
pmid: 16210187
arXiv: quant-ph/0111069
In the past decade quantum algorithms have been found which outperform the best classical solutions known for certain classical problems as well as the best classical methods known for simulation of certain quantum systems. This suggests that they may also speed up the simulation of some classical systems. I describe one class of discrete quantum algorithms which do so--quantum lattice gas automata--and show how to implement them efficiently on standard quantum computers.
13 pages, plain TeX, 10 PostScript figures included with epsf.tex; for related work see http://math.ucsd.edu/~dmeyer/research.html
quantum Fourier transform, Quantum Physics, Surface Properties, Physics, FOS: Physical sciences, Models, Biological, Diffusion, Kinetics, Models, Chemical, Quantum computation, Quantum Theory, Computer Simulation, Gases, Particle Size, quantum lattice-gas automata, Rheology, Quantum Physics (quant-ph), quantum simulation
quantum Fourier transform, Quantum Physics, Surface Properties, Physics, FOS: Physical sciences, Models, Biological, Diffusion, Kinetics, Models, Chemical, Quantum computation, Quantum Theory, Computer Simulation, Gases, Particle Size, quantum lattice-gas automata, Rheology, Quantum Physics (quant-ph), quantum simulation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 21 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
