Optimising the Solovay-Kitaev algorithm

The Solovay-Kitaev algorithm is the standard method used for approximating arbitrary single-qubit gates for fault-tolerant quantum computation. In this paper we introduce a technique called "search space expansion", which modifies the initial stage of the Solovay-Kitaev algorithm, increasing the length of the possible approximating sequences but without requiring an exhaustive search over all possible sequences. We show that our technique, combined with a GNAT geometric tree search outputs gate sequences that are almost an order of magnitude smaller for the same level of accuracy. This therefore significantly reduces the error correction requirements for quantum algorithms on encoded fault-tolerant hardware.Comment: 9 page

Understanding Interaction Capacity of CO2 with Organic Compounds at Molecular Level: A Theoretical Approach

In this chapter, interactions of CO2 with a number of organic compounds at molecular level are discussed in detail. The naked and substituted hydrocarbons along with compounds functionalized by hydroxyl, carbonyl, thiocarbonyl, carboxyl, sulfonyl, and amide groups have attracted much attention as CO2-philic agents. In general, interaction capacity between the functionalized organic compounds with CO2 is stronger than the hydrocarbon and its derivatives. An addition of more CO2 molecules into the interaction system formed by the functionalized organic compounds and CO2 leads to an increase in the stability of the complexes. The obtained results indicate that π…π linkages between CO2 and aromatic rings can significantly contribute to the interactions between CO2 and MOF/ZIF materials. Formic acid (HCOOH) is likely to be the most soluble compound as compared to the remaining host molecules (CH3OH, CH3NH2, HCHO, HCOOCH3, and CH3COCH3) when dissolved in CO2. The carbonyl (>C═O, >C═S) and sulfonyl (>S═O, >S═S) compounds have presented a higher stability, as compared to other functionalized groups, when they interact with CO2. Therefore, they can be valuable candidates in the design of CO2-philic materials and in the search of materials to adsorb CO2

VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning.

In this study, we introduce an ensemble selection method for deep ensemble systems called VEGAS. The deep ensemble models include multiple layers of the ensemble of classifiers (EoC). At each layer, we train the EoC and generates training data for the next layer by concatenating the predictions for training observations and the original training data. The predictions of the classifiers in the last layer are combined by a combining method to obtain the final collaborated prediction. We further improve the prediction accuracy of a deep ensemble model by searching for its optimal configuration, i.e., the optimal set of classifiers in each layer. The optimal configuration is obtained using the Variable-Length Genetic Algorithm (VLGA) to maximize the prediction accuracy of the deep ensemble model on the validation set. We developed three operators of VLGA: roulette wheel selection for breeding, a chunk-based crossover based on the number of classifiers to generate new offsprings, and multiple random points-based mutation on each offspring. The experiments on 20 datasets show that VEGAS outperforms selected benchmark algorithms, including two well-known ensemble methods (Random Forest and XgBoost) and three deep learning methods (Multiple Layer Perceptron, gcForest, and MULES)

A thorough theoretical investigation into complexes formed by interaction of dimethyl sulfoxide with two water molecules

A computational study of the stability and the cooperative effect of hydrogen bonds in the complexes of dimethyl sulfoxide and two water molecules was undertaken at the MP2/6-311++G(2d,2p) level of theory. The cooperative energies of obtained complexes are significantly negative, indicating that there is a large cooperativity between types of hydrogen bonds. The existence of the O−H∙∙∙O hydrogen bond present at dimer of water increases the stability of O−H∙∙∙O and C−H∙∙∙O hydrogen bonds in the ternary complexes compared to relevant binary complexes. By vibrational and NBO analyses, it is found that the magnitude of stretching frequency red shift of O−H bonds in the O−H···O hydrogen bonds is enhanced, whereas the extent of stretching frequency blue shift of C−H bonds in the C−H∙∙∙O hydrogen bonds is weakened when the cooperativity of hydrogen bonds happens in the ternary complexes. Obtained results of AIM analysis and stabilization energies indicate the larger contribution of the O−H∙∙∙O relative to the C−H∙∙∙O hydrogen bond to cooperativity. Keywords. Dimethyl sulfoxide, hydrogen bond, cooperativity

Multifactorial Evolutionary Algorithm For Clustered Minimum Routing Cost Problem

Minimum Routing Cost Clustered Tree Problem (CluMRCT) is applied in various fields in both theory and application. Because the CluMRCT is NP-Hard, the approximate approaches are suitable to find the solution for this problem. Recently, Multifactorial Evolutionary Algorithm (MFEA) has emerged as one of the most efficient approximation algorithms to deal with many different kinds of problems. Therefore, this paper studies to apply MFEA for solving CluMRCT problems. In the proposed MFEA, we focus on crossover and mutation operators which create a valid solution of CluMRCT problem in two levels: first level constructs spanning trees for graphs in clusters while the second level builds a spanning tree for connecting among clusters. To reduce the consuming resources, we will also introduce a new method of calculating the cost of CluMRCT solution. The proposed algorithm is experimented on numerous types of datasets. The experimental results demonstrate the effectiveness of the proposed algorithm, partially on large instance

Remarkable shifts of C(sp2)-H and O-H stretching frequencies and stability of complexes of formic acid with formaldehydes and thioformaldehydes

