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Related Concept Videos

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)

Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
The central atom need not be NMR-active because its electrons are affected by the electron polarization of the spin-active atoms. However, spin information is transmitted less effectively than in one-bond coupling, and 2J values are usually weaker than 1J values. The energy of...
Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)

Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
The extent of coupling depends on the C‑C bond length, the two H‑C‑C angles, any electron-withdrawing substituents, and the dihedral angle between the involved orbitals. The...
Spin–Spin Coupling: One-Bond Coupling01:17

Spin–Spin Coupling: One-Bond Coupling

Coupling interactions are strongest between NMR-active nuclei bonded to each other, where spin information can be transmitted directly through the pair of bonding electrons. While nuclei polarize their electrons to the opposite spins, the bonding electron pair has opposite spins. Configurations with antiparallel nuclear spins are expected to be lower in energy. When coupling makes antiparallel states more favorable, J is considered to have a positive value. The one-bond coupling constant, 1J,...
Condensins02:15

Condensins

Condensins are large protein complexes that use ATP to fuel the assembly of chromosomes during mitosis. They transform the tangled, shapeless mass of post-interphase DNA into individualized chromosomes by compacting, organizing, and segregating chromosomal DNA.
The plant and animal cells contain two types of condensin complexes—condensin I and condensin II. Both complexes have five subunits: two SMC (Structural Maintenance of Chromosomes) subunits, a kleisin subunit, and two HEAT-repeat...
Condensins02:15

Condensins

Condensins are large protein complexes that use ATP to fuel the assembly of chromosomes during mitosis. They transform the tangled, shapeless mass of post-interphase DNA into individualized chromosomes by compacting, organizing, and segregating chromosomal DNA.
The plant and animal cells contain two types of condensin complexes—condensin I and condensin II. Both complexes have five subunits: two SMC (Structural Maintenance of Chromosomes) subunits, a kleisin subunit, and two HEAT-repeat...
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...

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Related Experiment Video

Updated: May 22, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

Fragment, Entangle, and Consolidate: Strong Correlation through Bifold Quantum Circuits.

Arpan Choudhury1, Sonaldeep Halder2, Rahul Maitra2

  • 1School of Chemical Sciences, Indian Association for the Cultivation of Science, Kolkata 700032, India.

Journal of Chemical Theory and Computation
|May 21, 2026
PubMed
Summary
This summary is machine-generated.

We developed a new quantum algorithm to accurately simulate strong electronic correlation in molecules. This approach enhances the capabilities of variational quantum algorithms for quantum chemistry, enabling better exploration of novel chemical space.

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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
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Related Experiment Videos

Last Updated: May 22, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Quantum Computing

Background:

  • Accurate simulation of strong electronic correlation is crucial for understanding chemical phenomena.
  • Near-term variational quantum algorithms (VQAs) offer scalability but struggle with multireference effects.
  • Challenges in simulating strong correlation limit the rational design of new molecules.

Purpose of the Study:

  • To introduce a general and customizable scheme for handling strong electronic correlation.
  • To improve the accuracy and scalability of quantum algorithms for quantum chemistry.
  • To enable the exploration of novel chemical space through advanced simulations.

Main Methods:

  • A hybrid quantum scheme based on problem decomposition, entanglement buildup, and consolidation.
  • Utilizing hardware-efficient ansatze for entangled subsystem preparation.
  • Incorporating dynamic correlation via a unitary coupled cluster framework with specific ansatze.
  • Employing a hybrid architecture with separate ansatze for different correlation degrees.

Main Results:

  • The proposed scheme demonstrates encouraging accuracy and flexibility for strongly correlated systems.
  • Efficient construction of multireference states while respecting hardware topology.
  • Balanced capture of various correlation degrees using a hybrid architecture.
  • The method shows potential for resource-efficient quantum simulations.

Conclusions:

  • The developed scheme effectively addresses strong electronic correlation in quantum chemistry.
  • It offers a scalable and flexible approach for near-term quantum devices.
  • This work paves the way for exploring quantum algorithms in complex chemical systems.
  • The method shows promise for advancing rational molecular design.