Multi-Objective Routing Optimization for 6G Communication Networks Using a Quantum Approximate Optimization Algorithm

[EN] Sixth-generation wireless (6G) technology has been focused on in the wireless research community. Global coverage, massive spectrum usage, complex new applications, and strong security are among the new paradigms introduced by 6G. However, realizing such features may require computation capabilities transcending those of present (classical) computers. Large technology companies are already exploring quantum computers, which could be adopted as potential technological enablers for 6G. This is a promising avenue to explore because quantum computers exploit the properties of quantum states to perform certain computations significantly faster than classical computers. This paper focuses on routing optimization in wireless mesh networks using quantum computers, explicitly applying the quantum approximate optimization algorithm (QAOA). Single-objective and multi-objective examples are presented as robust candidates for the application of quantum machine learning. Moreover, a discussion about quantum supremacy estimation for this problem is provided.Urgelles-Pérez, H.; Picazo-Martínez, P.; Garcia-Roger, D.; Monserrat Del Río, JF. (2022). Multi-Objective Routing Optimization for 6G Communication Networks Using a Quantum Approximate Optimization Algorithm. Sensors. 22(19):1-14. https://doi.org/10.3390/s22197570114221

High-Performance Cloud Computing: A View of Scientific Applications

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape

Solving Partial Differential Equations with Monte Carlo / Random Walk on an Analog-Digital Hybrid Computer

Current digital computers are about to hit basic physical boundaries with respect to integration density, clock frequencies, and particularly energy consumption. This requires the application of new computing paradigms, such as quantum and analog computing in the near future. Although neither quantum nor analog computer are general purpose computers they will play an important role as co-processors to offload certain classes of compute intensive tasks from classic digital computers, thereby not only reducing run time but also and foremost power consumption. In this work, we describe a random walk approach to the solution of certain types of partial differential equations which is well suited for combinations of digital and analog computers (hybrid computers). The experiments were performed on an Analog Paradigm Model-1 analog computer attached to a digital computer by means of a hybrid interface. At the end we give some estimates of speedups and power consumption obtainable by using future analog computers on chip.Comment: 9 pages, 7 figures. Proceeding for the MikroSystemTechnik Kongress 2023 (VDE Verlag MST Kongress 2023

What is a quantum computer, and how do we build one?

The DiVincenzo criteria for implementing a quantum computer have been seminal in focussing both experimental and theoretical research in quantum information processing. These criteria were formulated specifically for the circuit model of quantum computing. However, several new models for quantum computing (paradigms) have been proposed that do not seem to fit the criteria well. The question is therefore what are the general criteria for implementing quantum computers. To this end, a formal operational definition of a quantum computer is introduced. It is then shown that according to this definition a device is a quantum computer if it obeys the following four criteria: Any quantum computer must (1) have a quantum memory; (2) facilitate a controlled quantum evolution of the quantum memory; (3) include a method for cooling the quantum memory; and (4) provide a readout mechanism for subsets of the quantum memory. The criteria are met when the device is scalable and operates fault-tolerantly. We discuss various existing quantum computing paradigms, and how they fit within this framework. Finally, we lay out a roadmap for selecting an avenue towards building a quantum computer. This is summarized in a decision tree intended to help experimentalists determine the most natural paradigm given a particular physical implementation

Using tablets for e-assessment of project-based learning

Technology is confirmed to be an effective tool for assessment and feedback, in particular for computer-assisted assessment (Irons, 2008; Challis, 2005), producing feedback (Heinrich et al., 2009) and publishing feedback (Bloxham and Boyd, 2007; Denton, 2003; Denton et al., 2008). The arrival of affordable mobile devices has introduced a new means for enhancing the above practices (Fabian and MacLean, 2014; Plimmer and Mason, 2006; Salem, 2013). Student preferences to smart phones and tablet devices steer the technological innovation towards ubiquitous mobile connectivity. Inspired by the benefits of such life and study style, educators have started exploring the use of these technologies. Tablet computers prove to become their preferred choice as they resolve some of the limitations associated with the design, readability and comprehensiveness of the feedback for mobile devices with smaller screens (Strain-Seymour, 2013, Rootman-le Grange and Lutz, 2013). This paper reports how tablets and the Form Connext mobile app have been used for engaging a sample of 300 Business Studies students in in-class online assessment and designing and providing timely comprehensive feedback. The study has followed an action research strategy that is grounded on a continuous and dynamic process of reflection (Carr and Kemmis, 2003) on the effectiveness of assessment of student projects documented electronically through wikis and electronic portfolios. It refines the use of tablets for summative and formative assessment of the project-based learning tasks through three review cycles, each of which incorporated a Reflection and Improvements stage. The experience resulted in enhancement of assessment strategies and contribution to the development of contemporary models of learning through effective assessment and feedback (Carr and Kemmis, 2003). The results of the work confirm that tablet computers are an effective tool in assessing e-materials in larger classes for two primary reasons. Firstly, design of e-forms facilitates rigorous process of reflection and understanding assessment criteria that in turn benefit students when preparing for the assessment. Hence, legible and detailed feedback is produced anytime anywhere with synchronous updates within the marking team. Secondly, students benefit from immediate comprehensive feedback allowing them to reflect on and improve their understanding of subject matters, as well as to engage in discussing specific details of the work that are captured through the form. An unexpected outcome was the enhanced reputation and respect to the tutors amongst students, the triggering of student curiosity and enthusiasm in applying similar approach to their own work. The diffusion for the practice amongst other units and identifying other purposes for which the mobile app could be used are also seen as achievements exceeding the expectations of the project team

Network Community Detection On Small Quantum Computers

In recent years a number of quantum computing devices with small numbers of qubits became available. We present a hybrid quantum local search (QLS) approach that combines a classical machine and a small quantum device to solve problems of practical size. The proposed approach is applied to the network community detection problem. QLS is hardware-agnostic and easily extendable to new quantum computing devices as they become available. We demonstrate it to solve the 2-community detection problem on graphs of size up to 410 vertices using the 16-qubit IBM quantum computer and D-Wave 2000Q, and compare their performance with the optimal solutions. Our results demonstrate that QLS perform similarly in terms of quality of the solution and the number of iterations to convergence on both types of quantum computers and it is capable of achieving results comparable to state-of-the-art solvers in terms of quality of the solution including reaching the optimal solutions