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We study quantum computing algorithms for solving certain constrained resource allocation problems we coin as Mission Covering Optimization (MCO). We compare formulations of constrained optimization problems using Quantum Annealing…

Quantum Physics · Physics 2022-05-05 Massimiliano Cutugno , Annarita Giani , Paul M. Alsing , Laura Wessing , Austars Schnore

Algorithms to compute the quantum Fourier transform over a cyclic group are fundamental to many quantum algorithms. This paper describes such an algorithm and gives a proof of its correctness, tightening some claimed performance bounds…

Quantum Physics · Physics 2007-05-23 Chris Lomont

The outcome statistics of an informationally complete quantum measurement for a system in a given state can be used to evaluate the ensemble expectation of any linear operator in the same state, by averaging a function of the outcomes that…

Quantum Physics · Physics 2009-12-21 G. M. D'Ariano , D. F. Magnani , P. Perinotti

Quantum mechanics permits certain kinds of non-local effects. This paper demonstrates how these can be used for distributed computation with minimal communication between various processors. The problem considered is that of estimating the…

Quantum Physics · Physics 2008-02-03 Lov K. Grover

Many combinatorial optimization problems admit a maximin fairness variant, where the aim is to find a distribution over possible solutions which maximizes an expected worst-case outcome. However, the support for an optimal distribution may…

Quantum Physics · Physics 2026-04-17 Bao Bach , Cameron Ibrahim , Reuben Tate , Jad Salem , Stephan Eidenbenz , Ilya Safro

This paper investigates the distributed power allocation problem for coordinated multipoint (CoMP) transmissions in distributed antenna systems (DAS). Traditional duality based optimization techniques cannot be directly applied to this…

Information Theory · Computer Science 2013-04-26 Xiujun Zhang , Yin Sun , Xiang Chen , Shidong Zhou , Jing Wang , Ness B. Shroff

This paper introduces the {\it particle swarm filter} (not to be confused with particle swarm optimization): a recursive and embarrassingly parallel algorithm that targets an approximation to the sequence of posterior predictive…

Methodology · Statistics 2021-02-16 Taylor R. Brown

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature address the consensus averaging problem by…

Information Theory · Computer Science 2009-11-13 Effrosyni Kokiopoulou , Pascal Frossard

Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant…

Quantum Physics · Physics 2024-06-05 Zichang He , Bo Peng , Yuri Alexeev , Zheng Zhang

Recent experimental breakthroughs have signalled the imminent arrival of the early fault-tolerant era. However, for a considerable period in the foreseeable future, relying solely on quantum error correction for full error suppression will…

Quantum Physics · Physics 2025-02-18 Kecheng Liu , Zhenyu Cai

The variational quantum imaginary time evolution algorithm is efficient in finding the ground state of a quantum Hamiltonian. This algorithm involves solving a system of linear equations in a classical computer and the solution is then used…

Quantum Physics · Physics 2024-05-10 Gaurav Saxena , Ahmed Shalabi , Thi Ha Kyaw

In this paper, we propose a very concise deep learning approach for collaborative filtering that jointly models distributional representation for users and items. The proposed framework obtains better performance when compared against…

Information Retrieval · Computer Science 2015-02-17 Zhang Junlin , Cai Heng , Huang Tongwen , Xue Huiping

Nowadays, quantum computing has reached the engineering phase, with fully-functional quantum processors integrating hundred of noisy qubits available. Yet -- to fully unveil the potential of quantum computing out of the labs and into…

Fueled by massive data, important decision making is being automated with the help of algorithms, therefore, fairness in algorithms has become an especially important research topic. In this work, we design new streaming and distributed…

Data Structures and Algorithms · Computer Science 2020-02-25 Ashish Chiplunkar , Sagar Kale , Sivaramakrishnan Natarajan Ramamoorthy

This letter presents a novel \textit{quantum algorithm} for signal denoising, which performs a thresholding in the frequency domain through amplitude amplification and using an adaptive threshold determined by local mean values. The…

Quantum Physics · Physics 2023-12-27 Sayantan Dutta , Adrian Basarab , Denis Kouamé , Bertrand Georgeot

Adaptive networks are suitable for decentralized inference tasks, e.g., to monitor complex natural phenomena. Recent research works have intensively studied distributed optimization problems in the case where the nodes have to estimate a…

Multiagent Systems · Computer Science 2023-07-19 Jie Chen , Cédric Richard , Ali. H. Sayed

Recent result shows how to compute distributively and efficiently the linear MMSE for the multiuser detection problem, using the Gaussian BP algorithm. In the current work, we extend this construction, and show that operating this algorithm…

Information Theory · Computer Science 2009-04-16 Danny Bickson , Ori Shental , Danny Dolev

We study the efficiency of quantum algorithms which aim at obtaining phase space distribution functions of quantum systems. Wigner and Husimi functions are considered. Different quantum algorithms are envisioned to build these functions,…

Quantum Physics · Physics 2007-05-23 M. Terraneo , B. Georgeot , D. L. Shepelyansky

In wireless systems there is always a trade-off between reducing the transmit power and mitigating the resultant signal-degradation imposed by the transmit-power reduction with the aid of sophisticated receiver algorithms, when considering…

Quantum Physics · Physics 2012-06-27 Sandor Imre , Laszlo Gyongyosi

We study efficient distributed algorithms for the fundamental problem of principal component analysis and leading eigenvector computation on the sphere, when the data are randomly distributed among a set of computational nodes. We propose a…

Optimization and Control · Mathematics 2021-10-28 Foivos Alimisis , Peter Davies , Bart Vandereycken , Dan Alistarh
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