Design and fabrication of ion traps for a scalable microwave quantum computer

This thesis describes the experimental work towards the development of a scalable quantum computer based on microfabricated ion trap using long-wavelength radiation and magnetic field gradient. There are three key elements in implementing such a quantum computer: the junction trap to shuttle ions, the structure to generate high gradient magnetic field and the structure to induce strong microwave coupling to the ions. A new dynamic simulation tool was developed addressing the problems faced by static solvers. This tool was used to aid the design and optimisation of an X junction geometry allowing the ions to be shuttled with minimised motional heating gain. The design and fabrication techniques were reported on the structure to generate a high gradient magnetic field. A discussion was given on the design of producing microwave and maximise the coupling to the cold ions. A review was given on the far-field methods and near-field methods. A novel design was reported where the single-qubit gate is predicted to be 45 times faster than a conventional setup. Two essential topics on the microfabrication of a reliable scalable quantum computer unit were discussed: breakdown and RF loss. Investigation using numerical simulations showed that dielectric can breakdown due to high voltage and local heating which are results of impedance mismatch. Microfabrication processes were improved, high-quality films were reported to have twice as much breakdown voltages. The mechanisms of RF loss were reviewed. Novel structures and smooth electroplating technique were developed to minimise the loss. A low loss ion trap was produced and tested. An experimentally observed anomalous glow discharge phenomenon was reported and investigated

A brief analysis of the positioning accuracy for the TH-2 satellite system

The TH-2 satellite system is China's first microwave surveying satellite system based on distributed interferometric technology. In this paper, the positioning accuracy of the satellite system is studied. According to the InSAR mechanism model, the error sources that affect the positioning accuracy are analyzed, and the InSAR data processing flow is designed. The satellite positioning accuracies in plain and mountain area are tested and verified by using the baseline measurement accuracy and ground processing accuracy of ground design and on-orbit test. The tests show that the plane and elevation accuracy of the satellite system after processing the measured data on orbit is better than that of the original simulation analysis at the baseline length of 700~1050 m in formation configuration, it can satisfy the surveying and mapping precision of 1∶50 000 scale topographic map in plain and mountain area for China

Key technologies for on-orbit azimuth antenna pattern measurement of TH-2 dual satellites

On-orbit (inflight) measurement of the antenna pattern of space-borne synthetic aperture radar (SAR) is an indispensable and important procedure for SAR calibration, performance tuning and index test. Usually, in practical on-orbit (inflight) measurement of the SAR antenna pattern, it is separated into the vertical (elevation) and the horizontal (azimuth) directions respectively. The TH-2 satellite set is made up of two satellites to enable bistatic interferometry SAR (InSAR) observation. At the beginning of the on-orbit tests, the two satellites adopted a "following" flying formation in which one satellite flew about 40 km away after the other one. In this phase, the two satellites worked independently in SAR observation model to facilitate calibration, tuning and test of the satellites individually. When conducting the azimuth antenna pattern measurement, the collected signals from the two satellites in the ground receiver were overlapped (interleaved) and superposed, leading to the difficulty of measurement with the method designed for only one satellite. Aiming at solving this problem, an efficient and fully automated signal separation method for azimuth antenna pattern measurement is proposed. Based on the modeling and analysis of the sampled signal in the ground receiver, a novel signal separation method based on three main parts: key pulse rising edge extraction, pulse position estimation and pulse amplitude estimation is proposed to realize the separation of the signals from different satellites. After signal separation, the subsequent antenna pattern measurement tasks can be done using the traditional single-satellite method. Experimental results sufficiently show the effectiveness of the proposed method. This method escorted the on-orbit tests of the satellites smoothly, and the test efficiency can be doubled compared with the individual test of each single satellite. The proposed method can be used in the on-orbit tests of similar satellites in the future

A powerful and efficient multivariate approach for voxel-level connectome-wide association studies