Thirty‐six stable complexes of formic acid with formaldehydes and thioformaldehydes were determined on the potential energy surface, in which the XCHO···HCOOH complexes are found to be more stable than the XCHS···HCOOH counterparts, with X = H, F, Cl, Br, CH3, NH2. All complexes are stabilized by hydrogen bonds, and their contribution to the total stabilization energy of the complexes increases in going from C‐H···S to C‐H···O to O‐H···S and finally to O‐H···O. Remarkably, a significant blueshift of Csp2‐H bond by 81–96 cm−1 in the Csp2‐H···O hydrogen bond has hardly ever been reported, and a considerable redshift of O‐H stretching frequency by 206–544 cm−1 in the O‐H···O/S hydrogen bonds is also predicted. The obtained results in our present work and previous literatures support that a distance contraction and a stretching frequency blueshift of C‐H bond involving hydrogen bond depend mainly on its polarity and gas phase basicity of proton acceptor, besides the rearrangement of electron density due to complex formation. Markedly, we suggest the ratio of deprotonation enthalpy to proton affinity (R c) as an indicator to prospect for classification of hydrogen bonds. The symmetry adapted perturbation theory results show a larger role of attractive electrostatic term in XO‐n as compared to that in XS‐n and the electrostatic interaction is overwhelming dispersion or induction counterparts in stabilizing XO‐n and XS‐n, with n = 1, 2, 3

Development of UV Laser Source Based on Distributed Feedback Dye Lasers Foruse in Measurement of Ozone in the Lower Atmosphere

We conducted a study to develop a transmitter consisting of two Distributed Feedback Dye Lasers (DFDL) using Rhodamine 6G as an active medium, pumped by a frequency-doubled Nd:YAG laser (5ns, 10 Hz, 532 nm). The BBO crystals are used for frequency-doubling of DFDLs to generate UV missions. This system has been set up and it generates selected wavelenghts at 282.9 nm and 286.4 nm with the energy of 30 $\mu$J/pulse and 60 $\mu$J/pulse respectively. A DIAL system using this UV transmitter is designed to measure the vertical distribution of ozone with high temporal and spatial resolution. Our simulations of received DIAL signal indicate that the altitude of ozone distribution measurement can reach to over 5000 m along with range resolution of 100 m

Transformer-Based Deep Learning Detector for Dual-Mode Index Modulation 3D-OFDM

In this paper, we propose a deep learning-based signal detector called TransD3D-IM, which employs the Transformer framework for signal detection in the Dual-mode index modulation-aided three-dimensional (3D) orthogonal frequency division multiplexing (DM-IM-3D-OFDM) system. In this system, the data bits are conveyed using dual-mode 3D constellation symbols and active subcarrier indices. As a result, this method exhibits significantly higher transmission reliability than current IM-based models with traditional maximum likelihood (ML) detection. Nevertheless, the ML detector suffers from high computational complexity, particularly when the parameters of the system are large. Even the complexity of the Log-Likelihood Ratio algorithm, known as a low-complexity detector for signal detection in the DM-IM-3D-OFDM system, is also not impressive enough. To overcome this limitation, our proposal applies a deep neural network at the receiver, utilizing the Transformer framework for signal detection of DM-IM-3D-OFDM system in Rayleigh fading channel. Simulation results demonstrate that our detector attains to approach performance compared to the model-based receiver. Furthermore, TransD3D-IM exhibits more robustness than the existing deep learning-based detector while considerably reducing runtime complexity in comparison with the benchmarks

Factors Affecting Successful Quality Assurance Implementation in Vietnamese Higher Education: A Qualitative Study

Quality assurance and accreditation was officially introduced into the higher education system in Vietnam over ten years ago. It is evident that quality assurance has resulted in positive impacts on university management, teaching, learning and research activities. This paper aims to explore factors that aid the successful implementation of higher education quality assurance and accreditation in Vietnam. Through semi-structured interviews with 32 participants, this study identified a number of factors that contributed to quality assurance processes, including awareness of the importance of quality assurance, better institutional manager leadership, support of university lecturers, staff, and students, and the vital responsibility of internal quality assurance staff. These confirm that internal stakeholders play an important role in undertaking quality assurance programmes and activities

Isogeometric Analysis for BIM-Based Design and Simulation of Sub-Rectangular Tunnel

The design and analysis of segmental tunnel lining is today often based on empirical solutions with simplified assumptions. This work showcases the application of Isogeometric Analysis (IGA) for computationally efficient simulations of tunnel linings [1, 2]. In our past research, we developed a design-through-analysis procedure that consists of i) parametric modeling of the segmented tunnel lining; ii) development of an IGA computational framework, iii) reconstruction of the BIM lining model for IGA analysis, and iv) simulation model for lining including a reconstructed IGA model, contact interfaces between the joints, and a non-linear soil-structure interaction model based on the Variational Hyperstatic Reaction Method (VHRM) [3].In this paper, we extend our method for the analysis of subrectangular tunnel linings and demonstrate its efficiency using the example of the Shanghai express tunnel. The advantage of our novel method is the flexibility in adapting the tunnel alignment with the help of NURBS/CAD technology. Employing the high-order geometry definition, convergence of the mesh refinement procedure can be obtained with much faster rate. As a result, the modelling effort and computational time are reduced significantly. Moreover, this approach allows to capture the bending moment with better regularity. The combination with an existing BIM modelling approach via geometryreconstruction leads to a very efficient framework for tunnel lining analysis and design