Comment on "Groverian Entanglement Measure and Evolution of Entanglement in Search Algorithm for n(= 3, 5)-Qubit Systems with Real Coefficients" (Volume 6, Number 4, August 2007), by Arti Chamoli and C. M. Bhandari

We point out that the main results-the analytic expressions for the Groverian Measure of Entanglement, in the above mentioned paper are erroneous. The technical mistake of the paper is discussed. It is shown by an explicit example that the formula for calculating the Groverian measure yields G(|\psi>) = 0 for some entangled states.Comment: 4 pages, published online in Quantum Info. Process. on 24 July 200

Exonuclease III-Assisted Upconversion Resonance Energy Transfer in a Wash-Free Suspension DNA Assay

© 2017 American Chemical Society. Sensitivity is the key in optical detection of low-abundant analytes, such as circulating RNA or DNA. The enzyme Exonuclease III (Exo III) is a useful tool in this regard; its ability to recycle target DNA molecules results in markedly improved detection sensitivity. Lower limits of detection may be further achieved if the detection background of autofluorescence can be removed. Here we report an ultrasensitive and specific method to quantify trace amounts of DNA analytes in a wash-free suspension assay. In the presence of target DNA, the Exo III recycles the target DNA by selectively digesting the dye-tagged sequence-matched probe DNA strand only, so that the amount of free dye removed from the probe DNA is proportional to the number of target DNAs. Remaining intact probe DNAs are then bound onto upconversion nanoparticles (energy donor), which allows for upconversion luminescence resonance energy transfer (LRET) that can be used to quantify the difference between the free dye and tagged dye (energy acceptor). This scheme simply avoids both autofluorescence under infrared excitation and many tedious washing steps, as the free dye molecules are physically located away from the nanoparticle surface, and as such they remain "dark" in suspension. Compared to alternative approaches requiring enzyme-assisted amplification on the nanoparticle surface, introduction of probe DNAs onto nanoparticles only after DNA hybridization and signal amplification steps effectively avoids steric hindrance. Via this approach, we have achieved a detection limit of 15 pM in LRET assays of human immunodeficiency viral DNA

A supramolecular self-assembly strategy for upconversion nanoparticle bioconjugation

© 2018 The Royal Society of Chemistry. An efficient surface modification for upconversion nanoparticles (UCNPs) is reported via supramolecular host-guest self-assembly. Cucurbit[7]uril (CB) can provide a hydrophilic surface and cavities for most biomolecules. High biological efficiency, activity and versatility of the approach enable UCNPs to be significantly applied in bio-imaging, early disease detection, and bio-sensing

Necessity of Superposition of Macroscopically Distinct States for Quantum Computational Speedup

For quantum computation, we investigate the conjecture that the superposition of macroscopically distinct states is necessary for a large quantum speedup. Although this conjecture was supported for a circuit-based quantum computer performing Shor's factoring algorithm [A. Ukena and A. Shimizu, Phys. Rev. A69 (2004) 022301], it needs to be generalized for it to be applicable to a large class of algorithms and/or other models such as measurement-based quantum computers. To treat such general cases, we first generalize the indices for the superposition of macroscopically distinct states. We then generalize the conjecture, using the generalized indices, in such a way that it is unambiguously applicable to general models if a quantum algorithm achieves exponential speedup. On the basis of this generalized conjecture, we further extend the conjecture to Grover's quantum search algorithm, whose speedup is large but quadratic. It is shown that this extended conjecture is also correct. Since Grover's algorithm is a representative algorithm for unstructured problems, the present result further supports the conjecture.Comment: 18 pages, 5 figures. Fixed typos throughout the manuscript. This version has been publishe

Electromigration-Induced Flow of Islands and Voids on the Cu(001) Surface

Electromigration-induced flow of islands and voids on the Cu(001) surface is studied at the atomic scale. The basic drift mechanisms are identified using a complete set of energy barriers for adatom hopping on the Cu(001) surface, combined with kinetic Monte Carlo simulations. The energy barriers are calculated by the embedded atom method, and parameterized using a simple model. The dependence of the flow on the temperature, the size of the clusters, and the strength of the applied field is obtained. For both islands and voids it is found that edge diffusion is the dominant mass-transport mechanism. The rate limiting steps are identified. For both islands and voids they involve detachment of atoms from corners into the adjacent edge. The energy barriers for these moves are found to be in good agreement with the activation energy for island/void drift obtained from Arrhenius analysis of the simulation results. The relevance of the results to other FCC(001) metal surfaces and their experimental implications are discussed.Comment: 9 pages, 13 ps figure

Plato's Cave Algorithm: Inferring Functional Signaling Networks from Early Gene Expression Shadows

Improving the ability to reverse engineer biochemical networks is a major goal of systems biology. Lesions in signaling networks lead to alterations in gene expression, which in principle should allow network reconstruction. However, the information about the activity levels of signaling proteins conveyed in overall gene expression is limited by the complexity of gene expression dynamics and of regulatory network topology. Two observations provide the basis for overcoming this limitation: a. genes induced without de-novo protein synthesis (early genes) show a linear accumulation of product in the first hour after the change in the cell's state; b. The signaling components in the network largely function in the linear range of their stimulus-response curves. Therefore, unlike most genes or most time points, expression profiles of early genes at an early time point provide direct biochemical assays that represent the activity levels of upstream signaling components. Such expression data provide the basis for an efficient algorithm (Plato's Cave algorithm; PLACA) to reverse engineer functional signaling networks. Unlike conventional reverse engineering algorithms that use steady state values, PLACA uses stimulated early gene expression measurements associated with systematic perturbations of signaling components, without measuring the signaling components themselves. Besides the reverse engineered network, PLACA also identifies the genes detecting the functional interaction, thereby facilitating validation of the predicted functional network. Using simulated datasets, the algorithm is shown to be robust to experimental noise. Using experimental data obtained from gonadotropes, PLACA reverse engineered the interaction network of six perturbed signaling components. The network recapitulated many known interactions and identified novel functional interactions that were validated by further experiment. PLACA uses the results of experiments that are feasible for any signaling network to predict the functional topology of the network and to identify novel relationships