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

Mass Analyzers: Common Types01:19

Mass Analyzers: Common Types

684
The quadrupole mass analyzer consists of four cylindrical metal rods arranged in a diamond carrying a DC voltage and a radio-frequency AC voltage. The motion of ions through the quadrupole depends on the field strength, causing only ions of a certain m/z to resonate successfully and strike the detector at a given field strength. Though the transmission rate for these analyzers is high, the exact elemental composition of the sample is not determined because of low resolution; however, they are...
684
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

42.8K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
42.8K
Quantum Numbers02:43

Quantum Numbers

35.2K
It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
35.2K
NMR Spectroscopy: Spin–Spin Coupling01:08

NMR Spectroscopy: Spin–Spin Coupling

1.5K
The spin state of an NMR-active nucleus can have a slight effect on its immediate electronic environment. This effect propagates through the intervening bonds and affects the electronic environments of NMR-active nuclei up to three bonds away; occasionally, even farther. This phenomenon is called spin–spin coupling or J-coupling. Coupling interactions are mutual and result in small changes in the absorption frequencies of both nuclei involved. While nuclei of the same element are involved...
1.5K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

98
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...
98
Inductive Effects on Chemical Shift: Overview01:27

Inductive Effects on Chemical Shift: Overview

1.3K
The protons in unsubstituted alkanes are strongly shielded with chemical shifts below 1.8 ppm. Methine, methylene, and methyl protons appear at approximately 1.7, 1.2 and 0.7 ppm, while the proton signal from methane appears at 0.23 ppm. An electronegative substituent, such as chlorine, withdraws the electron density from the protons, increasing their chemical shift. Progressive substitution of the hydrogens in methane by chlorine shifts the proton signals increasingly downfield, to 3.05 ppm in...
1.3K

You might also read

Related Articles

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

Sort by
Same author

Variation in outcome reporting in studies on the prevention and management of pregnancy-associated venous thromboembolism: a scoping review.

Research and practice in thrombosis and haemostasis·2026
Same author

Error Mitigation Thresholds in Noisy Random Quantum Circuits.

Physical review. B·2026
Same author

On the equivalence between classically verifiable position verification and certified randomness.

Nature communications·2026
Same author

Non-variational quantum random access optimization with alternating operator ansatz.

Scientific reports·2025
Same author

Certified randomness using a trapped-ion quantum processor.

Nature·2025
Same author

Phase transition in magic with random quantum circuits.

Nature physics·2025
Same journal

Integrated multi-assessment and structural performance index framework for stacking-sequence optimisation of natural fibre reinforced laminates.

Scientific reports·2026
Same journal

SuperiorGAT: graph attention networks for sparse LiDAR point cloud reconstruction in autonomous systems.

Scientific reports·2026
Same journal

The effect of stretching the pectoralis major, sternocleidomastoid, and iliopsoas muscles on 800 m swimming performance in master swimmers.

Scientific reports·2026
Same journal

ISNR-PQC: isometry noise resilience post quantum cryptography primitive.

Scientific reports·2026
Same journal

Identification of high-yielding and stable genotypes of barley in the cold climate of Iran using AMMI and GGE biplot models.

Scientific reports·2026
Same journal

Bayesian negative binomial modelling of spatial and temporal patterns of road traffic deaths in Ghana.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Aug 25, 2025

Experimental Methods for Trapping Ions Using Microfabricated Surface Ion Traps
11:45

Experimental Methods for Trapping Ions Using Microfabricated Surface Ion Traps

Published on: August 17, 2017

14.6K

Constrained quantum optimization for extractive summarization on a trapped-ion quantum computer.

Pradeep Niroula1,2,3, Ruslan Shaydulin4, Romina Yalovetzky1

  • 1JPMorgan Chase, New York, NY, USA.

Scientific Reports
|October 13, 2022
PubMed
Summary
This summary is machine-generated.

This study demonstrates the largest quantum optimization execution preserving constraints for extractive summarization. The Quantum Alternating Operator Ansatz algorithm (XY-QAOA) on trapped-ion hardware shows native constraint preservation is crucial for effective quantum advantage.

More Related Videos

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

9.7K
Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving
11:21

Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving

Published on: March 30, 2017

7.5K

Related Experiment Videos

Last Updated: Aug 25, 2025

Experimental Methods for Trapping Ions Using Microfabricated Surface Ion Traps
11:45

Experimental Methods for Trapping Ions Using Microfabricated Surface Ion Traps

Published on: August 17, 2017

14.6K
Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

9.7K
Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving
11:21

Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving

Published on: March 30, 2017

7.5K

Area of Science:

  • Quantum Computing
  • Computational Optimization
  • Artificial Intelligence

Background:

  • Near-term quantum computers offer potential for solving complex constrained-optimization problems, a key step towards quantum advantage.
  • Extractive summarization is a relevant industry problem that can be framed as a constrained-optimization task.
  • Existing quantum optimization algorithms often struggle with native constraint preservation.

Purpose of the Study:

  • To demonstrate the largest-to-date execution of a quantum optimization algorithm that natively preserves constraints on quantum hardware.
  • To investigate the Quantum Alternating Operator Ansatz algorithm with a Hamming-weight-preserving XY mixer (XY-QAOA) for constrained optimization.
  • To analyze the trade-offs associated with native constraint encoding versus unconstrained methods in quantum optimization.

Main Methods:

  • Execution of the XY-QAOA algorithm on a trapped-ion quantum computer.
  • Utilizing quantum circuits that restrict quantum evolution to the in-constraint subspace.
  • Scaling the execution to up to 20 qubits and a two-qubit gate depth of up to 159.
  • Comparison with Layer Variational Quantum Eigensolver (L-VQE) and Quantum Approximate Optimization Algorithm (QAOA).

Main Results:

  • Successful execution of XY-QAOA circuits with native constraint preservation on up to 20 qubits.
  • Demonstrated necessity of direct constraint encoding, showing a trade-off between in-constraint probability and solution quality for unconstrained methods.
  • Identified challenges in parameter selection due to the trade-off in unconstrained optimization.
  • Comparative analysis of XY-QAOA against L-VQE and QAOA, highlighting respective trade-offs.

Conclusions:

  • Native constraint preservation in quantum optimization algorithms like XY-QAOA is critical for achieving high-quality solutions in constrained problems such as extractive summarization.
  • Directly encoding constraints into quantum circuits is more effective than relying on unconstrained methods, despite potential parameter tuning difficulties.
  • The findings provide valuable insights into the practical execution and limitations of quantum optimization algorithms on near-term quantum hardware.