Related papers: Network-Aware Scheduling for Remote Gate Execution…
The work explores the integration of quantum computing into logistics and supply chain management, emphasising its potential for use in complex optimisation problems. The discussion introduces quantum computing principles, focusing on…
Measurement-Based Quantum Networks (MBQNs) rely on multipartite pre-shared entanglement resources to satisfy entanglement requests. Traditional designs optimize these resources for individual tasks, neglecting that multiple tasks may arrive…
Optimal routing is a fundamental challenge in quantum networking, with several approaches proposed to identify the most efficient path for end-to-end (e2e) entanglement generation between pairs of nodes. In this paper, we show that…
Quantum cloud computing enables remote access to quantum processors, yet the heterogeneity and noise of available quantum hardware create significant challenges for efficient resource orchestration. These issues complicate the optimization…
With the advent of exascale computing, effective load balancing in massively parallel software applications is critically important for leveraging the full potential of high performance computing systems. Load balancing is the distribution…
Resource scheduling is critical in many industries, especially in power systems. The Unit Commitment problem determines the on/off status and output levels of generators under many constraints. Traditional exact methods, such as…
We generalize a recently developed scheme for monitoring coherent quantum dynamics with good time-resolution and low backaction [Reuther et al., Phys. Rev. Lett. 102, 033602 (2009)] to the case of more complex quantum dynamics of one or…
Recent years have witnessed a rapid growth of distributed machine learning (ML) frameworks, which exploit the massive parallelism of computing clusters to expedite ML training. However, the proliferation of distributed ML frameworks also…
Greater capabilities of mobile communications technology enable interconnection of on-site medical care at a scale previously unavailable. However, embedding such critical, demanding tasks into the already complex infrastructure of mobile…
Quantum computing promises potential for science and industry by solving certain computationally complex problems faster than classical computers. Quantum computing systems evolved from monolithic systems towards modular architectures…
Mutual distance bounding (DB) protocols enable two distrusting parties to establish an upper-bound on the distance between them. DB has been so far mainly considered in classical settings and for classical applications, especially in…
Most protocols for Quantum Information Processing consist of a series of quantum gates, which are applied sequentially. In contrast, interactions, for example between matter and fields, as well as measurements such as homodyne detection of…
Efficient and coherent data retrieval and storage are essential for harnessing quantum algorithms' speedup. Such a fundamental task is addressed by a quantum Random Access Memory (qRAM). Despite their promising scaling properties, current…
Quantum networks facilitate numerous applications such as secure communication and distributed quantum computation by performing entanglement distribution. Multi-user quantum applications where quantum information is shared between multiple…
Queuing network control is essential for managing congestion in job-processing systems such as service systems, communication networks, and manufacturing processes. Despite growing interest in applying reinforcement learning (RL)…
Entanglement, a fundamental feature of quantum mechanics, has long been recognized as a valuable resource in enabling secure communications and surpassing classical limits. However, previous research has primarily concentrated on static…
We present a dynamic learning paradigm for "programming" a general quantum computer. A learning algorithm is used to find the control parameters for a coupled qubit system, such that the system at an initial time evolves to a state in which…
Currently, quantum computing is developing at a high speed because its high parallelism and high computing power bring new solutions to many fields. However, due to chip process technology, it is difficult to achieve full coupling of all…
Instruction scheduling is a key compiler optimization in quantum computing, just as it is for classical computing. Current schedulers optimize for data parallelism by allowing simultaneous execution of instructions, as long as their qubits…
In this paper, we address the power-aware scheduling of sporadic constrained-deadline hard real-time tasks using dynamic voltage scaling upon multiprocessor platforms. We propose two distinct algorithms. Our first algorithm is an off-line…