**1. Introduction**

26 Will-be-set-by-IN-TECH

74 Particle Physics

A. K. Ganguly, S. Konar and P. B. Pal (1999), *Physical Review D* 60 105014.

K. Bhattacharya and A. K. Ganguly (2003) , "The Axialvector vector amplitude and

M. Giovannini (2005), "Magnetized birefringence and CMB polarization," *Physical Review D*

R. Cameron *et al.* (1993), "Search for nearly massless, weakly coupled particles by optical

K. Bhattacharya and A. K. Ganguly (2003), "The Axialvector vector amplitude and neutrino effective charge in a *Physical Review D* 68, 053011. [arXiv:hep-ph/0308063]. R . Cameron. et al., (1993). Search for nearly massless, weakly coupled particles by optical

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neutrino effective charge in a magnetized medium," *Physical Review D* 68, 053011.

[arXiv:hep-ph/9905206].

[arXiv:hep-ph/0308063]. See for instance (A. K. Ganguly et al. , 1999).

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71, 021301. [arXiv:hep-ph/0410387].

techniques. *Physical Review D*, 47, 3707.

Research in the 21st century is increasingly driven by the analysis of large amounts of data within the e-Science paradigm. e-Science is the data centric analysis of science experiments unifying experiment, theory, and computing. According to Simon C. Lin and Eric Yen (Lin & Yen, 2009), e-Science or data-intensive science unifies theory, experiment, and simulations using exploration tools that link a network of scientists with their datasets. Results are analyzed using a shared computing infrastructure.

In this chapter, we use the concept of e-Science to combine experiment, theory and computing in particle physics in order to achieve a more efficient research process. Particle physics applications are generally regarded as a driver for developing this global e-Science infrastructure.

According to Tony Hey at Microsoft (Hey, 2006), thousands of years ago science focused on experiments to describe natural phenomena. In the last few hundreds of years, science became more theoretical. In the last few decades, science has become more computational, focusing on simulations. Today, science can be described as more data-intensive in nature, requiring a combination of experiment, theory, and computing. Attempts have been made to realize this e-Science concept. One e-Science application is the Worldwide Large Hadron Collider Computing Grid (WLCG), which realizes Ian Foster's definition of a grid (Foster et al., 2001). The grid is the combination of computing resources from multiple administrative domains to reach a common goal (Cho & Kim, 2009). As the global e-Science infrastructure is rapidly established, we must take advantage of worldwide e-Science progress. Highenergy physics has advanced the e-Science paradigm by successfully unifying experiments, theory, and computing (Cho et al., 2011).

We apply the e-Science concept to particle physics and show an example of this paradigm. As shown in Fig. 1, we construct a unified research model of experiment-theory-computing in order to probe the Standard Model and search for new physics.

This is not a simple collection of experiments, computing, and theory, but a fusion of research in order to achieve a more efficient research process. We apply this concept to the

<sup>1</sup> This chapter is based on the paper titled "Collider physics based on e-Science paradigm of experimentcomputing-theory" by K. Cho et al. in Computer Physics Communication Vol. 182, pp. 1756-1759 (2011).

The e-Science Paradigm for Particle Physics 77

supercomputers, in our work computing results are combined with theory and experiment. We use a combination of supercomputers and an e-Science environment. The components of an e-Science environment are data production for remote shifts, data processing for grid farms, and data analysis using the Enabling Virtual Organization (EVO) collaborative tool.

We define a computing-experiment tool as an e-Science research environment. In order to study particle physics, we can access the environment anytime and anywhere even if we are not on-site an accelerator laboratory. A virtual laboratory enables us to perform research as if we were on-site (Cho, 2008).We apply e-Science components to the CDF experiment.

The purpose of data production is to take both on-line shifts and off-line shifts anywhere. On-line shifts have been conducted through the use of a remote control room at KISTI and off-line shifts have been conducted via the sequential access through metadata (SAM) data handling (DH) system at KISTI. The remote control room is built to help non-US CDF members to fulfill their shift duties as a Consumer Operator (CO) part of the CDF data taking shift crew. The remote control room facilitates various monitoring applications that the CO has to monitor for a given eight hour shift. We have been operating the CDF remote control room at KISTI since July 22, 2008. A real Data Acquisition (DAQ) has been recorded at the remote control room at KISTI between August 1 and August 8, 2008. The CDF detector is an experimental apparatus for recording electrical events produced by the accelerator at an enormous rate. This apparatus is comprised of several components that perform different functions including a detector with millions of data channels transmitted to a corresponding number of electronic readout devices. The operation of an apparatus with this degree of complexity needs to be collaboratively controlled by researchers. In general, each shift crew takes an eight hour shift so that three shift crews will cover 24 hours. In the CDF experiment, the shift crew consists of three people with different missions. First, the Science Coordinator (SciCo) is responsible for the entire shift session and must have a lot of experience. The second person is the Ace shifter, who is an expert on the control of all detector components and electronic readout devices. The third person is the CO who has been trained in interpreting the meaning of the data being monitoring. UNIX processes intercept the on-line data transmitted from the front-end readout electronics and generate various plots that represent the quality of the data taken by the detector. These plots help the CO to determine whether or not the data collection is continuing as expected. Accordingly, the CO advises the Ace shifter to interrupt the detector operation in order to

Although the CO's monitoring task involves on-line data collection, this can be performed in a remote location due to its mostly monitoring-related nature. These remote control rooms are located at the Pisa University in Italy, the University of Tsukuba in Japan, and KISTI in Korea. In Korea, there are about 30 collaborators from six institutions, most of which have to fulfill CDF duties by taking detector operation shifts. All the plots that the consumers generate are accessible via web browsers where all the monitoring can be done. The CO has to not only monitor any plots generated by consumers but also must monitor

**2.1 For computing-experiment** 

**2.1.1.1 Data production** 

correct any problems.

**2.1.1 e-Science research environment** 

Collider Detector at Fermilab (CDF) experiment in the USA and the Belle/Belle II experiment at High Energy Accelerator Research Organization (KEK) in Japan.

For computing-experiment, we construct and use the components of the e-Science research environment, including data production, data processing, and data analysis using collaborative tools. We also develop new computational tools for future experiments. In high energy physics, the goal of e-Science is to perform and/or analyze high energy physics experiments anytime and anywhere. We apply this system to the Belle II experiment at KEK. For data processing, WLCG is one of the original new research infrastructures that show how an effective collaboration might be conducted between users and facilities (Cho, 2007). The Asia Pacific area should develop both an e-Science platform and best practices for collaboration in order to fill the gaps in e-Science development between other continents. The Academia Sinica Grid Centre (ASGC), as the coordinator of the Asia federation under Enabling Grid in e-Science (EGEE), has worked closely with partners for region specific applications in data processing. For data analysis using collaborative tools, community building should be the foundation for collaboration rather than just offering technology. The e-Science research environment provides a trusted way to allow people, resources, and knowledge to connect and participate via a virtual organization. More and more countries will deploy a grid system and take part in the e-Science research environment. According to Simon C. Lin (Simon & Yen, 2009), we are widening the uptake of e-Science through close collaboration regionally and internationally.

For experiment-theory, we develop a combination of phenomenology and data analysis. Experiments give results and tools for theories and theories give feedback to experiments. We apply this system to the CDF, D0, and Belle experiments in order to probe the standard model and search for new physics. For theory-computing, we study lattice gauge theory and use the supercomputer at the Korea Institute of Science and Technology Information (KISTI).

Fig. 1. The paradigm of e-Science in high energy physics, which is a fusion of experiment, computing, and theory research.
