方程。
  • 阶数是方程中所出现的最高阶导数的阶数。一阶表示只出现 $\tfrac{dy}{dx}$。
  • 微分方程即求得显式 $y = $($x$ 的表达式)或隐式关系 $F(x, y) = 0$ 满足该方程。
  • 通解含一个任意常数(一阶 DE)。特解是用初始条件(如 $y(0) = 1$)把通解中常数确定后的解。
  • 验证候选解 $y(x)$:代入方程两边,检查作为 $x$ 的函数是否相等。
Worked Example E5.1 (verify a solution)E5.1 例题(验证解)

Verify that $y = e^{x}$ is a solution of the differential equation $\tfrac{dy}{dx} = y$.验证 $y = e^{x}$ 是微分方程 $\tfrac{dy}{dx} = y$ 的解。

Differentiate the candidate. $\tfrac{dy}{dx} = \tfrac{d}{dx}(e^{x}) = e^{x}$.

对候选解求导。$\tfrac{dy}{dx} = \tfrac{d}{dx}(e^{x}) = e^{x}$。

Compare with the right-hand side. The DE says $\tfrac{dy}{dx} = y$. Substituting the candidate, $y = e^{x}$, so the right-hand side is $e^{x}$.

与右边比较。方程为 $\tfrac{dy}{dx} = y$。把候选解 $y = e^{x}$ 代入,右边为 $e^{x}$。

Conclusion. Left-hand side $e^{x}$ equals right-hand side $e^{x}$ for every $x$. Therefore $y = e^{x}$ satisfies the DE.

结论。左右两边对所有 $x$ 均为 $e^{x}$。故 $y = e^{x}$ 满足该方程。

Remark. $y = e^{x}$ is one particular solution. The general solution is $y = A e^{x}$ for any constant $A$, because differentiating $A e^{x}$ still gives $A e^{x}$. An initial condition such as $y(0) = 1$ would fix $A = 1$ and recover the candidate above.

注记。$y = e^{x}$ 只是一个特解。通解为 $y = A e^{x}$($A$ 为任意常数),因为 $A e^{x}$ 的导数仍为 $A e^{x}$。初始条件 $y(0) = 1$ 可确定 $A = 1$,恰好得到上述候选解。

Going deeper: why first-order DEs need exactly one constant深入:一阶 DE 为何只含一个常数

Integrating a first-order DE involves exactly one antiderivative step, and every antiderivative carries an additive constant of integration. Higher-order DEs require more antiderivative steps and pick up more constants: a second-order DE has a general solution with two arbitrary constants, and so on. In E5 we work with first-order equations only, so one initial condition is always enough to pin down a unique particular solution.

解一阶微分方程恰好做一次反求导(积分),每次反求导都带出一个积分常数。更高阶 DE 需要更多次反求导,从而引入更多任意常数:二阶 DE 的通解含两个任意常数,依此类推。E5 只处理一阶方程,所以一个初始条件总足以唯一确定特解。

Which of the following is a first-order differential equation?下列哪一个是一阶微分方程?
E5.1 · Q1
$y'' + y = 0$
$y = x^{2} + 3$
$\dfrac{dy}{dx} = x + y$
$\dfrac{d^{3} y}{dx^{3}} = 0$
The highest derivative in $\tfrac{dy}{dx} = x + y$ is $\tfrac{dy}{dx}$, which is first order. Option A is second order ($y''$). Option B is an algebraic equation with no derivative at all, so it is not a DE. Option D is third order.$\tfrac{dy}{dx} = x + y$ 中最高阶导数为 $\tfrac{dy}{dx}$,即一阶。选项 A 含 $y''$,为二阶;选项 B 不含导数,不是 DE;选项 D 为三阶。
Order equals the highest derivative present. Only $\tfrac{dy}{dx} = x + y$ has $\tfrac{dy}{dx}$ as its highest derivative.阶数即所出现的最高阶导数。只有 $\tfrac{dy}{dx} = x + y$ 的最高阶导数为 $\tfrac{dy}{dx}$。

Separable Variables分离变量法 HL AHL 5.17

The recipe. A first-order DE is separable if it can be written as $$ \frac{dy}{dx} \;=\; f(x) \, g(y). $$ Rearrange so all $y$ pieces sit on the left and all $x$ pieces on the right, then integrate both sides: $$ \int \frac{dy}{g(y)} \;=\; \int f(x) \, dx. $$ Add a single arbitrary constant $C$ (on either side; conventionally on the right). Solve for $y$ if the algebra allows; otherwise leave the answer implicit. Apply the initial condition after integrating to fix $C$.

Three traps.
  • If $g(y) = 0$ at some value of $y$, that constant function is also a solution. Check whether dividing by $g(y)$ lost a solution.
  • $\int \tfrac{dy}{y} = \ln |y| + C$, not $\ln y + C$. The absolute value disappears only after exponentiating into $y = A e^{(\dots)}$ with $A$ a real constant that may be positive or negative.
  • Constants combine: $\ln |y| = h(x) + C$ becomes $|y| = e^{C} e^{h(x)}$, then $y = A e^{h(x)}$ with $A = \pm e^{C} \neq 0$ (the case $A = 0$ comes from the lost constant solution $y = 0$).
套路。一阶 DE 若可写成 $$ \frac{dy}{dx} \;=\; f(x) \, g(y), $$ 则称可分离。整理使所有 $y$ 项在左、所有 $x$ 项在右,再两边积分: $$ \int \frac{dy}{g(y)} \;=\; \int f(x) \, dx. $$ 只需一个任意常数 $C$(习惯写在右边)。能解出 $y$ 就解出,否则留作隐式解。初始条件须在积分之后代入以确定 $C$。

三个陷阱。
  • 若 $g(y) = 0$ 在某 $y$ 值成立,则该常值函数也是解。检查"除以 $g(y)$"是否丢解。
  • $\int \tfrac{dy}{y} = \ln |y| + C$,不是 $\ln y + C$。绝对值在指数化为 $y = A e^{(\dots)}$($A$ 可正可负)后才消失。
  • 常数合并:$\ln |y| = h(x) + C$ 变为 $|y| = e^{C} e^{h(x)}$,再写作 $y = A e^{h(x)}$,其中 $A = \pm e^{C} \ne 0$($A = 0$ 对应被丢掉的常值解 $y = 0$)。
Worked Example E5.2 (separable with initial condition)E5.2 例题(含初始条件)

Solve $\dfrac{dy}{dx} = x y$ subject to $y(0) = 1$.求解 $\dfrac{dy}{dx} = x y$,初始条件 $y(0) = 1$。

Identify the form. Here $f(x) = x$ and $g(y) = y$, so the equation is separable.

