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Diffusion models have received wide attention in generation tasks. However, the expensive computation cost prevents the application of diffusion models in resource-constrained scenarios. Quantization emerges as a practical solution that…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Weilun Feng , Haotong Qin , Chuanguang Yang , Zhulin An , Libo Huang , Boyu Diao , Fei Wang , Renshuai Tao , Yongjun Xu , Michele Magno

Despite the recent progress in quantum computational algorithms for chemistry, there is a dearth of quantum computational simulations focused on material science applications, especially for the energy sector, where next generation sorbing…

Quantum computers are expected to give major speed-ups for the simulation of quantum systems. In these conference proceedings, we discuss quantum algorithms for the simulation of perturbative Quantum Chromodynamics (QCD) processes. In…

High Energy Physics - Phenomenology · Physics 2023-09-14 Herschel A. Chawdhry , Mathieu Pellen

The implementation and validation of the adaptive buffered force QM/MM method in two popular packages, CP2K and AMBER are presented. The implementations build on the existing QM/MM functionality in each code, extending it to allow for…

Kohn-Sham Density Functional Theory (KS-DFT) provides the exact ground state energy and electron density of a molecule, contingent on the as-yet-unknown universal exchange-correlation (XC) functional. Recent research has demonstrated that…

Computational fluid dynamics lies at the heart of many issues in science and engineering, but solving the associated partial differential equations remains computationally demanding. With the rise of quantum computing, new approaches have…

This article proposes a Variational Quantum Algorithm to solve linear and nonlinear thermofluid dynamic transport equations. The hybrid classical-quantum framework is applied to problems governed by the heat, wave, and Burgers' equation in…

Quantum Physics · Physics 2025-11-06 Sergio Bengoechea , Paul Over , Dieter Jaksch , Thomas Rung

The simulation of quantum dynamics on a digital quantum computer with parameterized circuits has widespread applications in fundamental and applied physics and chemistry. In this context, using the hybrid quantum-classical algorithm,…

Quantum Physics · Physics 2023-07-19 Tangyou Huang , Yongcheng Ding , Léonce Dupays , Yue Ban , Man-Hong Yung , Adolfo del Campo , Xi Chen

Achieving high-performance computation on quantum systems presents a formidable challenge that necessitates bridging the capabilities between quantum hardware and classical computing resources. This study introduces an innovative…

Quantum Physics · Physics 2024-03-19 Kuan-Cheng Chen , Xiaoren Li , Xiaotian Xu , Yun-Yuan Wang , Chen-Yu Liu

Determining the exponentially scaled ground state wavefunction and the associated molecular properties remains one of the central challenges in quantum chemistry. Hybrid quantum-classical algorithms implemented on quantum computers offer a…

Quantum Physics · Physics 2026-04-22 Dibyendu Mondal , Ashish Kumar Patra , Rahul Maitra

Many quantum algorithms, including recently proposed hybrid classical/quantum algorithms, make use of restricted tomography of the quantum state that measures the reduced density matrices, or marginals, of the full state. The most…

Quantum Physics · Physics 2018-05-16 Nicholas C. Rubin , Ryan Babbush , Jarrod McClean

Quantum computing has recently emerged as a transformative technology. Yet, its promised advantages rely on efficiently translating quantum operations into viable physical realizations. In this work, we use generative machine learning…

Quantum Physics · Physics 2024-05-22 Florian Fürrutter , Gorka Muñoz-Gil , Hans J. Briegel

Quantum computers can be used to address molecular structure, materials science and condensed matter physics problems, which currently stretch the limits of existing high-performance computing resources. Finding exact numerical solutions to…

Optimally-shaped electromagnetic fields have the capacity to coherently control the dynamics of quantum systems and thus offer a promising means for controlling molecular transformations relevant to chemical, biological, and materials…

Quantum Physics · Physics 2021-06-08 Alicia B. Magann , Matthew D. Grace , Herschel A. Rabitz , Mohan Sarovar

Quantum machine learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure…

Chemical Physics · Physics 2021-10-29 Manas Sajjan , Shree Hari Sureshbabu , Sabre Kais

The Hybrid Monte Carlo (HMC) algorithm currently is the favorite scheme to simulate quantum chromodynamics including dynamical fermions. In this talk-which is intended for a non-expert audience--I want to bring together methodical and…

High Energy Physics - Lattice · Physics 2009-10-30 Thomas Lippert

Quantum computing has the potential to reduce the computational cost required for quantum dynamics simulations. However, existing quantum algorithms for coupled electron-nuclear dynamics simulation either require fault-tolerant devices, or…

Quantum Physics · Physics 2026-03-03 Jong-Kwon Ha , Ryan J. MacDonell

We introduce a hybrid method for dielectric-metal composites that describes the dynamics of the metallic system classically whilst retaining a quantum description of the dielectric. The time-dependent dipole moment of the classical system…

Mesoscale and Nanoscale Physics · Physics 2016-10-05 Ryan J. McMillan , Lorenzo Stella , Myrta Grüning

This paper deals with a general method for the reduction of quantum systems with symmetry. For a Riemannian manifold M admitting a compact Lie group G as an isometry group, the quotient space Q = M/G is not a smooth manifold in general but…

Mathematical Physics · Physics 2009-10-31 Shogo Tanimura , Toshihiro Iwai

Molecular dynamics simulations are a central computational methodology in materials design for relating atomic composition to mechanical properties. However, simulating materials with atomic-level resolution on a macroscopic scale is…