Quantum Computing Modeling in Scala

Looking at it with a computing mindset, quantum state is not that different from classical or probabilistic state. In this presentation we will show a common abstraction that captures the similarities and differences in representing and evolving classical, probabilistic and quantum state. Concrete scenarios, like managing account balances, portfolio allocation, Bayesian inference and quantum computing simulation are used as examples, with running code. A particular type of monadic transformation ties all these use-cases together. The presentation touches upon the implementation of all 4 quantum postulates (state representation, evolution, measurement and composition) and visualizes them using biased coins, dice and complex histograms. We will also show a simple application of quantum computing: counting the number of binary words of a fixed length with no consecutive ones. This is, of course, a typical interview question about Fibonacci numbers.  https://github.com/logicalguess/quantum-scale/blob/master/docs/QuantumScala.pdf