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The design and benchmarking of quantum computer architectures traditionally rely on practical hardware restrictions, such as gate fidelities, control, and cooling. At the theoretical and software levels, numerous approaches have been…

The anticipated applications of quantum computers span across science and industry, ranging from quantum chemistry and many-body physics to optimization, finance, and machine learning. Proposed quantum solutions in these areas typically…

Over the last decade, Quantum Computing hardware has rapidly developed and become a very intriguing, promising, and active research field among scientists worldwide. To achieve the desired quantum functionalities, quantum algorithms require…

Quantum Physics · Physics 2022-09-05 Shamminuj Aktar , Abdel-Hameed A. Badawy , Nandakishore Santhi

Quantum computing is an emerging technology in which quantum mechanical properties are suitably utilized to perform certain compute-intensive operations faster than classical computers. Quantum algorithms are designed as a combination of…

Emerging Technologies · Computer Science 2023-06-06 Aravind Joshi , Akshara Kairali , Renju Raju , Adithya Athreya , Reena Monica P , Sanjay Vishwakarma , Srinjoy Ganguly

Image processing is one of the most promising applications for quantum machine learning (QML). Quanvolutional Neural Networks with non-trainable parameters are the preferred solution to run on current and near future quantum devices. The…

Quantum Physics · Physics 2024-10-10 Daniele Lizzio Bosco , Beatrice Portelli , Giuseppe Serra

A critical question for the field of quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond the capabilities of state-of-the-art classical computers,…

The quantum computer has become contemporary reality, with the first two-qubit machine of mere decades ago transforming into cloud-accessible devices with tens, hundreds, or -- in a few cases -- even thousands of qubits. While such hardware…

Understanding the theoretical capabilities and limitations of quantum machine learning (QML) models to solve machine learning tasks is crucial to advancing both quantum software and hardware developments. Similarly to the classical setting,…

Quantum Physics · Physics 2026-03-31 Qiuhao Chen , Yuling Jiao , Yinan Li , Xiliang Lu , Jerry Zhijian Yang

Any architecture for practical quantum computing must be scalable. An attractive approach is to create multiple cores, computing regions of fixed size that are well-spaced but interlinked with communication channels. This exploded…

Quantum Physics · Physics 2022-11-08 Hamza Jnane , Brennan Undseth , Zhenyu Cai , Simon C Benjamin , Bálint Koczor

The preparation of $n$-qubit quantum states is a cross-cutting subroutine for many quantum algorithms, and the effort to reduce its circuit complexity is a significant challenge. In the literature, the quantum state preparation algorithm by…

Quantum Physics · Physics 2026-02-09 Giacomo Belli , Michele Amoretti

A Quantum Computing Concept Inventory is needed for the acceleration of uptake of best practice in quantum computing education required to support the quantum computing workforce for the next two decades. Eight experts in quantum computing,…

Physics Education · Physics 2025-12-25 Lachlan McGinness

Equivalence checking of quantum circuits is an essential element in quantum program compilation, in which a quantum program can be synthesized into different quantum circuits that may vary in the number of qubits, initialization…

Quantum Physics · Physics 2024-04-19 Tian-Fu Chen , Jie-Hong R. Jiang , Min-Hsiu Hsieh

While the ability to build quantum computers is improving dramatically, developing quantum algorithms is limited and relies on human insight and ingenuity. Although a number of quantum programming languages have been developed, it is…

Software Engineering · Computer Science 2022-10-07 Kentaro Murakami , Jianjun Zhao

Application-specific quantum computers offer the most efficient means to tackle problems intractable by classical computers. Realizing these architectures necessitates a deep understanding of quantum circuit properties and their…

Quantum compiling means fast, device-aware implementation of quantum algorithms (i.e., quantum circuits, in the quantum circuit model of computation). In this paper, we present a strategy for compiling IBM Q -aware, low-depth quantum…

Quantum Physics · Physics 2020-03-13 Davide Ferrari , Michele Amoretti

Simulating molecular systems on quantum processors has the potential to surpass classical methods in computational resource efficiency. The limited qubit connectivity, small processor size, and short coherence times of near-term quantum…

Quantum Physics · Physics 2025-04-08 Abhishek Sadhu , Aritra Sarkar , Akash Kundu

Recent advancements in quantum computing (QC) and machine learning (ML) have garnered significant attention, leading to substantial efforts toward the development of quantum machine learning (QML) algorithms to address a variety of complex…

Quantum Physics · Physics 2024-12-18 Samuel Yen-Chi Chen

Quantum computing has become a promising computing approach because of its capability to solve certain problems, exponentially faster than classical computers. A $n$-qubit quantum system is capable of providing $2^{n}$ computational space…

Quantum Physics · Physics 2023-09-13 Saikat Basu , Amit Saha , Amlan Chakrabarti , Susmita Sur-Kolay

Recent developments in quantum hardware indicate that systems featuring more than 50 physical qubits are within reach. At this scale, classical simulation will no longer be feasible and there is a possibility that such quantum devices may…

Quantum Physics · Physics 2018-03-06 Mathias Soeken , Thomas Häner , Martin Roetteler

The potential of quantum computers to outperform classical ones in practically useful tasks remains challenging in the near term due to scaling limitations and high error rates of current quantum hardware. While quantum error correction…

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