识别形式。$f(x) = x$,$g(y) = y$,方程可分离。

Separate.

分离变量。

$$ \frac{dy}{y} \;=\; x \, dx. $$

Integrate both sides.

两边积分。

$$ \int \frac{dy}{y} \;=\; \int x \, dx \quad \Longrightarrow \quad \ln |y| \;=\; \frac{x^{2}}{2} + C. $$

Solve for $y$. Exponentiate both sides:

解出 $y$。两边取指数:

$$ |y| \;=\; e^{C} e^{x^{2}/2} \quad \Longrightarrow \quad y \;=\; A \, e^{x^{2}/2}, \qquad A = \pm e^{C}. $$

Apply the initial condition. $y(0) = 1$ gives $1 = A \cdot e^{0} = A$, so $A = 1$.

代入初始条件。$y(0) = 1$ 得 $1 = A \cdot e^{0} = A$,故 $A = 1$。

Particular solution.

特解。

$$ y \;=\; e^{x^{2}/2}. $$

Check. $\tfrac{dy}{dx} = e^{x^{2}/2} \cdot x = x y$, and $y(0) = e^{0} = 1$. Both sides match the original DE.

检验。$\tfrac{dy}{dx} = e^{x^{2}/2} \cdot x = x y$,且 $y(0) = e^{0} = 1$。与原方程一致。

Pitfall: lost constant solutions陷阱:丢失常值解 Dividing by $g(y)$ silently assumes $g(y) \neq 0$. For $\tfrac{dy}{dx} = x y$, the constant function $y = 0$ also satisfies the DE (both sides equal zero), but the form $y = A e^{x^{2}/2}$ recovers it only via the convention $A = 0$. Whenever you divide by an expression in $y$, write a brief note "($y = 0$ is also a solution)" before proceeding.用 $g(y)$ 除两边时隐含 $g(y) \ne 0$。对 $\tfrac{dy}{dx} = x y$,常值函数 $y = 0$ 也满足方程(两边均为零),但 $y = A e^{x^{2}/2}$ 仅当约定 $A = 0$ 时才覆盖该解。每次以 $y$ 表达式除两边前,先注明"($y = 0$ 亦为解)"。
The general solution of $\dfrac{dy}{dx} = \dfrac{x}{y}$ is:$\dfrac{dy}{dx} = \dfrac{x}{y}$ 的通解为:
E5.2 · Q1
$y = x + C$
$y^{2} = x^{2} + C$
$y = C e^{x}$
$y = \dfrac{x^{2}}{2} + C$
Separate: $y \, dy = x \, dx$. Integrate: $\tfrac{y^{2}}{2} = \tfrac{x^{2}}{2} + C_{1}$, so $y^{2} = x^{2} + C$ (absorbing $2 C_{1}$ into a new constant $C$).分离:$y \, dy = x \, dx$。积分:$\tfrac{y^{2}}{2} = \tfrac{x^{2}}{2} + C_{1}$,故 $y^{2} = x^{2} + C$(把 $2 C_{1}$ 并入新常数 $C$)。
Multiply both sides by $y$ to get $y \, dy = x \, dx$, then integrate to obtain $\tfrac{y^{2}}{2} = \tfrac{x^{2}}{2} + C_{1}$ or equivalently $y^{2} = x^{2} + C$.两边乘 $y$ 得 $y \, dy = x \, dx$,积分得 $\tfrac{y^{2}}{2} = \tfrac{x^{2}}{2} + C_{1}$,即 $y^{2} = x^{2} + C$。

Integrating Factor for Linear First-Order Equations线性一阶方程的积分因子 HL AHL 5.17

The standard form. A first-order DE is linear if it can be written $$ \frac{dy}{dx} + P(x) \, y \;=\; Q(x). $$ Here $y$ appears to the first power, $\tfrac{dy}{dx}$ appears to the first power, and there are no products of $y$ with $\tfrac{dy}{dx}$.

The integrating factor. $$ \mu(x) \;=\; \exp\Bigl( \int P(x) \, dx \Bigr). $$ Multiplying the standard form by $\mu(x)$ collapses the left-hand side into a product-rule derivative: $$ \frac{d}{dx} \bigl( \mu(x) \, y \bigr) \;=\; \mu(x) \, Q(x). $$ Integrate both sides with respect to $x$ and divide by $\mu(x)$ to recover $y$.

Three-line workflow. Identify $P, Q$. Compute $\mu = e^{\int P \, dx}$ (no $+ C$ needed inside the exponent, since any constant just rescales $\mu$). Write $\mu y = \int \mu Q \, dx + C$ and solve for $y$.
标准形式。一阶 DE 若可写为 $$ \frac{dy}{dx} + P(x) \, y \;=\; Q(x), $$ 则称线性。此处 $y$ 与 $\tfrac{dy}{dx}$ 均为一次幂,且不含两者的乘积。

积分因子。 $$ \mu(x) \;=\; \exp\Bigl( \int P(x) \, dx \Bigr). $$ 标准形式两边乘 $\mu(x)$ 后,左边化为乘积法则的导数: $$ \frac{d}{dx} \bigl( \mu(x) \, y \bigr) \;=\; \mu(x) \, Q(x). $$ 对 $x$ 积分两边、再除以 $\mu(x)$ 即得 $y$。

三行流程。识别 $P, Q$;算 $\mu = e^{\int P \, dx}$(指数内不必加 $+ C$,常数只缩放 $\mu$);写 $\mu y = \int \mu Q \, dx + C$ 并解出 $y$。
Worked Example E5.3 (integrating factor)E5.3 例题(积分因子)

Solve $\dfrac{dy}{dx} + 2 x y = 4 x$.求解 $\dfrac{dy}{dx} + 2 x y = 4 x$。

Identify $P$ and $Q$. $P(x) = 2 x$ and $Q(x) = 4 x$.

识别 $P$ 与 $Q$。$P(x) = 2 x$,$Q(x) = 4 x$。

Compute the integrating factor.

