aqora

Complex light for simulating quantum computing algorithms using reconfigurable optical vector-matrix multiplication

Isaac M. Nape

Complex Light and Optical ForcesMar 19, 20250 citations

Development of a technique for modeling entangled quantum computations that are applicable in Simon’s quantum algorithm

Viktor Potapov, S.M. Gushansky

This paper describes the basics of developing quantum algorithms and modeling entangled quantum computations applicable in quantum algorithms. Quantum algorithms involve the use of vector and matrix algebra. The basic tasks of the simulation proposed in the work are determined within the framework of the algorithm for executing quantum algorithms, taking into account entanglement. A technique has been developed for modeling entangled quantum calculations applicable in the Simon quantum algorithm, which helps to predict the behavior of the quantum algorithm (or any other computing process that proceeds as part of the work of a quantum computer system) with partial entanglement.This paper describes the basics of developing quantum algorithms and modeling entangled quantum computations applicable in quantum algorithms. Quantum algorithms involve the use of vector and matrix algebra. The basic tasks of the simulation proposed in the work are determined within the framework of the algorithm for executing quantum algorithms, taking into account entanglement. A technique has been developed for modeling entangled quantum calculations applicable in the Simon quantum algorithm, which helps to predict the behavior of the quantum algorithm (or any other computing process that proceeds as part of the work of a quantum computer system) with partial entanglement.

Informatization and communicationMay 5, 20200 citations

Towards realistic architectures for linear optical quantum computing

Sam Morley-Short

Jan 1, 20190 citations

Quantum State Vector Conjugate Matrix

Jincheng Zhang

Quantum state vector conjugate matrix represents a fundamental concept in quantum mechanics, offering a powerful tool for simplifying calculations and optimizing quantum algorithms. This paper explores the design and application of a novel computational model based on this matrix, aiming to enhance efficiency in the computation of quantum state vector eigenvalues. We detail the core mechanism of utilizing the matrix's properties for streamlined calculations, and present initial results demonstrating its potential for quantum algorithm improvement. The goal is to establish a robust and efficient framework for analyzing and manipulating quantum state vectors, providing a significant step towards practical quantum computing.Quantum state vector conjugate matrix represents a fundamental concept in quantum mechanics, offering a powerful tool for simplifying calculations and optimizing quantum algorithms. This paper explores the design and application of a novel computational model based on this matrix, aiming to enhance efficiency in the computation of quantum state vector eigenvalues. We detail the core mechanism of utilizing the matrix's properties for streamlined calculations, and present initial results demonstrating its potential for quantum algorithm improvement. The goal is to establish a robust and efficient framework for analyzing and manipulating quantum state vectors, providing a significant step towards practical quantum computing.

Sep 3, 20260 citations

Towards Optical Quantum Computing

Sverre Gullikstad Johnsen

Jan 1, 20020 citations

Core Claim: Design a dynamic matrix calculation validation method applied to quantum computers, leveraging the dynamic properties of matrices to enhance computational efficiency.

Jincheng Zhang

The development of quantum algorithms requires rigorous validation to ensure their correctness and stability. Static matrix representations often present challenges in efficiently verifying complex quantum circuits. This paper introduces a novel dynamic matrix calculation validation method specifically tailored for quantum computing, aiming to improve computational efficiency by dynamically adapting matrix properties during the verification process. We propose a mechanism that converts linear algebra calculations into quantum operations, optimizing the algorithm's execution flow. This approach offers a significant improvement over existing methods by dynamically adjusting matrix characteristics, reducing computational complexity and improving the overall accuracy of quantum algorithm validation. The paper details the design of the dynamic matrix validation framework, its implementation using a quantum simulator, and the resulting performance gains compared to traditional validation techniques. Furthermore, we discuss the potential benefits and limitations of this approach in the context of quantum computing.The development of quantum algorithms requires rigorous validation to ensure their correctness and stability. Static matrix representations often present challenges in efficiently verifying complex quantum circuits. This paper introduces a novel dynamic matrix calculation validation method specifically tailored for quantum computing, aiming to improve computational efficiency by dynamically adapting matrix properties during the verification process. We propose a mechanism that converts linear algebra calculations into quantum operations, optimizing the algorithm's execution flow. This approach offers a significant improvement over existing methods by dynamically adjusting matrix characteristics, reducing computational complexity and improving the overall accuracy of quantum algorithm validation. The paper details the design of the dynamic matrix validation framework, its implementation using a quantum simulator, and the resulting performance gains compared to traditional validation techniques. Furthermore, we discuss the potential benefits and limitations of this approach in the context of quantum computing.

Sep 7, 20260 citations

Laser beams offer simplified calculations for quantum computing

Abstract

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