Math plays a huge role in computer science. One example of this is in algorithms. Algorithms are mathematical equations for solving problems. For example the math behind encrypting. This algorithm takes a set of inputs from a user and sends a secure and encrypted version to another as explained in The 9 Algorithms That Changed The Future (chapter 4). Algorithms also determine the speed of programs and tasks that a computer tries to complete. A more optimized algorithm will result in faster operations so the creation of better algorithms is very important to computer scientists. Another connection between computer science and math is in the area of parallel computing. Parallel computing is a process that preforms multiple equations at the same (timehttps://en.wikipedia.org/wiki/Theoretical_computer_science). This process helps to increase the speed of programs and computers because the process of splitting up large equations and dividing up small equations between processors allows the processors to move on to the next task faster. But this speed also can result in some interesting bugs like the race condition that we demonstrated in scratch. A race condition is when the timing and sequence of the program causes a operation to be preformed more times than desired for example. This can result in incorrect outputs. Amazingly enough is that the maximum speed-up that a program can receive from using parallel computing is found through another formula called Amdahl's law.
Math also holds importance in quantum computation. Quantum computation is the use of computation systems to preform operations on data . These quantum computers can solve problems a lot faster than classical computers. Unfortunately quantum computing is still a relatively new field but there are a few examples of quantum algorithms that run faster than normal algorithms. One such algorithm is Simon's algorithm which uses the model of decision tree complexity. This algorithm sadly has very little in the terms of actual usefulness. The importance of math in quantum computing, parallel computing and other areas of computer science is that math provides a means to preform the needed functions and the tools to speed up the process. Another interesting connection between math and computer science is in the key people in computer science especially in the early days of computer science. Charles Babbage for example was a mathematician. He also was the inventor of the first computer. The computer was designed to help him do math, evidently pointing out that math is not only important in computer science but the reason for its creation. Math also directly links to computer science through applied mathematics. Applied mathematics is a area of mathematics that uses a system to study different components their effects and make predictions on them. Applied mathematics links up with several key computer science areas such as the training of systems in neural networks. This training is done by providing the computer with positive examples so that the computer can make guesses on what is and isn't correct (Pattern on the stone chapter 8). So this has been how math is a core part of computer science.
Works cited
"Theoretical Computer Science." Wikipedia. Wikimedia Foundation, n.d. Web. 14 Nov. 2016. <https://en.wikipedia.org/wiki/Theoretical_computer_science>.
Hillis, W. Daniel. The Pattern on the Stone: The Simple Ideas That Make Computers Work. New York: Basic, 1998. Print.
MacCormick, John. Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today's Computers. Princeton: Princeton UP, 2012. Print.
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