算积分因子。

$$ \mu(x) \;=\; \exp\Bigl( \int 2 x \, dx \Bigr) \;=\; e^{x^{2}}. $$

Multiply through and recognise the product-rule derivative.

两边乘 $\mu$,识别乘积法则。

$$ e^{x^{2}} \frac{dy}{dx} + 2 x \, e^{x^{2}} y \;=\; 4 x \, e^{x^{2}} \quad \Longleftrightarrow \quad \frac{d}{dx}\bigl( e^{x^{2}} y \bigr) \;=\; 4 x \, e^{x^{2}}. $$

Integrate both sides. Substitute $u = x^{2}$, so $du = 2 x \, dx$ and $4 x \, dx = 2 \, du$:

两边积分。取 $u = x^{2}$,则 $du = 2 x \, dx$,$4 x \, dx = 2 \, du$:

$$ \int 4 x \, e^{x^{2}} \, dx \;=\; \int 2 \, e^{u} \, du \;=\; 2 \, e^{u} + C \;=\; 2 \, e^{x^{2}} + C. $$

Therefore

$$ e^{x^{2}} y \;=\; 2 \, e^{x^{2}} + C. $$

Solve for $y$. Divide by $e^{x^{2}}$:

解出 $y$。除以 $e^{x^{2}}$:

$$ y \;=\; 2 + C \, e^{-x^{2}}. $$

Check. $\tfrac{dy}{dx} = -2 C x \, e^{-x^{2}}$, and $2 x y = 4 x + 2 C x \, e^{-x^{2}}$. Adding gives $\tfrac{dy}{dx} + 2 x y = 4 x$, which is the original equation.

检验。$\tfrac{dy}{dx} = -2 C x \, e^{-x^{2}}$,$2 x y = 4 x + 2 C x \, e^{-x^{2}}$。相加得 $\tfrac{dy}{dx} + 2 x y = 4 x$,与原方程一致。

Going deeper: why the integrating factor works深入:积分因子为何奏效

We want a function $\mu(x)$ such that $\mu y' + \mu P y$ is the derivative of some product. The product rule gives $\tfrac{d}{dx}(\mu y) = \mu' y + \mu y'$. Matching coefficients on $y$ requires $\mu' = \mu P$, which is itself a separable DE for $\mu$. Solving $\tfrac{d \mu}{\mu} = P \, dx$ gives $\ln |\mu| = \int P \, dx$, hence $\mu = e^{\int P \, dx}$ (the absolute value and overall sign are absorbed because any non-zero scalar multiple of $\mu$ still works). By construction, multiplying the standard form by this $\mu$ makes the left-hand side an exact derivative.

我们希望找到 $\mu(x)$ 使 $\mu y' + \mu P y$ 能写成某乘积的导数。由乘积法则 $\tfrac{d}{dx}(\mu y) = \mu' y + \mu y'$,要让 $y$ 的系数对得上需 $\mu' = \mu P$,这本身是一个关于 $\mu$ 的可分离方程。解 $\tfrac{d \mu}{\mu} = P \, dx$ 得 $\ln |\mu| = \int P \, dx$,故 $\mu = e^{\int P \, dx}$(绝对值与正负号可吸收,因为 $\mu$ 的任一非零数乘仍可作积分因子)。如此构造下,标准形式乘 $\mu$ 后左边恰为某函数的导数。

The integrating factor for $\dfrac{dy}{dx} + \dfrac{1}{x} y = x$ (with $x > 0$) is:$\dfrac{dy}{dx} + \dfrac{1}{x} y = x$($x > 0$)的积分因子为:
E5.3 · Q1
$e^{x}$
$\dfrac{1}{x}$
$x$
$\ln x$
$P(x) = \tfrac{1}{x}$, so $\int P \, dx = \ln x$ (for $x > 0$) and $\mu = e^{\ln x} = x$.$P(x) = \tfrac{1}{x}$,故 $\int P \, dx = \ln x$($x > 0$),$\mu = e^{\ln x} = x$。
Read $P(x) = \tfrac{1}{x}$ from the standard form, integrate to get $\ln x$, then exponentiate: $\mu = e^{\ln x} = x$.由标准形式读出 $P(x) = \tfrac{1}{x}$,积分得 $\ln x$,再指数化:$\mu = e^{\ln x} = x$。

Euler's Method (Numerical)欧拉法(数值方法) HL AHL 5.17

Setup. Given a first-order initial-value problem $$ \frac{dy}{dx} \;=\; f(x, y), \qquad y(x_{0}) \;=\; y_{0}, $$ Euler's method advances the approximation by a fixed step size $h$ using the linear tangent at the current point: $$ x_{n + 1} \;=\; x_{n} + h, \qquad y_{n + 1} \;=\; y_{n} + h \cdot f(x_{n}, y_{n}). $$ Interpretation. $y_{n + 1}$ is read off the tangent line at $(x_{n}, y_{n})$ after stepping $h$ units in $x$. The method is a polygonal approximation to the true solution curve.

Error behaviour. Halving $h$ roughly halves the total error (Euler is first-order accurate). The trade-off is twice the arithmetic. For exam problems with two or three steps, hand computation is expected; show every $f(x_{n}, y_{n})$ value.
设置。给定一阶初值问题 $$ \frac{dy}{dx} \;=\; f(x, y), \qquad y(x_{0}) \;=\; y_{0}, $$ 欧拉法按固定步长 $h$ 用当前点的切线推进: $$ x_{n + 1} \;=\; x_{n} + h, \qquad y_{n + 1} \;=\; y_{n} + h \cdot f(x_{n}, y_{n}). $$ 几何意义。$y_{n + 1}$ 是过 $(x_{n}, y_{n})$ 的切线沿 $x$ 推进 $h$ 后的纵坐标。整条折线即为对真实解曲线的多边形近似。

误差行为。$h$ 减半,总误差大致减半(欧拉法为一阶精度),但运算量翻倍。考题通常只要走两三步,要求手算;每个 $f(x_{n}, y_{n})$ 必须写出。
Worked Example E5.4 (Euler with two steps)E5.4 例题(欧拉两步)

Use Euler's method with step size $h = 0.1$ to approximate $y(0.2)$ for the initial-value problem $\dfrac{dy}{dx} = x + y$, $y(0) = 1$.用步长 $h = 0.1$ 的欧拉法近似初值问题 $\dfrac{dy}{dx} = x + y$、$y(0) = 1$ 的 $y(0.2)$。

Setup. $f(x, y) = x + y$. Start at $(x_{0}, y_{0}) = (0, 1)$.

