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

Significant Figures in Calculations00:58

Significant Figures in Calculations

10.4K
Uncertainty in measurements can be avoided by reporting the results of a calculation with the correct number of significant figures. This can be determined by the following rules for rounding numbers:
10.4K
Uncertainty in Measurement: Significant Figures03:34

Uncertainty in Measurement: Significant Figures

62.5K
All the digits in a measurement, including the uncertain last digit, are called significant figures or significant digits. Note that zero may be a measured value; for example, if a scale that shows weight to the nearest pound reads “140,” then the 1 (hundreds), 4 (tens), and 0 (ones) are all significant (measured) values.
62.5K
Numerical Calculations01:24

Numerical Calculations

342
In engineering applications, the representation of the numerical value is critical. Presenting or reporting the answer is one of the essential parts of engineering practices. Numerical calculations are performed using handheld calculators or computers since numerically accurate answers are always preferred.
The solution to a problem is obtained using different methods. While manually solving algebraic symbols is one of the most common methods, the graphical method is often preferred. Computers...
342
Rules for Significant Figures01:44

Rules for Significant Figures

12.6K
In any measurement, the precision of the measuring tool is an essential factor. An ordinary ruler, for example, can measure length to the closest millimeter; a caliper, on the other hand, can measure length to the nearest 0.01 mm. As a result, the caliper is a more precise measurement tool because it can measure extremely minute changes in length. The measurements will be more accurate if the measuring tool is more precise.
It should be emphasized that when we represent measured values, the...
12.6K
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

664
When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
664
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

1.3K
The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
1.3K

You might also read

Related Articles

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

Sort by
Same author

A scalable diagonalization framework for tensor-product bitstring selected configuration interaction.

The Journal of chemical physics·2026
Same author

Noncovalent Mg···N Interactions as Tunable Electronic Perturbations in Pyridine-Based Single-Molecule Junctions.

The journal of physical chemistry. A·2026
Same author

Electronic Transmission Signatures of Hydrogen-Bond Topology in Model Antiparallel β-Sheet Segments.

The journal of physical chemistry. A·2026
Same author

F-DATA: A Fugaku Workload Dataset for Job-centric Predictive Modelling in HPC Systems.

Scientific data·2025
Same author

Theoretical Study of 1s, 2s, and 2p Core Electron Binding Energies of Third-Period Elements Calculated by the ΔSCF Method, Koopmans' Theorem, and Slater's Transition State Theory within the Framework of Hartree-Fock and Kohn-Sham Theory.

The journal of physical chemistry. A·2025
Same author

Validation of Long-Range-Corrected LC2gau Functional for Koopmans' Prediction of Core and Valence Ionization Energies with Diverse Data.

The journal of physical chemistry. A·2025
Same journal

Improving PCM in Protic Media: Markov State Models for TD-DFT Calculations.

Journal of chemical theory and computation·2026
Same journal

Efficient Coupled-Cluster Python Frameworks for Next-Generation GPUs: A Comparative Study of CuPy and PyTorch on the Hopper and Grace Hopper Architecture.

Journal of chemical theory and computation·2026
Same journal

Extending the MARTINI 3 Coarse-Grained Force Field to Polypeptoids.

Journal of chemical theory and computation·2026
Same journal

Statistical Mechanics of Density- and Temperature-Dependent Potentials: Application to Condensed Phases within GenDPDE.

Journal of chemical theory and computation·2026
Same journal

BFEE-Docking: A User-Friendly and Customizable End-to-End Tool from High-Throughput Virtual Screening to Binding Free-Energy Calculations.

Journal of chemical theory and computation·2026
Same journal

On-the-Fly Trajectory Simulation of Two-Pulse, Three-Pulse, and Higher-Order Pump-Probe Signals.

Journal of chemical theory and computation·2026
See all related articles

Related Experiment Video

Updated: Jun 5, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.1K

Reducing Numerical Precision Requirements in Quantum Chemistry Calculations.

William Dawson1, Katsuhisa Ozaki2, Jens Domke1

  • 1RIKEN Center for Computational Science, Kobe 650-0047, Japan.

Journal of Chemical Theory and Computation
|December 7, 2024
PubMed
Summary
This summary is machine-generated.

Deep learning hardware advancements necessitate efficient simulation software. This study shows that lower precision in quantum chemistry calculations, specifically for the density matrix, can accelerate computations without losing scientific accuracy.

More Related Videos

Compact Quantum Dots for Single-molecule Imaging
17:14

Compact Quantum Dots for Single-molecule Imaging

Published on: October 9, 2012

18.1K
Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

2.2K

Related Experiment Videos

Last Updated: Jun 5, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.1K
Compact Quantum Dots for Single-molecule Imaging
17:14

Compact Quantum Dots for Single-molecule Imaging

Published on: October 9, 2012

18.1K
Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

2.2K

Area of Science:

  • Computational chemistry
  • High-performance computing
  • Quantum chemistry

Background:

  • The increasing demand for deep learning computational resources has spurred the development of low-precision hardware.
  • Simulation software must adapt to these new hardware architectures without compromising scientific accuracy.

Purpose of the Study:

  • To investigate the precision requirements of a key quantum chemistry kernel: calculating the single-particle density matrix.
  • To explore optimization opportunities for this kernel on low-precision hardware.

Main Methods:

  • Analysis of the precision needed for calculating the single-particle density matrix in Hartree-Fock and density functional theory using an LCAO basis.
  • Development of an approximation based on an error-free matrix multiplication transformation.

Main Results:

  • Double precision was found to be unnecessarily high for this specific quantum chemistry calculation.
  • The proposed approximation shows potential for accelerating the density matrix calculation kernel.
  • The findings suggest that adapting quantum chemistry software for future high-performance computing platforms is feasible.

Conclusions:

  • Lower precision levels are sufficient for accurate density matrix calculations in quantum chemistry.
  • An approximation leveraging error-free matrix multiplication can enhance computational efficiency.
  • This research provides a strategic approach for optimizing quantum chemistry software for next-generation computing hardware.