Decoherence induced by squeezing control errors in optical and ion trap holonomic quantum computations

We study decoherence induced by stochastic squeezing control errors considering the particular implementation of Hadamard gate on optical and ion trap holonomic quantum computers. We find the fidelity for Hadamard gate and compute the purity of the final state when the control noise is modeled by Ornstein-Uhlenbeck stochastic process. We demonstrate that in contradiction to the case of the systematic control errors the stochastic ones lead to decoherence of the final state. In the small errors limit we derive a simple formulae connecting the gate fidelity and the purity of the final state.Comment: RevTex, 5 pages, few typos correcte

The European position of Dutch plant communities

Contains fulltext : 72513.pdf (publisher's version ) (Open Access)14 p

Runoff at the micro-plot and slope scale following wildfire, central Portugal

Through their effects on soil properties and vegetation/litter cover, wildfires can strongly enhance overland flow generation and accelerate soil erosion [1] and, thereby, negatively affect land-use sustainability as well as downstream aquatic and flood zones. Wildfires are a common phenomenon in present-day Portugal, devastating in an average year some 100.000 ha of forest and woodlands and in an exceptional year like 2003 over 400.000 ha. There therefore exists a clear need in Portugal for a tool that can provide guidance to post-fire land management by predicting soil erosion risk, on the one hand, and, on the other, the mitigation effectiveness of soil conservation measures. Such a tool has recently been developed for the Western U.S.A. [3: ERMiT] but its suitability for Portuguese forests will need to be corroborated by field observations. Testing the suitability of existing erosion models in recently burned forest areas in Portugal is, in a nutshell, the aim of the EROSFIRE projects. In the first EROSFIRE project the emphasis was on the prediction of erosion at the scale of individual hill slopes. In the ongoing EROSFIRE-II project the spatial scope is extended to include the catchment scale, so that also the connectivity between hill slopes as well as channel and road processes are being addressed. Besides ERMiT, the principal models under evaluation for slope-scale erosion prediction are: (i) the variant of USLE [4] applied by the Portuguese Water Institute after the wildfires of 2003; (ii) the Morgan–Morgan–Finney model (MMF) [5]; (iii) MEFIDIS [6]. From these models, MEFIDIS and perhaps MMF will, after successful calibration at the slope scale, also be applied for predicting catchment-scale sediment yields of extreme events

FLOCK: Fast, Lightweight, and Scalable Allocation for Decentralized Services on Blockchain

Many decentralized services have recently emerged on top of blockchain, offering benefits like privacy, and allowing any node in the network to share its resources. In order to be a competitive alternative to their central counterparts, their performance needs to match up. Specifically, service allocation remains a performance bottleneck for many decentralized services.In this paper we present FLOCK, an allocation system which is highly scalable, fast, and lightweight. Furthermore, it allows nodes to indicate their preference for clients/sellers without needing to submit bids by using stable matching algorithms. We decouple the price discovery and outsource this function to a smart contract on the blockchain.Additionally, another smart contract is used to orchestrate the allocation and take care of service discovery, while trusted execution environments securely compute allocation solutions, and off-chain payment networks are used to send rewards.Evaluation of FLOCK shows that gas costs are manageable and improve upon other solutions which leverage auctions, and that our instance of the stable matching algorithm greatly improves run-time and throughput over auction counterparts. Finally, our discussion outlines practical improvements to further increase performance

The Case for AI Based Web3 Reputation Systems

Initiatives such as blockchains and decentralized storage networks are pushing for a decentralized Web3 to replace the current architecture. At the core of Web3 are network resource sharing services, which allow anyone to sell spare network capacity in return for rewards. These services require a way to establish trust, as parties are potentially malicious. This can be achieved by reputation systems. In this paper we make the case for using deep reinforcement learning in Web3 reputation calculation. More specifically, we propose a model which allows for decentralized calculation of scores with high personalization for the user

Runoff and erosion at the micro-plot and slope scale in a small burnt catchment, central Portugal

