相关论文: Maximizing the information gain of a single ion mi…

An apparatus for production of various atomic and molecular ions inside a linear Paul trap has been set up. The system applies a custom-made, low energy, pulsed electron gun to produce ions in electron impact process. Such ionization method…

Nanoscale focused ion beams (FIBs) represent one of the most useful tools in nanotechnology, enabling nanofabrication via milling and gas-assisted deposition, microscopy and microanalysis, and selective, spatially resolved doping of…

We present an alternative approach for interconnecting trapped ion processor nodes by a deterministic single ion transfer out of the trap, into a free space trajectory, followed by recapture in the trapping potential. Our experimental…

Bayesian inference provides a principled way of estimating the parameters of a stochastic process that is observed discretely in time. The overdamped Brownian motion of a particle confined in an optical trap is generally modelled by the…

Perm-selective ion transportation in a nanoscale structure has been extensively studied with aids of nanofabrication technology for a decade. While theoretical and experimental advances pushed the phenomenon to seminal innovative…

The Linac Coherent Light Source changes configurations multiple times per day, necessitating fast tuning strategies to reduce setup time for successive experiments. To this end, we employ a Bayesian approach to transport optics tuning to…

We present an imaging algorithm for polarimetric interferometric data from radio telescopes. It is based on Bayesian statistics and thereby able to provide uncertainties and to incorporate prior information such as positivity of the total…

We propose the combination of forward shape derivatives and the use of an iterative inversion scheme for Bayesian optimization to find optimal designs of nanophotonic devices. This approach widens the range of applicability of Bayesian…

Methods currently in use for locating and characterising sources in radio interferometry maps are designed for processing images, and require interferometric maps to be preprocessed so as to resemble conventional images. We demonstrate a…

Bayesian Optimal Experimental Design (BOED) is a powerful tool to reduce the cost of running a sequence of experiments. When based on the Expected Information Gain (EIG), design optimization corresponds to the maximization of some…

A simple model system is introduced for demonstrating how a single photon source might be used to transduce classical analog information. The theoretical scheme results in measurements of analog source samples that are (i) quantized in the…

Bayesian optimization is proposed for automatic learning of optimal controller parameters from experimental data. A probabilistic description (a Gaussian process) is used to model the unknown function from controller parameters to a…

We study a method for mass-selective removal of ions from a Paul trap by parametric excitation. This can be achieved by applying an oscillating electric quadrupole field at twice the secular frequency $\omega_{\text{sec}}$ using pairs of…

Design of experiments has traditionally relied on the frequentist hypothesis testing framework where the optimal size of the experiment is specified as the minimum sample size that guarantees a required level of power. Sample size…

Electron ptychography provides new opportunities to resolve atomic structures with deep sub-angstrom spatial resolution and studying electron-beam sensitive materials with high dose efficiency. In practice, obtaining accurate ptychography…

A source of deterministic single photons is proposed and demonstrated by the application of a measurement-based feedback protocol to a heralded single photon source consisting of an ensemble of cold rubidium atoms. Our source is stationary…

We demonstrate the ability to load, cool and detect singly-charged calcium ions in a surface electrode trap using only visible and infrared lasers for the trapped-ion control. As opposed to the standard methods of cooling using…

Bayesian optimization through Gaussian process regression is an effective method of optimizing an unknown function for which every measurement is expensive. It approximates the objective function and then recommends a new measurement point…

Techniques to reliably pick and place single nanoparticles into functional assemblies are required to incorporate exotic nanoparticles into standard electronic circuits. In this paper we explore the use of electric fields to drive and…

Integrated sensing and communications (ISAC) is a disruptive technology enabling future sixth-generation (6G) networks. This paper investigates target detection in a bistatic ISAC system, in which the base station (BS) transmits…