Related papers: Reinforcement learning assisted non-reciprocal opt…
Cavity optomechanical (COM) sensors, featuring efficient light-motion couplings, have been widely used for ultra sensitive measurements of various physical quantities ranging from displacements to accelerations or weak forces. Previous…
Reinforcement learning is finding its way to real-world problem application, transferring from simulated environments to physical setups. In this work, we implement vision-based alignment of an optical Mach-Zehnder interferometer with a…
Devices that achieve nonreciprocal microwave transmission are ubiquitous in radar and radio-frequency communication systems, and commonly rely on magnetically biased ferrite materials. Such devices are also indispensable in the readout…
We demonstrate nonreciprocal optical transmission for both intense classical fields and weak quantum signals within a reconfigurable optomechanical platform driven by three-mode parametric interactions. The platform is modular, where each…
Aligning a lens system relative to an imager is a critical challenge in camera manufacturing. While optimal alignment can be mathematically computed under ideal conditions, real-world deviations caused by manufacturing tolerances often…
In the present paper, a multi-frequency optical non-reciprocal transmission is first realized by using a non-Hermitian multi-mode resonator array.We find that the non-reciprocity can be used to route optical signals, to prevent the reverse…
We investigate perfect optical nonreciprocal transmission in a hybrid optomechanical system that incorporates an atomic ensemble. By introducing complex coupling strengths between the atomic ensemble and a mechanical oscillator,…
We study the nonreciprocal transmission and the fast-slow light effects in a cavity optomechanical system, in which the cavity supports a clockwise and a counter-clockwise circulating optical modes, both the two modes are driven…
Robot-assisted surgical systems have demonstrated significant potential in enhancing surgical precision and minimizing human errors. However, existing systems cannot accommodate individual surgeons' unique preferences and requirements.…
We study the nonreciprocal transmission of a single-photon in a cavity optomechanical system, in which the cavity supports a clockwise and a counter-clockwise circulating optical modes, the mechanical resonator (MR) is excited by a weak…
The recent surge of interest in temporal modulation schemes to induce magnet-free non-reciprocity has inspired several exciting opportunities for photonic technology. Here, we investigate a scheme to realize free-space isolators and highly…
Unmanned Aerial Vehicles (UAVs) are increasingly used in automated inspection, delivery, and navigation tasks that require reliable autonomy. This project develops a reinforcement learning (RL) approach to enable a single UAV to…
Resin infusion (RI) and resin transfer moulding (RTM) are critical processes for the manufacturing of high-performance fibre-reinforced polymer composites, particularly for large-scale applications such as wind turbine blades. Controlling…
We demonstrate experimentally the feasibility of applying reinforcement learning (RL) in flow control problems by automatically discovering active control strategies without any prior knowledge of the flow physics. We consider the turbulent…
This proceedings contains our considerations made during and after fruitful discussions held at EuCAIFCon 2025. We explore the use of deep reinforcement learning for autonomous locking of Fabry-Perot optical cavities in non-linear regimes,…
We propose nonreciprocal phonon lasing in a coupled cavity system composed of an optomechanical and a spinning resonator. We show that the optical Sagnac effect leads to significant modifications in both the mechanical gain and the power…
Photonic nonreciprocal components, such as isolators and circulators, provide highly desirable functionalities for optical circuitry. This motivates the active investigation of mechanisms that break reciprocity, and pose alternatives to…
This paper is a study of reinforcement learning (RL) as an optimal-control strategy for control of nonlinear valves. It is evaluated against the PID (proportional-integral-derivative) strategy, using a unified framework. RL is an autonomous…
Existing optical flow methods are erroneous in challenging scenes, such as fog, rain, and night because the basic optical flow assumptions such as brightness and gradient constancy are broken. To address this problem, we present an…
Nonreciprocal signal operation is highly desired for various acoustic applications, where protection from unwanted backscattering can be realized so that transmitting and receiving signals are processed in a full-duplex mode. Here we…