Qutrit Dichromatic Calculus and Its Universality

We introduce a dichromatic calculus (RG) for qutrit systems. We show that the decomposition of the qutrit Hadamard gate is non-unique and not derivable from the dichromatic calculus. As an application of the dichromatic calculus, we depict a quantum algorithm with a single qutrit. Since it is not easy to decompose an arbitrary d by d unitary matrix into Z and X phase gates when d > 2, the proof of the universality of qudit ZX calculus for quantum mechanics is far from trivial. We construct a counterexample to Ranchin's universality proof, and give another proof by Lie theory that the qudit ZX calculus contains all single qudit unitary transformations, which implies that qudit ZX calculus, with qutrit dichromatic calculus as a special case, is universal for quantum mechanics.Comment: In Proceedings QPL 2014, arXiv:1412.810

Stochastic Block Coordinate Frank-Wolfe Algorithm for Large-Scale Biological Network Alignment

With increasingly "big" data available in biomedical research, deriving accurate and reproducible biology knowledge from such big data imposes enormous computational challenges. In this paper, motivated by recently developed stochastic block coordinate algorithms, we propose a highly scalable randomized block coordinate Frank-Wolfe algorithm for convex optimization with general compact convex constraints, which has diverse applications in analyzing biomedical data for better understanding cellular and disease mechanisms. We focus on implementing the derived stochastic block coordinate algorithm to align protein-protein interaction networks for identifying conserved functional pathways based on the IsoRank framework. Our derived stochastic block coordinate Frank-Wolfe (SBCFW) algorithm has the convergence guarantee and naturally leads to the decreased computational cost (time and space) for each iteration. Our experiments for querying conserved functional protein complexes in yeast networks confirm the effectiveness of this technique for analyzing large-scale biological networks

Critical phenomena in gravitational collapse of Husain-Martinez-Nunez scalar field

We construct analytical models to study the critical phenomena in gravitational collapse of the Husain-Martinez-Nunez massless scalar field. We first use the cut-and-paste technique to match the conformally flat solution ($c=0$ ) onto an outgoing Vaidya solution. To guarantee the continuity of the metric and the extrinsic curvature, we prove that the two solutions must be joined at a null hypersurface and the metric function in Vaidya spacetime must satisfy some constraints. We find that the mass of the black hole in the resulting spacetime takes the form $M\propto (p-p^*)^\gamma$, where the critical exponent $\gamma$ is equal to $0.5$. For the case $c\neq 0$, we show that the scalar field must be joined onto two pieces of Vaidya spacetimes to avoid a naked singularity. We also derive the power-law mass formula with $\gamma=0.5$. Compared with previous analytical models constructed from a different scalar field with continuous self-similarity, we obtain the same value of $\gamma$. However, we show that the solution with $c\neq 0$ is not self-similar. Therefore, we provide a rare example that a scalar field without self-similarity also possesses the features of critical collapse.Comment: 14 pages, 6 figure

Negative Transfer of Chinese in English Learners’ Lexical Learning: A Markedness Theory Perspective

Based on the markedness theory, the article discusses the negative transfer of Chinese in English learners’ lexical learning from the morphological, semantic and pragmatic perspectives, proposes that raising the English learners’ markedness awareness and encouraging the students to read extensively to enhance their communicative competence facilitates overcoming the negative transfer

Cultivating Online English Learner Autonomy in Internet Plus Era: A DST Perspective

Based on Dynamic Systems Theory (DST), the article proposes that cultivating online English learner autonomy is a complex dynamic system. Under the interactions of learners, learning resources, learning task and learning environment, the development of online English learner autonomy is featured with being non-linearity, self-organization and “butterfly effects”. It proposes that in internet plus era, online English learner autonomy can be improved in resource-based, technology-based, student-based and teacher-based approach

Size and shape specific particles toward biomedical imaging: design, fabrication, and characterization

Thesis (Ph.D.)--Boston UniversityThe power of a biomedical imaging modality can be augmented and is, in large part, determined by the capabilities of the available contrast agents. For example, quantum dots represent a colorful palette of powerful contrast agents for optical fluorescence imaging and Raman spectroscopy, given their tunable multiplexing capability and long-term stability compared to traditional organic molecule-based fluorescent labels. On the contrary, as the workhorses in both clinical and research imaging, the full potentials of magnetic resonance imaging and computed tomography have yet to be actualized due to several existing fundamental limitations in the currently available contrast agents, including but not limited to, the lack of multiplexing capability, low sensitivity, as well as the lack of functional imaging capacity. Leveraging both traditional top-down micro- and nanoelectromechanical systems fabrication techniques and bottom-up self-assembly approaches, this dissertation explores the possibility of mitigating these limitations by engineering precisely controllable, size and shape (as well as a host of other materials properties) specific micro- and nanoparticles, for use as the next generation contrast agents for magnetic resonance imaging and computed tomography. Herein, the ways by which engineering approaches can impact the design, fabrication and characterization of contrast agents is investigated. Specifically, different configmations of magnetic micro- and nanoparticles, including double-disk and hollow-cylinder structmes, fabricated using a top-down approach were employed as magnetic resonance imaging contrast agents enabled with a multiplexing capability and improved sensitivity. Subsequently, a scalable nanomanufactming platform, utilizing nanoporous anodized aluminum oxide membranes as templates for pattern transfer as well as thermal/ultraviolet nanoimprinting techniques, was developed for the high throughput fabrication of size and shape specific polymeric nanorods. When ladened with X-ray attenuating tantalum oxide nanoparticle payloads, these polymeric nanorods can be used as contrast agents for computed tomography, yielding prolonged vascular circulation times, improved sensitivity, as well as targeted imaging capabilities. Furthermore, by applying various payload materials, this nanomanufacturing platform also has the flexibility to produce contrast agents for other imaging modalities, as well as the potential to realize dual-purpose agents for both diagnostic and therapeutic applications

