Solar cycle variation of real CME latitudes

With the assumption of radial motion and uniform longitudinal distribution of coronal mass ejections (CMEs), we propose a method to eliminate projection effects from the apparent observed CME latitude distribution. This method has been applied to SOHO LASCO data from 1996 January to 2006 December. As a result, we find that the real CME latitude distribution had the following characteristics: (1) High-latitude CMEs ($\theta>60^{\circ}$ where $\theta$ is the latitude) constituted 3% of all CMEs and mainly occurred during the time when the polar magnetic fields reversed sign. The latitudinal drift of the high-latitude CMEs was correlated with that of the heliospheric current sheet. (2) 4% of all CMEs occurred in the range $45^{\circ}\leq\theta\leq60^{\circ}$. These mid-latitude CMEs occurred primarily in 2000, near the middle of 2002 and in 2005, respectively, forming a prominent three-peak structure; (3) The highest occurrence probability of low-latitude ($\theta< 45^{\circ}$) CMEs was at the minimum and during the declining phase of the solar cycle. However, the highest occurrence rate of low-latitude CMEs was at the maximum and during the declining phase of the solar cycle. The latitudinal evolution of low-latitude CMEs did not follow the Sp\"{o}rer sunspot law, which suggests that many CMEs originated outside of active regions.Comment: 4 pages, 4 figures, accepted by ApJ Lette

A multicomponent assembly approach for the design of deep desulfurization heterogeneous catalysts

Deep desulfurization is a challenging task and global efforts are focused on the development of new approaches for the reduction of sulfur-containing compounds in fuel oils. In this work, we have proposed a new design strategy for the development of deep desulfurization heterogeneous catalysts. Based on the adopted design strategy, a novel composite material of polyoxometalate (POM)-based ionic liquid-grafted layered double hydroxides (LDHs) was synthesized by an exfoliation/grafting/assembly process. The structural properties of the as-prepared catalyst were characterized using FT-IR, XRD, TG, NMR, XPS, BET, SEM and HRTEM. The heterogeneous catalyst exhibited high activity in deep desulfurization of DBT (dibenzothiophene), 4,6-DMDBT (4,6-dimethyldibenzothiophene) and BT (benzothiophene) at 70 °C in 25, 30 and 40 minutes, respectively. The catalyst can be easily recovered and reused at least ten times without obvious decrease of its catalytic activity. Such excellent sulfur removal ability as well as the cost efficiency of the novel heterogeneous catalyst can be attributed to the rational design, where the spatial proximity of the substrate and the active sites, the immobilization of ionic liquid onto the LDHs via covalent bonding and the recyclability of the catalyst are carefully considered

Spin Space Groups: Full Classification and Applications

In this work, we exhaust all the spin-space symmetries, which fully characterize collinear, non-collinear, commensurate, and incommensurate spiral magnetism, and investigate enriched features of electronic bands that respect these symmetries. We achieve this by systematically classifying the so-called spin space groups (SSGs) - joint symmetry groups of spatial and spin operations that leave the magnetic structure unchanged. Generally speaking, they are accurate (approximate) symmetries in systems where spin-orbit coupling (SOC) is negligible (finite but weaker than the interested energy scale); but we also show that specific SSGs could remain valid even in the presence of a strong SOC. By representing the SSGs as O($N$) representations, we - for the first time - obtain the complete classifications of 1421, 9542, and 56512 distinct SSGs for collinear ($N=1$), coplanar ($N=2$), and non-coplanar ($N=3$) magnetism, respectively. SSG not only fully characterizes the symmetry of spin d.o.f., but also gives rise to exotic electronic states, which, in general, form projective representations of magnetic space groups (MSGs). Surprisingly, electronic bands in SSGs exhibit features never seen in MSGs, such as nonsymmorphic SSG Brillouin zone (BZ), where SSG operations behave as glide or screw when act on momentum and unconventional spin-momentum locking, which is completely determined by SSG, independent of Hamiltonian details. To apply our theory, we identify the SSG for each of the 1604 published magnetic structures in the MAGNDATA database on the Bilbao Crystallographic Server. Material examples exhibiting aforementioned novel features are discussed with emphasis. We also investigate new types of SSG-protected topological electronic states that are unprecedented in MSGs

Complexity analysis of weakly noisy quantum states via quantum machine learning

Quantum computers capable of fault-tolerant operation are expected to provide provable advantages over classical computational models. However, the question of whether quantum advantages exist in the noisy intermediate-scale quantum era remains a fundamental and challenging problem. The root of this challenge lies in the difficulty of exploring and quantifying the power of noisy quantum states. In this work, we focus on the complexity of weakly noisy states, which we define as the size of the shortest quantum circuit required to prepare the noisy state. To analyze the complexity, we propose a quantum machine learning (QML) algorithm that exploits the intrinsic-connection property of structured quantum neural networks. The proposed QML algorithm enables efficiently predicting the complexity of weakly noisy states from measurement results, representing a paradigm shift in our ability to characterize the power of noisy quantum computation

