We may interpret partial differentiation in the following manner:
The derivative \(f_x(x,y)\) is obtained by applying \(\frac{\partial}{\partial x}\) to the function \(f(x,y)\) from the left.
\(\frac{\partial}{\partial x}\) is neither a number nor a function. It's something different that we call a (partial) differential operator. The same argument applies to \(\frac{\partial}{\partial y}\). This interpretation of differential operators turns out to be useful in many situations. For example, for any constants \(a, b\in \mathbb{R}\), we may consider the following operator \(D\):
If we apply this operator to the function \(f(x,y)\) from the left, we obtain \(af_x(x,y) + bf_y(x,y)\) as a result. That is,
\[Df(x,y) = af_x(x,y) + bf_y(x,y).\]
Note that the result is different if we apply the operator to \(f(x,y)\) from the right, which will be another differential operator rather than a function:
The result is a vector function composed of the partial derivatives of \(f(x,y)\).
The nabla may be regarded as a vector. Suppose we have a vector function \(\mathbf{u}(x,y) = (u(x,y), v(x,y))\). Then, we can take their dot (scalar) product:
Example. For \(a,b\in\mathbb{R}\), let \(a\frac{\partial}{\partial x} + b\frac{\partial}{\partial y}\) be a differential operator that operates on functions of class \(C^{\infty}\). Then, \(\frac{\partial^2}{\partial x\partial y} = \frac{\partial^2}{\partial y\partial x}\). Accordingly, the following holds:
Defining the birth process Consider a colony of bacteria that never dies. We study the following process known as the birth process , also known as the Yule process . The colony starts with \(n_0\) cells at time \(t = 0\). Assume that the probability that any individual cell divides in the time interval \((t, t + \delta t)\) is proportional to \(\delta t\) for small \(\delta t\). Further assume that each cell division is independent of others. Let \(\lambda\) be the birth rate. The probability of a cell division for a population of \(n\) cells during \(\delta t\) is \(\lambda n \delta t\). We assume that the probability that two or more births take place in the time interval \(\delta t\) is \(o(\delta t)\). That is, it can be ignored. Consequently, the probability that no cell divides during \(\delta t\) is \(1 - \lambda n \delta t - o(\delta t)\). Note that this process is an example of the Markov chain with states \({n_0}, {n_0 + 1}, {n_0 + 2}...
Joseph Fourier introduced the Fourier series to solve the heat equation in the 1810s. In this post, we show how the Fourier transform arises naturally in a simplified version of the heat equation. Suppose we have the unit circle \(S\) made of a metal wire. Pick an arbitrary point \(A\) on the circle. Any point \(P\) on the circle is identified by the distance \(x\) from \(A\) to \(P\) along the circle in the counter-clockwise direction (i.e., \(x\) is the angle of the section between \(A\) and \(P\) in radian). Let \(u(t,x)\) represent the temperature at position \(x\) and time \(t\). The temperature distribution at \(t = 0\) is given by \(u(0, x) = f(x)\). Assuming no radiation of heat out of the metal wire, \(u(t,x)\) for \(t > 0\) and \(0\leq x \leq 2\pi\) is determined by the following partial differential equation (PDE) called the heat equation : \[\gamma\frac{\partial u}{\partial t} = \kappa\frac{\partial^2 u}{\partial x^2}\] and the initial condition \[u(0,x) = f(x...
Given a sequence \(\{a_n\}\), the expression \[\sum_{n=0}^{\infty}a_n = a_0 + a_1 + a_2 + \cdots\] is called a series (or infinite series ). This expression may or may not have value. At this point, it is purely formal. Note that the order of addition matters : We first add \(a_0\) and \(a_1\), to the result of which we add \(a_2\), to the result of which we add \(a_3\), and so on (Not something like we first add \(a_{101}\) and \(a_{58}\), then add \(a_{333051}\), and so on). We will see, however, that for a special class of series (the positive term series), the order of addition does not matter if the series converges. Example . The sum of a geometric progression \(\{ar^n\}\), that is, \(\sum_{n=0}^{\infty}ar^n\) is called a geometric series . It is understood that \(r^0 = 1\) including the case when \(r = 0\). □ Given a series \(\sum_{n=0}^{\infty}a_n\) and a number \(n\geq 0\), the sum \[\sum_{k=0}^{n}a_k = a_0 + a_1 + \cdots + a_n\] is called the \(n\)-th partial sum . We m...
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