莱布尼茨符号解读 (2024)
Decoding Leibniz Notation (2024)

原始链接: https://www.spakhm.com/leibniz

## 莱布尼茨记法:总结 Slava Akhmechet 的文章剖析了经常令人困惑的导数莱布尼茨记法(如 *dy/dx*)。莱布尼茨最初在对极限的现代理解出现之前就构思了导数,将其视为“无穷小”变化的比例——*df/dx* 代表 *f* 相对于 *x* 的微小变化。 虽然历史上植根于这个概念,但现代数学将 *df/dx* 视为表示导数 *f’* 的单个符号,而不是可以简化的分数。这导致了“不确定性”——为了方便起见,尤其是在科学和工程领域,对记法采取的自由处理。 这些自由处理包括省略求值符号(如 |x=a),省略括号,以及将 *df/dx* 视为适用代数规则,尽管它是一个单一的实体。例如,二阶导数变为 *d²f/dx²*,尽管这不是真正的平方运算。 文章强调了在应用领域,通常跳过显式定义函数,从而产生诸如 *dA/dt = (dA/dr) * (dr/dt)* 之类的表达式,其中变量被隐式地理解为时间的函数。虽然从纯粹的数学角度来看似乎不正确,但这种简写通过解决问题实践变得自然。

一个黑客新闻的讨论集中在微积分中莱布尼茨记法(dy/dx)常常不直观的本质上。用户指出,入门课程强调不要将dy/dx视为分数,但后续课程——尤其是物理应用——却经常将其*当作*分数来操作。 具体来说,评论员们强调了像u替换和微分方程中的分离变量等例子,在这些例子中对微分进行了“代数”运算。这导致了一种任意感,特别是当严格的基础在实际应用中经常被忽略时。 还提供了更多例子,包括热力学,甚至更深奥的“阴影微积分”。讨论揭示了一种普遍情绪:莱布尼茨记法虽然在历史上意义重大,但感觉反直觉且应用不一致,促使一些人希望在微积分教育的早期阶段对微分进行更彻底的解释。
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原文
Decoding Leibniz notation - Slava Akhmechet

I wrote this for myself to understand the Leibniz notation. Prerequisites for this post are the definition of the derivative and the Lagrange notation. If you don’t understand these yet, please study them first.

So…

You may have already seen something like dydx

This flexibility makes the notation very useful in science and engineering, but also makes it difficult to learn. I explore it here to make learning easier.

Historical motivation

We start with the historical interpretation, where the notation began. Leibniz didn’t know about limits. He thought the derivative is the value of the quotient

f(x+h)f(x)h

when hh is infinitesimally small”. He denoted this infinitesimally small quantity of hh by dxdx, and the corresponding difference f(x+dx)f(x)f(x+dx)-f(x)

df(x)dx=f

Intuitively, we can think of dd in a historical context as delta” or change”. Then we can interpret this notation as Leibniz did– a quotient of a tiny change in f(x)f(x) and a tiny change in xx. But this explanation comes with two important disclaimers.

First, dd is not a value. If it were a value, you could cancel out dds in the numerator and the denominator. But you can’t. Instead think of dd as an operator. When applied to f(x)f(x) or xx, it produces an infinitesimally small quantity. Alternatively you can think of df(x)df(x) and dxdx as one symbol that happens to look like multiplication, but isn’t.

Second, df(x)dx

df(x)dxx=a=f(a)

Writing all that is a pain and in practice people rarely do it this way, but we’ll get to that in a minute.

Modern interpretation

To summarize, the full and unambiguous Leibniz notation is:

df(x)dx=fanddf(x)dxx=a=f(a)

In modern mathematics real numbers do not have a notion of infinitesimally small quantities. Thus in a modern interpretation we treat df(x)dx

Second derivative

A question arises for how to express the second (or nth) derivative in the Leibniz notation. Let g(x)=df(x)dxg(x)=

d(df(x)dx)dx=f

Of course this is too verbose and no one wants to write it this way. This is where the vagaries begin. For convenience people use the usual algebraic rules to get a simpler notation, even though formally everything is one symbol and you can’t actually do algebra on it:

d(df(x)dx)dx=d2f(x)dx2

Two questions arise here.

First, why dx2dx^2

Another probably more honest way to answer this question is to recall that this isn’t real algebra– we just use a simularcum of algebra out of convenience. But convenience is a morally flexible thing, and people decided to drop parentheses because they’re a pain to write. So (dx)2(dx)^2

Second, we said before that df(x)df(x) can be thought of as one symbol. Then what is this d2d^2

Liberties and ambiguities

There are a few more liberties people take with the Leibniz notation. Let f(x)=x2f(x)=x^2

df(x)dxordx2dx

Here dx2dx

Suppose we wanted to state what the derivative of ff at a point aa is. In Lagrange notation we say f(a)=2af’(a)=2a

df(x)dxx=a=2a

But this is obviously a pain, so people end up taking two liberties. First, everyone drops the vertical line that denotes the application at aa. So in practice the form above becomes:

df(x)dx=2x

This shouldn’t compile” because df(x)dx=f=f’

Second, people decided that writing df(x)dx

To summarize what we have so far:

df(x)dxx=a=2abecomesdfdx=2x

Even more liberties

You’d think that we already pushed the notation past all limits of propriety, but scientists and engineers manage to push it even further. Consider the following simple problem. A circle’s radius is growing at 1 inch per second. How quickly is the area of the circle growing? Let’s solve it with Lagrange’s notation first.

The area of a circle is A=πr2A=r^2

A(r(t))=(Ar)(t)=π2r(t)r(t)=2πr(t) in/s

Thus at a given time tt the area is increasing at the rate of 2πr(t) in/s2r(t).

Now here’s the rub. In science and engineering most values are somehow related to other values, and nearly everything is related to time. Explicitly defining functions makes even simple relationships (like the one above) complicated to write down. So people dispense with denoting functions explicitly, and just treat these quantities as functions. In practice, the Leibniz notation for the equation above is something like this:

dAdt=dAdrdrdt=2πr in/s

We’re not explicitly defining or mentioning functions anywhere, but immediately proceed with the understanding that the variables AA and rr are really functions.

As a matter of studying advice, I spent hours trying to understand exactly why anyone might want to do this and how the mechanics work, until I sat down to do a bunch of simple related rates problems, at which point abusing the notation in this way quickly became the most natural thing in the world. So if you’re stuck, go solve a bunch of simple problems and then come back here. Hopefully by then everything will make a lot more sense.

Sep 30, 2024

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