Cauchy-Maclaurin Integral Test

Theorem (Cauchy-Maclaurin Integral Test)

Let f(x) be a continuous, positive, decreasing function on [1,\infty) in which f(n)=a_n. Then \sum_{n=1}^\infty a_n converges if \int_1^\infty f(x)dx is finite and diverges if the integral is infinite.

Proof. Using the left-end point method as seen in Figure 1

Figure 1. Integral Test

we see that a_1+a_2+\cdots+a_{n-1}\geq \int_1^nf(x)dx This means that if \int_1^{\infty}f(x)dx is infinite, \sum_{n=1}^\infty a_n diverges. Now using the right-end point method as seen in Figure 2

Figure 2. Integral Test

we see that a_2+a_3+\cdots+a_n\leq\int_1^n f(x)dx This means that if \int_1^\infty f(x)dx is finite, then \sum_{n=1}^\infty a_n converges. This completes the proof.

Example (The p-series).
For what values of p is the series \sum_{n=1}^\infty\frac{1}{n^p} convergent?

Solution. If p<0 then \lim_{n\to\infty}\frac{1}{n^p}=\infty. If p=0 then \lim_{n\to\infty}\frac{1}{n^p}=1. In either case, \lim_{n\to\infty}\frac{1}{n^p}\ne 0, so the series diverges. If p>0 then the function f(x)=\frac{1}{x^p} is continuous, positive and decreasing on [1,\infty).
Now,
\int_1^\infty\frac{1}{x^p}dx=\left\{\begin{array}{ccc} \left.\frac{x^{-p+1}}{-p+1}\right|_1^\infty & {\rm if} & p\ne 1,\\ \\ \ln x|_1^\infty & {\rm if} & p=1. \end{array}\right.
Therefore the series converges if p>1 and diverges if p\leq 1.

Example. Test the series \sum_{n=1}^\infty\frac{1}{n^2+1} for convergence or divergence.

Solution. f(x)=\frac{1}{x^2+1} is continuous, positive and decreasing on [1,\infty). \begin{align*}\int_1^\infty\frac{1}{x^2+1}dx&=\left.\arctan x\right|_1^\infty\\&=\arctan \infty-\arctan 1\\&=\frac{\pi}{4}\end{align*} Therefore, by the Integral Test the series converges.

Example. Determine whether \sum_{n=1}^\infty\frac{\ln n}{n} converges or diverges.

Solution. f(x)=\frac{\ln x}{x} is continuous, positive and decreasing on [3,\infty). (One can easily check f(x) is decreasing on (e,\infty) by its derivative f'(x).) \begin{align*}\int_3^\infty\frac{\ln x}{x}dx&=\frac{1}{2}\left.(\ln x)^2\right|_3^\infty\\&=\infty\end{align*} Therefore, \sum_{n=1}^\infty \frac{\ln n}{n} diverges.

Example. Use the integral test to show that the series \sum_{n=1}^\infty\frac{1}{a^{\ln x}} converges if a>e and diverges if 0<a\leq e.

