Computing requires classical bits, which can hold a value of 0 or 1. Quantum computing gets benefit from superposition of quantum bit (qubit). Qubit is a representation of state of quantum object (electron, proton, photon, etc). The qubit holds a value between 0 and 1 while it is in superposition state. Superposition means the qubit possesses multiple values at the same time so we can harness its power for parallel computing. Once we try to measure the value it can be collapsed into either 0 or 1 based on probability. (Observer collapses wave function simply by observing.) Using bloch sphere, we can represent qubit physically. (The bloch sphere is a physical model to represent a spin state of qubit) A state vector can point to any direction from the center of the sphere. If a vector points to Z+ and Z-, it represents 0 and 1 state respectively. All other vectors represent superposition state in a Z basis. Now, if a vector points to X+, X-, Y+, Y-, all are at a 90-degree angle from
We have seen the summarized article "monad in programming" in the previous post. Let's find out what is a monad in category theory and how the concept became relevant for functional programming. First, we need to understand the basics of category theory. Category A category consists of objects and morphisms (relationships) between those objects. More of it, the morphisms should be composable too. Below is an example of a category. Each dot is an object and each arrow shows morphism from some object to another. As arrows are composable, if there is a morphism from object a to object b , and there is another morphism from b to c , then we can find a morphism from a to c . If you notice, there is identity morphism too, it exists for each object, but we have shown it just for x . It is a morphism from an object to itself. If we compose identity morphism with any other morphism w , we get the same w in return. Functor A functor is a relationship between categories