135 research outputs found

    Interaction-based quantum metrology showing scaling beyond the Heisenberg limit

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    Quantum metrology studies the use of entanglement and other quantum resources to improve precision measurement. An interferometer using N independent particles to measure a parameter X can achieve at best the "standard quantum limit" (SQL) of sensitivity {\delta}X \propto N^{-1/2}. The same interferometer using N entangled particles can achieve in principle the "Heisenberg limit" {\delta}X \propto N^{-1}, using exotic states. Recent theoretical work argues that interactions among particles may be a valuable resource for quantum metrology, allowing scaling beyond the Heisenberg limit. Specifically, a k-particle interaction will produce sensitivity {\delta}X \propto N^{-k} with appropriate entangled states and {\delta}X \propto N^{-(k-1/2)} even without entanglement. Here we demonstrate this "super-Heisenberg" scaling in a nonlinear, non-destructive measurement of the magnetisation of an atomic ensemble. We use fast optical nonlinearities to generate a pairwise photon-photon interaction (k = 2) while preserving quantum-noise-limited performance, to produce {\delta}X \propto N^{-3/2}. We observe super-Heisenberg scaling over two orders of magnitude in N, limited at large N by higher-order nonlinear effects, in good agreement with theory. For a measurement of limited duration, super-Heisenberg scaling allows the nonlinear measurement to overtake in sensitivity a comparable linear measurement with the same number of photons. In other scenarios, however, higher-order nonlinearities prevent this crossover from occurring, reflecting the subtle relationship of scaling to sensitivity in nonlinear systems. This work shows that inter-particle interactions can improve sensitivity in a quantum-limited measurement, and introduces a fundamentally new resource for quantum metrology

    Observation of a pairing pseudogap in a two-dimensional Fermi gas

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    Pairing of fermions is ubiquitous in nature and it is responsible for a large variety of fascinating phenomena like superconductivity, superfluidity of 3^3He, the anomalous rotation of neutron stars, and the BEC-BCS crossover in strongly interacting Fermi gases. When confined to two dimensions, interacting many-body systems bear even more subtle effects, many of which lack understanding at a fundamental level. Most striking is the, yet unexplained, effect of high-temperature superconductivity in cuprates, which is intimately related to the two-dimensional geometry of the crystal structure. In particular, the questions how many-body pairing is established at high temperature and whether it precedes superconductivity are crucial to be answered. Here, we report on the observation of pairing in a harmonically trapped two-dimensional atomic Fermi gas in the regime of strong coupling. We perform momentum-resolved photoemission spectroscopy, analogous to ARPES in the solid state, to measure the spectral function of the gas and we detect a many-body pairing gap above the superfluid transition temperature. Our observations mark a significant step in the emulation of layered two-dimensional strongly correlated superconductors using ultracold atomic gases

    Entanglement-enhanced probing of a delicate material system

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    Quantum metrology uses entanglement and other quantum effects to improve the sensitivity of demanding measurements. Probing of delicate systems demands high sensitivity from limited probe energy and has motivated the field's key benchmark-the standard quantum limit. Here we report the first entanglement-enhanced measurement of a delicate material system. We non-destructively probe an atomic spin ensemble by means of near-resonant Faraday rotation, a measurement that is limited by probe-induced scattering in quantum-memory and spin-squeezing applications. We use narrowband, atom-resonant NOON states to beat the standard quantum limit of sensitivity by more than five standard deviations, both on a per-photon and per-damage basis. This demonstrates quantum enhancement with fully realistic loss and noise, including variable-loss effects. The experiment opens the way to ultra-gentle probing of single atoms, single molecules, quantum gases and living cells.Comment: 7 pages, 8 figures; Nature Photonics, advance online publication, 16 December 201

    Microbial sulfate reduction and metal attenuation in pH 4 acid mine water

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    Sediments recovered from the flooded mine workings of the Penn Mine, a Cu-Zn mine abandoned since the early 1960s, were cultured for anaerobic bacteria over a range of pH (4.0 to 7.5). The molecular biology of sediments and cultures was studied to determine whether sulfate-reducing bacteria (SRB) were active in moderately acidic conditions present in the underground mine workings. Here we document multiple, independent analyses and show evidence that sulfate reduction and associated metal attenuation are occurring in the pH-4 mine environment. Water-chemistry analyses of the mine water reveal: (1) preferential complexation and precipitation by H2S of Cu and Cd, relative to Zn; (2) stable isotope ratios of 34S/32S and 18O/16O in dissolved SO4 that are 2–3 ‰ heavier in the mine water, relative to those in surface waters; (3) reduction/oxidation conditions and dissolved gas concentrations consistent with conditions to support anaerobic processes such as sulfate reduction. Scanning electron microscope (SEM) analyses of sediment show 1.5-micrometer, spherical ZnS precipitates. Phospholipid fatty acid (PLFA) and denaturing gradient gel electrophoresis (DGGE) analyses of Penn Mine sediment show a high biomass level with a moderately diverse community structure composed primarily of iron- and sulfate-reducing bacteria. Cultures of sediment from the mine produced dissolved sulfide at pH values near 7 and near 4, forming precipitates of either iron sulfide or elemental sulfur. DGGE coupled with sequence and phylogenetic analysis of 16S rDNA gene segments showed populations of Desulfosporosinus and Desulfitobacterium in Penn Mine sediment and laboratory cultures