Proof. Let f(x)=\frac{1}{a^{\ln x}}. Then f(x) is positive and continuous on (1,\infty). If 0<a<1 then the series \sum_{n=1}^\infty\frac{1}{a^{\ln n}} diverges because the sequence \left\{\frac{1}{a^{\ln n}}\right\} is increasing. If a=e, the series becomes the harmonic series \sum_{n=1}^\infty\frac{1}{n} which diverges. Now we assume that 1\leq a< e or a>e. Then f(x) is decreasing (1,\infty). \begin{align*}\int_1^\infty\frac{dx}{a^{\ln x}}&=\int_1^\infty a^{-\ln x}dx\\&=-\int_0^{-\infty}a^ue^{-u}du\ (u=-\ln x,\ dx=-xdu=-e^{-u}dx)\\&=\int_{-\infty}^0a^ue^{-u}du\end{align*} Let v=a^u and dw=e^{-u}du. Then dv=a^u\ln a du and w=-e^{-u}. The integration by parts formula \int vdw=vw-\int wdv results in \int a^ue^{-u}du=-a^ue^{-u}+\ln a\int e^{-u}a^udu+C’ Hence we find \int a^ue^{-u}du=\frac{a^ue^{-u}}{\ln a-1}+C \begin{align*}\int_1^\infty\frac{dx}{a^{\ln x}}&=\int_{-\infty}^0a^ue^{-u}du\\&=\left[\frac{a^ue^{-u}}{\ln a-1}\right]_{-\infty}^0\\&=\frac{1}{\ln a-1}\left\{1-\lim_{u\to -\infty}\frac{a^u}{e^u}\right\}\end{align*} While \frac{a^u}{e^u} is an indeterminate form of type \frac{\infty}{\infty}, the L’Hôpital’s Rule is not helpful for finding the limit \lim_{u\to -\infty}\frac{a^u}{e^u} as \frac{(a^u)’}{(e^u)’}=\frac{a^u\ln a}{e^u}. Instead let y=\frac{a^u}{e^u}. Then \ln y=u(\ln a-1). \lim_{u\to -\infty}\ln y=\left\{\begin{array}{ccc}-\infty & \mbox{if} & a>e\\\infty & \mbox{if} & a<e\end{array}\right. i.e. \lim_{u\to -\infty}\frac{a^u}{e^u}=\left\{\begin{array}{ccc}e^{-\infty}=0 & \mbox{if} & a>e\\e^{\infty}=\infty & \mbox{if} & a<e\end{array}\right. Therefore, \int_1^\infty\frac{dx}{a^{\ln x}}=\left\{\begin{array}{ccc}\frac{1}{\ln a-1}<\infty & \mbox{if} & a>e\\\infty & \mbox{if} & a<e\end{array}\right. This completes the proof.

Theorem (Remainder Estimate for the Integral Test)
If \sum_{n=1}^\infty a_n converges by the Integral Test and R_n=S-s_n, then
\begin{equation}\label{eq:remest}\int_{n+1}^\infty f(x)dx\leq R_n\leq\int_n^\infty f(x)dx\end{equation}

Proof. Using the left-end point method we obtain R_n=a_{n+1}+a_{n+2}+\cdots\geq\int_{n+1}^\infty f(x)dx as seen in Figure 3.

Figure 3. Remainder Estimate

Now using the right-end point method we obtain R_n=a_{n+1}+a_{n+2}+\cdots\leq\int_n^\infty f(x)dx as seen in Figure 4.

Figure 4. Remainder Estimate

Hence proves \eqref{eq:remest}.

Example.

  1. Approximate the sum of the series \sum_{n=1}^\infty\frac{1}{n^3} by using the sum of the first 10 terms. Estimate the error involved in this approximation.
  2. How many terms are required to ensure that the sum is accurate to within 0.0005?

Solution. First we calculate \int_n^\infty\frac{1}{x^3}dx=\frac{1}{2n^2}

  1. s_{10}=\frac{1}{1^3}+\frac{1}{2^3}+\cdots+\frac{1}{10^3}\approx 1.197532. By the remainder estimate \eqref{eq:remest} R_{10}\leq\int_{10}^\infty\frac{1}{x^3}dx=\frac{1}{200}=0.005 So the size of the error is at most 0.005.
  2. R_n\leq\int_n^\infty\frac{1}{x^3}dx=\frac{1}{2n^2}.  Suppose \frac{1}{2n^2}<0.0005. Then we find n>\sqrt{1000}\approx 31.6. This means we need 32 terms to guarantee accuracy to within 0.0005.

Corollary. \begin{equation}\label{eq:sumest}s_n+\int_{n+1}^\infty f(x)dx\leq s\leq s_n+\int_n^\infty f(x)dx\end{equation}

Proof. Add s_n to each side of the inequalities in \eqref{eq:remest}

Example. Use the inequality \eqref{eq:sumest} with n=10 to estimate the sum of the series \sum_{n=1}^\infty\frac{1}{n^3}.

