A universal quantum circuit scheme for finding complex eigenvalues

We present a general quantum circuit design for finding eigenvalues of non-unitary matrices on quantum computers using the iterative phase estimation algorithm. In addition, we show how the method can be used for the simulation of resonance states for quantum systems.     

Hydrogen evolution characteristics of Ni–Mn microencapsulated MlNi3.03Si0.85Co0.60Mn0.31Al0.08 alloys in 6 M KOH

Nickel–manganese alloys were coated from sulphate baths by electrodeposition with ‘Packed Bed’ technique on the surface of proprietary lanthanum rich non-stoichiometric MlNi_3.03Si_0.85Co_0.60Mn_0.31Al_0.08 (Ml = lanthanum rich misch metal) hydrogen storage alloy particles. The structure and nature of the microencapsulated alloys were characterized using X-ray diffraction (XRD) and electron paramagnetic resonance (EPR). The hydrogen evolution reaction (HER) was investigated in 6 M KOH at 30 °C by galvnostatic cathodic polarisation technique. The effects of Ni/Mn ratio in the bath and deposition current density were studied. Among the investigated depositions, Ni₁₅₀Mn₁₀₀ (30) and Ni₁₅₀Mn₁₀ (60) (concentration of Ni and Mn salts in electrodeposition bath given in grams per liter; electrodeposition current density (CD) given within brackets in milliamphere per square centimeter) coated samples exhibited the highest activity towards the HER. It can be concluded that disordered paramagnetic coatings with Ni concentrations above 80 at.% exhibit higher catalytic activity towards HER. The Tafel mechanism is the easiest pathway for HER on most of the studied coatings. However, some of the Ni-rich coatings prefer the Volmer–Tafel path and one sample [Ni₁₅₀Mn₁₅₀ (80)] prefers the Heyrovsky–Volmer path.     

Solving general multi-class closed queuing networks using parametric decomposition

This paper presents a new approach to evaluate the performance of general multi-class closed queuing networks. The approach uses parametric characterization of the traffic processes to derive two-moment approximations for performance measures at individual nodes. Based on these approximations, linkage equations are derived to establish the relationships between the various nodes in the network. These relationships result in a system of non-linear equations that is solved using an iterative procedure. Numerical studies comparing the performance of the approach with detailed simulations suggest that the approach yields fairly accurate estimates of performance measures without significant computational complexity.     

Randomized leader election

We present an efficient randomized algorithm for leader election in large-scale distributed systems. The proposed algorithm is optimal in message complexity (O(n) for a set of n total processes), has round complexity logarithmic in the number of processes in the system, and provides high probabilistic guarantees on the election of a unique leader. The algorithm relies on a balls and bins abstraction and works in two phases. The main novelty of the work is in the first phase where the number of contending processes is reduced in a controlled manner. Probabilistic quorums are used to determine a winner in the second phase. We discuss, in detail, the synchronous version of the algorithm, provide extensions to an asynchronous version and examine the impact of failures.     

Robust Speaker Verification with Principal Pitch Components

We are presenting a new method that improves the accuracy of text dependent speaker verification systems. The new method exploits a set of novel speech features derived from a principal component analysis of pitch synchronous voiced speech segments. We use the term principal pitch components (PPCs) or optimal pitch bases (OPBs) to denote the new feature set. Utterance distances computed from these new PPC features are only loosely correlated with utterance distances computed from cepstral features. A distance measure that combines both cepstral and PPC features provides a discriminative power that cannot be achieved with cepstral features alone. By augmenting the feature space of a cepstral baseline system with PPC features we achieve a significant reduction of the equal error probability of incorrect customer rejection versus incorrect impostor acceptance. The proposed method delivers robust performance in various noise conditions.     

Incorporation of U-14C-leucine into the serum lipoproteins and proteins of partially hepatectomized rats

The incorporation of U-¹⁴C-leucine into five classes of serum lipoproteins and into lipoprotein-free serum proteins was investigated in partially hepatectomized, sham operated and normal rats. The serum concentration of very low density lipoprotein and the predominant subfraction of high density lipoprotein (HDL₂) was considerably reduced in partially hepatectomized rats as compared with both normal and sham operated rats. The incorporation of U-¹⁴C-leucine into HDL₂ of partially hepatectomized rats was only one third and one fourth of that observed with normal and sham operated rats, respectively. On the other hand, the incorporation of the label into low density lipoproteins and into serum proteins was slightly greater in partially hepatectomized rats as compared with normal rats. In sham operated animals, the incorporation into most fractions was considerably greater than those observed with lobectomized and normal rats.     

Controlled total variation regularization for image deconvolution

To resolve the image deconvolution problem, the total variation (TV) minimization approach has been proved to be very efficient. However, we observe that this approach has an over-minimizing TV effect in the sense that it gives a solution whose TV is usually smaller than that of the original image. This effect is due to the pre-pondering role of the TV in the corresponding minimization problem and prevents from finding the exact solution of the deconvolution problem when such a solution exists. We propose a modified version of the gradient descent algorithm, which leads to an exact solution of the deconvolution problem if it exists and to a satisfactory approximative solution if there is no exact one. The idea consists in introducing a control on the contribution of the TV in the classical gradient descent algorithm. The new algorithm has the advantage that the restored image has the TV closer to that of the original image, compared to the classical gradient descent approach. Numerical results show that our method is competitive compared to some recent ones.