    Exact model reduction of combinatorial reaction networks

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    Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models

    Bioinformatic Analysis Reveals High Diversity of Bacterial Genes for Laccase-Like Enzymes

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    Fungal laccases have been used in various fields ranging from processes in wood and paper industries to environmental applications. Although a few bacterial laccases have been characterized in recent years, prokaryotes have largely been neglected as a source of novel enzymes, in part due to the lack of knowledge about the diversity and distribution of laccases within Bacteria. In this work genes for laccase-like enzymes were searched for in over 2,200 complete and draft bacterial genomes and four metagenomic datasets, using the custom profile Hidden Markov Models for two- and three- domain laccases. More than 1,200 putative genes for laccase-like enzymes were retrieved from chromosomes and plasmids of diverse bacteria. In 76% of the genes, signal peptides were predicted, indicating that these bacterial laccases may be exported from the cytoplasm, which contrasts with the current belief. Moreover, several examples of putatively horizontally transferred bacterial laccase genes were described. Many metagenomic sequences encoding fragments of laccase-like enzymes could not be phylogenetically assigned, indicating considerable novelty. Laccase-like genes were also found in anaerobic bacteria, autotrophs and alkaliphiles, thus opening new hypotheses regarding their ecological functions. Bacteria identified as carrying laccase genes represent potential sources for future biotechnological applications

    The elusive Heisenberg limit in quantum enhanced metrology

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    We provide efficient and intuitive tools for deriving bounds on achievable precision in quantum enhanced metrology based on the geometry of quantum channels and semi-definite programming. We show that when decoherence is taken into account, the maximal possible quantum enhancement amounts generically to a constant factor rather than quadratic improvement. We apply these tools to derive bounds for models of decoherence relevant for metrological applications including: dephasing,depolarization, spontaneous emission and photon loss.Comment: 10 pages, 4 figures, presentation imporved, implementation of the semi-definite program finding the precision bounds adde

    Methane exchange in a boreal forest estimated by gradient method

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    Forests are generally considered to be net sinks of atmospheric methane (CH4) because of oxidation by methanotrophic bacteria in well-aerated forests soils. However, emissions from wet forest soils, and sometimes canopy fluxes, are often neglected when quantifying the CH4 budget of a forest. We used a modified Bowen ratio method and combined eddy covariance and gradient methods to estimate net CH4 exchange at a boreal forest site in central Sweden. Results indicate that the site is a net source of CH4. This is in contrast to soil, branch and leaf chamber measurements of uptake of CH4. Wetter soils within the footprint of the canopy are thought to be responsible for the discrepancy. We found no evidence for canopy emissions per se. However, the diel pattern of the CH4 exchange with minimum emissions at daytime correlated well with gross primary production, which supports an uptake in the canopy. More distant source areas could also contribute to the diel pattern; their contribution might be greater at night during stable boundary layer conditions

    Clostridia Initiate Heavy Metal Bioremoval in Mixed Sulfidogenic Cultures

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    Sulfate reducing bacteria (SRB) are widely used for attenuating heavy metal pollution by means of sulfide generation. Due to their low metal tolerance, several SRB species depend on associated bacteria in mixed cultures to cope with metal-induced stress. Yet the identity of the SRB protecting bacteria is largely unknown. We aimed to identify these associated bacteria and their potential role in two highly metal-resistant mixed SRB cultures by comparing bacterial community composition and SRB activity between these cultures and two sensitive ones. The SRB composition in the resistant and sensitive consortia was similar. However, whereas the SRB in the sensitive cultures were strongly inhibited by a mixture of copper, zinc, and iron, no influence of these metals was detected on SRB growth and activity in the resistant cultures. In the latter, a Gram-positive population mostly assigned to Clostridium spp.initiated heavy metal bioremoval based on sulfide generation from components of the medium (mainly sulfite) but not from sulfate. After metal levels were lowered by the Clostridium spp. populations, SRB started sulfate reduction and raised the pH of the medium. The combination of sulfite reducing Clostridium spp. with SRB may improve green technologies for removal of heavy metals
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