Solution. Using \eqref{eq:sumest} for n=10 we have s_{10}+\int_{11}^\infty\frac{1}{x^3}dx\leq s\leq s_{10}+\int_{10}^\infty\frac{1}{x^3}dx i.e. s_{10}+\frac{1}{2(11)^2}\leq s\leq s_{10}+\frac{1}{2(10)^2} Hence we get 1.201664\leq s\leq 1.202532 We can approximate s by taking the midpoint of this interval (i.e. the average of the boundary points) which is s\approx 1.2021. The error is then at most half the length of the interval i.e. the error is smaller than 0.0005. Recall that we had to use 32 terms to make error smaller than 0.0005 in the previous example but in this example we needed only 10 terms. So we can obtain a much improved estimate using \eqref{eq:sumest} than using s_n.

Infinite Series

Definition. Let a_1,a_2,\cdots,a_n\cdots be any sequence of quantities. Then the symbol
\begin{equation} \label{eq:series} \sum_{n=1}^\infty a_n=a_1+a_2+\cdots+a_n+\cdots \end{equation}
is called an infinite series. Let
\begin{align*} s_1&=a_1,\\ s_2&=a_1+a_2,\\ s_3&=a_1+a_2+a_3,\\ \cdots\\ s_n&=a_1+a_2+a_3+\cdots+a_n,\\ \cdots \end{align*}
The numbers s_n is called the n-th partial sums of the series \eqref{eq:series}.

Definition. An infinite series \sum_{n=1}^\infty a_n is said to converge if the sequence of partial sums \{s_n\} converges i.e. \sum_{n=1}^\infty a_n=s<\infty means that for any \epsilon>0 there exists a positive integer N such that
|s_n-s|<\epsilon\ \mbox{for all}\ n\geq N A series which does not converge is said to diverge.

Remark. It should be noted that there is no unique way to define the sum of an infinite series. While the definition we use is the conventional one, there are other ways to define the sum of an infinite series. Some of the divergent series according to the conventional definition may converge with a different definition. Although it may seem outrageous it can be shown that 1+2+3+\cdots=-\frac{1}{12}. It was first proved by the genius Indian mathematician Srinivasa Ramanujan. If you have a Netflix account, you can watch a biographical movie about Ramanujan. The movie title is The Man Who Knew Infinity which is based on a biography by Robert Kanigel The Man Who Knew Infinity: A Life of the Genius Ramanujan. I find divergent series fascinating. In case you are interested, I wrote about divergent series in blog articles here and here.

Proposition. If \sum_{n=1}^\infty a_n converges, then \lim_{n\to\infty}a_n=0.

Note that the converse of the proposition is not necessarily true. See the example on harmonic series below. The proposition, more precisely its contrapositive

If \lim_{n\to\infty}a_n\ne 0, then \sum_{n=1}^\infty a_n diverges.

can be used as a divergence test for series. For example, the series \sum_{n=1}^\infty\frac{n}{n+1} diverges because \lim_{n\to\infty}\frac{n}{n+1}=1\ne 0.

Theorem (Cauchy’s Criterion for the Convergence of a Sequence).
A necessary and sufficient condition for the convergence of a sequence \{a_n\} is that for any \epsilon>0 there exists a positive integer N such that
|a_n-a_m|<\epsilon\ \mbox{for all}\ n,m\geq N.

Corollary (Cauchy’s Criterion for the Convergence of a Series).
A necessary and sufficient condition for the convergence of a series \sum_{n=1}^\infty u_n is that for any \epsilon>0 there exists a positive integer N such that
|s_n-s_m|<\epsilon\ \mbox{for all}\ n,m\geq N.

Example (The Geometric Series).
The geometric sequence, starting with a and ratio r, is given by
a, ar,ar^2,\cdots,ar^{n-1},\cdots.
The nth partial sum is given by
s_n=a\frac{1-r^n}{1-r}.
Taking the limit as n\to\infty,
\lim_{n\to\infty}s_n=\frac{a}{1-r}\ \mbox{for}\ -1<r<1.
Hence the infinite geometric series converges for -1<r<1 and is given by
\sum_{n=1}^\infty ar^{n-1}=\frac{a}{1-r}.
On the other hand, if r\leq -1 or r\geq 1 then the infinite series diverges. For example, the series \frac{1}{2}+\frac{1}{4}+\frac{1}{8}+\frac{1}{16}+\cdots is a geometric series with a=\frac{1}{2} and r=\frac{1}{2}. Since -1<r<1, the series \sum_{n=1}^\infty\left(\frac{1}{2}\right)^n converges to \frac{\frac{1}{2}}{1-\frac{1}{2}}=\frac{1}{2}.

