1015SCG
Lecture 8
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Enrico Fermi (1901-1954) was an Italian physicist known for his major contributions to nuclear physics, quantum theory, and statistical mechanics.
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The Fermi Paradox asks why, given the vast size of the universe and the likelihood of extraterrestrial life, we have not yet observed any clear evidence of it.
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Fermi problems are estimation questions that use rough assumptions and simple calculations to obtain approximate answers.
An example is Enrico Fermi's estimate of the strength of the atomic bomb that detonated at the Trinity test, based on the distance traveled by pieces of paper he dropped from his hand during the blast. Fermi's estimate of 10 kilotons of TNT was well within an order of magnitude of the now-accepted value of 21 kilotons.
$AM = \bar{x} =\dfrac{1}{n}\ds \sum_{i=1}^{n}x_i$
Average of $n$ numbers $x_i$
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$\bar{x} =\dfrac{0.81+0.9+0.94+0.85+0.88}{5}$ $\quad =0.876 \text{ m}$ |
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$GM = \ds \left(\prod_{i=1}^{n} x_i\right)^{1/n}$
Multiplicative average of $n$ positive numbers $x_i$
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$GM = \left(0.81 \times 0.9 \times 0.94 \times 0.85 \times 0.88\right)^{1/5}$ $\;\;\;\quad \approx 0.875 \text{ m}$ |
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How to estimate unknown values?
What is the volume of a toilet cistern (the tank where water is stored)?
Underestimate: 1L
Underestimate: 50L
$GM = \sqrt{1\text{ L} \times 50 \text{ L}}$ $\approx 7 \text{ L}$
Underestimate: 25L
$GM = \sqrt{1\text{ L} \times 25 \text{ L}}$ $\approx 5 \text{ L}$
How many people in the world are sleeping at the moment?
Assume people sleep fro 6h a day.
Fraction of the time sleeping: \(\dfrac{6\text{ h}}{24\text{ h}}\) \(=\dfrac{1}{4}\)
Amount sleeping = Number of people $\times$ fraction sleeping $\qquad$
$\qquad\qquad$\(\approx\) 8 billion people $\times \dfrac{1}{4} $ \(\approx\) 2 billion people
A number is in normalized scientific notation if it is in the form \[ \large \pm r \times 10^n \]
It is easy to compare numbers! 😃
Example:
How many orders of magnitude there is between 2 mL and 80 L?
\(\dfrac{80 \text{ L}}{2 \text{ mL}}\) \(=\dfrac{80 \text{ L}}{2 \text{ mL}} \times \dfrac{1000 \text{ mL}}{1 \text{ L}}\) \(=\dfrac{80\,000 }{2 }\) \(=40\, 000\) \(=4\times 10^4\)
There are about 4 orders of magnitude between 2 mL and 80 L
It is easy to find the geometric mean
\(\sqrt{10^a \times 10^b}\) \(=\sqrt{10^{a+b}}\) \(=10^{\frac{a+b}{2}}\)
Example:
Find the geometric mean of $40000$ and $0.00006$.
\(\sqrt{4\times 10^4 \times 6\times 10^{-5}}\) \(=\sqrt{24\times 10^{-1}}\) \(=\sqrt{2.4}\) \(\approx 1.5\)
Find the geometric mean of $10,000,000$ and $0.004$.
\(\sqrt{10^7\times 4\times ^{-3}}\) \(=\sqrt{4\times 10^4 }\) \(=\sqrt{4}\sqrt{ 10^{4}}\) \(=2\times 10^{4/2}\) \(=2\times 10^2\) \(=200\)
How much toilet paper do we use in Australia each year?
We are looking for $\dfrac{\text{rolls}}{\text{year}}$
How many times a person visits the toilet?
Underestimate: $\;1 \dfrac{\text{visit}}{\text{day}}$
Overestimate: $\;25 \dfrac{\text{visit}}{\text{day}}$
$N_t = \sqrt{25}$ $=5$
How much toilet paper do we use in Australia each year?
We are looking for $\dfrac{\text{rolls}}{\text{year}}$
What is the amount used each visit?
Underestimate: $\;1 \dfrac{\text{sheet}}{\text{visit}}$
Overestimate: $\;20 \dfrac{\text{sheet}}{\text{visit}}$
$N_p = \sqrt{20}$ $\approx 4.47$ $\approx 4$
How much toilet paper do we use in Australia each year?
Thus we have $\;N_t =5 \dfrac{\text{visit}}{\text{day}}\;$ and $\;N_p = 4 \dfrac{\text{sheet}}{\text{visit}}$
How many sheets of toilet paper does a person use in a year?
