Analytical Error Analysis
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Types Of Errors In Analytical Chemistry Ppt
(3 and 13), Sascha Husa (26), Lawrence E. Kidder (3), Pablo Laguna (5), Lionel London (5), Geoffrey Lovelace (3 and 13 and 22), Carlos O. Lousto (8), Pedro Marronetti (20 and 23), Richard A. Matzner (24), Philipp Mösta (1 and 13), Abdul Mroué (10), Doreen Müller (6), Bruno C. Mundim (8 and 1), Andrea Nerozzi (25), Vasileios Paschalidis (4), Denis Pollney (26 and 27), George Reifenberger (20), Luciano Rezzolla (1 and 29), Stuart L. Shapiro (4 and 28), Deirdre Shoemaker (5), Andrea Taracchini (2), Nicholas W. Taylor (13), Saul A. Teukolsky (3), Marcus Thierfelder (6), Helvi Witek (17 and 25), Yosef Zlochower (8) ((1) Albert Einstein Institute, (2) University of Maryland, (3) Cornell University, (4) University of Illinois at Urbana-Champaign, (5) Georgia Institute of Technology, (6) Friedrich-Schiller-Universität Jena, (7) Institut des Hautes Études Scientifiques, (8) Rochester Institute of Technology, (9) Kyoto University, (10) University of Toronto, (11) Canadian Institute for Advanced Research, (12) Cardiff University, (13) California Institute of Technology, (14) Perimeter Institute for Theoretical Physics, (15) University of Guelph, (16) Louisiana State University, (17) University of Cambridge, (18) Institute of Space Sciences, (19) The University of Mississippi, (20) Florida Atlantic University, (21) University College Dublin, (22) California State University Fullerton, (23) Nati
feedback return to old SpringerLink Quantum Information ProcessingAugust 2016, Volume 15, Issue 8, pp 3065–3079Analytical
Define Error And Deviation In Chemistry
error analysis of Clifford gates by the fault-path tracer methodAuthorsAuthors and errors in analytical chemistry pdf affiliationsSmitha JanardanYu TomitaMauricio GutiérrezKenneth R. BrownEmail authorArticleFirst Online: 18 May 2016Received: 06 December 2015Accepted: 20 April 2016DOI: 10.1007/s11128-016-1330-zCite this article error analysis lab report example as: Janardan, S., Tomita, Y., Gutiérrez, M. et al. Quantum Inf Process (2016) 15: 3065. doi:10.1007/s11128-016-1330-z 1 Shares 58 Views Part of the following topical collections:Quantum https://arxiv.org/abs/1307.5307 Computer ScienceAbstractWe estimate the success probability of quantum protocols composed of Clifford operations in the presence of Pauli errors. Our method is derived from the fault-point formalism previously used to determine the success rate of low-distance error correction codes. Here we apply it to a wider range of quantum protocols and http://link.springer.com/article/10.1007/s11128-016-1330-z identify circuit structures that allow for efficient calculation of the exact success probability and even the final distribution of output states. As examples, we apply our method to the Bernstein–Vazirani algorithm and the Steane [[7,1,3]] quantum error correction code and compare the results to Monte Carlo simulations.KeywordsQuantum error correctionThresholdsBernstein–Vazirani algorithmClifford circuitsThis article is part of topical collection on Quantum Computer Science.References1.Chuang, I.L., Nielsen, M.A.: Prescription for experimental determination of the dynamics of a quantum black box. J. Mod. Opt. 44, 2455 (1997)ADSCrossRef2.Emerson, J., Silva, M., Moussa, O., Ryan, C., Laforest, M., Baugh, J., Cory, D.G., Laflamme, R.: Symmetrized characterization of noisy quantum processes. Science 317, 1893 (2007)ADSCrossRef3.Knill, E., Leibfried, D., Reichle, R., Britton, J., Blakestad, R.B., Jost, J.D., Langer, C., Ozeri, R., Seidelin, S., Wineland, D.J.: Randomized benchmarking of quantum gates. Phys. Rev. A 77, 012307 (2008)ADSCrossRefMATH4.Flammia, S.T., Liu, Y.K.: Direct fidelity estimation from few Pauli measurements. Phys. Rev. Lett. 106, 230501 (2011)ADSCr
simple piece of laboratory equipment, for example a burette or a thermometer, one would expect the number of variables contributing to uncertainties in that measurement to be http://www.csudh.edu/oliver/che230/textbook/ch05.htm fewer than a measurement which is the result of a multi-step process consisting of two or more weight measurements, a titration and the use of a variety of reagents. It is important to be able to estimate the uncertainty in any measurement because not doing so leaves the investigator as ignorant as though there were no measurement at all. The phrase "not doing error analysis so" perpetuates the myth that somehow a person can make a measurement and not know anything about the variability of the measurement. That doesn't happen very often. A needle swings back and forth or a digital output shows a slight instability, so the investigator can estimate the uncertainty, but what if a gross error is made in judgment, leading one to estimate an unrealistic types of error "safe" envelope of uncertainty in the measurement? Consider the anecdote offered by Richard Feynman about one of his experiences while working on the Manhattan Project during World War II. Although this example doesn't address the uncertainty of a particular measurement it touches on problems which can arise when there is complete ignorance of parameter boundaries: Some of the special problems I had at Los Alamos were rather interesting. One thing had to do with the safety of the plant at Oak Ridge, Tennessee. Los Alamos was going to make the [atomic] bomb, but at Oak Ridge they were trying to separate the isotopes of uranium -- uranium 238 and uranium 235, the explosive one. They were just beginning to get infinitesimal amounts from an experimental thing [isotope separation] of 235, and at the same time they were practicing the chemistry. There was going to be a big plant, they were going to have vats of the stuff, and then they were going to take the purified stuff and repurify and get it ready for the next stage. (You have to purify it in several stages.) So they were practicing
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