We study the dynamics of a driven optomechanical cavity coupled to a charged nanomechanical resonator via Coulomb interaction, in which the tunable double optomechanically induced transparency (OMIT) can be observed from the output field at the probe frequency by controlling the strength of the Coulomb interaction. We calculate the splitting of the two transparency windows, which varies near linearly with the Coulomb coupling strength in a robust way against the cavity decay. Our double-OMIT is much different from the previously mentioned double-EIT or double-OMIT, and might be applied to measure the Coulomb coupling strength.

We propose a system for realizing controllable optomechanically induced transparency (OMIT) and ponderomotive squeezing. In this system, an atomic ensemble driven by an external optical field couples with the cavity field in a typical optomechanical cavity. When the cavity is driven by a coupling laser and a probe laser, we can produce a switch for the probe field and adjust the width of the transparency window flexibly by manipulating the coupling strength between the atomic ensemble and the external optical field. We also investigate the ponderomotive squeezing properties of the transmitted field by analyzing its spectrum. Interestingly, the coupling strength between the atomic ensemble and the cavity field plays an important role in controlling the squeezing properties and the squeezing spectrum presents distinct features at red-detuned and blue-detuned frequencies by adjusting the coupling strength.

Optical techniques have boosted a new class of cryptographic systems with some remarkable advantages, and optical encryption not only has spurred practical developments but also has brought a new insight into cryptography. However, this does not mean that it is elusive for the opponents to attack optical encryption systems. In this paper, for the first time to our knowledge, we experimentally demonstrate the machine-learning attacks on interference-based optical encryption. Using machine-learning models that are trained by a series of ciphertext-plaintext pairs, an unauthorized person is capable to retrieve the unknown plaintexts from the given ciphertexts without the usage of various different optical encryption keys existing in interference-based optical encryption. In comparison with conventional cryptanalytic methods, the proposed machine-learning-based attacking method can estimate transfer function or point spread function of interference-based optical encryption systems without subsidiary conditions. Simulations and optical experiments demonstrate feasibility and effectiveness of the proposed method, and the proposed machine-learning-based attacking method provides a versatile approach to analyzing the vulnerability of interferencebased optical encryption.

We theoretically demonstrate an efficient method to control slow and fast light in microwave regime with a coupled system consisting of a nanomechanical resonator (NR) and a superconducting Cooper-pair box (CPB). Using the pump-probe technique, we find that both slow and fast light effects of the probe field can appear in this coupled system. Furthermore, we show that a tunable switch from slow light to fast light can be achieved by only adjusting the pump-CPB detuning from the NR frequency to zero. Our coupled system may have potential applications, for example, in optical communication, microwave photonics, and nonlinear optics.

Optical encryption has provided a new insight for securing information; however, it is always desirable that high security can be achieved to withstand the attacks. In this Letter, we propose a new method via learning complex scattering media for optical encryption. After the recordings through complex scattering media, a designed learning model is trained. The proposed method uses an optical setup with complex scattering media to experimentally record the ciphertexts and uses a learning model to generate security keys. During the decryption, the trained learning model with its parameters is applied as security keys. In addition, various parameters, e.g., virtual phase-only masks, can be flexibly applied to further enlarge key space. It is experimentally demonstrated that the proposed learning-based encryption approach possesses high security. The proposed method could open up a new research perspective for optical encryption.