Trainability Analysis of Quantum Optimization Algorithms from a Bayesian Lens

The Quantum Approximate Optimization Algorithm (QAOA) is an extensively studied variational quantum algorithm utilized for solving optimization problems on near-term quantum devices. A significant focus is placed on determining the effectiveness of training the $n$-qubit QAOA circuit, i.e., whether the optimization error can converge to a constant level as the number of optimization iterations scales polynomially with the number of qubits. In realistic scenarios, the landscape of the corresponding QAOA objective function is generally non-convex and contains numerous local optima. In this work, motivated by the favorable performance of Bayesian optimization in handling non-convex functions, we theoretically investigate the trainability of the QAOA circuit through the lens of the Bayesian approach. This lens considers the corresponding QAOA objective function as a sample drawn from a specific Gaussian process. Specifically, we focus on two scenarios: the noiseless QAOA circuit and the noisy QAOA circuit subjected to local Pauli channels. Our first result demonstrates that the noiseless QAOA circuit with a depth of $\tilde{\mathcal{O}}\left(\sqrt{\log n}\right)$ can be trained efficiently, based on the widely accepted assumption that either the left or right slice of each block in the circuit forms a local 1-design. Furthermore, we show that if each quantum gate is affected by a $q$-strength local Pauli channel with the noise strength range of $1/{\rm poly} (n)$ to 0.1, the noisy QAOA circuit with a depth of $\mathcal{O}\left(\log n/\log(1/q)\right)$ can also be trained efficiently. Our results offer valuable insights into the theoretical performance of quantum optimization algorithms in the noisy intermediate-scale quantum era

An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography : Implications for aerosol pH estimate

Water-soluble inorganic ions such as ammonium, nitrate and sulfate are major components of fine aerosols in the atmosphere and are widely used in the estimation of aerosol acidity. However, different experimental practices and instrumentation may lead to uncertainties in ion concentrations. Here, an intercomparison experiment was conducted in 10 different laboratories (labs) to investigate the consistency of inorganic ion concentrations and resultant aerosol acidity estimates using the same set of aerosol filter samples. The results mostly exhibited good agreement for major ions Cl-, SO2-4, NO-3, NHC4 and KC. However, F-, Mg2C and Ca2C were observed with more variations across the different labs. The Aerosol Chemical Speciation Monitor (ACSM) data of nonrefractory SO2-4, NO-3 and NHC4 generally correlated very well with the filter-analysis-based data in our study, but the absolute concentrations differ by up to 42 %. Cl-from the two methods are correlated, but the concentration differ by more than a factor of 3. The analyses of certified reference materials (CRMs) generally showed a good detection accuracy (DA) of all ions in all the labs, the majority of which ranged between 90 % and 110 %. The DA was also used to correct the ion concentrations to showcase the importance of using CRMs for calibration check and quality control. Better agreements were found for Cl-, SO2-4, NO-3, NHC4 and KC across the labs after their concentrations were corrected with DA; the coefficient of variation (CV) of Cl-, SO2-4, NO-3, NHC4 and KC decreased by 1.7 %, 3.4 %, 3.4 %, 1.2 % and 2.6 %, respectively, after DA correction. We found that the ratio of anion to cation equivalent concentrations (AE/CE) and ion balance (anions-cations) are not good indicators for aerosol acidity estimates, as the results in different labs did not agree well with each other. In situ aerosol pH calculated from the ISORROPIA II thermodynamic equilibrium model with measured ion and ammonia concentrations showed a similar trend and good agreement across the 10 labs. Our results indicate that although there are important uncertainties in aerosol ion concentration measurements, the estimated aerosol pH from the ISORROPIA II model is more consistent

Tratamiento interdisciplinario del espacio literario en la serie de novelas Manolito Gafotas

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Filosofía y Letras, Departamento de Filología Española. Fecha de lectura: 16-12-2021Esta tesis tiene embargado el acceso al texto completo hasta el 16-06-2023Haciendo uso de una voz infantil y de una ubicación geográfica precisa, la serie de novelas Manolito Gafotas ofrece un collage literario, geográfico y emocional de Madrid y del barrio de Carabanchel Alto a finales de siglo XX, proponiendo una lectura de la identidad geográfica, social y cultural de sus espacios urbanos. La presente tesis doctoral presenta un acercamiento multidisciplinar a la serie de novelas Manolito Gafotas mediante un énfasis teórico en el punto de vista de la geografía humanística, para poner de relieve el efecto multidimensional de sus espacios. A lo largo la tesis se lleva a cabo una lectura sociológica, fenomenológica, filosófica y literaria sobre los espacios en la serie de novelas juveniles en cuestió