设置。$f(x, y) = x + y$。起点 $(x_{0}, y_{0}) = (0, 1)$。

Step 1: advance to $x_{1} = 0.1$.

第 1 步:推进到 $x_{1} = 0.1$。

$$ f(x_{0}, y_{0}) \;=\; 0 + 1 \;=\; 1, \qquad y_{1} \;=\; y_{0} + h \cdot f(x_{0}, y_{0}) \;=\; 1 + 0.1 \cdot 1 \;=\; 1.1. $$

Step 2: advance to $x_{2} = 0.2$.

第 2 步:推进到 $x_{2} = 0.2$。

$$ f(x_{1}, y_{1}) \;=\; 0.1 + 1.1 \;=\; 1.2, \qquad y_{2} \;=\; y_{1} + h \cdot f(x_{1}, y_{1}) \;=\; 1.1 + 0.1 \cdot 1.2 \;=\; 1.22. $$

Approximation. $y(0.2) \approx 1.22$.

近似值。$y(0.2) \approx 1.22$。

Remark. The exact solution to this initial-value problem is $y(x) = 2 e^{x} - x - 1$, giving $y(0.2) = 2 e^{0.2} - 1.2 \approx 1.2428$. The Euler estimate $1.22$ is low by about $0.023$. Halving $h$ to $0.05$ (four steps instead of two) would roughly halve that error.

注记。本题的精确解为 $y(x) = 2 e^{x} - x - 1$,故 $y(0.2) = 2 e^{0.2} - 1.2 \approx 1.2428$。欧拉估计 $1.22$ 偏小约 $0.023$。$h$ 减半到 $0.05$(改为四步)可大致把误差减半。

Table layout earns marks表格排版能拿分 For multi-step Euler problems in exams, set up a table with columns $n, x_{n}, y_{n}, f(x_{n}, y_{n}), h \cdot f(x_{n}, y_{n}), y_{n + 1}$ and fill row by row. Markers look for systematic arithmetic. A single number with no working earns no method marks even if the answer is correct.考试中多步欧拉题,建议列表:$n, x_{n}, y_{n}, f(x_{n}, y_{n}), h \cdot f(x_{n}, y_{n}), y_{n + 1}$,逐行填写。阅卷重视系统化运算;只写一个数字而无过程,即使答对也不给方法分。
Apply Euler's method with $h = 0.5$ to $\dfrac{dy}{dx} = y$, $y(0) = 1$. Approximate $y(0.5)$.对 $\dfrac{dy}{dx} = y$、$y(0) = 1$ 用步长 $h = 0.5$ 的欧拉法。近似 $y(0.5)$。
E5.4 · Q1
$1.0$
$1.5$
$e^{0.5} \approx 1.649$
$2.0$
One step: $y_{1} = y_{0} + h \cdot f(x_{0}, y_{0}) = 1 + 0.5 \cdot 1 = 1.5$. The exact value is $e^{0.5} \approx 1.649$, so Euler underestimates by about $0.149$; that gap shrinks as $h$ shrinks.一步:$y_{1} = y_{0} + h \cdot f(x_{0}, y_{0}) = 1 + 0.5 \cdot 1 = 1.5$。精确值 $e^{0.5} \approx 1.649$,欧拉偏小约 $0.149$;$h$ 减小该差距收缩。
One step of Euler: $y_{1} = 1 + 0.5 \cdot f(0, 1) = 1 + 0.5 \cdot 1 = 1.5$. The exact solution $e^{0.5}$ is the limit as $h \to 0$, not the Euler value at $h = 0.5$.欧拉一步:$y_{1} = 1 + 0.5 \cdot f(0, 1) = 1 + 0.5 \cdot 1 = 1.5$。精确解 $e^{0.5}$ 是 $h \to 0$ 的极限,不是 $h = 0.5$ 的欧拉值。

Slope (Direction) Fields斜率场(方向场) HL AHL 5.17

What a slope field is. For the DE $\tfrac{dy}{dx} = f(x, y)$, at each grid point $(x, y)$ draw a short line segment whose slope equals $f(x, y)$. The collection of segments is the slope field (also called the direction field). A solution curve through any starting point follows the local slope at every step, so the curve must be tangent to the segments it passes through.

Reading a slope field.
  • Horizontal segments ($f = 0$) mark equilibrium or turning behaviour. Constant solutions $y = c$ live where $f(x, c) = 0$ for all $x$.
  • Steep upward segments ($f$ large positive) indicate fast growth; steep downward ($f$ large negative) indicate fast decay.
  • If $f(x, y)$ depends only on $y$ (the DE is autonomous), all segments at the same $y$-level have the same slope: the field is invariant under horizontal shifts.
Why use it. The slope field gives the qualitative behaviour of every solution without solving algebraically. Useful when the DE is not separable, not linear, or simply too messy to integrate.
斜率场是什么。对方程 $\tfrac{dy}{dx} = f(x, y)$,在每个格点 $(x, y)$ 画一段短线段,斜率为 $f(x, y)$。这些线段的集合称为斜率场(或方向场)。过任一起点的解曲线必处处沿当地斜率,故曲线在所经过的每段线段处都与之相切。

读图要点。
  • 水平线段($f = 0$)标记平衡极值。常值解 $y = c$ 出现在 $f(x, c) = 0$ 对所有 $x$ 成立处。
  • 陡峭向上线段($f$ 大正)表示快速增长;陡峭向下($f$ 大负)表示快速衰减。
  • 若 $f(x, y)$ 只依赖 $y$(自治方程),同一 $y$ 高度上所有线段斜率相同:斜率场在水平方向平移不变。
用途。无须解析求解即可获得所有解的定性行为。当方程不可分离、不线性、或难以积分时尤其有用。
Worked Example E5.5 (read a slope field)E5.5 例题(读斜率场)

For the DE $\dfrac{dy}{dx} = y - x$, compute the slope at the grid points $(0, 0)$, $(0, 1)$, $(1, 0)$, $(1, 1)$, $(2, 1)$, and describe how a solution curve passing through $(0, 1)$ behaves locally.对方程 $\dfrac{dy}{dx} = y - x$,在格点 $(0, 0)$、$(0, 1)$、$(1, 0)$、$(1, 1)$、$(2, 1)$ 求斜率,并描述过 $(0, 1)$ 的解曲线在局部的行为。

Tabulate slopes. Slope at $(x, y)$ equals $y - x$.