Geometric series also can be used to write repeating decimal expansions to fractions. For example, let us write 1.0\overline{35} as a fraction. \begin{align*}1.0\overline{35}&=1.035353535\cdots\\&=1+0.035+0.00035+0.0000035+\cdots\\&=1+\frac{35}{10^3}+\frac{35}{10^5}+\frac{35}{10^7}+\cdots\\&=1+\frac{35}{10^3}\left(1+\frac{1}{10^2}+\frac{1}{10^4}+\cdots\right)\\&=1+\frac{35}{10^3}\frac{1}{1-\frac{1}{10^2}}\\&=1+\frac{35}{990}=\frac{1025}{990}=\frac{205}{198}\end{align*} In practice, there is an easier and a quicker way to convert a repeating decimal expansion to a fraction as you may have learned in high school or earlier: 1000\times 1.0\overline{35}-10\times  1.0\overline{35}=1035-10=1025 so 1.0\overline{35}=\frac{1025}{990}=\frac{205}{198}

Example (The Harmonic Series).
Consider the harmonic series
\sum_{n=1}^\infty\frac{1}{n}=1+\frac{1}{2}+\frac{1}{3}+\cdots+\frac{1}{n}+\cdots.
Group the terms as
1+\frac{1}{2}+\left(\frac{1}{3}+\frac{1}{4}\right)+\left(\frac{1}{5}+\frac{1}{6}+\frac{1}{7}+\frac{1}{8}\right) +\left(\frac{1}{9}+\cdots+\frac{1}{16}\right)+\cdots.
Then each pair of parentheses encloses p terms of the form
\frac{1}{p+1}+\frac{1}{p+2}+\cdots+\frac{1}{p+p}>\frac{p}{2p}=\frac{1}{2}.
Forming partial sums by adding the parenthetical groups one by one, we obtain
s_1=1, s_2=1+\frac{1}{2}, s_4>1+\frac{2}{2}, s_8>1+\frac{3}{2}, s_{16}>1+\frac{4}{2},\cdots, s_{2^n}>1+\frac{n}{2},\cdots.
This shows that \lim_{n\to\infty}s_{2^n}=\infty and so \{s_n\} diverges. Therefore, the harmonic series diverges.

Example. The following type of series are called telescoping series. #2 is left as an exercise.

  1. Show that
    \sum_{n=1}^\infty\frac{1}{(2n-1)(2n+1)}=\frac{1}{2} Solution. \begin{align*}s_n&=\sum_{k=1}^n\frac{1}{(2k-1)(2k+1)}\\&=\frac{1}{2}\sum_{k=1}^n\left(\frac{1}{2k-1}-\frac{1}{2k+1}\right)\\&=\frac{1}{2}\left(1-\frac{1}{2n+1}\right)\\&=\frac{n}{2n+1}\end{align*} and \lim_{n\to\infty}s_n=\frac{1}{2}.
  2. Show that \sum_{n=1}^\infty\frac{1}{n(n+1)}=1

Sequences

Definition. A succession of real numbers a_1,a_2,\cdots,a_n,\cdots in a definite order is called a sequence. a_n is called the n-th term or the general term. The sequence \{a_1,a_2,\dots,a_n,\cdots\} is denoted by \{a_n\} or \{a_n\}_{n=1}^\infty.

Example.

  1. The set of natural numbers 1,2,3,4,\cdots,n,\cdots
  2. 1,-2,3,-4,\cdots,(-1)^{n-1}n,\cdots
  3. \frac{1}{2},-\frac{1}{4},\frac{1}{8},-\frac{1}{16},\cdots,(-1)^{n-1}\frac{1}{2^n},\cdots
  4. 0,1,0,1,\cdots,\frac{1}{2}[1+(-1)^n],\cdots
  5. 2,3,5,7,11,\cdots,p_n,\cdots

It is not essential that the general term of a sequence is given by some simple formula as is the case in the first four examples above. The sequence in 5 represents the succession of prime numbers. p_n stands for the n-th prime number. There is no formula available for the determination of p_n.

