Gaussian processes for choosing laser parameters for driven, dissipative Rydberg aggregates

To facilitate quantum simulation of open quantum systems at finite temperatures, an important ingredient is to achieve thermalization on a given time-scale. We consider a Rydberg aggregate (an arrangement of Rydberg atoms that interact via long-range interactions) embedded in a laser-driven atomic environment. For the smallest aggregate (two atoms), suitable laser parameters can be found by brute force scanning of the four tunable laser parameters. For more atoms, however, such parameter scans are too computationally costly. Here we apply Gaussian processes to predict the thermalization performance as a function of the laser parameters for two-atom and four-atom aggregates. These predictions perform remarkably well using just 1000 simulations, demonstrating the utility of Gaussian processes in an atomic physics setting. Using this approach, we find and present effective laser parameters for generating thermalization, the robustness of these parameters to variation, as well as different thermalization dynamics

Generic guide concepts for the European Spallation Source

The construction of the European Spallation Source (ESS) faces many challenges from the neutron beam transport point of view: The spallation source is specified as being driven by a 5 MW beam of protons, each with 2 GeV energy, and yet the requirements in instrument background suppression relative to measured signal vary between 10$^{-6}$ and 10$^{-8}$. The energetic particles, particularly above 20 MeV, which are expected to be produced in abundance in the target, have to be filtered in order to make the beamlines safe, operational and provide good quality measurements with low background. We present generic neutron guides of short and medium length instruments which are optimized for good performance at minimal cost. Direct line of sight to the source is avoided twice, with either the first point out of line of sight or both being inside the bunker (20\,m) to minimize shielding costs. These guide geometries are regarded as a baseline to define standards for instruments to be constructed at ESS. They are used to find commonalities and develop principles and solutions for common problems. Lastly, we report the impact of employing the over-illumination concept to mitigate losses from random misalignment passively, and that over-illumination should be used sparingly in key locations to be effective. For more widespread alignment issues, a more direct, active approach is likely to be needed

MeV Neutron Production from Thermal Neutron Capture in {6}^Li Simulated with Geant4

Various Li compounds are commonly used at neutron facilities as neutron absorbers. These compounds provide one of the highest ratios of neutron attenuation to $\gamma$-ray production. Unfortunately, the usage of these compounds can also give rise to fast neutron emission with energies up to almost 16 MeV. Historically, some details in this fast neutron production mechanism can be absent from some modeling packages under some optimization scenarios. In this work, we tested Geant4 to assess the performance of this simulation toolkit for the fast neutron generation mechanism. We compare the results of simulations performed with Geant4 to available measurements. The outcome of our study shows that results of the Geant4 simulations are in good agreement with the available measurements for $^6$Li fast neutron production, and suitable for neutron instrument background evaluation at spallation neutron sources.Comment: 6 pages, 3 figures, Proceeding of The Sixth European Conference on Neutron Scattering, Zaragoza Spain, August 30 to September 4 201

Novel battery model of an all-electric personal rapid transit vehicle to determine state-of-health through subspace parameter estimation and a Kalman Estimator

Abstract--The paper describes a real-time adaptive battery model for use in an all-electric Personal Rapid Transit vehicle. Whilst traditionally, circuit-based models for lead-acid batteries centre on the well-known Randles’ model, here the Randles’ model is mapped to an equivalent circuit, demonstrating improved modelling capabilities and more accurate estimates of circuit parameters when used in Subspace parameter estimation techniques. Combined with Kalman Estimator algorithms, these techniques are demonstrated to correctly identify and converge on voltages associated with the battery State-of-Charge, overcoming problems such as SoC drift (incurred by coulomb-counting methods due to over-charging or ambient temperature fluctuations). Online monitoring of the degradation of these estimated parameters allows battery ageing (State-of-Health) to be assessed and, in safety-critical systems, cell failure may be predicted in time to avoid inconvenience to passenger networks. Due to the adaptive nature of the proposed methodology, this system can be implemented over a wide range of operating environments, applications and battery topologies

