Using Variational Eigensolvers on Low-End Hardware to Find the Ground State Energy of Simple Molecules

Key properties of physical systems can be described by the eigenvalues of matrices that represent the system. Computational algorithms that determine the eigenvalues of these matrices exist, but they generally suffer from a loss of performance as the matrix grows in size. This process can be expanded to quantum computation to find the eigenvalues with better performance than the classical algorithms. One application of such an eigenvalue solver is to determine energy levels of a molecule given a matrix representation of its Hamiltonian using the variational principle. Using a variational quantum eigensolver, we determine the ground state energies of different molecules. We focus on the choice of optimization strategy for a Qiskit simulator on low-end hardware. The benefits of several different optimizers were weighed in terms of accuracy in comparison to an analytic classical solution as well as code efficiency

Finding Optimal Training Parameters for Quantum Generative Adversarial Networks

Some of the most impressive achievements of contemporary Machine Learning systems comes from the GAN (Generative Adversarial Network) structure. DALLE-2 and GPT- 3, two of the most impressive and recognizable feats of ML in recent years, were both trained using adversarial techniques. The world of Quantum Computing is already well aware of the value of such techniques on near-term Quantum Hardware: QGANs provide a highly efficient method for loading classical data into a quantum state. We investigate the performance of these techniques in an attempt to determine some of the optimal training parameters in a Qiskit-style Parameterized Circuit QGAN framework

Competitors’ stock price reactions in response to private equity placements: evidence from a transitional economy

This paper examines whether information conveyed by private equity placement decisions transfers to non-applying companies within the same industry. In particular, it investigates the impact of a company’s announcements of the application for, withdrawal, rejection, approval and completion of private equity placement, while examining the cross-sectional differences of the market performance of their industry counterparts, both in the short- and long-term. It was found that an intra-industry reaction exists; competitors experience a decrease in stock prices in response to the announcement of the application for, approval and completion of private equity placement and an increase in stock prices around the announcement of the withdrawal or rejection of applications. Further, it was found that competitors experience a decrease in their long-term stock performance following private placements. A higher discount on private equity placement is detrimental for private equity (P.E.) issuing companies in the long-term. This study, therefore, provides evidence of the existence of a contagion effect in the long-term while a competitive effect dominates in the short-term

Single photon nonlinearities using arrays of cold polar molecules

We model single photon nonlinearities resulting from the dipole-dipole interactions of cold polar molecules. We propose utilizing ``dark state polaritons'' to effectively couple photon and molecular states; through this framework, coherent control of the nonlinearity can be expressed and potentially used in an optical quantum computation architecture. Due to the dipole-dipole interaction the photons pick up a measurable nonlinear phase even in the single photon regime. A manifold of protected symmetric eigenstates is used as basis. Depending on the implementation, major sources of decoherence result from non-symmetric interactions and phonon dispersion. We discuss the strength of the nonlinearity per photon and the feasibility of this system.Comment: 8 pages, 9 figures Accepted for publication in Physical Review

Prediction and assessment of the effects of mixtures of four xenoestrogens.

The assessment of mixture effects of estrogenic agents is regarded as an issue of high priority by many governmental agencies and expert decision-making bodies all over the world. However, the few mixture studies published so far have suffered from conceptual and experimental problems and are considered to be inconclusive. Here, we report the results of assessments of two-, three- and four-component mixtures of o,p'-DDT, genistein, 4-nonylphenol, and 4-n-octylphenol, all compounds with well-documented estrogenic activity. Extensive concentration-response analyses with the single agents were carried out using a recombinant yeast screen (yeast estrogen screen, YES). Based on the activity of the single agents in the YES assay we calculated predictions of entire concentration-response curves for mixtures of our chosen test agents assuming additive combination effects. For this purpose we employed the models of concentration addition and independent action, both well-established models for the calculation of mixture effects. Experimental concentration-response analyses revealed good agreement between predicted and observed mixture effects in all cases. Our results show that the combined effect of o,p'-DDT, genistein, 4-nonylphenol, and 4-n-octylphenol in the YES assay does not deviate from expected additivity. We consider both reference models as useful tools for the assessment of combination effects of multiple mixtures of xenoestrogens

Enhancing Performance of SnO 2

Although liquid electrolyte based dye-sensitized solar cells (DSCs) have shown higher photovoltaic performance in their class, they still suffer from some practical limitations such as solvent evaporation, leakage, and sealing imperfections. These problems can be circumvented to a certain extent by replacing the liquid electrolytes with quasi-solid-state electrolytes. Even though SnO2 shows high election mobility when compared to the semiconductor material commonly used in DSCs, the cell performance of SnO2-based DSCs is considerably low due to high electron recombination. This recombination effect can be reduced through the use of ultrathin coating layer of ZnO on SnO2 nanoparticles surface. ZnO-based DSCs also showed lower performance due to its amphoteric nature which help dissolve in slightly acidic dye solution. In this study, the effect of the composite SnO2/ZnO system was investigated. SnO2/ZnO composite DSCs showed 100% and 38% increase of efficiency compared to the pure SnO2-based and ZnO-based devices, respectively, with the gel electrolyte consisting of LiI salt

The interactions between different types of financial and human resource slacks on firm performance: Evidence from a developing country

This paper investigates the effect of both FS and HR slack together on firm performance and how different levels of these slack resources affect performance of private-owned enterprises (POEs) and state-owned enterprises (SOEs). Hypotheses are tested using a longitudinal data set of 11,985 listed Chinese companies from 2000 to 2009. Findings reveal that the unabsorbed-financial slack and HR slack show an inverse U shape relationship on firm performance for both POEs and SOEs. However, a less-negative interaction occurs for unabsorbed-financial and HR slacks for POEs. The absorbedfinancial and HR slacks also shows an inverse U shape relationship on performance and this relationship does not have a significant negative effect on SOE’s performance. The article concludes with theoretical contributions and practical implications of the findings

High Efficient Dye-Sensitized Solar Cells Based on Synthesized SnO 2

In this study, SnO2 semiconductor nanoparticles were synthesized for DSC applications via acid route using tin(ii) chloride as a starting material and hydrothermal method through the use of tin(iv) chloride. Powder X-ray diffraction studies confirmed the formation of the rutile phase of SnO2 with nanoranged particle sizes. A quasi-solid-state electrolyte was employed instead of a conventional liquid electrolyte in order to overcome the practical limitations such as electrolyte leakage, solvent evaporation, and sealing imperfections associated with liquid electrolytes. The gel electrolytes were prepared incorporating lithium iodide (LiI) and tetrapropylammonium iodide (Pr4N+I−) salts, separately, into the mixture which contains polyacrylonitrile as a polymer, propylene carbonate and ethylene carbonate as plasticizers, iodide/triiodide as the redox couple, acetonitrile as the solvent, and 4-tertiary butylpyridine as an electrolyte additive. In order to overcome the recombination problem associated with the SnO2 due to its higher electron mobility, ultrathin layer of CaCO3 coating was used to cover the surface recombination sites of SnO2 nanoparticles. Maximum energy conversion efficiency of 5.04% is obtained for the device containing gel electrolyte incorporating LiI as the salt. For the same gel electrolyte, the ionic conductivity and the diffusion coefficient of the triiodide ions are 4.70 × 10−3 S cm−1 and 4.31 × 10−7 cm2 s−1, respectively