We describe an approach to multivariate analysis, termed structured kernel principal component regression (sKPCR), to identify associations in voxel-level connectomes using resting-state functional magnetic resonance imaging (rsfMRI) data. This powerful and computationally efficient multivariate method can identify voxel-phenotype associations based on the whole-brain connectivity pattern of voxels, and it can detect linear and non-linear signals in both volume-based and surface-based rsfMRI data. For each voxel, sKPCR first extracts low-dimensional signals from the spatially smoothed connectivities by structured kernel principal component analysis, and then tests the voxel-phenotype associations by an adaptive regression model. The method's power is derived from appropriately modelling the spatial structure of the data when performing dimension reduction, and then adaptively choosing an optimal dimension for association testing using the adaptive regression strategy. Simulations based on real connectome data have shown that sKPCR can accurately control the false-positive rate and that it is more powerful than many state-of-the-art approaches, such as the connectivity-wise generalized linear model (GLM) approach, multivariate distance matrix regression (MDMR), adaptive sum of powered score (aSPU) test, and least-square kernel machine (LSKM). Moreover, since sKPCR can reduce the computational cost of non-parametric permutation tests, its computation speed is much faster. To demonstrate the utility of sKPCR for real data analysis, we have also compared sKPCR with the above methods based on the identification of voxel-wise differences between schizophrenic patients and healthy controls in four independent rsfMRI datasets. The results showed that sKPCR had better between-sites reproducibility and a larger proportion of overlap with existing schizophrenia meta-analysis findings. Code for our approach can be downloaded from https://github.com/weikanggong/sKPCR. [Abstract copyright: Copyright © 2018 Elsevier Inc. All rights reserved.

Privacy Preserved Self-Awareness on the Community via Crowd Sensing

In social activities, people are interested in some statistical data, such as purchase records, monthly consumption, and health data, which are usually utilized in recommendation systems. And it is seductive for them to acquire the ranking of these data among friends or other communities. In the meantime, they want their privacy data to be confidential. Therefore, a strategy is presented to allow users to obtain the result of calculating their privacy data while preserving these data. In this method, firstly a polynomial approximation function model is set up for each user. Afterwards, “fragment” the coefficients of each model into pieces. Eventually “blend” all scraps to build the global model of all users. Users can use the global model to gain their corresponding ranking results after a special computing. Security analyses of three aspects elaborate the validity of proposed privacy method, even if some spiteful attackers try to steal private data of users, no matter who they are (users or someone outside the community). Experiments results manifest that the global model competently fits all users data and all privacy data are protected

The Rapidly Flaring Afterglow of the Very Bright and Energetic GRB 070125

We report on multi-wavelength observations, ranging from the X-ray to radio wave bands, of the IPN-localized gamma-ray burst GRB 070125. Spectroscopic observations reveal the presence of absorption lines due to O I, Si II, and C IV, implying a likely redshift of z = 1.547. The well-sampled light curves, in particular from 0.5 to 4 days after the burst, suggest a jet break at 3.7 days, corresponding to a jet opening angle of ~7.0 degrees, and implying an intrinsic GRB energy in the 1 - 10,000 keV band of around E = (6.3 - 6.9)x 10^(51) erg (based on the fluences measured by the gamma-ray detectors of the IPN network). GRB 070125 is among the brightest afterglows observed to date. The spectral energy distribution implies a host extinction of Av < 0.9 mag. Two rebrightening episodes are observed, one with excellent time coverage, showing an increase in flux of 56% in ~8000 seconds. The evolution of the afterglow light curve is achromatic at all times. Late-time observations of the afterglow do not show evidence for emission from an underlying host galaxy or supernova. Any host galaxy would be subluminous, consistent with current GRB host-galaxy samples. Evidence for strong Mg II absorption features is not found, which is perhaps surprising in view of the relatively high redshift of this burst and the high likelihood for such features along GRB-selected lines of sight.Comment: 50 pages, 9 figures, 5 tables Accepted to the Astrophysical Journa

Binary systems and their nuclear explosions

Peer ReviewedPreprin