Charm Production in Deep Inelastic Scattering from Threshold to High $Q^{2}

Charm final states in deep inelastic scattering constitute $\sim 25$ of the inclusive cross-section at small $x$ as measured at HERA. These data can reveal important information on the charm and gluon structure of the nucleon if they are interpreted in a consistent perturbative QCD framework which is valid over the entire energy range from threshold to the high energy limit. We describe in detail how this can be carried out order-by-order in PQCD in the generalized \msbar formalism of Collins (generally known as the ACOT approach), and demonstrate the inherent smooth transition from the 3-flavor to the 4-flavor scheme in a complete order $\alpha_s$ calculation, using a Monte Carlo implementation of this formalism. This calculation is accurate to the same order as the conventional NLO $F_2$ calculation in the limit $\frac{Q}{m_c} >> 1$. It includes the resummed large logarithm contributions of the 3-flavor scheme (generally known in this context as the fixed-flavor-number or FFN scheme) to all orders of $\alpha_s\ln(m_c^2/Q^2)$. For the inclusive structure function, comparison with recent HERA data and the existing FFN calculation reveals that the relatively simple order-$\alpha_s$ (NLO) 4-flavor ($m_c \neq 0$) calculation can, in practice, be extended to rather low energy scales, yielding good agreement with data over the full measured $Q^2$ range. The Monte Carlo implementation also allows the calculation of differential distributions with relevant kinematic cuts. Comparisons with available HERA data show qualitative agreement; however, they also indicate the need to extend the calculation to the next order to obtain better description of the differential distributions.Comment: 22 pages (LATEX), 8 figures (EPS); A few clarifying changes made; version published in JHE

An Aircraft Ranging Algorithm Based on Two Frames of Image in Monocular Image Sequence

We proposed a novel rotation-invariant feature based passive ranging algorithm to estimate the distance of an imaged non-cooperation target to camera. This improved algorithm avoids sometimes occurrence of physically unreasonable results in solving the existing quartic equation, such as the happening of complex or negative value. This method uses three matched points in two adjacent frames of an image sequence to extract depth-dependent line features of the target. With this line features combination of the observer’s displacement and imaging directions, a quadratic equation was build to estimate the distance. Analysis shows that the proposed new passive ranging equation would be solvable when the observer is with non-zero displacement in adjacent sampling instances. Our reduced-model experiment also demonstrates that the proposed algorithm is not only simple and feasible but also with a relative ranging error no more than 4 per cent in most cases.Defence Science Journal, Vol. 64, No. 1, January 2014, DOI:10.14429/dsj.64.288

Numerical simulation of clouds and precipitation depending on different relationships between aerosol and cloud droplet spectral dispersion

The aerosol effects on clouds and precipitation in deep convective cloud systems are investigated using the Weather Research and Forecast (WRF) model with the Morrison two-moment bulk microphysics scheme. Considering positive or negative relationships between the cloud droplet number concentration (Nc) and spectral dispersion (ɛ), a suite of sensitivity experiments are performed using an initial sounding data of the deep convective cloud system on 31 March 2005 in Beijing under either a maritime (‘clean’) or continental (‘polluted’) background. Numerical experiments in this study indicate that the sign of the surface precipitation response induced by aerosols is dependent on the ɛ−Nc relationships, which can influence the autoconversion processes from cloud droplets to rain drops. When the spectral dispersion ɛ is an increasing function of Nc, the domain-average cumulative precipitation increases with aerosol concentrations from maritime to continental background. That may be because the existence of large-sized rain drops can increase precipitation at high aerosol concentration. However, the surface precipitation is reduced with increasing concentrations of aerosol particles when ɛ is a decreasing function of Nc. For the ɛ−Nc negative relationships, smaller spectral dispersion suppresses the autoconversion processes, reduces the rain water content and eventually decreases the surface precipitation under polluted conditions. Although differences in the surface precipitation between polluted and clean backgrounds are small for all the ɛ−Nc relationships, additional simulations show that our findings are robust to small perturbations in the initial thermal conditions. Keywords: aerosol indirect effects, cloud droplet spectral dispersion, autoconversion parameterization, deep convective systems, two-moment bulk microphysics schem