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Hamiltonian simulation is one of the most important problems in quantum computation, and quantum singular value transformation (QSVT) is an efficient way to simulate a general class of Hamiltonians. However, the QSVT circuit typically…

Quantum Physics · Physics 2023-05-15 Yulong Dong , K. Birgitta Whaley , Lin Lin

Solving non-Hermitian quantum many-body systems on a quantum computer by minimizing the variational energy is challenging as the energy can be complex. Here, based on energy variance, we propose a variational method for solving the…

Quantum Physics · Physics 2024-02-21 Xu-Dan Xie , Zheng-Yuan Xue , Dan-Bo Zhang

Determining the vibrational structure of a molecule is central to fundamental applications in several areas, from atmospheric science to catalysis, fuel combustion modeling, biochemical imaging, and astrochemistry. However, when significant…

Quantum Physics · Physics 2021-12-22 Nicolas P. D. Sawaya , Francesco Paesani , Daniel P. Tabor

Simulating the Hubbard model is of great interest to a wide range of applications within condensed matter physics, however its solution on classical computers remains challenging in dimensions larger than one. The relative simplicity of…

Quantum Physics · Physics 2025-05-21 Antonios M. Alvertis , Abid Khan , Thomas Iadecola , Peter P. Orth , Norm Tubman

Determining the quantum circuit complexity of a unitary operation is closely related to the problem of finding minimal length paths in a particular curved geometry [Nielsen et al, Science 311, 1133-1135 (2006)]. This paper investigates many…

Quantum Physics · Physics 2007-05-23 Mark R. Dowling , Michael A. Nielsen

We present a quantum algorithm for finding the minimum of a function based on multistep quantum computation and apply it for optimization problems with continuous variables, in which the variables of the problem are discretized to form the…

Quantum Physics · Physics 2023-07-03 Hefeng Wang , Hua Xiang

A quantum realization of the Relativistic Harmonic Oscillator is realized in terms of the spatial variable $x$ and ${\d\over \d x}$ (the minimal canonical representation). The eigenstates of the Hamiltonian operator are found (at lower…

Mathematical Physics · Physics 2009-10-31 J. Guerrero , V. Aldaya

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of…

The variational quantum eigensolver (VQE), a type of variational quantum algorithm, is a hybrid quantum-classical algorithm to find the lowest-energy eigenstate of a particular Hamiltonian. We investigate ways to optimize the VQE solving…

Quantum Physics · Physics 2024-10-30 Adam Hutchings , Eric Yarnot , Xinpeng Li , Qiang Guan , Ning Xie , Shuai Xu , Vipin Chaudhary

Quantum coherence inherently affects the dynamics and the performances of a quantum machine. Coherent control can, at least in principle, enhance the work extraction and boost the velocity of evolution in an open quantum system. Using…

Quantum Physics · Physics 2018-12-10 Vasco Cavina , Andrea Mari , Alberto Carlini , Vittorio Giovannetti

Quantum computing has recently been emerging in theoretical chemistry as a realistic avenue meant to offer computational speedup to challenging eigenproblems in the context of strongly-correlated molecular systems or extended materials.…

Quantum Physics · Physics 2026-03-05 Joachim Knapik , Bruno Senjean , Benjamin Lasorne , Yohann Scribano

Advances in quantum simulator technology is increasingly required because research on quantum algorithms is becoming more sophisticated and complex. State vector simulation utilizes CPU and memory resources in computing nodes exponentially…

Quantum Physics · Physics 2024-09-04 Mikio Morita , Yoshinori Tomita , Junpei Koyama , Koichi Kimura

The variational quantum eigensolver (VQE) is one of the most appealing quantum algorithms to simulate electronic structure properties of molecules on near-term noisy intermediate-scale quantum devices. In this work, we generalize the VQE…

Quantum Physics · Physics 2022-06-09 Jie Liu , Lingyun Wan , Zhenyu Li , Jinlong Yang

The computational cost of quantum algorithms for physics and chemistry is closely linked to the spectrum of the Hamiltonian, a property that manifests in the necessary rescaling of its eigenvalues. The typical approach of using the 1-norm…

The unitary coupled cluster (UCC) algorithm is one of the most promising implementations of the variational quantum eigensolver for quantum computers. However, for large systems, the number of UCC factors leads to deep quantum circuits,…

Quantum Physics · Physics 2026-02-17 Jeremy Canfield , Dominika Zgid , J K Freericks

We report the first electronic structure calculation performed on a quantum computer without exponentially costly precompilation. We use a programmable array of superconducting qubits to compute the energy surface of molecular hydrogen…

The time evolution of quantum many-body systems is one of the most promising applications for near-term quantum computers. However, the utility of current quantum devices is strongly hampered by the proliferation of hardware errors. The…

Quantum Physics · Physics 2024-05-21 Maurits S. J. Tepaske , David J. Luitz , Dominik Hahn

Estimating the eigenstate properties of quantum systems is a long-standing, challenging problem for both classical and quantum computing. Existing universal quantum algorithms typically rely on ideal and efficient query models (e.g. time…

Quantum Physics · Physics 2026-01-21 Jinzhao Sun , Pei Zeng , Tom Gur , M. S. Kim

We initiate the systematic study of experimental quantum physics from the perspective of computational complexity. To this end, we define the framework of quantum algorithmic measurements (QUALMs), a hybrid of black box quantum algorithms…

Quantum Physics · Physics 2022-03-09 Dorit Aharonov , Jordan Cotler , Xiao-Liang Qi

Hybrid quantum/classical variational algorithms can be implemented on noisy intermediate-scale quantum computers and can be used to find solutions for combinatorial optimization problems. Approaches discussed in the literature minimize the…

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