The following is the quantifying definition of the limit of a sequence due to Augustin-Louis Cauchy.

Definition. A sequence \{a_n\} has a limit L and we write \lim_{n\to\infty}a_n=L or a_n\to L as n\to\infty if for any \epsilon>0 there exists a positive integer N such that |a_n-L|<\epsilon\ \mbox{for all}\ n\geq N.

Example.

  1. Show that \lim_{n\to\infty}\frac{1}{n}=0
  2. Show that \lim_{n\to\infty}\frac{1}{10^n}=0
  3. Let \{a_n\} be a sequence defined by a_1=0.3, a_2=0.33, a_3=0.333,\cdots, show that \lim_{n\to\infty}a_n=\frac{1}{3}

Proof. I will prove 1. 2 and 3 are left as exercises. Let \epsilon>o be given. Then |a_n-L|=\frac{1}{n}<\epsilon\Longrightarrow n>\frac{1}{\epsilon}. Choose N a positive integer \frac{1}{\epsilon}. Then for all n>N |a_n-L|<\epsilon.

The following limit laws allow us to break a complicated limit to simpler ones.

Theorem. Let \lim_{n\to\infty}a_n=L and \lim_{n\to\infty}b_n=M. Then

  1. \lim_{n\to\infty}(a_n\pm b_m)=L\pm M
  2. \lim_{n\to\infty}ca_n=cL where c is a constant.
  3. \lim_{n\to\infty}a_nb_n=LM
  4. \lim_{n\to\infty}\frac{a_n}{b_n}=\frac{L}{M} provided M\ne 0.

Example. Find \lim_{n\to\infty}\frac{n}{n+1}.

Solution. \begin{align*}\lim_{n\to\infty}\frac{n}{n+1}&=\lim_{n\to\infty}\frac{1}{1+\frac{1}{n}}=1\end{align*} since \lim_{n\to\infty}\frac{1}{n}=0.

The following theorem is also an important tool for calculating limits of certain sequences.

Theorem (Squeeze Theorem). If a_n\leq b_n\leq c_n for n\geq n_0 and \lim_{n\to\infty}a_n=\lim_{n\to\infty}c_n=L then \lim_{n\to\infty}b_n=L.

Corollary. If \lim_{n\to\infty}|a_n|=0 then \lim_{n\to\infty}a_n=0.

Proof. It follows from the inequality -|a_n|\leq a_n\leq |a_n| for all n and the Squeeze Theorem.

Example. Use the Squeeze Theorem to show \lim_{n\to\infty}\frac{n!}{n^n}=0

Solution. It follows from 0\leq\frac{n!}{n^n}=\frac{1\cdot 2\cdot 3\cdots n}{n\cdot n\cdot n\cdots n}\leq\frac{1}{n} for all n.

The following theorem enables you to use a cool formula you learned in Calculus I, L’Hôpital’s rule!

Theorem. If \lim_{x\to\infty}f(x)=L and f(n)=a_n, then \lim_{n\to\infty}a_n=L.

Example. Calculate \lim_{n\to\infty}\frac{\ln n}{n}.

Solution. Let f(x)=\frac{\ln x}{x}. Then \lim_{x\to\infty}f(x) is an indeterminate form of  type \frac{\infty}{\infty}. So by L’Hôpital’s rule \begin{align*}\lim_{x\to\infty}\frac{\ln x}{x}&=\lim_{x\to\infty}\frac{(\ln x)’}{x’}\\&=\lim_{x\to\infty}\frac{1}{x}\\&=0\end{align*} Hence by the Theorem above \lim_{n\to\infty}\frac{\ln n}{n}=0.

Example. Calculate \lim_{n\to\infty}\root n\of{n}.