列表算斜率。$(x, y)$ 处的斜率为 $y - x$。

$(x, y)$$(0, 0)$$(0, 1)$$(1, 0)$$(1, 1)$$(2, 1)$
Slope $f(x, y)$$0$$1$$-1$$0$$-1$

Equilibrium line. Slope is zero whenever $y = x$. The line $y = x$ is a locus of horizontal segments. (It is not itself a solution: if $y = x$, then $\tfrac{dy}{dx} = 1$, not $0$. The line is the boundary between regions of increasing and decreasing slope.)

零斜率线。$y = x$ 时斜率为 $0$。直线 $y = x$ 是水平线段的轨迹。(它本身不是解:$y = x$ 给 $\tfrac{dy}{dx} = 1 \ne 0$。该直线只是增减分界。)

Behaviour through $(0, 1)$. At $(0, 1)$ the slope is $+1$, so the solution starts heading up-right at $45^{\circ}$. Just past $x = 1$ the curve approaches the line $y = x$ from above; once it dips below $y = x$, the slope turns negative and the curve begins to fall.

过 $(0, 1)$ 的局部行为。$(0, 1)$ 处斜率 $+1$,解曲线以 $45^{\circ}$ 向右上方出发。$x$ 越过 $1$ 后,曲线从上方接近直线 $y = x$;一旦跌落至 $y = x$ 之下,斜率变负,曲线开始下降。

Going deeper: matching a solution to a slope field深入:将解与斜率场匹配

A common exam task shows three or four candidate slope-field diagrams and asks which one corresponds to a given DE. The drill is: pick two or three test points where the DE is easy to evaluate (often along the axes), compute the slope, and check which diagram has matching segments. Look first at where the slope is zero (horizontal segments): that is the fastest discriminator between candidate fields.

常见题型给出三四张候选斜率场图,问哪一张对应给定方程。做法:选两三个易代入的测试点(通常在坐标轴上)计算斜率,再核对哪张图的线段方向相符。最先看的应是零斜率位置(水平线段),它是最快区分候选图的特征。

For $\dfrac{dy}{dx} = y$, the slope of the slope-field segment at the point $(3, 2)$ is:$\dfrac{dy}{dx} = y$ 的斜率场在 $(3, 2)$ 处线段的斜率为:
E5.5 · Q1
$3$
$5$
$2$
$0$
Slope is $f(x, y) = y$, evaluated at the grid point. Here $y = 2$, so the slope is $2$. The $x$-coordinate does not enter because the DE is autonomous.斜率为 $f(x, y) = y$,在格点处求值。$y = 2$,故斜率为 $2$。$x$ 坐标不参与(方程为自治)。
The slope-field value is simply $f(x, y)$ at the grid point. For $\tfrac{dy}{dx} = y$, slope equals $y$ alone, so at $(3, 2)$ the slope is $2$.斜率场的值就是 $f(x, y)$ 在格点处的值。对 $\tfrac{dy}{dx} = y$,斜率即 $y$,故 $(3, 2)$ 处为 $2$。

Applications: Growth, Decay, Cooling应用:增长、衰减、冷却 HL AHL 5.17

Three canonical models.
  • Exponential growth or decay. $\tfrac{dy}{dt} = k y$ with $k$ constant. Separable. Solution $y(t) = y_{0} e^{k t}$. Positive $k$ gives growth; negative $k$ gives decay.
  • Newton's law of cooling. $\tfrac{dT}{dt} = -k (T - T_{\text{env}})$ with $k > 0$ and $T_{\text{env}}$ the ambient temperature. Separable after the substitution $u = T - T_{\text{env}}$. Solution $T(t) = T_{\text{env}} + (T_{0} - T_{\text{env}}) e^{-k t}$.
  • Logistic growth. $\tfrac{dP}{dt} = k P (M - P)$ with $M > 0$ the carrying capacity. Separable; the $P$-side needs partial fractions. Solution $P(t) = \dfrac{M}{1 + B e^{-k M t}}$ for some constant $B$ fixed by the initial condition.
The recurring trick. Newton's law and the logistic equation both yield to a clean substitution that turns the right-hand side into something straightforwardly separable. For Newton's law, set $u = T - T_{\text{env}}$. For logistic, use partial fractions on $\tfrac{1}{P(M - P)} = \tfrac{1}{M} \bigl( \tfrac{1}{P} + \tfrac{1}{M - P} \bigr)$.
三个经典模型。
  • 指数增长或衰减。$\tfrac{dy}{dt} = k y$($k$ 为常数)。可分离。解 $y(t) = y_{0} e^{k t}$。$k > 0$ 增长,$k < 0$ 衰减。
  • 牛顿冷却律。$\tfrac{dT}{dt} = -k (T - T_{\text{env}})$($k > 0$,$T_{\text{env}}$ 为环境温度)。换元 $u = T - T_{\text{env}}$ 后可分离。解 $T(t) = T_{\text{env}} + (T_{0} - T_{\text{env}}) e^{-k t}$。
  • 逻辑斯蒂增长。$\tfrac{dP}{dt} = k P (M - P)$($M > 0$ 为环境容量)。可分离;$P$ 一侧需部分分式。解 $P(t) = \dfrac{M}{1 + B e^{-k M t}}$,$B$ 由初始条件确定。
反复用到的技巧。牛顿冷却与逻辑斯蒂方程都靠一次干净的换元,把右边化为容易分离的形式。牛顿冷却取 $u = T - T_{\text{env}}$;逻辑斯蒂对 $\tfrac{1}{P(M - P)} = \tfrac{1}{M} \bigl( \tfrac{1}{P} + \tfrac{1}{M - P} \bigr)$ 做部分分式。
Worked Example E5.6 (Newton's law of cooling)E5.6 例题(牛顿冷却律)

