相关论文: Extreme Spin Squeezing from Deep Reinforcement Lea…

The open radio access network (O-RAN) architecture supports intelligent network control algorithms as one of its core capabilities. Data-driven applications incorporate such algorithms to optimize radio access network (RAN) functions via…

We study the generation of metrologically useful entanglement in a three-level (spin-1) system naturally realized in arrays of dipole-interacting Rydberg atoms confined in optical tweezers. In the spin-quadrupolar operator basis, the…

Entangled atomic states, such as spin squeezed states, represent a promising resource for a new generation of quantum sensors and atomic clocks. We demonstrate that optimal control techniques can be used to substantially enhance the degree…

We discuss the possibility of generating spin squeezed states by means of driven superradiance, analytically affirming and broadening the finding in [Phys. Rev. Lett. 110, 080502 (2013)]. In an earlier paper [Phys. Rev. Lett. 112, 140402…

Spin-orbit coupling in solids describes an interaction between an electron's spin, an internal quantum-mechanical degree of freedom, with its linear momentum, an external property. Spin-orbit interaction, due to its relativistic nature, is…

Classical pixel-based Visual Servoing (VS) approaches offer high accuracy but suffer from a limited convergence area due to optimization nonlinearity. Modern deep learning-based VS methods overcome traditional vision issues but lack…

Discrimination of entangled states is an important element of quantum enhanced metrology. This typically requires low-noise detection technology. Such a challenge can be circumvented by introducing nonlinear readout process. Traditionally,…

The spin-orbit coupling (SOC) can mediate electric-dipole spin resonance (EDSR) in an a.c. electric field. In this letter, the EDSR is essentially understood as an spin precession under an effective a.c. magnetic field induced by the SOC in…

The remarkable properties of silicon have made it the central material for the fabrication of current microelectronic devices. Silicon's fundamental properties also make it an attractive option for the development of devices for spintronics…

Squeezed states of spin systems are an important entangled resource for quantum technologies, particularly quantum metrology and sensing. Here we consider the generation of spin squeezed states by interacting the spins with a dissipative…

This paper describes a deep reinforcement learning (DRL) approach that won Phase 1 of the Real Robot Challenge (RRC) 2021, and then extends this method to a more difficult manipulation task. The RRC consisted of using a TriFinger robot to…

Quantum entanglement can provide enhanced precision beyond standard quantum limit (SQL), the highest precision achievable with classical means. It remains challenging, however, to observe large enhancement limited by the experimental…

Control theory provides engineers with a multitude of tools to design controllers that manipulate the closed-loop behavior and stability of dynamical systems. These methods rely heavily on insights about the mathematical model governing the…

Deep Reinforcement Learning (deep RL) has made several breakthroughs in recent years in applications ranging from complex control tasks in unmanned vehicles to game playing. Despite their success, deep RL still lacks several important…

This study presents the first experimental implementation of deep reinforcement learning (DRL) for the active real-time suppression of flow-induced vibrations in simultaneously vibrating tandem cylinders using rotary actuation, considering…

Spin models are the prime example of simplified manybody Hamiltonians used to model complex, real-world strongly correlated materials. However, despite their simplified character, their dynamics often cannot be simulated exactly on…

We investigate the spin dynamics of a quantum dot with a spin-1/2 ground state in the Coulomb blockade regime and in the presence of a magnetic rf field leading to electron spin resonances (ESR). We show that by coupling the dot to leads,…

High-fidelity control of one- and two-qubit gates past the error correction threshold is an essential ingredient for scalable quantum computing. We present a reinforcement learning (RL) approach to find entangling protocols for…

Parkinson's disease is marked by altered and increased firing characteristics of pathological oscillations in the brain. In other words, it causes abnormal synchronous oscillations and suppression during neurological processing. In order to…

We propose a scheme leveraging reinforcement learning to engineer control fields for generating non-classical states. It is exemplified by the application to prepare spin-squeezed states for an open collective spin model where a linear…