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

Parallel Processing01:20

Parallel Processing

143
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
143
Neural Circuits01:25

Neural Circuits

974
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
974
Protein Networks02:26

Protein Networks

2.2K
2.2K
Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule

1.1K
In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
1.1K
NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences01:17

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences

721
A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
721
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

10.9K
In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
10.9K

You might also read

Related Articles

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

Sort by
Same author

Statistical Testing of Random Number Generators and Their Improvement Using Randomness Extraction.

Entropy (Basel, Switzerland)·2025
Same author

Evaluating the Jones polynomial with tensor networks.

Physical review. E·2019
Same author

Optimal free descriptions of many-body theories.

Nature communications·2017
Same author

Surgical management of the partially edentulous atrophic mandibular ridge using a modified sandwich osteotomy: a case report.

The International journal of oral & maxillofacial implants·2005
Same author

Simultaneous placement of implant and bone graft in the anterior maxilla: a case report.

The International journal of oral & maxillofacial implants·2004
Same journal

MT-MRI for detection of renal interstitial fibrosis in renovascular disease.

Scientific reports·2026
Same journal

Detection of underground objects from GPR data using a lightweight YOLO-based approach.

Scientific reports·2026
Same journal

Early systemic inflammatory-metabolic trajectory phenotypes are associated with survival outcomes in metastatic renal cell carcinoma treated with nivolumab.

Scientific reports·2026
Same journal

Water balance components in a dry-seeded rice-wheat system: Untangling the effects of tillage and mulching practices.

Scientific reports·2026
Same journal

Topological approaches to quantum tensor train compression via ZX-calculus and SVD.

Scientific reports·2026
Same journal

determinants of flood impacts and adaptive capacity among market vendors in Walukuba-Masese, Jinja city, Uganda.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: May 24, 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

472

Sequence processing with quantum-inspired tensor networks.

Carys Harvey1,2, Richie Yeung3,4, Konstantinos Meichanetzidis3

  • 1Quantinuum, 17 Beaumont Street, Oxford, UK. carys.harvey@bristol.ac.uk.

Scientific Reports
|February 28, 2025
PubMed
Summary
This summary is machine-generated.

We developed efficient tensor network models for sequence processing, inspired by quantum computing. These models improve classification tasks in bioinformatics and natural language processing, demonstrating potential for near-term quantum devices.

More Related Videos

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
00:07

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

Published on: September 5, 2019

8.4K
Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
09:23

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

14.4K

Related Experiment Videos

Last Updated: May 24, 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

472
A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
00:07

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

Published on: September 5, 2019

8.4K
Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
09:23

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

14.4K

Area of Science:

  • Artificial Intelligence
  • Quantum Computing
  • Computational Linguistics

Background:

  • Tensor network models offer a promising avenue for sequence processing tasks.
  • Probabilistic graphical models provide a foundation for understanding complex data structures.
  • Quantum computing presents novel computational paradigms for machine learning.

Purpose of the Study:

  • To introduce efficient tensor network models for sequence processing.
  • To leverage inductive biases for improved network architecture and data correlation.
  • To explore the potential of these models on near-term quantum processors.

Main Methods:

  • Utilizing complex and unitary tensors to create expressive networks.
  • Introducing inductive bias through network architecture for correlation and compositionality.
  • Representing models as parameterized quantum circuits for physical process description.

Main Results:

  • Achieved logarithmic treewidth for enhanced trainability and efficient contraction.
  • Demonstrated successful binary classification in bioinformatics and natural language processing.
  • Implemented models on Quantinuum's H2-1 trapped-ion quantum processor.

Conclusions:

  • Tensor network models offer a scalable approach for exploring tensor structure and syntactic priors in NLP.
  • The models' operational mapping to qubits enables unbiased sampling via quantum measurements.
  • Near-term quantum devices show potential for executing these advanced machine learning models.