Modelling Non-Markovian Quantum Processes with Recurrent Neural Networks

Quantum systems interacting with an unknown environment are notoriously difficult to model, especially in presence of non-Markovian and non-perturbative effects. Here we introduce a neural network based approach, which has the mathematical simplicity of the Gorini-Kossakowski-Sudarshan-Lindblad master equation, but is able to model non-Markovian effects in different regimes. This is achieved by using recurrent neural networks for defining Lindblad operators that can keep track of memory effects. Building upon this framework, we also introduce a neural network architecture that is able to reproduce the entire quantum evolution, given an initial state. As an application we study how to train these models for quantum process tomography, showing that recurrent neural networks are accurate over different times and regimes.Comment: 10 pages, 8 figure

A Statistical Framework for Automatic Leakage Detection in Smart Water and Gas Grids

In the last few years, due to the technological improvement of advanced metering infrastructures, water and natural gas grids can be regarded as smart-grids, similarly to power ones. However, considering the number of studies related to the application of computational intelligence to distribution grids, the gap between power grids and water/gas grids is notably wide. For this purpose, in this paper, a framework for leakage identification is presented. The framework is composed of three sections aimed at the extraction and the selection of features and at the detection of leakages. A variation of the Sequential Feature Selection (SFS) algorithm is used to select the best performing features within a set, including, also, innovative temporal ones. The leakage identification is based on novelty detection and exploits the characterization of a normality model. Three statistical approaches, The Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and One-Class Support Vector Machine (OC-SVM), are adopted, under a comparative perspective. Both residential and office building environments are investigated by means of two datasets. One is the Almanac of Minutely Power dataset (AMPds), and it provides water and gas data consumption at 1, 10 and 30 min of time resolution; the other is the Department of International Development (DFID) dataset, and it provides water and gas data consumption at 30 min of time resolution. The achieved performance, computed by means of the Area Under the Curve (AUC), reaches 90 % in the office building case study, thus confirming the suitability of the proposed approach for applications in smart water and gas grids

Investigation into the Influence of the Process Parameters on the Stability of a Poly(Vinyl)-Alcohol-Based Coating System

Most tablets put on the market are coated with polymers soluble in water. The Opadry II 85 series from Colorcon Inc., is a family of PVA-based products marketed since the 1990s. Despite numerous publications on the properties of PVA, to date, limited work has been undertaken to determine the physico-chemical parameters (i.e., UV light, high temperature, and relative humidity) that could affect the performance of PVA-based coatings. To this end, we performed artificial ageing processes on samples made of Opadry Orange II or of some selected components of this coating and analysed them by means of a multidisciplinary approach, using, for example, FTIR, NMR, rheology, and DMTA measurements. In this way, we analysed the influence of the critical components of the Opadry Orange II formula, such as titanium dioxide and aluminium hydroxide, on the coating characteristics under ageing conditions

Expanding the circularity of plastic and biochar materials by developing alternative low environmental footprint sensors

Flexible screen-printing technology combined with the use of a nano/material coating for improving electrode functionalities boosted the manufacturing of highly sensitive electrochemical sensors addressing the need for fast and easy-to-handle tests in different application fields. However, due to the large-scale production and disposable and single-use nature of these devices, their environmental footprint should be taken into careful consideration. Herein, the innovative reuse of post-consumer polyethene terephthalate (PET) plastics as an alternative substrate coupled with biochar as an environmentally friendly and cost-effective modifier is described as a sustainable alternative for the production of robust electrochemical sensors. The good printability of reused plastics with graphite inks despite the chemical heterogeneity, different crystallinity, and surface roughness was demonstrated using atomic force microscopy and attenuated total reflection Fourier transform infrared spectroscopy. Functionalization with brewers' spent grain biochar enabled the fabrication of highly performing electrochemical sensors for nitrite detection in water having a limit of detection and a limit of quantification of 3.3 nM and 10.3 nM, respectively, with a linear range spanning from 0.01 to 500 & mu;M, and good reproducibility (RSD% 8%). The innovative intervention of the biochar-multilayer system markedly enhanced the electron transfer process at the electrode interface while simultaneously serving as an absorptive material for the investigated analyte. This work lays a foundation for repurposing end-of-life plastics for the electronics industry and presents a customizable reuse strategy aimed to keep the value of plastics in the economy and reduce waste and leakage into the natural environment

