By Lee Spector
Automatic Quantum laptop Programming offers an advent to quantum computing for non-physicists, in addition to an creation to genetic programming for non-computer-scientists. The e-book explores numerous ways that genetic programming can aid automated quantum desktop programming and provides exact descriptions of particular innovations, in addition to a number of examples in their human-competitive functionality on particular difficulties. resource code for the author’s QGAME quantum laptop simulator is incorporated as an appendix, and tips to extra on-line assets provide the reader with an array of instruments for automated quantum computing device programming.
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Extra resources for Automatic Quantum Computer Programming: A Genetic Programming Approach
These gates are “Boolean” in the sense that they can have one of two possible effects on their output qubits on any particular invocation, but unlike classical logic gates they cannot act by setting their output qubits to 0 or 1 as such behavior would be non-unitary. The alternative convention adopted in most work on quantum computing, and built into QGAME, is that a Boolean gate acts by flipping or not flipping its output qubit to indicate an output of 1 or 0 respectively. The “flip” here is implemented as a QNOT, and all oracle gates can therefore be thought of as CNOT gates with more complex controls.
The functions used in the run must all return values of this same type, and must take arguments only of this type. These restrictions prevent type incompatibility errors, but they are inconvenient; several ways to relax these restrictions are discussed in Chapter 6. Additional steps must often be taken to ensure that arbitrary programs are also semantically valid — that is, that they will always execute without error, producing interpretable (even if incorrect) results. For AUTOMATIC QUANTUM COMPUTER PROGRAMMING 48 example, one must sometimes engineer special return values for “pathological” calls, such as division by zero.
The parameters are the indices of the input qubits, and is the index of the output qubit. For example, the following expression: (ORACLE (0 0 0 1) 2 1 0) calls a gate that flips qubit 0 (the right-most qubit) when (and only when) the values of qubits 2 and 1 are both 1. In other words, this oracle acts as the following matrix: This particular matrix, incidentally, is also known as the “Toffoli” gate; it can be used to implement quantum versions of classical NAND and FANOUT gates, meaning that all possible deterministic classical computations can be computed on quantum computers using appropriately connected Toffoli gates (Nielsen and Chuang, 2000, pp.