Determination of the chemical potential using energy-biased sampling

An energy-biased method to evaluate ensemble averages requiring test-particle insertion is presented. The method is based on biasing the sampling within the subdomains of the test-particle configurational space with energies smaller than a given value freely assigned. These energy-wells are located via unbiased random insertion over the whole configurational space and are sampled using the so called Hit&Run algorithm, which uniformly samples compact regions of any shape immersed in a space of arbitrary dimensions. Because the bias is defined in terms of the energy landscape it can be exactly corrected to obtain the unbiased distribution. The test-particle energy distribution is then combined with the Bennett relation for the evaluation of the chemical potential. We apply this protocol to a system with relatively small probability of low-energy test-particle insertion, liquid argon at high density and low temperature, and show that the energy-biased Bennett method is around five times more efficient than the standard Bennett method. A similar performance gain is observed in the reconstruction of the energy distribution.Comment: 10 pages, 4 figure

Gauge and matter fields as surfaces and loops - an exploratory lattice study of the Z(3) Gauge-Higgs model

We discuss a representation of the Z(3) Gauge-Higgs lattice field theory at finite density in terms of dual variables, i.e., loops of flux and surfaces. In the dual representation the complex action problem of the conventional formulation is resolved and Monte Carlo simulations at arbitrary chemical potential become possible. A suitable algorithm based on plaquette occupation numbers and link-fluxes is introduced and we analyze the model at zero temperature and finite density both in the weak and strong coupling phases. We show that at zero temperature the model has different first order phase transitions as a function of the chemical potential both for the weak and strong coupling phases. The exploratory study demonstrates that alternative degrees of freedom may successfully be used for Monte Carlo simulations in several systems with gauge and matter fields.Comment: Typos corrected and some statements refined. Final version to appear in Phys. Rev.

Divergences in Kaluza-Klein Models and their String Regularization

Effective field theories with (large) extra dimensions are studied within a physical regularization scheme provided by string theory. Explicit string calculations then allow us to consistently analyze the ultraviolet sensitivity of Kaluza--Klein theories in the presence or absence of low energy supersymmetry.Comment: 50 pages, LaTe

Theory of electronic transport through a triple quantum dot in the presence of magnetic field

Theory of electronic transport through a triangular triple quantum dot subject to a perpendicular magnetic field is developed using a tight binding model. We show that magnetic field allows to engineer degeneracies in the triple quantum dot energy spectrum. The degeneracies lead to zero electronic transmission and sharp dips in the current whenever a pair of degenerate states lies between the chemical potential of the two leads. These dips can occur with a periodicity of one flux quantum if only two levels contribute to the current or with half flux quantum if the three levels of the triple dot contribute. The effect of strong bias voltage and different lead-to-dot connections on Aharonov-Bohm oscillations in the conductance is also discussed

Fluctuating hydrodynamic modelling of fluids at the nanoscale

A good representation of mesoscopic fluids is required to combine with molecular simulations at larger length and time scales (De Fabritiis {\it et. al}, Phys. Rev. Lett. 97, 134501 (2006)). However, accurate computational models of the hydrodynamics of nanoscale molecular assemblies are lacking, at least in part because of the stochastic character of the underlying fluctuating hydrodynamic equations. Here we derive a finite volume discretization of the compressible isothermal fluctuating hydrodynamic equations over a regular grid in the Eulerian reference system. We apply it to fluids such as argon at arbitrary densities and water under ambient conditions. To that end, molecular dynamics simulations are used to derive the required fluid properties. The equilibrium state of the model is shown to be thermodynamically consistent and correctly reproduces linear hydrodynamics including relaxation of sound and shear modes. We also consider non-equilibrium states involving diffusion and convection in cavities with no-slip boundary conditions

Supersymmetry without a light Higgs boson but with a light pseudoscalar

We consider the lambda-SUSY model, a version of the NMSSM with large lambda H_1 H_2 S coupling, relaxing the approximation of large singlet mass and negligible mixing of the scalar singlet with the scalar doublets. We show that there are regions of the parameter space in which the lightest pseudoscalar can be relatively light, with unusual consequences on the decay pattern of the CP-even Higgs bosons and thus on the LHC phenomenology.Comment: 11 pages, 3 figures. v3: Conforms to published versio

New centrality and causality metrics assessing air traffic network interactions

In ATM systems, the massive number of interacting entities makes it difficult to identify critical elements and paths of disturbance propagation, as well as to predict the system-wide effects that innovations might have. To this end, suitable metrics are required to assess the role of the interconnections between the elements and complex network science provides several network metrics to evaluate the network functioning. Here we focus on centrality and causality metrics measuring, respectively, the importance of a node and the propagation of disturbances along links. By investigating a dataset of US flights, we show that existing centrality and causality metrics are not suited to characterise the effect of delays in the system. We then propose generalisations of such metrics that we prove suited to ATM applications. Specifically, the new centrality is able to account for the temporal and multi-layer structure of ATM network, while the new causality metric focuses on the propagation of extreme events along the system

Towards new metrics assessing air traffic network interactions

In ATM systems, the massive number of interactin entities makes it difficult to predict the system-wide effects that innovations might have. Here, we present the approach proposed by the project Domino to assess such effects and identify the impact that innovations might bring for the different stake-holders, based on agent-based modelling and complex network science. Domino will model scenarios mirroring different system innovations which change the agents’ actions and behaviour. Suitable network metrics are needed to evaluate the effect of innovations on the network functioning. We review existing centrality and causality metrics and show their limitations in characterising the network by applying them to a dataset of US flights. We finally suggest improvements that should be introduced to obtain new metrics answering to Domino’s needs