Pretty good state transfer in qubit chains-The Heisenberg Hamiltonian

Pretty good state transfer in networks of qubits occurs when a continuous-time quantum walk allows the transmission of a qubit state from one node of the network to another, with fidelity arbitrarily close to 1. We prove that in a Heisenberg chain with n qubits, there is pretty good state transfer between the nodes at the jth and (n − j + 1)th positions if n is a power of 2. Moreover, this condition is also necessary for j = 1. We obtain this result by applying a theorem due to Kronecker about Diophantine approximations, together with techniques from algebraic graph theory

Neither hereditary periodic fever nor periodic fever, aphthae, pharingitis, adenitis: Undifferentiated periodic fever in a tertiary pediatric center

AIM: To describe the frequency and clinical characteristics of patients with undifferentiated periodic fever (UPF) and to investigate whether a clinical classification of UPF based on the PRINTO-Eurofever score can help predicting the response to treatment and the outcome at follow-up. METHODS: Clinical and therapeutic information of patients with recurrent fever who presented at a single pediatric rheumatology center from January 2006 through April 2016 were retrospectively collected. Patients with a clinical suspicion of hereditary periodic fever (HPF) syndrome and patients with clinical picture of periodic fever, aphthae, pharingitis, adenitis (PFAPA) who were refractory to tonsillectomy underwent molecular analysis of five HPF-related genes: MEFV (NM_000243.2), MVK (NM_000431.3), TNFRSF1A (NM_001065.3), NLRP3 (NM_001079821.2), NLRP12 (NM_001277126.1). All patients who had a negative genetic result were defined as UPF and further investigated. PRINTO-Eurofever score for clinical diagnosis of HPF was calculated in all cases. RESULTS: Of the 221 patients evaluated for periodic fever, twelve subjects with a clinical picture of PFAPA who were refractory to tonsillectomy and 22 subjects with a clinical suspicion of HPF underwent genetic analysis. Twenty-three patients (10.4%) resulted negative and were classified as UPF. The median age at presentation of patients with UPF was 9.5 mo (IQR 4-24). Patients with UPF had a higher frequency of aphthae (52.2% vs 0%, P = 0.0026) and musculoskeletal pain (65.2% vs 18.2%, P = 0.0255) than patients with genetic confirmed HPF. Also, patients with UPF had a higher frequency of aphthous stomatitis (52.2% vs 10.7%, P < 0.0001), musculoskeletal pain (65.2% vs 8,0%, P < 0.0001), and abdominal pain (52.2% vs 4.8%, P < 0.0001) and a lower frequency of pharyngitis (56.6% vs 81.3%, P = 0.0127) compared with typical PFAPA in the same cohort. Twenty-one of 23 patients with UPF (91.3%) received steroids, being effective in 16; 13 (56.2%) were given colchicine, which was effective in 6. Symptoms resolution occurred in 2 patients with UPF at last follow-up. Classification according to the PRINTO-Eurofever score did not correlate with treatment response and prognosis. CONCLUSION: UPF is not a rare diagnosis among patients with periodic fever. Clinical presentation place UPF half way on a clinical spectrum between PFAPA and HPF. The PRINTO-Eurofever score is not useful to predict clinical outcome and treatment response in these patients

Molecular origin of the two-step mechanism of gellan aggregation

Among hydrocolloids, gellan is one of the most studied polysaccharides due to its ability to form mechanically stable gels. Despite its long-standing use, the gellan aggregation mechanism is still not understood because of the lack of atomistic information. Here, we fill this gap by developing a new gellan force field. Our simulations offer the first microscopic overview of gellan aggregation, detecting the coil to single-helix transition at dilute conditions and the formation of higher-order aggregates at high concentration through a two-step process: first, the formation of double helices and then their assembly into superstructures. For both steps, we also assess the role of monovalent and divalent cations, complementing simulations with rheology and atomic force microscopy experiments and highlighting the leading role of divalent cations. These results pave the way for future use of gellan-based systems in a variety of applications, from food science to art restoration

A Roadmap for HEP Software and Computing R&D for the 2020s

Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.Peer reviewe

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements