Encoding dependent generalization bounds for parametrized quantum circuits

A large body of recent work has begun to explore the potential of parametrized quantum circuits PQCs as machine learning models, within the framework of hybrid quantum classical optimization. In particular, theoretical guarantees on the out of sample performance of such models, in terms of generalization bounds, have emerged. However, none of these generalization bounds depend explicitly on how the classical input data is encoded into the PQC. We derive generalization bounds for PQC based models that depend explicitly on the strategy used for data encoding. These imply bounds on the performance of trained PQC based models on unseen data. Moreover, our results facilitate the selection of optimal data encoding strategies via structural risk minimization, a mathematically rigorous framework for model selection. We obtain our generalization bounds by bounding the complexity of PQC based models as measured by the Rademacher complexity and the metric entropy, two complexity measures from statistical learning theory. To achieve this, we rely on a representation of PQC based models via trigonometric functions. Our generalization bounds emphasize the importance of well considered data encoding strategies for PQC based model

Encoding dependent generalization bounds for parametrized quantum circuits

A large body of recent work has begun to explore the potential of parametrized quantum circuits PQCs as machine learning models, within the framework of hybrid quantum classical optimization. In particular, theoretical guarantees on the out of sample performance of such models, in terms of generalization bounds, have emerged. However, none of these generalization bounds depend explicitly on how the classical input data is encoded into the PQC. We derive generalization bounds for PQC based models that depend explicitly on the strategy used for data encoding. These imply bounds on the performance of trained PQC based models on unseen data. Moreover, our results facilitate the selection of optimal data encoding strategies via structural risk minimization, a mathematically rigorous framework for model selection. We obtain our generalization bounds by bounding the complexity of PQC based models as measured by the Rademacher complexity and the metric entropy, two complexity measures from statistical learning theory. To achieve this, we rely on a representation of PQC based models via trigonometric functions. Our generalization bounds emphasize the importance of well considered data encoding strategies for PQC based model

Antibacterial E ect of Chitosan–Gold Nanoparticles and Computational Modeling of the Interaction between Chitosan and a Lipid Bilayer Model

Pathogenic bacteria have the ability to develop antibiotic resistance mechanisms. Their action consists mainly in the production of bacterial enzymes that inactivate antibiotics or the appearance of modifications that prevent the arrival of the drug at the target point or the alteration of the target point itself, becoming a growing problem for health systems. Chitosan–gold nanoparticles (Cs-AuNPs) have been shown as effective bactericidal materials avoiding damage to human cells. In this work, Cs-AuNPs were synthesized using chitosan as the reducing agent, and a systematic analysis of the influence of the synthesis parameters on the size and zeta potential of the Cs-AuNPs and their UV-vis spectra was carried out. We used a simulation model to characterize the interaction of chitosan with bacterial membranes, using a symmetric charged bilayer and two different chitosan models with different degrees of the chitosan amine protonation as a function of pH, with the aim to elucidate the antibacterial mechanism involving the cell wall disruption. The Cs-AuNP antibacterial activity was evaluated to check the simulation model

Antibacterial Effect of Chitosan–Gold Nanoparticles and Computational Modeling of the Interaction between Chitosan and a Lipid Bilayer Model

Pathogenic bacteria have the ability to develop antibiotic resistance mechanisms. Their action consists mainly in the production of bacterial enzymes that inactivate antibiotics or the appearance of modifications that prevent the arrival of the drug at the target point or the alteration of the target point itself, becoming a growing problem for health systems. Chitosan–gold nanoparticles (Cs-AuNPs) have been shown as effective bactericidal materials avoiding damage to human cells. In this work, Cs-AuNPs were synthesized using chitosan as the reducing agent, and a systematic analysis of the influence of the synthesis parameters on the size and zeta potential of the Cs-AuNPs and their UV-vis spectra was carried out. We used a simulation model to characterize the interaction of chitosan with bacterial membranes, using a symmetric charged bilayer and two different chitosan models with different degrees of the chitosan amine protonation as a function of pH, with the aim to elucidate the antibacterial mechanism involving the cell wall disruption. The Cs-AuNP antibacterial activity was evaluated to check the simulation model.Fil: Fuster, M.G.. Universidad de Murcia. Facultad de Química; EspañaFil: Montalbán, M. G.. Universidad de Murcia. Facultad de Química; EspañaFil: Carissimi, G.. Universidad de Murcia. Facultad de Química; EspañaFil: Lima, Beatriz Viviana. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Feresin, Gabriela Egly. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Cano, M.. Universidad de Cordoba. Instituto Universitario de Investigación En Química Fina y Nanoquímica.; EspañaFil: Giner Casares, J. J.. Universidad de Cordoba. Instituto Universitario de Investigación En Química Fina y Nanoquímica.; EspañaFil: López Cascales, J.J.. Universidad Politécnica de Cartagena; EspañaFil: Enriz, Ricardo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Víllora, G.. Universidad de Murcia. Facultad de Química; Españ

Two-domains bulklike Fermi surface of Ag films deposited onto Si(111)-(7x7)

