His primary areas of study are Control theory, Nonlinear system, Control theory, Quantum network and Quantum operation. In his study, Quantum system and Product is strongly linked to Quantum computer, which falls under the umbrella field of Control theory. Matthew R. James combines subjects such as Kalman filter, Partial differential equation and Dissipative system with his study of Nonlinear system.
His Quantum operation research incorporates themes from Quantum information and Quantum probability, Quantum process. The study incorporates disciplines such as Quantum technology and Applied mathematics in addition to Quantum probability. His work deals with themes such as Quantum algorithm and Quantum error correction, which intersect with Quantum process.
His main research concerns Control theory, Quantum, Nonlinear system, Control theory and Quantum system. As part of his studies on Control theory, he often connects relevant areas like Dynamic programming. His Quantum study incorporates themes from Quantum optics, Stochastic differential equation, Applied mathematics, Statistical physics and Topology.
His studies in Statistical physics integrate themes in fields like Quantum algorithm, Open quantum system, Quantum operation and Quantum probability, Quantum process. He usually deals with Quantum process and limits it to topics linked to Quantum dissipation and Quantum error correction. His Control theory study integrates concerns from other disciplines, such as Stability and Control system.
Quantum, Statistical physics, Control theory, Quantum system and Quantum state are his primary areas of study. His Quantum research includes elements of Stochastic differential equation, Gaussian and Topology. His Control theory research is multidisciplinary, relying on both Quantum capacity and Quantum operation.
His Quantum operation research incorporates elements of Quantum dissipation, Quantum channel and Quantum probability. The concepts of his Quantum state study are interwoven with issues in State and Mathematical optimization. His biological study spans a wide range of topics, including Control system and Optimal control.
His primary scientific interests are in Quantum, Statistical physics, Quantum system, Quantum operation and Control theory. His Quantum research is multidisciplinary, incorporating elements of Stochastic differential equation, Applied mathematics and Hilbert space. Matthew R. James combines subjects such as Colors of noise, Inequality and Quantum protocols with his study of Statistical physics.
He has included themes like Quantum information, Quantum algorithm, Quantum error correction and Quantum process in his Quantum operation study. Particularly relevant to Quantum probability is his body of work in Quantum process. His research on Control theory focuses in particular on Control theory.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Control of Linear Quantum Stochastic Systems
Matthew R. James;Hendra I. Nurdin;Ian R. Petersen.
Quantum-Atom Optics Downunder (2007), paper QME32 (2007)
An Introduction to Quantum Filtering
Luc Bouten;Ramon Van Handel;Matthew R. James.
Siam Journal on Control and Optimization (2007)
The Series Product and Its Application to Quantum Feedforward and Feedback Networks
J. Gough;M.R. James.
IEEE Transactions on Automatic Control (2009)
$H^{\infty}$ Control of Linear Quantum Stochastic Systems
M.R. James;H.I. Nurdin;I.R. Petersen.
IEEE Transactions on Automatic Control (2008)
Minimax optimal control of stochastic uncertain systems with relative entropy constraints
I.R. Petersen;M.R. James;P. Dupuis.
IEEE Transactions on Automatic Control (2000)
Coherent quantum LQG control
Hendra I. Nurdin;Matthew R. James;Ian R. Petersen.
Automatica (2009)
Risk-sensitive control and dynamic games for partially observed discrete-time nonlinear systems
M.R. James;J.S. Baras;R.J. Elliott.
IEEE Transactions on Automatic Control (1994)
Extending H-infinity Control to Nonlinear Systems: Control of Nonlinear Systems to Achieve Performance Objectives
J. William Helton;Matthew R. James.
(1987)
Squeezing Components in Linear Quantum Feedback Networks
John Edward Gough;Matthew R. James;Hendra I. Nurdin.
Physical Review A (2010)
Asymptotic analysis of nonlinear stochastic risk-sensitive control and differential games
Matthew R. James.
Mathematics of Control, Signals, and Systems (1992)
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