A cup of coffee at $T(0) = 95 \, ^{\circ}\text{C}$ sits in a room at constant temperature $T_{\text{env}} = 22 \, ^{\circ}\text{C}$. It cools according to Newton's law $\tfrac{dT}{dt} = -k (T - T_{\text{env}})$. Find an explicit formula for $T(t)$ in terms of $k$ and $t$.一杯咖啡 $T(0) = 95 \, ^{\circ}\text{C}$ 放在恒温 $T_{\text{env}} = 22 \, ^{\circ}\text{C}$ 的房间中,按牛顿冷却律 $\tfrac{dT}{dt} = -k (T - T_{\text{env}})$ 散热。求 $T(t)$ 关于 $k$ 与 $t$ 的显式表达。

Substitute $u = T - 22$. Then $\tfrac{du}{dt} = \tfrac{dT}{dt}$, and the DE becomes

换元 $u = T - 22$。则 $\tfrac{du}{dt} = \tfrac{dT}{dt}$,方程化为

$$ \frac{du}{dt} \;=\; -k \, u. $$

Solve the reduced DE. Separate: $\tfrac{du}{u} = -k \, dt$. Integrate: $\ln |u| = -k t + C_{1}$, so $u = A e^{-k t}$ with $A$ a real constant.

解化简后的方程。分离:$\tfrac{du}{u} = -k \, dt$。积分:$\ln |u| = -k t + C_{1}$,故 $u = A e^{-k t}$,$A$ 为实常数。

Translate back. $T = u + 22 = 22 + A e^{-k t}$.

换回原变量。$T = u + 22 = 22 + A e^{-k t}$。

Apply the initial condition. $T(0) = 95$ gives $95 = 22 + A$, so $A = 73$.

代入初始条件。$T(0) = 95$ 得 $95 = 22 + A$,故 $A = 73$。

Final formula.

最终公式。

$$ T(t) \;=\; 22 + 73 \, e^{-k t}. $$

Sanity checks. At $t = 0$, $T(0) = 22 + 73 = 95$. As $t \to \infty$, $T(t) \to 22$, the ambient temperature. Both consistent with the physical setup.

合理性检查。$t = 0$ 时 $T(0) = 22 + 73 = 95$。$t \to \infty$ 时 $T(t) \to 22$,即环境温度。物理意义一致。

Going deeper: deriving the logistic solution深入:推导逻辑斯蒂方程的解

Starting from $\tfrac{dP}{dt} = k P (M - P)$, separate: $$ \frac{dP}{P (M - P)} \;=\; k \, dt. $$ Decompose by partial fractions: $\tfrac{1}{P (M - P)} = \tfrac{1}{M} \bigl( \tfrac{1}{P} + \tfrac{1}{M - P} \bigr)$. Integrate both sides: $$ \frac{1}{M} \bigl( \ln |P| - \ln |M - P| \bigr) \;=\; k t + C_{1} \quad \Longrightarrow \quad \ln \Bigl| \frac{P}{M - P} \Bigr| \;=\; k M t + C_{2}. $$ Exponentiate: $\tfrac{P}{M - P} = D e^{k M t}$. Solve for $P$: $$ P \;=\; (M - P) D e^{k M t} \quad \Longrightarrow \quad P \bigl( 1 + D e^{k M t} \bigr) \;=\; M D e^{k M t} \quad \Longrightarrow \quad P \;=\; \frac{M}{1 + B e^{-k M t}}, $$ where $B = 1 / D$. As $t \to \infty$, $P \to M$, recovering the carrying-capacity behaviour.

由 $\tfrac{dP}{dt} = k P (M - P)$ 出发,分离: $$ \frac{dP}{P (M - P)} \;=\; k \, dt. $$ 部分分式:$\tfrac{1}{P (M - P)} = \tfrac{1}{M} \bigl( \tfrac{1}{P} + \tfrac{1}{M - P} \bigr)$。两边积分: $$ \frac{1}{M} \bigl( \ln |P| - \ln |M - P| \bigr) \;=\; k t + C_{1} \quad \Longrightarrow \quad \ln \Bigl| \frac{P}{M - P} \Bigr| \;=\; k M t + C_{2}. $$ 取指数:$\tfrac{P}{M - P} = D e^{k M t}$。解出 $P$: $$ P \;=\; (M - P) D e^{k M t} \quad \Longrightarrow \quad P \bigl( 1 + D e^{k M t} \bigr) \;=\; M D e^{k M t} \quad \Longrightarrow \quad P \;=\; \frac{M}{1 + B e^{-k M t}}, $$ 其中 $B = 1 / D$。$t \to \infty$ 时 $P \to M$,复现环境容量行为。

A radioactive sample of mass $m(t)$ decays at a rate proportional to its mass: $\dfrac{dm}{dt} = -k m$ with $k > 0$. If $m(0) = m_{0}$, then $m(t)$ equals:放射性样品 $m(t)$ 按 $\dfrac{dm}{dt} = -k m$($k > 0$)衰减。若 $m(0) = m_{0}$,则 $m(t)$ 等于:
E5.6 · Q1
$m_{0} e^{-k t}$
$m_{0} e^{k t}$
$m_{0} (1 - k t)$
$m_{0} - k t$
Separable: $\tfrac{dm}{m} = -k \, dt$, so $\ln |m| = -k t + C$, hence $m = A e^{-k t}$. Initial condition $m(0) = m_{0}$ gives $A = m_{0}$, so $m(t) = m_{0} e^{-k t}$.可分离:$\tfrac{dm}{m} = -k \, dt$,故 $\ln |m| = -k t + C$,即 $m = A e^{-k t}$。$m(0) = m_{0}$ 给 $A = m_{0}$,故 $m(t) = m_{0} e^{-k t}$。
This is the canonical exponential decay model. Separate to $\tfrac{dm}{m} = -k \, dt$, integrate, and apply $m(0) = m_{0}$ to obtain $m(t) = m_{0} e^{-k t}$. The negative exponent encodes decay.这是经典指数衰减模型。分离为 $\tfrac{dm}{m} = -k \, dt$,积分,再代 $m(0) = m_{0}$ 得 $m(t) = m_{0} e^{-k t}$。负指数即代表衰减。

