A fast quantum mechanical algorithm for estimating the median

光学机械系统中阶梯状机械能增长

Staircase mechanical energy growth in optomechanical systems of median mechanical frequencies

研究发现，在中等机械频率的光学机械系统中，双频驱动下机械谐振子能量呈现阶梯状增长现象，揭示了其动态特性及应用潜力。

A framework for fast quantum mechanical algorithms

A framework is presented for the design and analysis of quantum mechanical algorithms, the sqrt(N) step quantum search algorithm is an immediate consequence of this framework. It leads to several other search-type applications - several examples are presented. Also, it leads to quantum mechanical algorithms for problems not immediately connected with search - two such algorithms are presented for estimating the mean and median of statistical distributions. Both algorithms require fewer steps than the fastest possible classical algorithms; also both are considerably simpler and faster than exis…

Directly estimating non-classicality

We establish a method of directly measuring and estimating non-classicality - operationally defined in terms of the distinguishability of a given state from one with a positive Wigner function. It allows to certify non-classicality, based on possibly much fewer measurement settings than necessary for obtaining complete tomographic knowledge, and is at the same time equipped with a full certificate. We find that even from measuring two conjugate variables alone, one may infer the non-classicality of quantum mechanical modes. This method also provides a practical tool to eventually certify such …

Multi-parameter Optimization for Ground-state Cooling of Mechanical Mode using Quantum Dots

Cooling a mechanical mode to its motional ground state opens up avenues for both scientific and technological advancements in the field of quantum meteorology and information processing. We propose a multi-parameter optimization scheme for ground-state cooling of a mechanical mode using quantum dots. Applying the master equation approach, we formulate the optimization scheme over a broad range of system parameters including detunings, decay rates, pumping rates, and coupling strengths. We implement the optimization scheme on two major types of semiconductor quantum dot systems: colloidal and e…

Quantum Telecomputation

Quantum mechanics permits certain kinds of non-local effects. This paper demonstrates how these can be used for distributed computation with minimal communication between various processors. The problem considered is that of estimating the mean of N items to a certain precision. First a serial quantum mechanical algorithm for this is presented that is faster than any classical algorithm. Next it is shown how this can be efficiently parallelized with quantum mechanical processors that are remotely located. These processors consist of coupled EPR particles. Each processor has just to communicate…

Estimating the Euclidean quantum propagator with deep generative modeling of Feynman paths

Feynman path integrals provide an elegant, classically inspired representation for the quantum propagator and the quantum dynamics, through summing over a huge manifold of all possible paths. From computational and simulational perspectives, the ergodic tracking of the whole path manifold is a hard problem. Machine learning can help, in an efficient manner, to identify the relevant subspace and the intrinsic structure residing at a small fraction of the vast path manifold. In this work, we propose the Feynman path generator for quantum mechanical systems, which efficiently generates Feynman pa…