$N_t \times N_p \times \dfrac{365.25\text{ days}}{\text{year}}$
$5 \dfrac{\text{visit}}{\text{day}} \times 4 \dfrac{\text{sheet}}{\text{visit}} \times \dfrac{365.25\text{ days}}{\text{year}}$ $=7305\dfrac{\text{sheets}}{\text{year}}$
How much toilet paper do we use in Australia each year?
$5 \dfrac{\text{visit}}{\text{day}} \times 4 \dfrac{\text{sheet}}{\text{visit}} \times \dfrac{365.25\text{ days}}{\text{year}}$ $=7305\dfrac{\text{sheets}}{\text{year}}$
🧻 Assume: $\;200 \dfrac{\text{sheets}}{\text{roll}}$
Then we have $\;\dfrac{7305\dfrac{\text{sheets}}{\text{year}}}{200 \dfrac{\text{sheets}}{\text{roll}}}$ $\approx 37 \dfrac{\text{rolls}}{\text{year}}$ per person
Population of Australia $\approx 28$ million $=2.8\times 10^7$
How much toilet paper do we use in Australia each year?
Population of Australia $\approx 28$ million $=2.8\times 10^7$
👉$\;\; 37 \dfrac{\text{rolls}}{\text{year}}$ per person
Therefore $\;37 \dfrac{\text{rolls}}{\text{year}}\times 2.8\times 10^7 $ $\approx 10^9 \dfrac{\text{rolls}}{\text{year}}$
How much air would you breathe in a year?
Try it yourself! 📝 😃
Any function $f(x)$ can be rewritten as an infinite sum \[f(x)= a_0 + a_1 x + a_2x^2 + a_3x^3+\cdots a_nx^n + \cdots\]
Example:
\(e^x \) \(= 1 +x + \dfrac{x^2}{2!}+ \dfrac{x^3}{3!} + \cdots + \dfrac{x^n}{n!}+ \cdots\)
where $n! = 1 \times 2 \times 3 \times \cdots \times (n-1) \times n.$
Truncating the Taylor series at second order gives useful approximations:
| Function | 2nd-order Taylor approx. |
| $e^x$ | $1 + x + \dfrac{x^2}{2}$ |
| $(1+x)^n$ | $1 + nx + \dfrac{n(n-1)}{2}x^2$ |
| $\ln(1+x)$ | $x - \dfrac{x^2}{2}$ |
| $\sin x$ | $x$ |
| $\cos x$ | $1 - \dfrac{x^2}{2}$ |
| $\tan x$ | $x$ |
These approximations are valid when $|x| \ll 1$.
\( \ds e^x = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + \cdots \)
| Approximation order | Expression | Estimate for $x=0.05$ |
| First order | $1 + x$ | $1 + 0.05$$\,=1.05$ |
| Second order | $1 + x + \dfrac{x^2}{2}$ | $1 + 0.05 + \dfrac{(0.05)^2}{2}$$\,=1.05125$ |
| Third order | $1 + x + \dfrac{x^2}{2} + \dfrac{x^3}{6}$ | $1.05125 + \dfrac{(0.05)^3}{6} \approx 1.05127$ |
| Calculator | $e^{0.05}$ | $\approx 1.051271096376024\ldots$ |
Higher-order approximations give better accuracy for small $x$.
\( \ds \cos x = \; \large ??? \)
| Approximation order | Expression | Estimate for $x=0.1$ |
| First order | ||
| Second order | ||
| Third order | ||
| Calculator |
Odd-power terms vanish for $\cos x$, so first- and third-order approximations coincide.
\( \ds \cos x = 1 - \frac{x^2}{2!} + \frac{x^4}{4!} - \cdots \)
| Approximation order | Expression | Estimate for $x=0.1$ |
| First order | $1$ | $1$ |
| Second order | $1 - \dfrac{x^2}{2}$ | $1 - \dfrac{(0.1)^2}{2} = 0.995$ |
| Third order | $1 - \dfrac{x^2}{2}$ | $0.995$ |
| Calculator | Exact value | $\cos(0.1) \approx 0.995004165\ldots$ |
Odd-power terms vanish for $\cos x$, so first- and third-order approximations coincide.
The population of the bacteria in the sample is given by \[ \large P(t) = 500 e^{0.001t} \] where $t$ is given in weeks.
Consider a second order approximation of $e^t$.
Using a second-order Taylor approximation for \( e^t\): \( \ds \;e^x \approx 1 + x + \frac{x^2}{2}. \)
That's all for today!See you in Week 9!
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