Thick metallic silver films have been deposited onto Si(111)-(7x7) substrates at room temperature. Their electronic properties have been studied by using angle resolved photoelectron spectroscopy (ARPES). In addition to the electronic band dispersion along the high-symmetry directions, the Fermi surface topology of the grown films has been investigated. Using ARPES, the spectral weight distribution at the Fermi level throughout large portions of the reciprocal space has been determined at particular perpendicular electron-momentum values. Systematically, the contours of the Fermi surface of these films reflected a sixfold symmetry instead of the threefold symmetry of Ag single crystal. This loss of symmetry has been attributed to the fact that these films appear to be composed by two sets of domains rotated 60$^o$ from each other. Extra, photoemission features at the Fermi level were also detected, which have been attributed to the presence of surface states and \textit{sp}-quantum states. The dimensionality of the Fermi surface of these films has been analyzed studying the dependence of the Fermi surface contours with the incident photon energy. The behavior of these contours measured at particular points along the Ag $\Gamma$L high-symmetry direction puts forward the three-dimensional character of the electronic structure of the films investigated.Comment: 10 pages, 12 figures, submitted to Physical Review

A dynamic neural field approach to natural and efficient human-robot collaboration

A major challenge in modern robotics is the design of autonomous robots that are able to cooperate with people in their daily tasks in a human-like way. We address the challenge of natural human-robot interactions by using the theoretical framework of dynamic neural fields (DNFs) to develop processing architectures that are based on neuro-cognitive mechanisms supporting human joint action. By explaining the emergence of self-stabilized activity in neuronal populations, dynamic field theory provides a systematic way to endow a robot with crucial cognitive functions such as working memory, prediction and decision making . The DNF architecture for joint action is organized as a large scale network of reciprocally connected neuronal populations that encode in their firing patterns specific motor behaviors, action goals, contextual cues and shared task knowledge. Ultimately, it implements a context-dependent mapping from observed actions of the human onto adequate complementary behaviors that takes into account the inferred goal of the co-actor. We present results of flexible and fluent human-robot cooperation in a task in which the team has to assemble a toy object from its components.The present research was conducted in the context of the fp6-IST2 EU-IP Project JAST (proj. nr. 003747) and partly financed by the FCT grants POCI/V.5/A0119/2005 and CONC-REEQ/17/2001. We would like to thank Luis Louro, Emanuel Sousa, Flora Ferreira, Eliana Costa e Silva, Rui Silva and Toni Machado for their assistance during the robotic experiment

Evidence for a mixed mass composition at the `ankle' in the cosmic-ray spectrum

We report a first measurement for ultra-high energy cosmic rays of the correlation between the depth of shower maximum and the signal in the water Cherenkov stations of air-showers registered simultaneously by the fluorescence and the surface detectors of the Pierre Auger Observatory. Such a correlation measurement is a unique feature of a hybrid air-shower observatory with sensitivity to both the electromagnetic and muonic components. It allows an accurate determination of the spread of primary masses in the cosmic-ray flux. Up till now, constraints on the spread of primary masses have been dominated by systematic uncertainties. The present correlation measurement is not affected by systematics in the measurement of the depth of shower maximum or the signal in the water Cherenkov stations. The analysis relies on general characteristics of air showers and is thus robust also with respect to uncertainties in hadronic event generators. The observed correlation in the energy range around the `ankle' at $\lg(E/{\rm eV})=18.5-19.0$ differs significantly from expectations for pure primary cosmic-ray compositions. A light composition made up of proton and helium only is equally inconsistent with observations. The data are explained well by a mixed composition including nuclei with mass $A > 4$. Scenarios such as the proton dip model, with almost pure compositions, are thus disfavoured as the sole explanation of the ultrahigh-energy cosmic-ray flux at Earth.Comment: Published version. Added journal reference and DOI. Added Report Numbe

Search for composite and exotic fermions at LEP 2

A search for unstable heavy fermions with the DELPHI detector at LEP is reported. Sequential and non-canonical leptons, as well as excited leptons and quarks, are considered. The data analysed correspond to an integrated luminosity of about 48 pb^{-1} at an e^+e^- centre-of-mass energy of 183 GeV and about 20 pb^{-1} equally shared between the centre-of-mass energies of 172 GeV and 161 GeV. The search for pair-produced new leptons establishes 95% confidence level mass limits in the region between 70 GeV/c^2 and 90 GeV/c^2, depending on the channel. The search for singly produced excited leptons and quarks establishes upper limits on the ratio of the coupling of the excited fermio

Search for charginos in e+e- interactions at sqrt(s) = 189 GeV

An update of the searches for charginos and gravitinos is presented, based on a data sample corresponding to the 158 pb^{-1} recorded by the DELPHI detector in 1998, at a centre-of-mass energy of 189 GeV. No evidence for a signal was found. The lower mass limits are 4-5 GeV/c^2 higher than those obtained at a centre-of-mass energy of 183 GeV. The (\mu,M_2) MSSM domain excluded by combining the chargino searches with neutralino searches at the Z resonance implies a limit on the mass of the lightest neutralino which, for a heavy sneutrino, is constrained to be above 31.0 GeV/c^2 for tan(beta) \geq 1.Comment: 22 pages, 8 figure