Related papers: Network Capabilities for the HL-LHC Era
Learning in high-dimensional action spaces is a key challenge in applying reinforcement learning (RL) to real-world systems. In this paper, we study the possibility of controlling power networks using RL methods. Power networks are critical…
Accurate reliability modeling for ultra-reliable low latency communication (URLLC) and hyper-reliable low latency communication (HRLLC) networks is challenging due to the complex interactions between network layers required to meet…
The synthesis of high-performance computing (particularly graphics processing units), cloud computing services (like Google Colab), and high-level deep learning frameworks (such as PyTorch) has powered the burgeoning field of artificial…
Scientific research increasingly depends on robust and scalable IT infrastructures to support complex computational workflows. With the proliferation of services provided by research infrastructures, NRENs, and commercial cloud providers,…
The demand for computer in our daily lives has led to the proliferation of Datacenters that power indispensable many services. On the other hand, computing has become essential for some research for various scientific fields, that require…
Machine learning has played an important role in the analysis of high-energy physics data for decades. The emergence of deep learning in 2012 allowed for machine learning tools which could adeptly handle higher-dimensional and more complex…
Today's 5G and NextG wireless networks are moving toward using the coordinated multi-point (CoMP) transmission and reception technique, where a client can be simultaneously served by multiple base stations (BSs) for better communication…
With the dynamic demands and stringent requirements of various applications, networks need to be high-performance, scalable, and adaptive to changes. Researchers and industries view network softwarization as the best enabler for the…
HL-LHC federates the efforts and R&D of a large international community towards the ambitious HL- LHC objectives and contributes to establishing the European Research Area (ERA) as a focal point of global research cooperation and a leader…
Federated learning has shown enormous promise as a way of training ML models in distributed environments while reducing communication costs and protecting data privacy. However, the rise of complex cyber-physical systems, such as the…
Modern HENP experiments such as CMS and Atlas involve as many as 2000 collaborators around the world. Collaborations this large will be unable to meet often enough to support working closely together. Many of the tools currently available…
High energy particle colliders have been in the forefront of particle physics for more than three decades. At present the near term US, European and international strategies of the particle physics community are centered on full…
The ongoing research and industrial exploitation of SDN and NFV technologies promise higher flexibility on network automation and infrastructure optimization. Choosing the location of Virtual Network Functions is a central problem in the…
Robustness in complex systems is of significant engineering and economic importance. However, conventional attack-based a posteriori robustness assessments incur prohibitive computational overhead. Recently, deep learning methods, such as…
Accelerator technology has advanced tremendously since the introduction of accelerators in the 1930s, and particle accelerators have become indispensable instruments in high energy physics (HEP) research to probe Nature at smaller and…
Every year the PHENIX collaboration deals with increasing volume of data (now about 1/4 PB/year). Apparently the more data the more questions how to process all the data in most efficient way. In recent past many developments in HEP…
The good performance of the LHC provided enough data at 7 TeV and 8 TeV to allow the experiments to perform very competitive measurements and to expand the knowledge about the fundamental interaction far beyond that from previous colliders.…
The paper is aimed at analyzing the potential of new information networks to solve the problems of energy management network with the use of renewable energy sources. One of the basic problems of renewable energy sources is their temporal…
This paper has been prepared by the HEP Software Foundation (HSF) Physics Event Generator Working Group (WG), as an input to the second phase of the LHCC review of High-Luminosity LHC (HL-LHC) computing, which is due to take place in…
Realistic environments for prototyping, studying and improving analysis workflows are a crucial element on the way towards user-friendly physics analysis at HL-LHC scale. The IRIS-HEP Analysis Grand Challenge (AGC) provides such an…