Wildfires can have important impacts on hydrological processes and soil erosion in forest catchments, due to the destruction of vegetation cover and changes to soil properties. However, the processes involved are non-linear and not fully understood. This has severely limited the understanding on the impacts of wildfires, especially in the up-scaling from hillslopes to catchments; in consequence, current models are poorly adapted for burnt forest conditions. The objective of this presentation is to give an overview of the hydrological response and sediment yield from the micro-plot to slope scale, in the first year following a wildfire (2008/2009) that burnt an entire catchment nearby the Colmeal village, central Portugal. The overview will focus on three slopes inside the catchment, with samples including: • Runoff at micro-plot scale (12 bounded plots) and slope scale (12 open plots); • Sediments and Organic Matter loss at micro-plot scale (12 bounded plots) and slope scale (12 open plots plus 3 Sediment fences); • Rainfall and Soil moisture data; • Soil Water Repellency and Ground Cover data. The analysis of the first year following the wildfire clearly shows the complexity of runoff generation and the associated sediment transport in recently burnt areas, with pronounced differences between hillslopes and across spatial scales as well as with marked variations through time. This work was performed in the framework of the EROSFIRE-II project (PTDC/AGR-CFL/70968/2006) which has as overall aim to predict soil erosion risk in recently burnt forest areas, including common post-fire forest management practices; the project focuses on the simultaneous measurement of runoff and soil erosion at multiple spatial scales.The results to be presented in this session are expected to show how sediment is generated, transported and exported in the Colmeal watershed; and contribute to understand and simulate erosion processes in burnt catchments, including for model development and evaluation

Hydrological and erosion response at micro-plot to -catchment scale following forest wildfire, north-central Portugal

Wildfires can have important impacts on hydrological and soil erosion processes, due to the destruction of vegetation cover and changes to soil properties. According to Shakesby and Doerr (2006), these wildfire effects are: i) much better known at small spatial scales (especially erosion plots) than at the scale of catchments; ii) much better studied with respect to overland flow and streamflow (and, then, especially peak discharges) than to soil erosion. Following up on a precursor project studying runoff generation and the associated soil losses from micro-plot to slope-scale in Portuguese eucalypt forests, the EROSFIRE-II project addresses the connectivity of these processes across hillslopes as well as within the channel network. This is done in the Colmeal study area in central Portugal, where the outlet of an entirely burnt catchment of roughly 10 ha was instrumented with a gauging station continuously recording water level and tubidity, and five slopes were each equipped with 4 runoff plots of < 0,5 m2 (“micro-plot”) and 4 slope-scale plots as well as 1 slope-scale sediment fence. Starting one month after the August 2008 wildfire, the plots were monitored at 1- to 2-weekly intervals, depending on the occurrence of rainfall. The gauging station became operational at the end of November 2008, since the in-situ construction of an H-flume required several weeks. A preliminary analysis of the data collected till the end of 2008, focusing on two slopes with contrasting slope lengths as well as the gauging station: revealed clear differences in runoff and erosion between: (i) the micro-plot and slope-scale plots on the same hillslope; (ii) the two slopes; (iii) an initial dry period and a subsequent much wetter period; (iv) the slopes and the catchment-scale, also depending on the sampling period. These results suggest that the different processes govern the hydrological and erosion response at different spatial scales as well as for different periods, with soil water repellency playing a role during the initial post-fire period. The current presentation will review these preliminary results based on the data collected during the first year after the wildfire

Paired and altruistic kidney donation in the UK: algorithms and experimentation

We study the computational problem of identifying optimal sets of kidney exchanges in the UK. We show how to expand an integer programming-based formulation [1, 19] in order to model the criteria that constitute the UK definition of optimality. The software arising from this work has been used by the National Health Service Blood and Transplant to find optimal sets of kidney exchanges for their National Living Donor Kidney Sharing Schemes since July 2008.We report on the characteristics of the solutions that have been obtained in matching runs of the scheme since this time. We then present empirical results arising from the real datasets that stem from these matching runs, with the aim of establishing the extent to which the particular optimality criteria that are present in the UK influence the structure of the solutions that are ultimately computed. A key observation is that allowing 4-way exchanges would be likely to lead to a significant number of additional transplants