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Ming-Yan Sun

Publications and source records attributed to Ming-Yan Sun.

4 recordsLinked to original sources

Programmable optical parametric amplifier synthesizer for cubic phase states and amplified Schrodinger cat states

We introduce a programmable optical parametric amplifier (OPA) synthesizer that, under a heralded photon-number-resolving framework, generates high-fidelity cubic phase states and amplifies Schrodinger cat states. By systematically exploring both the catalytic configuration, where the idler input and output contain the same number of photons ($m=n$), and non-catalytic configurations ($m\neq n$), we discover two qualitatively different functionalities. First, with a coherent-state signal input, our protocol generates cubic phase states with fidelity exceeding 0.99 across a broad range of $(m,n)$ configurations. Second, using a Schr\"odinger cat state as the signal input, the same framework amplifies the cat state: an input cat with amplitude $\alpha_{\mathrm{in}}\le 1$ is transformed into an output squeezed cat with $\alpha_{\mathrm{out}}\ge 2$ while maintaining fidelity above 0.99. The catalytic configuration preserves the input parity and restores the idler state, whereas non-catalytic configurations enable parity-flipping amplification with higher success rates. Moreover, the amplified output can serve as a seed for subsequent amplification rounds, offering a self-seeding pathway to progressively larger cat states. Our protocol requires only moderate-gain OPA operation and low-order photon-number-resolving detection, providing a flexible and experimentally accessible platform for cubic phase state preparation and amplified squeezed cat state generation.

quant-ph

Multiphoton heralding generates large-amplitude squeezed Schr\"odinger cat states and parity-selective Fock superpositions from squeezed vacuum via an OPA

We propose a multiphoton heralding scheme using an optical parametric amplifier (OPA) that converts squeezed vacuum into two families of non-Gaussian states: large-amplitude squeezed Schr\"odinger cat states and low-order parity-selective Fock superpositions. By injecting m photons into the idler port and detecting n photons at the output, effective high-order photon subtraction is realized in a single OPA device. The heralded states exhibit strong Wigner negativity and high phase-space complexity. Remarkably, under photon loss, the complexity remains substantial even after negativity vanishes, indicating a loss-resilient quantum resource. These states also surpass the Heisenberg limit in phase estimation. Our protocol establishes the OPA as a versatile platform for generating non-Gaussian states, with promising applications in loss-resilient quantum metrology and fault-tolerant quantum information processing.

quant-ph

JefiAtten: An Attention Based Neural Network Model for Solving Maxwell's Equations with Charge and Current Sources

We present JefiAtten, a novel neural network model employing the attention mechanism to solve Maxwell's equations efficiently. JefiAtten uses self-attention and cross-attention modules to understand the interplay between charge density, current density, and electromagnetic fields. Our results indicate that JefiAtten can generalize well to a range of scenarios, maintaining accuracy across various spatial distribution and handling amplitude variations. The model showcases an improvement in computation speed after training, compared to traditional integral methods. The adaptability of the model suggests potential for broader applications in computational physics, with further refinements to enhance its predictive capabilities and computational efficiency. Our work is a testament to the efficacy of integrating attention mechanisms with numerical simulations, marking a step forward in the quest for data-driven solutions to physical phenomena.

physics.comp-ph

RBG-Maxwell Framework: Simulation of Collisional Plasma Systems via Coupled Boltzmann-Maxwell equations on GPU

This paper presents the RBG-Maxwell framework, a relativistic collisional plasma simulator on GPUs. We provide detailed discussions on the fundamental equations, numerical algorithms, implementation specifics, and key testing outcomes. The RBG-Maxwell framework is a robust numerical code designed for simulating the evolution of plasma systems through a kinetic approach on large-scale GPUs. It offers easy adaptability to a wide range of physical systems. Given the appropriate initial distributions, particle masses, charges, differential cross-sections, and external forces (which are not confined to electromagnetic forces), the RBG-Maxwell framework can direct the evolution of a particle system from a non-equilibrium state to a thermal state.

physics.plasm-ph