We present our recent effort towards building an integrated photonic circuitry on thin-film lithium niobate platform for squeezed state of light generation from an optical parametric oscillator.
ISBN:
(纸本)9781957171258
We present our recent effort towards building an integrated photonic circuitry on thin-film lithium niobate platform for squeezed state of light generation from an optical parametric oscillator.
We propose a model-based reinforcement learning (RL) approach for noisy time-dependent gate optimization with reduced sample complexity over model-free RL. Sample complexity is defined as the number of controller inte...
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We propose a model-based reinforcement learning (RL) approach for noisy time-dependent gate optimization with reduced sample complexity over model-free RL. Sample complexity is defined as the number of controller interactions with the physical system. Leveraging an inductive bias, inspired by recent advances in neural ordinary differential equations (ODEs), we use an autodifferentiable ODE, parametrized by a learnable Hamiltonian ansatz, to represent the model approximating the environment, whose time-dependent part, including the control, is fully known. Control alongside Hamiltonian learning of continuous time-independent parameters is addressed through interactions with the system. We demonstrate an order of magnitude advantage in sample complexity of our method over standard model-free RL in preparing some standard unitary gates with closed and open system dynamics, in realistic computational experiments incorporating single-shot measurements, arbitrary Hilbert space truncations, and uncertainty in Hamiltonian parameters. Also, the learned Hamiltonian can be leveraged by existing control methods like GRAPE (gradient ascent pulse engineering) for further gradient-based optimization with the controllers found by RL as initializations. Our algorithm, which we apply to nitrogen vacancy (NV) centers and transmons, is well suited for controlling partially characterized one- and two-qubit systems.
Addressing the urgency of climate change necessitates a coordinated and inclusive effort from all relevant stakeholders. Critical to this effort is the modeling, analysis, control, and integration of technological inn...
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The duality between controllability and observability enables methods developed for full-state control to be applied to full-state estimation, and vice versa. In applications in which control or estimation of all stat...
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Detecting a non-zero electric dipole moment (EDM) in a particle would unambiguously signify physics beyond the Standard Model. A potential pathway towards this is the detection of a nuclear Schiff moment, the magnitud...
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Steganography and digital watermarking are the tasks of hiding recoverable data in image pixels. Deep neural network (DNN) based image steganography and watermarking techniques are quickly replacing traditional hand-e...
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We experimentally report on a real-time self-guided method to search for maximal CHSH violations between two observers sharing polarization entangled photon pairs using uncalibrated piezoelectric fiber squeezers as po...
We report on the formation of surface relief structures of azopolymers by irradiation of optical skyrmionic hopfion. The reliefs reflect exotic polarization textures of hopfion and will pave the way for advanced rewri...
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ISBN:
(数字)9798350372076
ISBN:
(纸本)9798350372083
We report on the formation of surface relief structures of azopolymers by irradiation of optical skyrmionic hopfion. The reliefs reflect exotic polarization textures of hopfion and will pave the way for advanced rewritable-ultrahigh-density optical data-storages.
Quantum information processing has conceptually changed the way we process and transmit information. Our understanding of quantum physics, which explains the seemingly strange behavior of matter at the microscopic sca...
Quantum information processing has conceptually changed the way we process and transmit information. Our understanding of quantum physics, which explains the seemingly strange behavior of matter at the microscopic scales, has matured to the extent that we can now explore technologies based on the phenomenon. One such exciting application of quantum physics with far-reaching consequences is quantum computing. Quantum computing, which uses quantum bits (qubits) for information processing, has changed the way we process and transmit information in a fundamental way. Experiments suggest that the most successful candidates for realizing qubits are photons. Therefore, integrated photonic platforms play a crucial role in harnessing the potential of quantum technology. This paper surveys the various photonic platforms based on different materials for quantum information processing. The future of this technology depends on the successful materials that can be used to universally realize quantum devices, similar to silicon, which shaped the industry toward the end of the last century. While it would be hazardous to make definitive predictions about the quantum revolution, our overview of the current status of research on the various platforms based on the materials used could shed light on how the future of quantum computing could unfold.
This paper presents a (transceiver) TRX front-end structure design for Phased Array applications in 40nm CMOS Bulk process. The proposed structure consists of the Power Amplifier (PA) the Low Noise Amplifier (LNA) alo...
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