Physical modeling translates measured data into a physical model. Physical modeling is a major objective in physics and is generally regarded as a creative process. How good are computers at solving this task? Here, we show that in the absence of physical heuristics, the inference of optimal quantum models cannot be computed efficiently (unless $\text{P}=\text{NP}$ ). This result illuminates rigorous limits to the extent to which computers can be used to further our understanding of nature.Physical modeling translates measured data into a physical model. Physical modeling is a major objective in physics and is generally regarded as a creative process. How good are computers at solving this task? Here, we show that in the absence of physical heuristics, the inference of optimal quantum models cannot be computed efficiently (unless $\text{P}=\text{NP}$). This result illuminates rigorous limits to the extent to which computers can be used to further our understanding of nature.

arXiv:1510.02800Physical Review AFeb 8, 20186 citations

Physics of Computation

International Journal of Theoretical PhysicsDec 1, 19827 citations

A comparative study of universal quantum computing models: Toward a physical unification

Dongsheng Wang

Quantum computing has been a fascinating research field in quantum physics. Recent progresses motivate us to study in depth the universal quantum computing models (UQCMs), which lie at the foundation of quantum computing and have tight connections with fundamental physics. Although being developed decades ago, a physically concise principle or picture to formalize and understand UQCM is still lacking. This is challenging given the diversity of still-emerging models, but important to understand the difference between classical and quantum computing. In this work, we carried out a primary attempt to unify UQCM by classifying a few of them as two categories, hence making a table of models. With such a table, some known models or schemes appear as hybridization or combination of models, and more importantly, it leads to new schemes that have not been explored yet. Our study of UQCM also leads to some insights into quantum algorithms. This work reveals the importance and feasibility of systematic study of computing models.Quantum computing has been a fascinating research field in quantum physics. Recent progresses motivate us to study in depth the universal quantum computing models (UQCMs), which lie at the foundation of quantum computing and have tight connections with fundamental physics. Although being developed decades ago, a physically concise principle or picture to formalize and understand UQCM is still lacking. This is challenging given the diversity of still-emerging models, but important to understand the difference between classical and quantum computing. In this work, we carried out a primary attempt to unify UQCM by classifying a few of them as two categories, hence making a table of models. With such a table, some known models or schemes appear as hybridization or combination of models, and more importantly, it leads to new schemes that have not been explored yet. Our study of UQCM also leads to some insights into quantum algorithms. This work reveals the importance and feasibility of systematic study of computing models.

arXiv:2108.07909Quantum EngineeringNov 26, 202117 citations

a Physics of Computation.

Wakefield Scott Stornetta

Jan 1, 19890 citations

Novel models of computation from novel physical substrates: a bosonic example

Sampreet Kalita, Benjamin W. Butler, Susan Stepney +1 more

Unconventional physical computing is producing many novel and exotic devices that can potentially be used in a computational mode. Currently, these tend to be used to implement traditional models of computation, such as boolean logic circuits, or neuromorphic approaches. This runs the risk of failing to exploit the devices to their full potential. Here we describe a methodology for deriving a model of computation and domain specific language more closely matched to a given physical device's capabilities, and illustrate it with a case study of bosonic computing as implemented by a physical multi-component interferometer.Unconventional physical computing is producing many novel and exotic devices that can potentially be used in a computational mode. Currently, these tend to be used to implement traditional models of computation, such as boolean logic circuits, or neuromorphic approaches. This runs the risk of failing to exploit the devices to their full potential. Here we describe a methodology for deriving a model of computation and domain specific language more closely matched to a given physical device's capabilities, and illustrate it with a case study of bosonic computing as implemented by a physical multi-component interferometer.

arXiv:2603.24531Mar 25, 20260 citations

\text{P}=\text{NP}

). This result illuminates rigorous limits to the extent to which computers can be used to further our understanding of nature.