Flexible scheme to truncate the hierarchy of pure states

The hierarchy of pure states (HOPS) is a wavefunction-based method which can be used for numerically modeling open quantum systems. Formally, HOPS recovers the exact system dynamics for an infinite depth of the hierarchy. However, truncation of the hierarchy is required to numerically implement HOPS. We want to choose a 'good' truncation method, where by 'good' we mean that it is numerically feasible to check convergence of the results. For the truncation approximation used in previous applications of HOPS, convergence checks are numerically challenging. In this work we demonstrate the application of the '$n$-particle approximation' ($n$PA) to HOPS. We also introduce a new approximation, which we call the '$n$-mode approximation' ($n$MA). We then explore the convergence of these truncation approximations with respect to the number of equations required in the hierarchy. We show that truncation approximations can be used in combination to achieve convergence in two exemplary problems: absorption and energy transfer of molecular aggregates.Comment: 8 pages, 3 figure

Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles

Abstract—This paper describes the application of state-estimation techniques for the real-time prediction of the state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, approaches based on the well-known Kalman Filter (KF) and Extended Kalman Filter (EKF), are presented, using a generic cell model, to provide correction for offset, drift, and long-term state divergence—an unfortunate feature of more traditional coulomb-counting techniques. The underlying dynamic behavior of each cell is modeled using two capacitors (bulk and surface) and three resistors (terminal, surface, and end), from which the SoC is determined from the voltage present on the bulk capacitor. Although the structure of the model has been previously reported for describing the characteristics of lithium-ion cells, here it is shown to also provide an alternative to commonly employed models of lead-acid cells when used in conjunction with a KF to estimate SoC and an EKF to predict state-of-health (SoH). Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior to more traditional techniques, with accuracy in determining the SoC within 2% being demonstrated. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack

Observer techniques for estimating the state-of-charge and state-of-health of VRLABs for hybrid electric vehicles

The paper describes the application of observer-based state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, an approach based on the well-known Kalman filter, is employed, to estimate SoC, and the subsequent use of the EKF to accommodate model non-linearities to predict battery SoH. The underlying dynamic behaviour of each cell is based on a generic Randles' equivalent circuit comprising of two-capacitors (bulk and surface) and three resistors, (terminal, transfer and self-discharging). The presented techniques are shown to correct for offset, drift and long-term state divergence-an unfortunate feature of employing stand-alone models and more traditional coulomb-counting techniques. Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC, with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior with SoC being estimated to be within 1% of measured. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack

In-Beam Background Suppression Shield

The long (3ms) proton pulse of the European Spallation Source (ESS) gives rise to unique and potentially high backgrounds for the instrument suite. In such a source an instrument capabilities will be limited by it's Signal to Noise (S/N) ratio. The instruments with a direct view of the moderator, which do not use a bender to help mitigate the fast neutron background, are the most challenging. For these beam lines we propose the innovative shielding of placing blocks of material directly into the guide system, which allow a minimum attenuation of the cold and thermal fluxes relative to the background suppression. This shielding configuration has been worked into a beam line model using Geant4. We study particularly the advantages of single crystal sapphire and silicon blocks .Comment: 12 pages, 8 figures, proceeding of NDS 2015, 4th International Workshop on Neutron Delivery Systems, 28 -30 September 2015, ILL Grenoble, Franc

Battery health determination by subspace parameter estimation and sliding mode control for an all-electric Personal Rapid Transit vehicle — the ULTra

The paper describes a real-time adaptive battery modelling methodology for use in an all electric personal rapid transit (PRT) vehicle. Through use of a sliding-mode observer and online subspace parameter estimation, the voltages associated with monitoring the state of charge (SoC) of the battery system are shown to be accurately estimated, even with erroneous initial conditions in both the model and parameters. In this way, problems such as self- discharge during storage of the cells and SoC drift (as usually incurred by coulomb-counting methods due to overcharging or ambient temperature fluctuations) are overcome. Moreover, through online monitoring of the degradation of the estimated parameters, battery ageing (State of Health) can be monitored and, in the case of safety- critical systems, cell failure may be predicted in time to avoid inconvenience to passenger networks. Due to the adaptive nature of the proposed methodology, this system can be implemented over a wide range of operating environments, applications and battery topologies, by adjustment of the underlying state-space model

State-of-charge and state-of-health prediction of lead-acid batteries for hybrid electric vehicles using non-linear observers

The paper describes the application of state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Approaches based on the extended Kalman filter (EKF) are presented to provide correction for offset, drift and state divergence - an unfortunate feature of more traditional coulomb-counting techniques. Experimental results are employed to demonstrate the relative attributes of the proposed methodolog