Solution. Let f(x)=x^{\frac{1}{x}}. Then \lim_{x\to\infty}f(x) is an indeterminate form of type \infty^0. As you learned in Calculus I, you will have to convert the limit into an indeterminate form of type \frac{\infty}{\infty} or type \frac{0}{0} so that you can apply L’Hôpital’s rule to evaluate the limit. Let y=x^{\frac{1}{x}}. Then \ln y=\frac{\ln x}{x}. As we calculated in the previous example, \lim_{x\to\infty}\ln y=0. Since \ln y is continuous on (0,\infty), \lim_{x\to\infty}\ln y=\ln(\lim_{x\to\infty} y) Hence, \lim_{x\to\infty}x^{\frac{1}{x}}=e^0=1 i.e. \lim_{n\to\infty}\root n\of{n}=1.

Theorem. \lim_{n\to\infty}\root n\of{a}=1 for a>0.

Example. \lim_{n\to\infty}\frac{1}{\root n\of{2}}=1.

Definition. A sequence \{a_n\} is said to diverge if it fails to converge. Divergent sequences include sequences that tend to infinity or negative infinity, for example 1,2,3,\cdots,n,\cdots and sequences that oscillates such as  1,-1,1,-1,\cdots.

Definition. A sequence \{a_n\} is said to be bounded if there exists M>0 such that |a_n|<M for every n.

Theorem. A convergent sequence is bounded but the converse need not be true.

Definition. A sequence \{a_n\} is said to be monotone if it satisfies either a_n\leq a_{n+1}\ \mbox{for all}\ n or a_n\geq a_{n+1}\ \mbox{for all}\ n

Equivalently, one can show that a sequence \{a_n\} is monotone increasing by checking to see if it satisfies  \frac{a_{n+1}}{a_n}\geq 1\ \mbox{for all}\ n or a_{n+1}-a_n\geq 0\ \mbox{for all}\ n

The following theorem is called the Monotone Sequence Theorem.

Theorem. A monotone sequence which is bounded is convergent.

Example.

  1. Show that the sequence \frac{1}{2},\frac{1}{3}+\frac{1}{4},\frac{1}{4}+\frac{1}{5}+\frac{1}{6},\cdots,\frac{1}{n+1}+\frac{1}{n+2}+\cdots+\frac{1}{2n},\cdots is convergent.
  2. Show that the sequence 1,1+\frac{1}{2},1+\frac{1}{2}+\frac{1}{4},\cdots,1+\frac{1}{2}+\frac{1}{4}+\cdots+\frac{1}{2^n},\cdots is convergent.

Solution. 2 is left as an exercise. a_{n+1}-a_n=\frac{1}{2n+2}+\frac{1}{2n+1}-\frac{1}{n+1}=\frac{4n+1}{(2n+2)(2n+1)}>0 for all n. So it is monotone increasing. a_n=\frac{1}{n+1}+\cdots+\frac{1}{n+n}\leq\frac{1}{n}+\cdots+\frac{1}{n}=\frac{n}{n}=1 for all n. So it is bounded. Therefore, it is convergent by the monotone sequence theorem.

Why Can’t Speeds Exceed c?

This is a guest post by Dr. Lawrence R. Mead. Dr. Mead is a Professor Emiritus of Physics at the University of Southern Mississippi.

It is often stated in elementary books and repeated by many that the reason that an object with mass cannot achieve or exceed the speed of light in vacuum is the “mass becomes infinite”, or “time stops” or even “the object has zero size”. There are correct viewpoints for why matter or energy or any signal of any kind cannot exceed light speed and these reasons have little to do directly with mass changes or time dilations or Lorentz contractions.

