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Quantum Computing Market by Technology, Infrastructure, Services, and Industry Verticals 2025 - 2030
»óǰÄÚµå : 1698614
¸®¼­Ä¡»ç : Mind Commerce
¹ßÇàÀÏ : 2025³â 04¿ù
ÆäÀÌÁö Á¤º¸ : ¿µ¹® 206 Pages
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Overview:

This quantum computing market report assesses the technology, organizations, R&D efforts, and potential solutions facilitated by quantum computing.

The report provides global and regional forecasts as well as the outlook for quantum computing impact on infrastructure including hardware, software, applications, and services from 2025 to 2030.

Analysis includes the quantum computing market across all major industry verticals. It also assesses technology, companies/organizations, R&D efforts, and potential solutions facilitated by quantum computing.

Select Report Findings:

Quantum computing is a theoretical computational system based on quantum theory, dealing with nanoscale physical phenomena. A key aspect is the quantum bit (qubit), a unit of quantum information that exists in multiple states simultaneously due to the superposition principle.

Unlike classical bits, which are either 0 or 1, qubits' simultaneous multi-state nature allows for significantly faster processing for certain problems. This has major implications for data processing, communications, digital commerce and security, and the internet.

The quantum computing market includes platforms, processors, and chipsets relying on quantum theory at the nanoscale. The qubit's superposition enables simultaneous existence in multiple states.

While not having a faster clock speed, quantum computing is much faster than classical computing for specific problems by handling exponentially larger datasets. The market is well-positioned for areas like cybersecurity and cryptocurrencies that depend on prime factoring, a time-consuming task for classical computers.

Despite the hype, quantum computing will initially complement classical High-Performance Computing (HPC) for most general tasks, with HPC potentially used for initial problem setup. Quantum computing excels at problems with many possible outcomes, such as molecular modeling in materials science, where classical computing struggles. Conversely, it faces challenges with problems involving many input/output iterations, necessitating HPC assistance.

Quantum computing platforms have physical constraints, often requiring a vacuum and cryogenic cooling for superconductivity to prevent decoherence. Current systems also need error checking.

Presently, quantum computers are typically purpose-built for specific problems and algorithms like Grover's for unstructured search and Shor's for prime factoring, supporting big data analytics and cybersecurity, respectively.

Unlike software-updatable classical computers, quantum computers often require hardware adaptation for different algorithms, meaning distinct quantum computers might be needed for tasks like big data analytics versus cybersecurity.

Different methods exist for building quantum computers based on how qubits are created (electrons, photons, superconducting magnets), leading to platform variations like Ion Trap, Nuclear Magnetic Resonance, Optical Method, Quantum Annealing, Quantum Dot Computing, Superconducting, and Topological methods.

Despite challenges, quantum computing has a promising future in various industries and applications, initially supporting research areas like cryptography, data science, materials science, and molecular physics. Breakthroughs in these fields are expected to drive value in sectors such as aviation, cybersecurity, financial services, and healthcare, with quantum chemistry potentially revolutionizing drug discovery.

The technology is rapidly advancing. For example, a Chinese research team has recently employed their indigenously developed 72-qubit Origin Wukong quantum computer to fine-tune a massive AI model containing a billion parameters. This process led to enhanced model performance despite a parameter reduction exceeding 75%, signifying significant progress in the convergence of quantum computing and sophisticated AI applications.

The researchers used Origin Wukong to fine-tune a billion-parameter model in one experiment. This resulted in a 15% decrease in training loss on a psychological counseling dialogue dataset, a significant indicator of improved learning. Furthermore, the model's accuracy on a mathematical reasoning task increased substantially from 68% to 82%.

Mind Commerce anticipates many additional advances in the field of quantum computing, ultimately leading to certain computing tasks becoming quantum-centric rather than relying upon classical computing. As a preparatory measure, we encourage all industry verticals to adopt a hybrid quantum/classical policy now, with an emphasis on certain key areas such as encryption. Current public-key cryptography (PKC) algorithms like RSA and ECC, which underpin much of modern digital security (including TLS/SSL, SSH, and digital signatures), will become vulnerable to quantum computers running Shor's algorithm.

Table of Contents

1.0. Executive Summary

2.0. Introduction

3.0. Quantum Computing Technology and Market Analysis

4.0. Quantum Computing Market Overview

5.0. Quantum Computing Drivers and Challenges

6.0. Quantum Computing Use Cases

7.0. Quantum Computing Value Chain Analysis

8.0. Quantum Computing Company Analysis

9.0. Quantum Computing Market Analysis and Forecasts 2025-2030

10.0. Conclusions and Recommendations

11.0. Appendix: Quantum Computing and Classical HPC

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