Quantum Computing for Location Determination
- URL: http://arxiv.org/abs/2106.11751v2
- Date: Thu, 24 Jun 2021 01:39:32 GMT
- Title: Quantum Computing for Location Determination
- Authors: Ahmed Shokry and Moustafa Youssef
- Abstract summary: We introduce an example for the expected gain of using quantum algorithms for location determination research.
The proposed quantum algorithm has a complexity that is exponentially better than its classical algorithm version, both in space and running time.
We discuss both software and hardware research challenges and opportunities that researchers can build on to explore this exciting new domain.
- Score: 6.141741864834815
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum computing provides a new way for approaching problem solving,
enabling efficient solutions for problems that are hard on classical computers.
It is based on leveraging how quantum particles behave. With researchers around
the world showing quantum supremacy and the availability of cloud-based quantum
computers with free accounts for researchers, quantum computing is becoming a
reality. In this paper, we explore both the opportunities and challenges that
quantum computing has for location determination research. Specifically, we
introduce an example for the expected gain of using quantum algorithms by
providing an efficient quantum implementation of the well-known RF
fingerprinting algorithm and run it on an instance of the IBM Quantum
Experience computer. The proposed quantum algorithm has a complexity that is
exponentially better than its classical algorithm version, both in space and
running time. We further discuss both software and hardware research challenges
and opportunities that researchers can build on to explore this exciting new
domain.
Related papers
- Quantum Algorithm for a Stochastic Multicloud Model [0.0]
A quantum computing algorithm was applied to a problem of the atmospheric science.
The nature of a multi-cloud model was reproduced by utilizing outputs of computed quantum states.
Our results demonstrate that quantum computers can suitably solve some problems in atmospheric and oceanic phenomena.
arXiv Detail & Related papers (2024-06-17T09:14:20Z) - Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
Quantum computing sets the foundation for new ways of designing algorithms.
New challenges arise concerning which field quantum speedup can be achieved.
Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
arXiv Detail & Related papers (2024-02-26T09:32:07Z) - A Quantum Algorithm Based Heuristic to Hide Sensitive Itemsets [1.8419202109872088]
We present a quantum approach to solve a well-studied problem in the context of data sharing.
We present results on experiments involving small datasets to illustrate how the problem could be solved using quantum algorithms.
arXiv Detail & Related papers (2024-02-12T20:44:46Z) - Quantum algorithms: A survey of applications and end-to-end complexities [90.05272647148196]
The anticipated applications of quantum computers span across science and industry.
We present a survey of several potential application areas of quantum algorithms.
We outline the challenges and opportunities in each area in an "end-to-end" fashion.
arXiv Detail & Related papers (2023-10-04T17:53:55Z) - Quantum Machine Learning: from physics to software engineering [58.720142291102135]
We show how classical machine learning approach can help improve the facilities of quantum computers.
We discuss how quantum algorithms and quantum computers may be useful for solving classical machine learning tasks.
arXiv Detail & Related papers (2023-01-04T23:37:45Z) - Iterative Qubits Management for Quantum Index Searching in a Hybrid
System [56.39703478198019]
IQuCS aims at index searching and counting in a quantum-classical hybrid system.
We implement IQuCS with Qiskit and conduct intensive experiments.
Results demonstrate that it reduces qubits consumption by up to 66.2%.
arXiv Detail & Related papers (2022-09-22T21:54:28Z) - Optimal Stochastic Resource Allocation for Distributed Quantum Computing [50.809738453571015]
We propose a resource allocation scheme for distributed quantum computing (DQC) based on programming to minimize the total deployment cost for quantum resources.
The evaluation demonstrates the effectiveness and ability of the proposed scheme to balance the utilization of quantum computers and on-demand quantum computers.
arXiv Detail & Related papers (2022-09-16T02:37:32Z) - Quantum Computing for Power Flow Algorithms: Testing on real Quantum
Computers [0.0]
This paper goes beyond quantum computing simulations and performs an experimental application of Quantum Computing for power systems on a real quantum computer.
We use five different quantum computers, apply the HHL quantum algorithm, and examine the impact of current noisy quantum hardware on the accuracy and speed of an AC power flow algorithm.
arXiv Detail & Related papers (2022-04-29T11:53:16Z) - An Application of Quantum Annealing Computing to Seismic Inversion [55.41644538483948]
We apply a quantum algorithm to a D-Wave quantum annealer to solve a small scale seismic inversions problem.
The accuracy achieved by the quantum computer is at least as good as that of the classical computer.
arXiv Detail & Related papers (2020-05-06T14:18:44Z) - Quantum algorithms for quantum chemistry and quantum materials science [2.867517731896504]
We briefly describe central problems in chemistry and materials science, in areas of electronic structure, quantum statistical mechanics, and quantum dynamics, that are of potential interest for solution on a quantum computer.
We take a detailed snapshot of current progress in quantum algorithms for ground-state, dynamics, and thermal state simulation, and analyze their strengths and weaknesses for future developments.
arXiv Detail & Related papers (2020-01-10T22:49:56Z)
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.