Optimal allocation of quantum resources
- URL: http://arxiv.org/abs/2006.16134v4
- Date: Mon, 8 Mar 2021 15:47:29 GMT
- Title: Optimal allocation of quantum resources
- Authors: Roberto Salazar, Tanmoy Biswas, Jakub Czartowski, Karol \.Zyczkowski,
Pawe{\l} Horodecki
- Abstract summary: This paper investigates the optimal allocation of resources in multipartite quantum systems.
We show the relevance of proportional fairness and optimal reliability criteria for the application of quantum resources.
- Score: 0.09545101073027092
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The optimal allocation of resources is a crucial task for their efficient use
in a wide range of practical applications in science and engineering. This
paper investigates the optimal allocation of resources in multipartite quantum
systems. In particular, we show the relevance of proportional fairness and
optimal reliability criteria for the application of quantum resources.
Moreover, we present optimal allocation solutions for an arbitrary number of
qudits using measurement incompatibility as an exemplary resource theory.
Besides, we study the criterion of optimal equitability and demonstrate its
relevance to scenarios involving several resource theories such as nonlocality
vs local contextuality. Finally, we highlight the potential impact of our
results for quantum networks and other multi-party quantum information
processing, in particular to the future Quantum Internet.
Related papers
- Unified Framework for Calculating Convex Roof Resource Measures [4.096738674942227]
We introduce a unified computational framework for a class of widely utilized quantum resource measures, derived from convex roof extensions.
We substantiate the efficacy of our method by applying it to several key quantum resources, including entanglement, coherence, and magic states.
arXiv Detail & Related papers (2024-06-28T06:45:58Z) - Generative AI-enabled Quantum Computing Networks and Intelligent
Resource Allocation [80.78352800340032]
Quantum computing networks execute large-scale generative AI computation tasks and advanced quantum algorithms.
efficient resource allocation in quantum computing networks is a critical challenge due to qubit variability and network complexity.
We introduce state-of-the-art reinforcement learning (RL) algorithms, from generative learning to quantum machine learning for optimal quantum resource allocation.
arXiv Detail & Related papers (2024-01-13T17:16:38Z) - Resource Management in Quantum Virtual Private Networks [10.257460386235024]
We provide insights into the potential of genetic and learning-based algorithms for optimizing qVPNs.
Our findings demonstrate that compared to traditional greedy based links, genetic and learning-based algorithms can identify better paths.
arXiv Detail & Related papers (2023-05-05T01:19:41Z) - Assessing requirements to scale to practical quantum advantage [56.22441723982983]
We develop a framework for quantum resource estimation, abstracting the layers of the stack, to estimate resources required for large-scale quantum applications.
We assess three scaled quantum applications and find that hundreds of thousands to millions of physical qubits are needed to achieve practical quantum advantage.
A goal of our work is to accelerate progress towards practical quantum advantage by enabling the broader community to explore design choices across the stack.
arXiv Detail & Related papers (2022-11-14T18:50:27Z) - Quantum Network Utility Maximization [2.525518484388622]
We extend the notion of Network Utility Maximization (NUM) to quantum networks.
We propose three quantum utility functions -- each incorporating a different entanglement measure.
These ideas provide ideas regarding the suitability of quantum network utility definitions to different quantum applications.
arXiv Detail & Related papers (2022-10-14T22:02:02Z) - DQC$^2$O: Distributed Quantum Computing for Collaborative Optimization
in Future Networks [54.03701670739067]
We propose an adaptive distributed quantum computing approach to manage quantum computers and quantum channels for solving optimization tasks in future networks.
Based on the proposed approach, we discuss the potential applications for collaborative optimization in future networks, such as smart grid management, IoT cooperation, and UAV trajectory planning.
arXiv Detail & Related papers (2022-09-16T02:44:52Z) - Quantifying Qubit Magic Resource with Gottesman-Kitaev-Preskill Encoding [58.720142291102135]
We define a resource measure for magic, the sought-after property in most fault-tolerant quantum computers.
Our formulation is based on bosonic codes, well-studied tools in continuous-variable quantum computation.
arXiv Detail & Related papers (2021-09-27T12:56:01Z) - Experimental multi-state quantum discrimination through a Quantum
network [63.1241529629348]
We have experimentally implemented two discrimination schemes in a minimum-error scenario based on a receiver featured by a network structure and a dynamical processing of information.
The first protocol achieves binary optimal discrimination, while the second one provides a novel approach to multi-state quantum discrimination, relying on the dynamical features of the network-like receiver.
arXiv Detail & Related papers (2021-07-21T09:26:48Z) - Entanglement Rate Optimization in Heterogeneous Quantum Communication
Networks [79.8886946157912]
Quantum communication networks are emerging as a promising technology that could constitute a key building block in future communication networks in the 6G era and beyond.
Recent advances led to the deployment of small- and large-scale quantum communication networks with real quantum hardware.
In quantum networks, entanglement is a key resource that allows for data transmission between different nodes.
arXiv Detail & Related papers (2021-05-30T11:34:23Z) - One-Shot Manipulation of Dynamical Quantum Resources [0.0]
We develop a unified framework to characterize one-shot transformations of dynamical quantum resources in terms of resource quantifiers.
Our framework encompasses all dynamical resources represented as quantum channels.
We show that our conditions become necessary and sufficient for broad classes of important theories.
arXiv Detail & Related papers (2020-12-03T19:09:14Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.