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| Alternative arcitectures for nanocomputing In addition to single electron transistors, two promising alternatives to traditional computers are molecular computing and quantum computing. These two methods are intimately related, yet deal with information on two different levels. Much progress has been made in these areas during the last years and both have been shown to be feasible replacements for semiconductor chips. Quantum computing seeks to write, process and read information on the quantum level. It is at the nanoscale that quantum mechanical effects such as (the wave particle duality) begin to become apparent. Numerous scientists are seeking ways to store information within the quantum mechanical realm. This is not a simple task because of the delicate nature of quantum mechanical systems. However, since the laws of quantum mechanics involves unintuitive principles such as superposition and entanglement, a quantum computer would be able to violate some rules that limit our classical computers. For instance, taking advantage of superposition would mean that a quantum bit of information, termed a qubit would be able to be used in several computations at the same time. Taking advantage of entanglement would mean that the information could be processed over long distances without the classical requirement of wires. Molecular computation is another method complimentary to quantum computing that seeks to write, process and read information within single molecules. One molecule that has proved most promising for molecular computation is Deoxyribonucleic acid (DNA). DNA is a long polymer made of 4 different nucleotides that can be represented by the letters A, T, C and G. The order or sequence of these nucleotides within DNA provides the information for making protein, the main components of the molecular scale machinery used by living organisms to carry out life sustaining functions. Mathematicians have figured out numerous ways to use DNA an the various proteins that come with it to carry out numerical computations that are notoriously difficult for silicon computers, namely NP-complete problems. The advantage that molecular computing using DNA has over conventional computing is that it is massively parallel. This means that each DNA molecule can function as a single processor, which greatly improves the speed of computation for complex problems. |
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