Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

38
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
38

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mixed-Precision <i>Ab Initio</i> Tensor Network State Methods Adapted for NVIDIA Blackwell Technology via Emulated FP64 Arithmetic.

Journal of chemical theory and computation·2026
Same author

Assessing the Reliability of Truncated Coupled Cluster Wave Function: Estimating the Distance from the Exact Solution.

Journal of chemical theory and computation·2025
Same author

Orbital Optimization of Large Active Spaces via AI-Accelerators.

Journal of chemical theory and computation·2025
Same author

Tensor Network State Algorithms on AI Accelerators.

Journal of chemical theory and computation·2024
Same author

DMRG-Tailored Coupled Cluster Method in the 4c-Relativistic Domain: General Implementation and Application to the NUHFI and NUF<sub>3</sub> Molecules.

Journal of chemical theory and computation·2024
Same author

Parallel Implementation of the Density Matrix Renormalization Group Method Achieving a Quarter petaFLOPS Performance on a Single DGX-H100 GPU Node.

Journal of chemical theory and computation·2024

Related Experiment Video

Updated: May 29, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

477

Massively Parallel Tensor Network State Algorithms on Hybrid CPU-GPU Based Architectures.

Andor Menczer1,2, Örs Legeza1,3

  • 1Strongly Correlated Systems "Lendület" Research Group, Wigner Research Centre for Physics, H-1525 Budapest, Hungary.

Journal of Chemical Theory and Computation
|February 4, 2025
PubMed
Summary
This summary is machine-generated.

This study enhances tensor network state (TNS) algorithms for high-performance computing (HPC), enabling larger quantum simulations. Novel methods push computational boundaries for strongly correlated molecules.

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

359
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K

Related Experiment Videos

Last Updated: May 29, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

477
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

359
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K

Area of Science:

  • Computational Physics
  • Quantum Chemistry
  • High-Performance Computing

Background:

  • Tensor Network States (TNS) are crucial for simulating quantum systems.
  • Bridging quantum and classical simulations requires advanced algorithms.
  • High-performance computing (HPC) is essential for tackling large quantum problems.

Purpose of the Study:

  • To develop novel algorithmic solutions for TNS algorithms.
  • To extend the capabilities of TNS algorithms on HPC infrastructure.
  • To leverage state-of-the-art hardware and software for quantum simulations.

Main Methods:

  • Massively parallelized TNS algorithms.
  • Implementation of novel algorithmic solutions.
  • Large-scale Density Matrix Renormalization Group (DMRG) simulations.
  • Utilizing multi-GPU NVIDIA A100 systems.

Main Results:

  • Demonstrated extension of TNS algorithm limits on HPC.
  • Achieved benchmark results for strongly correlated molecular systems.
  • Successfully addressed Hilbert space dimensions up to 4.17 × 10^35.
  • Validated performance on advanced hardware.

Conclusions:

  • Novel algorithms significantly advance TNS capabilities on HPC.
  • The developed methods enable simulations of unprecedented scale.
  • This work provides a pathway for future quantum simulations of complex molecular systems.