Integrated quantum photonics
As the field has progressed new quantum algorithms have been developed which provide short and long term routes towards the demonstration of the superiority of quantum computers over their classical counterparts. Cluster state computation is now generally accepted as the approach that will be used to develop a fully fledged quantum computer. Whilst development of quantum computer will require the synthesis of many different aspects of integrated optics, boson sampling seeks to demonstrate the power of quantum computation via technologies readily available and is therefore a very promising near term algorithm to doing so. In fact shortly after its proposal there were several small scale experimental demonstrations of the boson sampling algorithm
Quantum neural network
Rinkus proposes that distributed representation, specifically "sparse distributed representation" (SDR), provides a classical implementation of quantum computing. Specifically, the set of SDR codes stored in an SDR coding field will generally intersect with each other to varying degrees. In other work, Rinkus describes a fixed time learning (and inference) algorithm that preserves similarity in the input space into similarity (intersection size) in the SDR code space. Assuming that input similarity correlates with probability, this means that any single active SDR code is also a probability distribution over all stored inputs, with the probability of each input measured by the fraction of its SDR code that is active (i.e., the size of its intersection with the active SDR code). The learning/inference algorithm can also be viewed as a state update operator and because any single active SDR simultaneously represents both the probability of the single input, X, to which it was assigned during learning and the probabilities of all other stored inputs, the same physical process that updates the probability of X also updates all stored probabilities. By 'fixed time', it is meant that the number of computational steps comprising this process (the update algorithm) remains constant as the number of stored codes increases. This theory departs radically from the standard view of quantum computing and quantum physical theory more generally: rather than assuming that the states of the lowest level entities in the system, i.e., single binary neurons, exist in superposition, it assumes only that higher-level, i.e., composite entities, i.e., whole SDR codes (which are sets of binary neurons), exist in superposition.