M Chandler, F Langbein, C Jenkins, S Schirmer. Quantum Control for Magnetic Resonance Spectroscopy. All Wales Medical Physics and Engineering Summer Meeting, poster, 2017. [PDF]
B. Thorpe, Sophie Schirmer, Karol Kalna, Frank Langbein. Monte Carlo simulation of Spin Transport and Recovery in a 25 nm gate length InGaAs Field Effect Transistor. In: European Materials Resdarch Society 2017 Fall Meeting, Symposium F: Spintronics in semiconductors, 2D materials and topological insulators, F.FP.7, 2017. [WWW]
B. Thorpe, K. Kalna, F. C. Langbein, S. G. Schirmer. Spin Recovery in the 25nm Gate Length InGaAs Field Effect Transistor. In: Proc. Int. Workshop on Computational Nanotechnology, pp. 168-169, Windermere, UK, 6-9 June, 2017. [Abstract] [Poster] [WWW]
E. A. Jonckheere, S. G. Schirmer, F.C. Langbein. Structured Singular Value Analysis for Spintronics network Information Transfer Control. IEEE Trans Automatic Control, 62(12):6568-6574, 2017. [DOI:10.1109/TAC.2017.2714623][arxiv:1706.03247][PDF]
Sophie Schirmer, Frank Langbein, Edmond Jonckheere. Control of Quantum Spin Devices, feedback control laws and hidden feedback. Principles and Applications of Control in Quantum Systems, 11th Workshop, PRACQSYS 2017.
E. Jonckheere, S. G. Schirmer, F.C. Langbein. Jonckheere-Terpstra test for nonclassical error versus log-sensitivity relationship of quantum spin network controllers. Int J Robust and Nonlinear Control, 28(6):2383-2403, 2018. [DOI:10.1002/rnc.4022] [arXiv:1612.02784] [PDF]
B. Thorpe, K. Kalna, F.C. Langbein, S.G. Schirmer. Monte Carlo Simulations of Spin Transport in Nanoscale InGaAs Field Effect Transistors. J Applied Physics, 122, 223903, 2017. [DOI:10.1063/1.4994148] [arXiv:1610.04114] [PDF]
S. G. Schirmer, E. Jonckheere, F. C. Langbein. Design of Feedback Control Laws for Information Transfer in Spintronics Networks. IEEE Trans Automatic Control, 63(8):2523-2536, 2018. [DOI:10.1109/TAC.2017.2777187] [arXiv:1607.05294] [PDF]
FC Langbein, S O’Neil, SG Schirmer. Energy landscape controllers for quantum state transfer in spin-1/2 networks with ring topology, Research Directions, Cambridge Open Engage, 2023. [DOI:10.33774/coe-2022-35xgg]
N. Rahimi, P. Kerfriden, F. C. Langbein, R.R. Martin. CAD Model simplification error estimation for electrostatics problems. SIAM J. Sci. Comput. 40(1):B196–B227, 2018. [DOI:10.1137/16M1078641] [arXiv:1606.02223] [PDF]
This code is an extension to PostgreSQL for finding CAD features efficiently. Development of this code has been supported by the Marie Curie Initial Training Network INSIST, funded by the 7th EU Framework Programme (FP7) under grant agreement n° 289361.
This code is to estimate the simplification error. It’s an an extension to ngsolve / netgen to estimate the effect of model simplifications on a quantity of interest aimed at electrostatics problems.