But recent advances in the realization of a large scale quantum computer may eventually prove quantum information theorists wrong: Rather than supporting the dismissal of the quantum measurement problem, these advances may surprisingly lead to its empirical solution.
Another scheme to reduce errors in the implementation of quantum algorithms on large scale quantum computers is to encode information in noiseless subsystems, or decoherence free subspaces (Lidar, Chuang & Whaley 1998).
Nevertheless the understanding of the full scale of effects which can be expected in these systems requires a more detailed analysis of large scale quantum coherences and entanglement.
Another philosophical implication of the realization of a large scale quantum computer regards the long-standing debate in the philosophy of mind on the autonomy of computational theories of the mind (Fodor 1974).
Also here the model was proved to be efficiently simulated on a standard quantum computer (Freedman, Kitaev, Wang 2000, Aharonov et al. 2005), but its merit lies in its high tolerance to errors resulting from any possible realization of a large scale quantum computer (see below).
These large scale quantum calculations elucidate the role of the hydrogen bonded network as well as point mutations in the absorption spectra of the DsRed and mCherry proteins.
Consequently, experimentalists around the world are engaged in tremendous attempts to tackle the technological difficulties that await the realization of such a large scale quantum computer.
(2) operationally, can we actually realize a large scale quantum computer to run these algorithms?
Finally, as the implementation of Shor's algorithm on a large scale quantum computer seems still beyond our reach, quantum information scientists turn to the original goal of using quantum computers to simulate quantum systems.
One is building a large scale quantum computer and the other is achieving superconductivity above the freezing point of water, colloquially known as room temperature superconductivity.
