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Complex quantum networks are not only hard to establish, but also difficult to simulate due to the exponentially growing state space and noise-induced imperfections. In this work, we propose an alternative approach that leverage quantum…

Quantum Physics · Physics 2025-09-30 Ferran Riera-Sàbat , Jorge Miguel-Ramiro , Wolfgang Dür

Error-correcting codes were invented to correct errors on noisy communication channels. Quantum error correction (QEC), however, may have a wider range of uses, including information transmission, quantum simulation/computation, and…

Quantum Physics · Physics 2022-08-05 Ningping Cao , Junan Lin , David Kribs , Yiu-Tung Poon , Bei Zeng , Raymond Laflamme

Noise in quantum devices is generally considered detrimental to computational accuracy. However, the recent proposal of noise-assisted simulation has demonstrated that noise can be an asset in digital quantum simulations of open systems on…

The Variational Quantum Eigensolver (VQE) is a promising algorithm for future Noisy Intermediate-Scale Quantum (NISQ) devices to simulate chemical systems. In this paper, we consider the classical simulation of the iterative Qubit Coupled…

Quantum Physics · Physics 2025-02-27 Damian S. Steiger , Thomas Häner , Scott N. Genin , Helmut G. Katzgraber

Quantum computers hold immense potential in the field of chemistry, ushering new frontiers to solve complex many body problems that are beyond the reach of classical computers. However, noise in the current quantum hardware limits their…

Quantum Physics · Physics 2024-03-20 Chayan Patra , Sonaldeep Halder , Rahul Maitra

Quantum computing technology has the potential to revolutionize the simulation of materials and molecules in the near future. A primary challenge in achieving near-term quantum advantage is effectively mitigating the noise effects inherent…

Quantum Physics · Physics 2024-01-17 Tao Jiang , John Rogers , Marius S. Frank , Ove Christiansen , Yong-Xin Yao , Nicola Lanatà

Variational quantum algorithms are suitable for use on noisy quantum systems. One of the most important use-cases is the quantum simulation of materials, using the variational quantum eigensolver (VQE). To optimize VQE performance, a…

Quantum Physics · Physics 2022-01-12 Waheeda Saib , Petros Wallden , Ismail Akhalwaya

One of the most promising applications of noisy intermediate-scale quantum computers is the simulation of molecular Hamiltonians using the variational quantum eigensolver. We show that encoding symmetries of the simulated Hamiltonian in the…

A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the next decade or so, our access is restricted to noisy intermediate-scale…

Quantum Physics · Physics 2023-02-22 Archismita Dalal , Amara Katabarwa

Variational quantum algorithm (VQA), which is comprised of a classical optimizer and a parameterized quantum circuit, emerges as one of the most promising approaches for harvesting the power of quantum computers in the noisy intermediate…

Quantum Physics · Physics 2021-12-01 Samuel Stein , Yufei Ding , Nathan Wiebe , Bo Peng , Karol Kowalski , Nathan Baker , James Ang , Ang Li

Quantum computing presents a promising path toward precise quantum chemical simulations, particularly for systems that challenge classical methods. This work investigates the performance of the Variational Quantum Eigensolver (VQE) in…

Quantum Physics · Physics 2025-10-28 Zakaria Boutakka , Nouhaila Innan , Muhammed Shafique , Mohamed Bennai , Z. Sakhi

Variational quantum eigensolvers (VQEs) are one of the most important and effective applications of quantum computing, especially in the current noisy intermediate-scale quantum (NISQ) era. There are mainly two ways for VQEs:…

Quantum Physics · Physics 2024-11-19 Xin Wang , Bo Qi , Yabo Wang , Daoyi Dong

Variational quantum eigensolver (VQE), aiming at determining the ground state energy of a quantum system described by a Hamiltonian on noisy intermediate scale quantum (NISQ) devices, is among the most significant applications of…

Quantum Physics · Physics 2024-04-12 Ze-Tong Li , Fan-Xu Meng , Han Zeng , Zai-Chen Zhang , Xu-Tao Yu

Quantum computing has emerged as a promising technology for solving problems that are intractable for classical computers. In this study, we introduce quantum computing and implement the Variational Quantum Eigensolver (VQE) algorithm using…

Quantum Physics · Physics 2023-05-12 Maomin Qing , Wei Xie

The realization of quantum error correction is an essential ingredient for reaching the full potential of fault-tolerant universal quantum computation. Using a range of different schemes, logical qubits can be redundantly encoded in a set…

Finding ground states and low-lying excitations of a given Hamiltonian is one of the most important problems in many fields of physics. As a novel approach, quantum computing on Noisy Intermediate-Scale Quantum (NISQ) devices offers the…

Quantum computing has recently exhibited great potentials in predicting chemical properties for various applications in drug discovery, material design, and catalyst optimization. Progress has been made in simulating small molecules, such…

Quantum error detection (QED) offers a promising pathway to fault tolerance in near-term quantum devices by balancing error suppression with minimal resource overhead. However, its practical utility hinges on optimizing design…

Quantum Physics · Physics 2025-04-14 Tom Ginsberg , Vyom Patel

We present a collection of optimizers tuned for usage on Noisy Intermediate-Scale Quantum (NISQ) devices. Optimizers have a range of applications in quantum computing, including the Variational Quantum Eigensolver (VQE) and Quantum…

Quantum Physics · Physics 2021-04-16 Wim Lavrijsen , Ana Tudor , Juliane Müller , Costin Iancu , Wibe de Jong

The variational quantum eigensolver (or VQE) uses the variational principle to compute the ground state energy of a Hamiltonian, a problem that is central to quantum chemistry and condensed matter physics. Conventional computing methods are…