Exam Strategy and Common Pitfalls考试策略与常见陷阱

Classify before solving (Paper 1 / Paper 2 / Paper 3)先分类再求解(Paper 1 / 2 / 3)
  • Test for separability first. If $\tfrac{dy}{dx}$ factors as $f(x) g(y)$, separation is the cleanest route. Worth checking even when the DE is also linear, because separation usually beats integrating factor for marks per minute.
  • 先测可分离性。若 $\tfrac{dy}{dx}$ 能分解为 $f(x) g(y)$,分离法最干净。即便方程也是线性的,仍值得先试分离,因为通常分离法单位时间得分更高。
  • If not separable, try the linear form. Reshape into $\tfrac{dy}{dx} + P(x) y = Q(x)$ and read off $P, Q$. The integrating factor $\mu = e^{\int P \, dx}$ then unlocks the equation.
  • 若不可分离,尝试线性形式。整理为 $\tfrac{dy}{dx} + P(x) y = Q(x)$ 后读出 $P, Q$。积分因子 $\mu = e^{\int P \, dx}$ 即可破题。
Constants of integration (every paper)积分常数(各 Paper 通用)
  • Write $+ C$ explicitly. Omitting the constant is a guaranteed mark loss. Show it appearing on the first integration step and then solve for it after the initial condition.
  • $+ C$ 必须显式写出。漏写常数必扣分。在第一步积分时就写出,再由初始条件解出。
  • Combine constants by renaming. $e^{C_{1}}$ becomes a new constant $A$; do not carry chains of $C_{1}, C_{2}, C_{3}$ through the algebra. One symbol per final constant is cleaner.
  • 合并常数时重命名。$e^{C_{1}}$ 重命名为新常数 $A$;不要把 $C_{1}, C_{2}, C_{3}$ 链条带到最后。一个最终常数对应一个符号更清晰。
  • For separable DEs, $\int \tfrac{dy}{y}$ is $\ln |y|$. Drop the absolute value only after exponentiating into $y = A e^{(\dots)}$ where $A$ ranges over all real numbers.
  • 分离法中 $\int \tfrac{dy}{y}$ 写作 $\ln |y|$。取指数化为 $y = A e^{(\dots)}$($A$ 可正可负可零)后才能去掉绝对值。
Euler and slope fields (Paper 3 HL)欧拉法与斜率场(Paper 3 HL)
  • For Euler, tabulate. Columns $n, x_{n}, y_{n}, f(x_{n}, y_{n}), h \cdot f, y_{n + 1}$. Every cell scores. Pure numerical answers lose method marks.
  • 欧拉法务必列表。列 $n, x_{n}, y_{n}, f(x_{n}, y_{n}), h \cdot f, y_{n + 1}$。每格都计分;只写数字会丢方法分。
  • Compare Euler to the exact solution when possible. Showing that $y_{\text{Euler}}$ undershoots or overshoots, and explaining the link to the concavity of the exact curve, earns commentary marks.
  • 有可能时把欧拉值与精确解比较。说明 $y_{\text{Euler}}$ 偏低或偏高,并用精确解的凹凸性解释,可拿评注分。
  • For slope-field questions, start at the zeros. Where $f(x, y) = 0$ marks horizontal segments, which is the fastest way to identify or rule out a candidate diagram.
  • 斜率场题先看零点。$f(x, y) = 0$ 处是水平线段,是辨识或排除候选图最快的特征。

Flashcards闪卡

0 / 12 flipped已翻 0 / 12
Order of a DE?微分方程的阶数?
The order of the highest derivative present.所出现的最高阶导数的阶数。
General vs particular solution?通解与特解?
General has an arbitrary constant; particular fixes it via an initial condition.通解含任意常数;特解由初始条件确定常数。
Separable form?可分离形式?
$$\frac{dy}{dx} = f(x) \, g(y)$$
Separable recipe?分离法的核心式?
$$\int \frac{dy}{g(y)} = \int f(x) \, dx + C$$
Linear first-order standard form?线性一阶标准形式?
$$\frac{dy}{dx} + P(x) \, y = Q(x)$$
Integrating factor formula?积分因子公式?
$$\mu(x) = e^{\int P(x) \, dx}$$
What does $\mu$ achieve?乘 $\mu$ 后左边变成?
$$\frac{d}{dx}(\mu \, y) = \mu \, Q$$
Euler step formula?欧拉法步进公式?
$$y_{n + 1} = y_{n} + h \cdot f(x_{n}, y_{n})$$
Slope-field segment slope at $(x, y)$?斜率场在 $(x, y)$ 处的斜率?
Equals $f(x, y)$, the right-hand side of $\tfrac{dy}{dx} = f(x, y)$.等于方程 $\tfrac{dy}{dx} = f(x, y)$ 的右边 $f(x, y)$。
Exponential model solution?指数模型的解?
$$\frac{dy}{dt} = k y \;\Rightarrow\; y = y_{0} e^{k t}$$
Newton's law of cooling?牛顿冷却律?
$$\frac{dT}{dt} = -k (T - T_{\text{env}})$$
Logistic equation?逻辑斯蒂方程?
$$\frac{dP}{dt} = k P (M - P)$$