Reason Number One

Consider a signal of any kind (mass, energy or just information) which travels at speed u=\alpha c beginning at point x_A at time t=0 and arriving at position x_B at later time t>0. From elementary kinematics,
t=(x_B -x_A)/u = {\Delta x \over \alpha c}.
Now suppose the signal travels at a speed exceeding c, that is \alpha > 1. Let us calculate the elapsed time as measured by a frame going by at speed V<c. According to the Lorentz transformation,
\begin{equation}\label{eqno1}t’ = \gamma (t-{Vx \over c^2}),\end{equation} where \gamma=\frac{1}{\sqrt{1-\frac{V^2}{c^2}}}.
There are two events: the signal leaves x=x_A at t=0, and the signal arrives at x=x_B at time t=\Delta t. According to \eqref{eqno1}, these events in the moving frame happen at times,
t’_A=\gamma ( 0 -Vx_A/c^2) and
t’_B=\gamma (\Delta t – Vx_B/c^2).
Thus, the interval between events in the moving frame is, \begin{equation}\begin{aligned}\Delta t’ &= t’_B-t’_A\\ &=\gamma \Delta t -\gamma \frac{V}{c^2}(x_B-x_A)\\ &=\gamma \Delta t ( 1-\alpha V/ c).\end{aligned}\label{eqno2}\end{equation}
Now suppose that \alpha V/c > 1, which implies that,
c > V > c/\alpha . Then for moving frames within that range of speeds it follows from \eqref{eqno2} that,
\Delta t’= t’_B-t’_A <0, meaning physically that the signal arrived before it was sent! This is a logical paradox which is impossible on physical grounds; no one will argue that in any frame a person can be shot before the gun is fired, or you obtain the knowledge of the outcome of a horse race before the race has begun.

Well now what if the two events at x_A and x_B are not causally connected but one (say at x_B for definiteness) simply happened after the other? How does the above argument change? How does the above math “know” that there is or is not a causal connection between the events? Everything goes the same up to the second line of equation \eqref{eqno2}:
\begin{equation}\label{eqno3} \Delta t’ = \gamma \{ \Delta t – V(x_B-x_A)/c^2 \}. \end{equation}
Can there be a moving frame of speed V<c for which the event at x_B (the later one in S) happens before the event at x_A (the earlier one in S)? If so, \Delta t’ < 0; from \eqref{eqno3} then we find,
\Delta t – V(x_B-x_A)/c^2 < 0, or solving for V,
c > V > c{c\over \Delta x/ \Delta t}. In order for V to be less
than c, it must therefore be that, {c\over \Delta x /\Delta t} < 1, or
{\Delta x \over \Delta t} > c. This is possible for sufficiently large \Delta x and/or sufficiently small \Delta t because the ratio {\Delta x \over \Delta t} is not the velocity of any signal, though it has the units of speed.

What is the Speed of “Light” Anyway?

Note that the Lorentz transformation contains the speed c in it. What is this speed? Without referencing Maxwell’s equations of Electromagnetism, one does not know that c is in fact the speed of light itself. But the above analysis shows – without reference to Maxwell – that the speed c cannot be exceeded. And what is the speed talked about in the previous discussion? Well, it is the maximum speed at which one event can influence another with given (fixed) separation – thus, c above isn’t really the speed of light at all; rather it is the speed of causality!

Reason Number Two

Imagine, for example, a constant force F acting on a particle of (rest) mass m. Newton’s second Law in its relativistic form gives,
\begin{equation}\begin{aligned} F &= {dp \over dt} \\ &= {d \over dt} \, mv\gamma \\ &= m \gamma^3 \, \dot v, \end{aligned}\label{eqno4}\end{equation}
where we have assumed straight line motion. This is an autonomous differential equation whose solution, assuming the object is initially at rest, is,
v(t)=at/(1+a^2t^2/c^2)^{1/2},
where a=F/m. It is clear that as t \to \infty, v(t)
approaches c and not infinity. Moreover, the differential impulse at arbitrary time t on the particle can be found from taking the derivative of v(t) given in the last equation,
\begin{equation}\label{eqno5}m\, dv = { F \, dt \over (1+a^2t^2/c^2)^{3/2}}. \end{equation}
From equation \eqref{eqno5}, it is clear that the incremental speed increase dv over time dt approaches zero as t \to \infty. Thus, from this point of view we see that while the force still does work, the increase in speed for a given interval of time and incremental amount of work, is less and less as time goes on which is why the speed never reaches c over any finite time interval.

Reason Number Three

In the interval of time dt as measured in some inertial frame observing a moving body, the clock attached to the body ticks off proper time
\begin{equation}\label{eqno6}d\tau = \sqrt{1-v^2/c^2}\, dt. \end{equation}
However, for light v\equiv c, and therefore d\tau\equiv 0. Light takes no proper time to go between two points however distantly separated in space. Thus, no object could travel faster than taking no time. This is the oft-repeated mantra of textbooks, and, while the mathematics verifies it, there are far more fundamental reasons, the best being causality as outlined above.

