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As we enter the post-Moore era, we experience the rise of various non-von-Neumann-architectures to address the increasing computational demand for modern applications, with quantum computing being among the most prominent and promising…

Major players in the global aerospace industry are shifting their focus toward achieving net carbon-neutral operations by 2050. A considerable portion of the overall carbon emission reduction is expected to come from new aircraft…

Variational hybrid quantum-classical optimization represents one of the most promising avenue to show the advantage of nowadays noisy intermediate-scale quantum computers in solving hard problems, such as finding the minimum-energy state of…

Quantum Physics · Physics 2020-11-18 Laura Gentini , Alessandro Cuccoli , Stefano Pirandola , Paola Verrucchi , Leonardo Banchi

Optimization of circuits is an essential task for both quantum and classical computers to improve their efficiency. In contrast, classical logic optimization is known to be difficult, and a lot of heuristic approaches have been developed so…

Quantum Physics · Physics 2025-05-14 Yusei Mori , Hideaki Hakoshima , Kyohei Sudo , Toshio Mori , Kosuke Mitarai , Keisuke Fujii

Quantum computers can exploit a Hilbert space whose dimension increases exponentially with the number of qubits. In experiment, quantum supremacy has recently been achieved by the Google team by using a noisy intermediate-scale quantum…

Quantum Physics · Physics 2021-02-02 Suguru Endo , Zhenyu Cai , Simon C. Benjamin , Xiao Yuan

Universal fault-tolerant quantum computers will require error-free execution of long sequences of quantum gate operations, which is expected to involve millions of physical qubits. Before the full power of such machines will be available,…

Quantum computing has the potential to revolutionize multiple fields by solving complex problems that can not be solved in reasonable time with current classical computers. Nevertheless, the development of quantum computers is still in its…

This work addresses the challenge of enabling practitioners without quantum expertise to transition from classical to hybrid quantum-classical machine learning workflows. We propose a three-stage framework: starting with a classical…

We develop an hybrid quantum-classical algorithm to solve an optimal population transfer problem for a molecule subject to a laser pulse. The evolution of the molecular wavefunction under the laser pulse is simulated on a quantum computer,…

Quantum Physics · Physics 2021-02-25 Davide Castaldo , Marta Rosa , Stefano Corni

Quantum computers show potential for achieving computational advantage over classical computers, with many candidate applications in combinatorial optimisation. We present an application level benchmarking framework for near-term quantum…

The development of quantum computers has been the stimulus that enables the realization of Quantum Machine Learning (QML), an area that integrates the calculational framework of quantum mechanics with the adaptive properties of classical…

Computational Engineering, Finance, and Science · Computer Science 2025-09-04 Bhavna Bose , Saurav Verma

The emergence of quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. The ability of quantum computers to scale computations implies better performance and…

Software Engineering · Computer Science 2024-03-29 Vlad Stirbu , Majid Haghparast

Quantum computing is a promising paradigm based on quantum theory for performing fast computations. Quantum algorithms are expected to surpass their classical counterparts in terms of computational complexity for certain tasks, including…

This work is a benchmark study for quantum-classical computing method with a real-world optimization problem from industry. The problem involves scheduling and balancing jobs on different machines, with a non-linear objective function. We…

Quantum Physics · Physics 2024-08-06 Abhishek Awasthi , Nico Kraus , Florian Krellner , David Zambrano

Mixed Integer Linear Programming (MILP) can be considered the backbone of the modern power system optimization process, with a large application spectrum, from Unit Commitment and Optimal Transmission Switching to verifying Neural Networks…

Quantum Physics · Physics 2024-04-17 Petros Ellinas , Samuel Chevalier , Spyros Chatzivasileiadis

Combinatorial optimization is a challenging problem applicable in a wide range of fields from logistics to finance. Recently, quantum computing has been used to attempt to solve these problems using a range of algorithms, including…

Quantum Physics · Physics 2024-03-06 Jonathan Wurtz , Stefan Sack , Sheng-Tao Wang

Quantum algorithms for simulating large and complex molecular systems are still in their infancy, and surpassing state-of-the-art classical techniques remains an ever-receding goal post. A promising avenue of inquiry in the meanwhile is to…

Quantum Physics · Physics 2025-08-07 Soohaeng Yoo Willow , D. ChangMo Yang , Chang Woo Myung

Quantum Variational Circuits (QVCs) are often claimed as one of the most potent uses of both near term and long term quantum hardware. The standard approaches to optimizing these circuits rely on a classical system to compute the new…

Quantum Physics · Physics 2022-02-11 Owen Lockwood

Classical program analysis techniques, such as abstract interpretation and symbolic execution, are essential for ensuring software correctness, optimizing performance, and enabling compiler optimizations. However, these techniques face…

Quantum Physics · Physics 2025-10-14 Yicheng Guang , Pietro Zanotta , Kai Zhou , Yueqi Chen , Ramin Ayanzadeh

Interconnecting clusters of qubits will be an essential element of scaling up future quantum computers. Operations between quantum processing units (QPUs) are usually significantly slower and costlier than those within a single QPU, so…

Quantum Physics · Physics 2022-09-09 Edwin Tham , Ilia Khait , Aharon Brodutch