Towards optimal sensor placement for inverse problems in spaces of measures

This paper studies the identification of a linear combination of point sources from a finite number of measurements. Since the data are typically contaminated by Gaussian noise, a statistical framework for its recovery is considered. It relies on two main ingredients, first, a convex but non-smooth Tikhonov point estimator over the space of Radon measures and, second, a suitable mean-squared error based on its Hellinger-Kantorovich distance to the ground truth. Assuming standard non-degenerate source conditions as well as applying careful linearization arguments, a computable upper bound on the latter is derived. On the one hand, this allows to derive asymptotic convergence results for the mean-squared error of the estimator in the small small variance case. On the other, it paves the way for applying optimal sensor placement approaches to sparse inverse problems.Comment: 31 pages, 8 figure

An advanced hardware-in-the-loop battery simulation platform for the experimental testing of battery management system

Extensive testing of a battery management system (BMS) on real battery storage system (BSS) requires lots of efforts in setting up and configuring the hardware as well as protecting the system from unpredictable faults during the test. To overcome this complexity, a hardware-in-the-loop (HIL) simulation tool is employed and integrated to the BMS test system. By using this tool, it allows to push the tested system up to the operational limits, where may incur potential faults or accidents, to examine all possible test cases within the simulation environment. In this paper, an advanced HIL-based virtual battery module (VBM), consists of one “live” cell connected in series with fifteen simulated cells, is introduced for the purposes of testing the BMS components. First, the complete cell model is built and validated using real world driving cycle while the HIL-based VBM is then exercised under an Urban Dynamometer Driving Schedule (UDDS) driving cycle to ensure it is fully working and ready for the BMS testing in real-time. Finally, commissioning of the whole system is performed to guarantee the stable operation of the system for the BMS evaluation

Deploying quantum light sources on nanosatellites II: lessons and perspectives on CubeSat spacecraft

To enable space-based quantum key distribution proposals the Centre for Quantum Technologies is developing a source of entangled photons ruggedized to survive deployment in space and greatly miniaturised so that it conforms to the strict form factor and power requirements of a 1U CubeSat. The Small Photon Entangling Quantum System is an integrated instrument where the pump, photon pair source and detectors are combined within a single optical tray and electronics package that is no larger than 10 cm x 10 cm x 3 cm. This footprint enables the instrument to be placed onboard nanosatellites or the CubeLab structure aboard the International Space Station. We will discuss the challenges and future prospects of CubeSat-based missions.Comment: Submitted to SPIE Quantum Information Science and Technology. Paper number 9648-4

From the Laboratory to The Vineyard—Evolution of The Measurement of Grape Composition using NIR Spectroscopy towards High-Throughput Analysis

Compared to traditional laboratory methods, spectroscopic techniques (e.g., near infrared, hyperspectralimaging)provideanalystswithaninnovativeandimprovedunderstandingofcomplex issuesbydeterminingseveralchemicalcompoundsandmetabolitesatonce,allowingforthecollection of the sample “fingerprint”. These techniques have the potential to deliver high-throughput options for the analysis of the chemical composition of grapes in the laboratory, the vineyard and before or during harvest, to provide better insights of the chemistry, nutrition and physiology of grapes. Faster computers, the development of software and portable easy to use spectrophotometers and data analytical methods allow for the development of innovative applications of these techniques for the analyses of grape composition

From the Laboratory to The Vineyard—Evolution of The Measurement of Grape Composition using NIR Spectroscopy towards High-Throughput Analysis

Compared to traditional laboratory methods, spectroscopic techniques (e.g., near infrared, hyperspectralimaging)provideanalystswithaninnovativeandimprovedunderstandingofcomplex issuesbydeterminingseveralchemicalcompoundsandmetabolitesatonce,allowingforthecollection of the sample “fingerprint”. These techniques have the potential to deliver high-throughput options for the analysis of the chemical composition of grapes in the laboratory, the vineyard and before or during harvest, to provide better insights of the chemistry, nutrition and physiology of grapes. Faster computers, the development of software and portable easy to use spectrophotometers and data analytical methods allow for the development of innovative applications of these techniques for the analyses of grape composition

Unweighting multijet event generation using factorisation-aware neural networks

In this article we combine a recently proposed method for factorisation-aware matrix element surrogates with an unbiased unweighting algorithm. We show that employing a sophisticated neural network emulation of QCD multijet matrix elements based on dipole factorisation can lead to a drastic acceleration of unweighted event generation. We train neural networks for a selection of partonic channels contributing at the tree-level to Z+4,5 jets and t¯t + 3, 4 jets production at the LHC which necessitates a generalisation of the dipole emulation model to include initial state partons as well as massive final state quarks. We also present first steps towards the emulation of colour-sampled amplitudes. We incorporate these emulations as fast and accurate surrogates in a two-stage rejection sampling algorithm within the SHERPA Monte Carlo that yields unbiased unweighted events suitable for phenomenological analyses and post-processing in experimental workflows, e.g. as input to a time-consuming detector simulation. For the computational cost of unweighted events we achieve a reduction by factors between 16 and 350 for the considered channels