Scaling up quantum simulations

Self-Explanatory Simulations: Scaling Up to Large Models

Qualitative reasoners have been hamstrung by the inability to analyze large models . This includes selfexplanatory simulators, which tightly integrate qualitative and numerical models to provide both precision and explanatory power . While they have important potential applications in training, instruction, and conceptual design, a critical step towards realizing this potential is the ability t...

Scaling-Up Quantum Heat Engines Efficiently via Shortcuts to Adiabaticity

The finite-time operation of a quantum heat engine that uses a single particle as a working medium generally increases the output power at the expense of inducing friction that lowers the cycle efficiency. We propose to scale up a quantum heat engine utilizing a many-particle working medium in combination with the use of shortcuts to adiabaticity to boost the nonadiabatic performance by elimina...

Towards scaling up trapped ion quantum information processing

Recent theoretical advances have identified several computational algorithms that can be implemented utilizing quantum information processing (QIP), which gives an exponential speedup over the corresponding (known) algorithms on conventional computers. QIP makes use of the counter-intuitive properties of quantum mechanics, such as entanglement and the superposition principle. Unfortunately it h...

Scaling Up

Scaling Up

Most analytical and experimental results on evolutionary programming (EP) are obtained using low-dimensional problems, e.g., smaller than 50. It is unclear, however, whether the empirical results obtained from the low-dimensional problems still hold for high-dimensional cases. This paper investigates the behaviour of four diierent EP algorithms for large-scale problems, i.e., problems whose dim...