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Grover's algorithm, orginally conceived as a means of searching an unordered database, can also be used to extract solutions from the result sets generated by quantum computations. The Grover algorithm exploits the concept of an oracle…

Quantum Physics · Physics 2024-11-19 Fintan M. Bolton

There has been increasing interest in developing efficient quantum algorithms for hard classical problems. The Network Signal Coordination (NSC) problem is one such problem known to be NP complete. We implement Grover's search algorithm to…

Quantum Physics · Physics 2026-03-06 Vinayak Dixit , Richard Pech

Quantum contextuality is a limitation on deterministic hidden variable models, testable in measurement scenarios where outcomes differ under quantum or classical descriptions due to a common set of constraints. When considering measurements…

Quantum Physics · Physics 2025-09-25 Colm Kelleher , Frédéric Holweck

Quantum algorithms require accurate representations of electronic states on a quantum device, yet the approximation of electronic wave functions for strongly correlated systems remains a profound theoretical challenge, with existing methods…

Quantum Physics · Physics 2025-04-29 Dipanjali Halder , Dibyendu Mondal , Rahul Maitra

We provide a tight analysis of Grover's recent algorithm for quantum database searching. We give a simple closed-form formula for the probability of success after any given number of iterations of the algorithm. This allows us to determine…

Quantum Physics · Physics 2015-06-26 Michel Boyer , Gilles Brassard , Peter Hoeyer , Alain Tapp

A general quantum search algorithm aims to evolve a quantum system from a known source state $|s\rangle$ to an unknown target state $|t\rangle$. It uses a diffusion operator $D_{s}$ having source state as one of its eigenstates and $I_{t}$,…

Quantum Physics · Physics 2015-09-02 Avatar Tulsi

Near-term quantum computers are noisy, and therefore must run algorithms with a low circuit depth and qubit count. Here we investigate how noise affects a quantum neural network (QNN) for state discrimination, applicable on near-term…

Quantum Physics · Physics 2021-01-27 Andrew Patterson , Hongxiang Chen , Leonard Wossnig , Simone Severini , Dan Browne , Ivan Rungger

The imminent era of error-corrected quantum computing urgently demands robust methods to characterize complex quantum states, even from limited and noisy measurements. We introduce the Quantum Attention Network (QuAN), a versatile classical…

This paper demonstrates that how well a state performs as an input to Grover's search algorithm depends critically upon the entanglement present in that state; the more entanglement, the less well the algorithm performs. More precisely,…

Quantum Physics · Physics 2009-11-07 Ofer Biham , Michael A. Nielsen , Tobias J. Osborne

Boolean networks model finite discrete dynamical systems with complex behaviours. The state of each component is determined by a Boolean function of the state of (a subset of) the components of the network. This paper addresses the…

Artificial Intelligence · Computer Science 2020-02-28 Stéphanie Chevalier , Christine Froidevaux , Loïc Paulevé , Andrei Zinovyev

We develop a computation model for solving Boolean networks that implements wires through quantum ground-state computation and implements gates through identities following from angular momentum algebra and statistics. The gates are static…

Quantum Physics · Physics 2007-05-23 Giuseppe Castagnoli , David Ritz Finkelstein

A quantum system will stay near its instantaneous ground state if the Hamiltonian that governs its evolution varies slowly enough. This quantum adiabatic behavior is the basis of a new class of algorithms for quantum computing. We test one…

Quantum Physics · Physics 2009-11-07 Edward Farhi , Jeffrey Goldstone , Sam Gutmann , Joshua Lapan , Andrew Lundgren , Daniel Preda

Quantum search is a quantum mechanical technique for searching N possibilities in only sqrt(N) steps. This paper gives a fresh perspective on the algorithm in terms of a resonance phenomenon which is implemented through classical coupled…

Quantum Physics · Physics 2007-05-23 Lov K. Grover , Anirvan Sengupta

In this article we consider an experimental study showing the influence of emotion regulation strategies on human memory performance: part of such experimental results are difficult to explain within a classic cognitive allocation model. We…

Quantum Physics · Physics 2008-04-22 Riccardo Franco

Grover's algorithm is one of the most famous algorithms which explicitly demonstrates how the quantum nature can be utilized to accelerate the searching process. In this work, Grover's quantum search problem is mapped to a time-optimal…

Quantum Physics · Physics 2019-08-28 Chungwei Lin , Yebin Wang , Grigory Kolesov , Uroš Kalabić

In recent years, machine learning and deep learning have driven advances in domains such as image classification, speech recognition, and anomaly detection by leveraging multi-layer neural networks to model complex data. Simultaneously,…

Quantum Physics · Physics 2025-11-25 Hibah Agha , Samuel Yen-Chi Chen , Huan-Hsin Tseng , Shinjae Yoo

We investigate the issue of speed-up and the necessity of entanglement in Grover's quantum search algorithm. We find that in a pure state implementation of Grover's algorithm entanglement is present even though the initial and target states…

Quantum Physics · Physics 2007-05-23 Samuel L. Braunstein , Arun K. Pati

$ $In its usual form, Grover's quantum search algorithm uses $O(\sqrt{N})$ queries and $O(\sqrt{N} \log N)$ other elementary gates to find a solution in an $N$-bit database. Grover in 2002 showed how to reduce the number of other gates to…

Quantum Physics · Physics 2016-10-24 Srinivasan Arunachalam , Ronald de Wolf

Two-way quantum computing (2WQC) represents a novel approach to quantum computing that introduces a CPT version of state preparation. This paper analyses the influence of this approach on Grover's algorithm and compares the behaviour of…

General Physics · Physics 2024-10-22 Grzegorz Czelusta , Dev Rishi Verma , Govind Wanjalkar

We examine the large-network, low-loading behaviour of an attractor neural network, the so-called bistable gradient network (BGN). We use analytical and numerical methods to characterize the attractor states of the network and their basins…

Disordered Systems and Neural Networks · Physics 2007-05-23 Patrick N. McGraw , Michael Menzinger
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