Multiself-loop Lackadaisical Quantum Walk with Partial Phase Inversion

Quantum walks are the quantum counterpart of classical random walks and provide an intuitive framework for building new quantum algorithms. The lackadaisical quantum walk, which is a quantum analog of the lazy random walk, is obtained by adding a self-loop transition to each state allowing the walker to stay stuck in the same state, being able to improve the performance of the quantum walks as search algorithms. However, the high dependence of a weight $l$ makes it a key parameter to reach the maximum probability of success in the search process. Although many advances have been achieved with search algorithms based on quantum walks, the number of self-loops can also be critical for search tasks. Believing that the multiple self-loops have not yet been properly explored, this article proposes the quantum search algorithm Multiself-loop Lackadaisical Quantum Walk with Partial Phase Inversion, which is based on a lackadaisical quantum walk with multiple self-loops where the target state phase is partially inverted. Each vertex has $m$ self-loops, with weights $l' = l/m$, where $l$ is a real parameter. The phase inversion is based on Grover's algorithm and acts partiality, modifying the phase of a given quantity $s \leqslant m$ of self-loops. On a hypercube structure, we analyzed the situation where $s=1$ and $1 \leqslant m \leqslant 30$ and investigated its effects in the search for 1 to 12 marked vertices. Based on two ideal weights $l$ used in the literature, we propose two new weight values. As a result, with the proposal of the Multiself-loop Lackadaisical Quantum Walk with partial phase inversion of target states and the new weight values for the self-loop, this proposal improved the maximum success probabilities to values close to 1. This article contributes with a new perspective on the use of quantum interferences in the construction of new quantum search algorithms.Comment: 16 pages, 4 figures, 3 table

On Applying the Lackadaisical Quantum Walk Algorithm to Search for Multiple Solutions on Grids

Quantum computing holds the promise of improving the information processing power to levels unreachable by classical computation. Quantum walks are heading the development of quantum algorithms for searching information on graphs more efficiently than their classical counterparts. A quantum-walk-based algorithm that is standing out in the literature is the lackadaisical quantum walk. The lackadaisical quantum walk is an algorithm developed to search two-dimensional grids whose vertices have a self-loop of weight $l$. In this paper, we address several issues related to the application of the lackadaisical quantum walk to successfully search for multiple solutions on grids. Firstly, we show that only one of the two stopping conditions found in the literature is suitable for simulations. We also demonstrate that the final success probability depends on the space density of solutions and the relative distance between solutions. Furthermore, this work generalizes the lackadaisical quantum walk to search for multiple solutions on grids of arbitrary dimensions. In addition, we propose an optimal adjustment of the self-loop weight $l$ for such scenarios of arbitrary dimensions. It turns out the other fits of $l$ found in the literature are particular cases. Finally, we observe a two-to-one relation between the steps of the lackadaisical quantum walk and the ones of Grover's algorithm, which requires modifications in the stopping condition. In conclusion, this work deals with practical issues one should consider when applying the lackadaisical quantum walk, besides expanding the technique to a wider range of search problems.Comment: Extended version of the conference paper available at https://doi.org/10.1007/978-3-030-61377-8_9 . 21 pages, 6 figure

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks

Scaling solutions from interacting fluids

We examine the dynamical implications of an interaction between some of the fluid components of the universe. We consider the combination of three matter components, one of which is a perfect fluid and the other two are interacting. The interaction term generalizes the cases found in scalar field cosmologies with an exponential potential. We find that attracting scaling solutions are obtained in several regions of parameter space, that oscillating behaviour is possible, and that new curvature scaling solutions exist. We also discuss the inflationary behaviour of the solutions and present some of the constraints on the strength of the coupling, namely those arising from nucleosynthesis.Comment: RevTeX, 21 pages, 8 figure

Conhecimento, Responsabilidade, Visão e Futuro: bases programáticas da Lista F para o 3.º mandato do Conselho Geral da Universidade de Évora 2016-20

O presente documento inclui o programa de acção e os elementos de campanha da Lista F, candidata ao 3.º mandato do Conselho Geral da Universidade de Évora (2016-20)