Unit E5 Practice Quiz单元 E5 练习测验

The general solution of $\dfrac{dy}{dx} = 3 y$ is:$\dfrac{dy}{dx} = 3 y$ 的通解为:
Q1
$y = 3 x + C$
$y = A e^{3 x}$
$y = e^{3 x} + C$
$y = \tfrac{3}{2} x^{2} + C$
Separable: $\tfrac{dy}{y} = 3 \, dx$, so $\ln |y| = 3 x + C_{1}$, hence $y = A e^{3 x}$ with $A = \pm e^{C_{1}}$. The constant $A$ is real and may be zero (recovering $y = 0$ as a solution).可分离:$\tfrac{dy}{y} = 3 \, dx$,故 $\ln |y| = 3 x + C_{1}$,即 $y = A e^{3 x}$,$A = \pm e^{C_{1}}$。$A$ 为实数,可取 $0$(覆盖 $y = 0$ 这个解)。
This is exponential growth: the rate equals a constant times the value. Separate, integrate $\tfrac{dy}{y}$ to get $\ln |y|$, exponentiate to recover $y = A e^{3 x}$.这是指数增长:变化率为常数乘函数值。分离、对 $\tfrac{dy}{y}$ 积分得 $\ln |y|$,再取指数得 $y = A e^{3 x}$。
Solve $\dfrac{dy}{dx} + y = e^{x}$ using an integrating factor. The general solution is:用积分因子法解 $\dfrac{dy}{dx} + y = e^{x}$。通解为:
Q2
$y = e^{x} + C$
$y = \tfrac{1}{2} e^{x} + C e^{x}$
$y = \tfrac{1}{2} e^{x} + C e^{-x}$
$y = e^{2 x} + C e^{-x}$
$P(x) = 1$, so $\mu = e^{x}$. Multiplying: $\tfrac{d}{dx}(e^{x} y) = e^{x} \cdot e^{x} = e^{2 x}$. Integrating: $e^{x} y = \tfrac{1}{2} e^{2 x} + C$, hence $y = \tfrac{1}{2} e^{x} + C e^{-x}$.$P(x) = 1$,$\mu = e^{x}$。两边乘 $\mu$:$\tfrac{d}{dx}(e^{x} y) = e^{x} \cdot e^{x} = e^{2 x}$。积分:$e^{x} y = \tfrac{1}{2} e^{2 x} + C$,故 $y = \tfrac{1}{2} e^{x} + C e^{-x}$。
Standard form has $P = 1$, $Q = e^{x}$. $\mu = e^{x}$. $\tfrac{d}{dx}(e^{x} y) = e^{2 x}$, integrate to $e^{x} y = \tfrac{1}{2} e^{2 x} + C$, divide by $e^{x}$ to get $y = \tfrac{1}{2} e^{x} + C e^{-x}$.标准形式中 $P = 1$、$Q = e^{x}$,$\mu = e^{x}$。$\tfrac{d}{dx}(e^{x} y) = e^{2 x}$,积分得 $e^{x} y = \tfrac{1}{2} e^{2 x} + C$,除以 $e^{x}$ 得 $y = \tfrac{1}{2} e^{x} + C e^{-x}$。
Apply Euler's method with $h = 0.1$ to $\dfrac{dy}{dx} = x y$, $y(0) = 1$. The approximation for $y(0.2)$ is closest to:对 $\dfrac{dy}{dx} = x y$、$y(0) = 1$ 用步长 $h = 0.1$ 的欧拉法。$y(0.2)$ 的近似值最接近:
Q3
$1.00$
$1.02$
$1.01$
$1.05$
Step 1: $f(0, 1) = 0$, so $y_{1} = 1 + 0.1 \cdot 0 = 1$. Step 2: $f(0.1, 1) = 0.1 \cdot 1 = 0.1$, so $y_{2} = 1 + 0.1 \cdot 0.1 = 1.01$. Therefore $y(0.2) \approx 1.01$.第 1 步:$f(0, 1) = 0$,$y_{1} = 1 + 0.1 \cdot 0 = 1$。第 2 步:$f(0.1, 1) = 0.1 \cdot 1 = 0.1$,$y_{2} = 1 + 0.1 \cdot 0.1 = 1.01$。故 $y(0.2) \approx 1.01$。
First step gives $y_{1} = 1$ because $f(0, 1) = 0$. Second step gives $y_{2} = 1 + 0.1 \cdot 0.1 = 1.01$. The exact solution is $e^{x^{2}/2}$, so $y(0.2) = e^{0.02} \approx 1.0202$.第 1 步因 $f(0, 1) = 0$ 得 $y_{1} = 1$。第 2 步得 $y_{2} = 1 + 0.1 \cdot 0.1 = 1.01$。精确解为 $e^{x^{2}/2}$,$y(0.2) = e^{0.02} \approx 1.0202$。
A bacterial culture grows so that $\dfrac{dN}{dt} = 0.5 \, N$, where $N$ is the population at time $t$ (hours). If $N(0) = 100$, then $N(4)$ equals:细菌培养满足 $\dfrac{dN}{dt} = 0.5 \, N$($t$ 单位为小时)。若 $N(0) = 100$,则 $N(4)$ 等于:
Q4
$100 \, e^{0.5}$
$100 \, e^{2}$
$400$
$200$
Exponential growth: $N(t) = N_{0} e^{k t} = 100 \, e^{0.5 t}$. At $t = 4$: $N(4) = 100 \, e^{2} \approx 739$.指数增长:$N(t) = N_{0} e^{k t} = 100 \, e^{0.5 t}$。$t = 4$:$N(4) = 100 \, e^{2} \approx 739$。
Solve the separable DE to get $N(t) = N_{0} e^{k t} = 100 \, e^{0.5 t}$. Substitute $t = 4$: exponent is $2$, so $N(4) = 100 \, e^{2}$.解可分离方程得 $N(t) = N_{0} e^{k t} = 100 \, e^{0.5 t}$。代 $t = 4$:指数为 $2$,故 $N(4) = 100 \, e^{2}$。
A liquid at $80 \, ^{\circ}\text{C}$ cools in a room at $20 \, ^{\circ}\text{C}$ according to Newton's law of cooling. After ten minutes its temperature is $50 \, ^{\circ}\text{C}$. The model $T(t) = 20 + A e^{-k t}$ requires:液体由 $80 \, ^{\circ}\text{C}$ 在 $20 \, ^{\circ}\text{C}$ 房间中按牛顿冷却律降温。十分钟后温度为 $50 \, ^{\circ}\text{C}$。模型 $T(t) = 20 + A e^{-k t}$ 要求:
Q5
$A = 60$ and $e^{-10 k} = \tfrac{1}{2}$
$A = 80$ and $e^{-10 k} = \tfrac{1}{2}$
$A = 60$ and $k = \tfrac{1}{2}$
$A = 30$ and $k = 0$
From $T(0) = 80$: $80 = 20 + A$, so $A = 60$. From $T(10) = 50$: $50 = 20 + 60 e^{-10 k}$, so $30 = 60 e^{-10 k}$, hence $e^{-10 k} = \tfrac{1}{2}$ (which gives $k = \tfrac{\ln 2}{10}$).由 $T(0) = 80$:$80 = 20 + A$,故 $A = 60$。由 $T(10) = 50$:$50 = 20 + 60 e^{-10 k}$,$30 = 60 e^{-10 k}$,故 $e^{-10 k} = \tfrac{1}{2}$(即 $k = \tfrac{\ln 2}{10}$)。
Use $T(0) = 80$ to find $A$: $80 = 20 + A \Rightarrow A = 60$. Then $T(10) = 50$ gives $e^{-10 k} = \tfrac{1}{2}$.由 $T(0) = 80$ 求 $A$:$80 = 20 + A \Rightarrow A = 60$。再由 $T(10) = 50$ 得 $e^{-10 k} = \tfrac{1}{2}$。

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