Assessments of macroscopicity for quantum optical states

With the slow but constant progress in the coherent control of quantum systems, it is now possible to create large quantum superpositions. There has therefore been an increased interest in quantifying any claims of macroscopicity. We attempt here to motivate three criteria which we believe should enter in the assessment of macroscopic quantumness: The number of quantum fluctuation photons, the purity of the states, and the ease with which the branches making up the state can be distinguished

Tomography of a displacement photon counter for discrimination of single-rail optical qubits

We investigate the performance of a Kennedy receiver, which is known as a beneficial tool in optical coherent communications, to the quantum state discrimination of the two superpositions of vacuum and single photon states corresponding to the $\hat\sigma_x$ eigenstates in the single-rail encoding of photonic qubits. We experimentally characterize the Kennedy receiver in vacuum-single photon two-dimensional space using quantum detector tomography and evaluate the achievable discrimination error probability from the reconstructed measurement operators. We furthermore derive the minimum error rate obtainable with Gaussian transformations and homodyne detection. Our proof of principle experiment shows that the Kennedy receiver can achieve a discrimination error surpassing homodyne detection

GROUNDED COMPUTATIONAL ANALYSIS: A HANDS-ON APPROACH TO ANALYSING DIGITAL INNOVATION

As socio-technical processes related to digital innovation are increasingly connected and distributed across geographical, organisational, and temporal boundaries, the methods we use to study them must be adapted to accommodate the greater detail and scope of the phenomenon. Specifically, there is a need to operationalise methods for generating inductive theory of distributed digital innovation from digital trace data. An emerging stream of IS research on computationally intensive inductive theorising lays the groundwork for such methods. This paper builds on this foundation to develop a hands-on approach to operationalising grounded theorizing in computational analysis of digital trace data. The paper first conceptualises trace data of digital innovation as a new research context before articulating an approach to operationalising grounded theory in computational analysis of digital innovation. The application of the grounded computational analysis approach is then briefly illustrated in the context of digital trace data from an online social network before possible directions for further research are laid out

Architecture and noise analysis of continuous variable quantum gates using two-dimensional cluster states

Due to its unique scalability potential, continuous variable quantum optics is a promising platform for large scale quantum computing and quantum simulation. In particular, very large cluster states with a two-dimensional topology that are suitable for universal quantum computing and quantum simulation can be readily generated in a deterministic manner, and routes towards fault-tolerance via bosonic quantum error-correction are known. In this article we propose a complete measurement-based quantum computing architecture for the implementation of a universal set of gates on the recently generated two-dimensional cluster states [1,2]. We analyze the performance of the various quantum gates that are executed in these cluster states as well as in other two-dimensional cluster states (the bilayer-square lattice and quad-rail lattice cluster states [3,4]) by estimating and minimizing the associated stochastic noise addition as well as the resulting gate error probability. We compare the four different states and find that, although they all allow for universal computation, the quad-rail lattice cluster state performs better than the other three states which all exhibit similar performance

Experimental evidence for a partially dissociated water bilayer on Ru{0001}

Core-level photoelectron spectra, in excellent agreement with ab initio calculations, confirm that the stable wetting layer of water on Ru{0001} contains O-H and H2O in roughly 3:5 proportion, for OHx coverages between 0.25 and 0.7 ML, and T<170 K. Proton disorder explains why the wetting structure looks to low energy electron diffraction (LEED) to be an ordered p(root3xroot3)R30degrees adlayer, even though approximate to3/8 of its molecules are dissociated. Complete dissociation to atomic oxygen starts near 190 K. Low photon flux in the synchrotron experiments ensured that the diagnosis of the nature of the wetting structure quantified by LEED is free of beam-induced damage

Super sensitivity and super resolution with quantum teleportation

We propose a method for quantum enhanced phase estimation based on continuous variable (CV) quantum teleportation. The phase shift probed by a coherent state can be enhanced by repeatedly teleporting the state back to interact with the phase shift again using a supply of two-mode squeezed vacuum states. In this way, both super resolution and super sensitivity can be obtained due to the coherent addition of the phase shift. The protocol enables Heisenberg limited sensitivity and super- resolution given sufficiently strong squeezing. The proposed method could be implemented with current or near-term technology of CV teleportation.Comment: 5 pagers, 3 figure

The off-line programming of a PC based industrial robot with sensory feedback (volume I of II)

The need for sensor-based automatic motion planning and control of industrial robots in an unstructured environment is extensive. For example in-factory transportation, household chores, military applications, chemical, radioactive, and other applications dangerous to humans. Researchers are attempting to build systems capable of generating purposeful motion in highly uncertain co-nplex environments, using on-line information from robot sensors. An example of such a task would be moving a mobile robot or a manipulator arm from its starting position to a goal position in a scene with unknown arbitrarily shaped obstacles. Carrying out such tasks requires, first, sensors and relatedGR201

The capacity to maintain ion and water homeostasis underlies interspecific variation in Drosophila cold tolerance

Many insects, including Drosophila, succumb to the physiological effects of chilling at temperatures well above those causing freezing. Low temperature causes a loss of extracellular ion and water homeostasis in such insects, and chill injuries accumulate. Using an integrative and comparative approach, we examined the role of ion and water balance in insect chilling susceptibility/ tolerance. The Malpighian tubules (MT), of chill susceptible Drosophila species lost [Na+] and [K+] selectivity at low temperatures, which contributed to a loss of Na+ and water balance and a deleterious increase in extracellular [K+]. By contrast, the tubules of chill tolerant Drosophila species maintained their MT ion selectivity, maintained stable extracellular ion concentrations, and thereby avoided injury. The most tolerant species were able to modulate ion balance while in a cold-induced coma and this ongoing physiological acclimation process allowed some individuals of the tolerant species to recover from chill coma during low temperature exposure. Accordingly, differences in the ability to maintain homeostatic control of water and ion balance at low temperature may explain large parts of the wide intra- and interspecific variation in insect chilling tolerance