Related papers: Recent developments in the tmLQCD software suite
Experimental methods are being developed to enable quantum communication systems research in testbeds. We describe testbed architectures for emerging quantum technologies and how they can integrate with existing fibre optical testbeds,…
Modern TOF-PET scanner systems require high-speed computing resources for efficient data processing, monitoring and image reconstruction. In this article we present the data flow and software architecture for the novel TOF-PET scanner…
Modern TOF-PET scanner systems require high-speed computing resources for efficient data processing, monitoring and image reconstruction. In this article we present the data flow and software architecture for the novel TOF-PET scanner…
Recent advancements in quantum computing have shown promising computational advantages in many problem areas. As one of those areas with increasing attention, hybrid quantum-classical machine learning systems have demonstrated the…
Maintaining code quality in large-scale software systems presents significant challenges, particularly in settings where a large numbers of engineers work concurrently on a codebase. This paper introduces Code Quality Score (CQS) system to…
This report discusses 3 distinct, but overlapping topics. Firstly, it recommends the tools and best practices for research software engineering and data science that are most relevant to the researchers working on the Wales Multimorbidity…
In recent years there has been much progress on the investigation of the QCD phase diagram with lattice QCD. This talk will focus on the developments in the last few years. Especially the addition of external influences and extended ranges…
DEMIRCI software aims to aid RFQ design efforts by making the process easy, fast and accurate. In this report, DEMIRCI 8-term potential results are compared with the results provided by other commercially available simulation software.…
Recent advancements in quantum computing (QC) and machine learning (ML) have fueled significant research efforts aimed at integrating these two transformative technologies. Quantum machine learning (QML), an emerging interdisciplinary…
Models of random phylogenetic networks have been used since the inception of the field, but the introduction and rigorous study of mathematically tractable models is a much more recent topic that has gained momentum in the last 5 years.…
As distributed quantum architectures begin to emerge, understanding the interaction between quantum circuit optimisation and circuit partitioning becomes increasingly important. In this work, we study how circuit optimisation influences…
Recent results in soft QCD at LHC by the ATLAS, CMS and TOTEM Collaborations are presented. Special focus is reserved to studies in diffractive and forward physics, and to the underlying event, with comparison with previous results and…
The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously…
Traditional query processing relies on engines that are carefully optimized and engineered by many experts. However, new techniques and user requirements evolve rapidly, and existing systems often cannot keep pace. At the same time, these…
I highlight recent progress in cluster computer technology and assess status and prospects of cluster computers for lattice QCD with respect to the development of QCDOC and apeNEXT. Taking the LatFor test case, I specify a 512-processor…
Large quantum computers promise to solve some critical problems not solvable otherwise. However, modern quantum technologies suffer various imperfections such as control errors and qubit decoherence, inhibiting their potential utility. The…
Semiconductor spin qubits are a promising platform for large-scale quantum computing, but have yet to take full advantage of the broad class of quantum low-density parity check (QLDPC) codes, which promise high encoding rates and efficient…
We discuss recent progress in understanding the issues essential to the development of better cone jet algorithms.
xMLC is the second book of this `Machine Learning Tools in Fluid Mechanics' Series and focuses on Machine Learning Control (MLC). The objectives of this book are two-fold: First, provide an introduction to MLC for students, researchers, and…
For the last several months the main focus of development in the ROOT I/O package has been code consolidation and performance improvements. Access to remote files is affected both by bandwidth and latency. We introduced a pre-fetch…