Designing high-power, octave spanning entangled photon sources for quantum spectroscopy.

Entangled photon spectroscopy is a nascent field that has important implications for measurement and imaging across chemical, biology, and materials fields. Entangled photon spectroscopy potentially offers improved spatial and temporal-frequency resolutions, increased cross sections for multiphoton and nonlinear measurements, and new abilities in inducing or measuring quantum correlations. A critical step in enabling entangled photon spectroscopies is the creation of high-flux entangled sources that can use conventional detectors as well as provide redundancy for the losses in realistic samples. Here, we report a periodically poled, chirped, lithium tantalate platform that generates entangled photon pairs with ∼10-7 efficiency. For a near watt level diode laser, this results in a near µW-level flux. The single photon per mode limit that is necessary to maintain non-classical photon behavior is still satisfied by distributing this power over up to an octave-spanning bandwidth. The spectral-temporal photon correlations are observed via a Michelson-type interferometer that measures the broadband Hong-Ou-Mandel two-photon interference. A coherence time of 245 fs for a 10 nm bandwidth in the collinear case and a coherence time of 62 fs for a 125 nm bandwidth in the non-collinear case are measured using a CW pump laser and, essentially, collecting the full photon cone. We outline in detail the numerical methods used for designing and tailoring the entangled photons source, such as changing center wavelength or bandwidth, with the ultimate aim of increasing the availability of high-flux UV-Vis entangled photon sources in the optical spectroscopy community.

fMLC: fast multi-level clustering and visualization of large molecular datasets.

Motivation: Despite successful applications of data clustering and visualization techniques in molecular sequence identification, current technologies still do not scale to large biological datasets. Results: We address this problem by a new multi-threaded tool, fMLC, primarily developed to cluster DNA sequences, that is supplemented with an interactive web-based visualization component, DiVE. fMLC enabled to compare, cluster and visualize 350K ITS fungal sequences at the species level. It took less than two hours to compare and cluster the dataset, which is twelve times faster than the time reported previously. Availability and implementation: https://github.com/FastMLC/fMLC (doi: 10.5281/zenodo.926820). Contact: d.vu@westerdijkinstitute.nl or v.robert@westerdijkinstitute.nl.

DNA barcoding analysis of more than 9 000 yeast isolates contributes to quantitative thresholds for yeast species and genera delimitation.

DNA barcoding is a global initiative for species identification through sequencing of short DNA sequence markers. Sequences of two loci, ITS and LSU, were generated as barcode data for all (ca. 9k) yeast strains included in the CBS collection, originally assigned to ca. 2 000 species. Taxonomic sequence validation turned out to be the most severe bottleneck due to the large volume of generated trace files and lack of reference sequences. We have analysed and validated CBS strains and barcode sequences automatically. Our analysis shows that there were 6 and 9.5 % of CBS yeast species that could not be distinguished by ITS and LSU, respectively. Among them, ∼3 % were indistinguishable by both loci. Except for those species, both loci were successfully resolving yeast species as the grouping of yeast DNA barcodes with the predicted taxonomic thresholds was more than 90 % similar to the grouping with respect to the expected taxon names. The taxonomic thresholds predicted to discriminate yeast species were 98.41 % for ITS and 99.51 % for LSU. To discriminate current yeast genera, thresholds were 96.31 % for ITS and 97.11 % for LSU. Using ITS and LSU barcodes, we were also able to show that the recent reclassifications of basidiomycetous yeasts in 2015 have made a significant improvement for the generic taxonomy of those organisms. The barcodes of 4 730 (51 %) CBS yeast strains of 1 351 (80 %) accepted yeast species that were manually validated have been released to GenBank and the CBS-KNAW website as reference sequences for yeast identification.