Fungal Planet description sheets: 868-950

Novel species of fungi described in this study include those from various countries as follows: Australia, Chaetomella pseudocircinoseta and Coniella pseudodiospyri on Eucalyptus microcorys leaves, Cladophialophora eucalypti, Teratosphaeria dunnii and Vermiculariopsiella dunnii on Eucalyptus dunnii leaves, Cylindrium grande and Hypsotheca eucalyptorum on Eucalyptus grandis leaves, Elsinoe salignae on Eucalyptus saligna leaves, Marasmius lebeliae on litter of regenerating subtropical rainforest, Phialoseptomonium eucalypti (incl. Phialoseptomonium gen. nov.) on Eucalyptus grandis × camaldulensis leaves, Phlogicylindrium pawpawense on Eucalyptus tereticornis leaves, Phyllosticta longicauda as an endophyte from healthy Eustrephus latifolius leaves, Pseudosydowia eucalyptorum on Eucalyptus sp. leaves, Saitozyma wallum on Banksia aemula leaves, Teratosphaeria henryi on Corymbia henryi leaves. Brazil, Aspergillus bezerrae, Backusella azygospora, Mariannaea terricola and Talaromyces pernambucoensis from soil, Calonectria matogrossensis on Eucalyptus urophylla leaves, Calvatia brasiliensis on soil, Carcinomyces nordestinensis on Bromelia antiacantha leaves, Dendryphiella stromaticola on small branches of an unidentified plant, Nigrospora brasiliensis on Nopalea cochenillifera leaves, Penicillium alagoense as a leaf endophyte on a Miconia sp., Podosordaria nigrobrunnea on dung, Spegazzinia bromeliacearum as a leaf endophyte on Tilandsia catimbauensis, Xylobolus brasiliensis on decaying wood. Bulgaria, Kazachstania molopis from the gut of the beetle Molops piceus. Croatia, Mollisia endocrystallina from a fallen decorticated Picea abies tree trunk. Ecuador, Hygrocybe rodomaculata on soil. Hungary, Alfoldia vorosii (incl.Alfoldia gen. nov.) from Juniperus communis roots, Kiskunsagia ubrizsyi (incl. Kiskunsagia gen. nov.) from Fumana procumbens roots. India, Aureobasidium tremulum as laboratory contaminant, Leucosporidium himalayensis and Naganishia indica from windblown dust on glaciers. Italy, Neodevriesia cycadicola on Cycas sp. leaves, Pseudocercospora pseudomyrticola on Myrtus communis leaves, Ramularia pistaciae on Pistacia lentiscus leaves, Neognomoniopsis quercina (incl. Neognomoniopsis gen. nov.) on Quercus ilex leaves. Japan, Diaporthe fructicola on Passiflora edulis × P. edulis f. flavicarpa fruit, Entoloma nipponicum on leaf litter in a mixed Cryptomeria japonica and Acer spp. forest. Macedonia, Astraeus macedonicus on soil. Malaysia, Fusicladium eucalyptigenum on Eucalyptus sp. twigs, Neoacrodontiella eucalypti (incl. Neoacrodontiella gen. nov.) on Eucalyptus urophylla leaves. Mozambique, Meliola gorongosensis on dead Philenoptera violacea leaflets. Nepal, Coniochaeta dendrobiicola from Dendriobium lognicornu roots. New Zealand, Neodevriesia sexualis and Thozetella neonivea on Archontophoenix cunninghamiana leaves. Norway, Calophoma sandfjordenica from a piece of board on a rocky shoreline, Clavaria parvispora on soil, Didymella finnmarkica from a piece of Pinus sylvestris driftwood. Poland, Sugiyamaella trypani from soil. Portugal, Colletotrichum feijoicola from Acca sellowiana. Russia, Crepidotus tobolensis on Populus tremula debris, Entoloma ekaterinae, Entoloma erhardii and Suillus gastroflavus on soil, Nakazawaea ambrosiae from the galleries of Ips typographus under the bark of Picea abies. Slovenia, Pluteus ludwigii on twigs of broadleaved trees. South Africa, Anungitiomyces stellenboschiensis (incl. Anungitiomyces gen. nov.) and Niesslia stellenboschiana on Eucalyptus sp. leaves, Beltraniella pseudoportoricensis on Podocarpus falcatus leaf litter, Corynespora encephalarti on Encephalartos sp. leaves, Cytospora pavettae on Pavetta revoluta leaves, Helminthosporium erythrinicola on Erythrina humeana leaves, Helminthosporium syzygii on a Syzygium sp. barkcanker, Libertasomyces aloeticus on Aloe sp. leaves, Penicillium lunae from Musa sp. fruit, Phyllosticta lauridiae on Lauridia tetragona leaves, Pseudotruncatella bolusanthi (incl. Pseudotruncatellaceae fam. nov.) and Dactylella bolusanthi on Bolusanthus speciosus leaves. Spain, Apenidiella foetida on submerged plant debris, Inocybe grammatoides on Quercus ilex subsp. ilex forest humus, Ossicaulis salomii on soil, Phialemonium guarroi from soil. Thailand, Pantospora chromolaenae on Chromolaena odorata leaves. Ukraine, Cadophora helianthi from Helianthus annuus stems. USA, Boletus pseudopinophilus on soil under slash pine, Botryotrichum foricae, Penicillium americanum and Penicillium minnesotense from air. Vietnam, Lycoperdon vietnamense on soil. Morphological and culture characteristics are supported by DNA barcodes