We build upon recent work on the use of machine-learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supe...
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We build upon recent work on the use of machine-learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning, where the weak-measurement training record can be labeled with known Hamiltonian parameters, and (2) unsupervised learning, where no labels are available. The first has the advantage of not requiring an explicit representation of the quantum state, thus potentially scaling very favorably to a larger number of qubits. The second requires the implementation of a physical model to map the Hamiltonian parameters to a measurement record, which we implement using an integrator of the physical model with a recurrent neural network to provide a model-free correction at every time step to account for small effects not captured by the physical model. We test our construction on a system of two qubits and demonstrate accurate prediction of multiple physical parameters in both the supervised context and the unsupervised context. We demonstrate that the model benefits from larger training sets, establishing that it is “learning,” and we show robustness regarding errors in the assumed physical model by achieving accurate parameter estimation in the presence of unanticipated single-particle relaxation.
Collaboration of agents in a natural swarm enables the accomplishment of tasks that would be difficult or impossible for a single agent to complete alone. For example, a swarm of autonomous Unmanned Aerial Vehicles (U...
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Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist...
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Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.
Well-known implementations of software systems for predicting sports events based on artificial neural networks do not provide sufficiently accurate results in individual sports. The main difficulty in this case is th...
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This paper presents a case study to evaluate the impact of the low-voltage ride-through (LVRT) on the virtual synchronous generator (VSG) strategy performance applied to power flow control in grid-forming distributed ...
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This paper is concerned with the problem of safety stabilization for switched systems where the solvability of the problem under study for individual subsystems is not assumed.A new state-dependent switching strategy ...
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This paper is concerned with the problem of safety stabilization for switched systems where the solvability of the problem under study for individual subsystems is not assumed.A new state-dependent switching strategy with guaranteed dwell-time for switched systems is constructed,and a sufficient condition for absence of Zeno behavior is ***,a novel switched control design method is proposed to simultaneously guarantee the safety of the switched closed-loop system and stabilize the system based on the union of a common barrier function and a single Lyapunov function,which effectively handles the conflict between safety and stability ***,two examples are presented to demonstrate the effectiveness of the proposed design approach.
In this paper, we present a Risk-Aware Nonlinear Reduced-Order Model Predictive control framework that utilizes real-time state estimation, reduced-order modeling, and optimization for reliable and efficient path plan...
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In this paper, an improved 3D objective detection algorithm called Frustum PSPNet (F-PSPNet) is proposed combing RGB algorithm and point cloud data. First, the 2D region proposals in the RGB image are generated by usi...
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Marine autonomy research has focused on al-gorithmic and technical developments, targeting autonomous craft in restricted areas where international rules and regu-lations are not prioritised. This paper addresses the ...
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This paper explains in detail the development, validation and simulation of a standard PI controller that can boost the WECS (Wind energy conversion system) power through two strategies. In the first strategy, the pow...
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