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Xiaoguang Huo

Publications and source records attributed to Xiaoguang Huo.

2 recordsLinked to original sources

Interaction-enhanced transmission imaging with Rydberg atoms

Atomic-scale imaging offers a reliable tool to directly measure the movement of microscopic particles. We present a scheme for achieving a nondestructive and ultrasensitive imaging of Rydberg atoms within an ensemble of cold probe atoms. This is made possible by the interaction-enhanced electromagnetically induced transparency at off-resonance which enables an extremely narrow absorption dip for an enhanced transmission. Through the transmission of a probe beam, we obtain the distribution of Rydberg atoms with both high spatial resolution and fast response, which ensures a more precise real-time imaging. Increased resolution compared to the prior interaction-enhanced imaging technique allows us to accurately locate the atoms by adjusting the probe detuning only. This new type of interaction-enhanced transmission imaging can be utilized to other impure systems containing strong many-body interactions, and is promising to develop super-resolution microscopy of cold atoms.

physics.atom-ph

Risk-Aware Multi-Armed Bandit Problem with Application to Portfolio Selection

Sequential portfolio selection has attracted increasing interests in the machine learning and quantitative finance communities in recent years. As a mathematical framework for reinforcement learning policies, the stochastic multi-armed bandit problem addresses the primary difficulty in sequential decision making under uncertainty, namely the exploration versus exploitation dilemma, and therefore provides a natural connection to portfolio selection. In this paper, we incorporate risk-awareness into the classic multi-armed bandit setting and introduce an algorithm to construct portfolio. Through filtering assets based on the topological structure of financial market and combining the optimal multi-armed bandit policy with the minimization of a coherent risk measure, we achieve a balance between risk and return.

q-fin.PM