Hot Zero and Full Power Validation of PHISICS RELAP-5 Coupling

PHISICS is a reactor analysis toolkit developed over the last 3 years at the Idaho National Laboratory. It has been coupled with the reactor safety analysis code RELAP5-3D. PHISICS is aimed at providing an optimal trade off between needed computational resources (in the range of 10~100 computer processors) and accuracy. In fact, this range has been identified as the next 5 to 10 years average computational capability available to nuclear reactor design and optimization nuclear reactor cores. Detailed information about the individual modules of PHISICS can be found in [1]. An overview of the modules used in this study is given in the next subsection. Lately, the Idaho National Laboratory gained access plant data for the first cycle of a PWR, including Hot Zero Power (HZP) and Hot Full Power (HFP). This data provides the opportunity to validate the transport solver, the interpolation capability for mixed macro and micro cross section and the criticality search option of the PHISICS pack

Proper orthogonal decomposition of solar photospheric motions

The spatio-temporal dynamics of the solar photosphere is studied by performing a Proper Orthogonal Decomposition (POD) of line of sight velocity fields computed from high resolution data coming from the MDI/SOHO instrument. Using this technique, we are able to identify and characterize the different dynamical regimes acting in the system. Low frequency oscillations, with frequencies in the range 20-130 microHz, dominate the most energetic POD modes (excluding solar rotation), and are characterized by spatial patterns with typical scales of about 3 Mm. Patterns with larger typical scales of 10 Mm, are associated to p-modes oscillations at frequencies of about 3000 microHz.Comment: 8 figures in jpg in press on PR

An Optimal Execution Problem with Market Impact

We study an optimal execution problem in a continuous-time market model that considers market impact. We formulate the problem as a stochastic control problem and investigate properties of the corresponding value function. We find that right-continuity at the time origin is associated with the strength of market impact for large sales, otherwise the value function is continuous. Moreover, we show the semi-group property (Bellman principle) and characterise the value function as a viscosity solution of the corresponding Hamilton-Jacobi-Bellman equation. We introduce some examples where the forms of the optimal strategies change completely, depending on the amount of the trader's security holdings and where optimal strategies in the Black-Scholes type market with nonlinear market impact are not block liquidation but gradual liquidation, even when the trader is risk-neutral.Comment: 36 pages, 8 figures, a modified version of the article "An optimal execution problem with market impact" in Finance and Stochastics (2014

Hough Transform Proposal and Simulations for Particle Track Recognition for LHC Phase-II Upgrade

In the near future, LHC experiments will continue future upgrades by overcoming the technological obsolescence of the detectors and the readout capabilities. Therefore, after the conclusion of a data collection period, CERN will have to face a long shutdown to improve overall performance, by updating the experiments, and implementing more advanced technologies and infrastructures. In particular, the largest LHC experiment, i.e., ATLAS, will upgrade parts of the detector, the trigger, and the data acquisition system. In addition, the ATLAS experiment will complete the implementation of new strategies, algorithms for data handling, and transmission to the final storage apparatus. This paper presents an overview of an upgrade planned for the second half of this decade for the ATLAS experiment. In particular, we show a study of a novel pattern recognition algorithm used in the trigger system, which is a device designed to provide the information needed to select physical events from unnecessary background data. The idea is to use a well known mathematical transform, the Hough transform, as the algorithm for the detection of particle trajectories. The effectiveness of the algorithm has already been validated in the past, regardless of particle physics applications, to recognize generic shapes within images. On the contrary, here, we first propose a software emulation tool, and a subsequent hardware implementation of the Hough transform, for particle physics applications. Until now, the Hough transform has never been implemented on electronics in particle physics experiments, and since a hardware implementation would provide benefits in terms of overall Latency, we complete the studies by comparing the simulated data with a physical system implemented on a Xilinx hardware accelerator (FELIX-II card). In more detail, we have implemented a low-abstraction RTL design of the Hough transform on Xilinx UltraScale+ FPGAs as target devices for filtering applications

Hough Transform FPGA solution for High Energy Physics online fast tracking

In the coming years, significant upgrades are planned for ATLAS and other High Energy Physics experiments at CERN. Both the technologies and methodologies employed will undergo changes for the scheduled runs at the end of the decade. The LHC accelerator itself will also undergo multiple modifications, allowing it to achieve a peak of instantaneous luminosity up to 5–7.5 × 1034 cm−2 s−1. These enhancements will necessitate the experiments to handle a greater number of events at the conclusion of the data acquisition chain. For instance, ATLAS will be compelled to employ online tracking for its inner detector, aiming to achieve a final event rate of 10 kHz from the 1MHz originating from the Calorimeters and the Muon Spectrometer trigger discrimination. Among the architectures explored to expedite fast tracking, there is consideration of a “hardware accelerator” farm, an infrastructure made of interconnected accelerators such as GPUs and FPGAs, designed to accelerate the tracking processes. The project presented here proposes a tuned Hough Transform algorithm implementation on high-end FPGA technology, specifically designed to adapt to various tracking situations. A development platform comprising software and firmware tools has been created to study different datasets. This platform utilizes software to simulate the firmware and to perform hardware tests. AMD-Xilinx FPGAs were chosen to implement and asses the system, with specific boards such as the VC709, the VCU1525 and the Alveo U250. Strategies such as low-level design for the firmware architecture, leveraging the card’s features like PCI Express data transfer, and the > 1 million gates array available have been exploited. The system underwent testing using internally simulated events generated within the ATLAS environment. Simulated 200 pile up events were used to evaluate the algorithm effectiveness. The average processing time was estimated to be below 5 μs, with the capability to concurrently process two events per algorithm instance. Internal efficiency tests have shown conditions where track finding performance for single muon tracking exceeded 95%