Quantum Model Reduction

The field-theoretic foundations of quantum optics admit a rigorous, hierarchical approach to modeling circuits/networks of quantum input-output devices coupled by propagating coherent fields. To analyze and design complex systems, however, we rely critically on practical techniques for dimensional reduction of quantum models. Rigorous approaches to quantum model reduction provide crucial insight into what specific properties make partially-coherent (“NISQ”) quantum systems fundamentally difficult to simulate on conventional computers, and therefore potentially useful as supra-classical resources. Our current work in this area focuses on addressing new challenges raised by ultrafast nonlinear nanophotonics.

All recent publications in this category

Selected earlier work in this category

“Optical devices based on limit cycles and amplification in semiconductor optical cavities,” R. Hamerly and H. Mabuchi, Phys. Rev. Applied 4, 024016 (2015).

“A coherent perceptron for all-optical learning,” N. Tezak and H. Mabuchi, EPJ Quantum Technology 2:10 (2015).

“Photonic circuits for iterative decoding of a class of low-density parity check codes,” D. S. Pavlichin and H. Mabuchi, New J. Phys. 16, 105017 (2014).

“Gauge subsystems, separability, and robustness in autonomous quantum memories,” G. Sarma and H. Mabuchi, New J. Phys. 15, 035014 (2013).

“Specification of photonic circuits using Quantum Hardware Description Language,” N. Tezak, A. Niederberger, D. S. Pavlichin, G. Sarma and H. Mabuchi, Phil. Trans. Roy. Soc. A. 370, 5270-5290 (2012).

“Quantum filter reduction for measurement-feedback control via unsupervised manifold learning,” A. E. B. Nielsen, A. Hopkins and H. Mabuchi, New J. Phys. 11, 105043 (2009).

“Derivation of Maxwell-Bloch-type equations by projection of quantum models,” H. Mabuchi, Phys. Rev. A 78, 015801 (2008).