Is FTL (Faster-Than-Light) Possible?

Often you hear that Einstein’s relativity prevents FTL (Faster-Than-Light). Is that true? The answer is yes and no. It is not possible for a spaceship to travel faster than the speed of light. But there may be a particle that travels FTL and the existence of such a particle would not violate the principles of relativity if its speed already exceeds the speed of light when it is created. The hypothetical particle that travels FTL is called a tachyon. (tachys means fast in Greek) The name was coined by a Columbia University physicist Gerald Feinberg in 1967. When he was asked why he thought about such a particle Feinberg reportedly quoted a Jewish proverb “Everything which is not forbidden is allowed.” (Author’s note: This is from something I read more than 3 decades ago when I was a high school student so I cannot cite its source. Also I could not find any such Jewish proverb either. It is however a constitutional principle of English law.)

For a Tachyon, the Lorentz transformation is given by the complex coordinates \begin{align*}t’&=-i\frac{t-\frac{v}{c^2}x}{\sqrt{\frac{v^2}{c^2}-1}}\\x’&=-i\frac{x-vt}{\sqrt{\frac{v^2}{c^2}-1}}\end{align*} where i=\sqrt{-1}. Although this is a complex transformation, it is still an isometry i.e. it preserves the Minkowski metric. In order for its energy E to be real one has to assume that its rest mass is purely imaginary im_0 where m_0>0 is real and hence from the relativistic energy E=\frac{im_0c^2}{\sqrt{1-\frac{v^2}{c^2}}}=\frac{im_0c^2}{i\sqrt{\frac{v^2}{c^2}-1}}=\frac{m_0c^2}{\sqrt{\frac{v^2}{c^2}-1}} Imaginary rest mass may sound weird but rest mass is not an observable because a particle is never at rest. What’s important is energy being real as it is an observable. The following figure shows energies of a subluminal particle (in red) and a superluminal particle (in blue) with m_0=c=1).

Properties of Tachyons:

  1. The speed of light c is the greatest lower bound of Tachyon’s speed. There is no upper limit of Tachyon’s speed.
  2. Tachyons have imaginary rest mass (as we discussed above).
  3. In order for a tachyon to slow down to the speed of light, it requires infinite amount of energy and momentum.
  4. Another peculiar nature of tachyons. If a tachyon looses energy, its speed increases. At E=0, v=\infty.

How do we detect tachyons if they exist? Since tachyons travel FTL, we can’t see them coming. However if they are charged particles, they will emit electromagnetic Mach shock waves called Tscherenkov (also spelled Cherenkov) radiations. This always happens when charged particles are passing through a medium with a higher speed than the phase speed of light in the medium. By detecting such Tscherenkov radiations we may be able to confirm the existence of tachyons.

An interesting question is “can we use tachyons for FTL communications? ” It was answered by Richard C. Tolman as negative in his book [2] (pp 54-55). In [2]. Tolman considered the following thought experiment. Suppose a signal is being sent from a point A (cause) to another point B (effect) with speed u. In an inertial frame S where A and B are at rest, the time of arrival at B is given by \Delta t=t_B-t_A=\frac{B-A}{u} In another inertial frame S’ moving with speed v relative to S the time of arrival at B is given, according to the Lorentz transformation, by \begin{align*}\Delta t’&=t’_{B}-t’_{A}\\&=\frac{t_B-\frac{v}{c^2}x_B}{\sqrt{1-\frac{v^2}{c^2}}}-\frac{t_A-\frac{v}{c^2}x_A}{\sqrt{1-\frac{v^2}{c^2}}}\\&=\frac{1-u\frac{v}{c^2}}{\sqrt{1-\frac{v^2}{c^2}}}\Delta t\end{align*} If u>c then certain values of v can make \Delta t’ negative. In other words, the effect occurs before the cause in this frame, the violation of causality!

Food for Thought: Can one possibly use tachyons to send a message (signal) to the past?

References:

  1. Walter Greiner, Classical Mechanics, Point Particles and Relativity, Springer, 2004
  2. Richard C. Tolman, The Theory of the Relativity of Motion, University of California Press, 1917. A scanned copy is available for viewing online here.