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

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

35.1K
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.
35.1K
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.1K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.1K
Inductive Effects on Chemical Shift: Overview01:27

Inductive Effects on Chemical Shift: Overview

1.2K
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...
1.2K
The Pauli Exclusion Principle03:06

The Pauli Exclusion Principle

44.6K
The arrangement of electrons in the orbitals of an atom is called its electron configuration. We describe an electron configuration with a symbol that contains three pieces of information:
44.6K
Molecular Spectroscopy: Absorption and Emission01:14

Molecular Spectroscopy: Absorption and Emission

2.4K
Molecules possess discrete energy levels called quantum states. Unlike atoms, which have simpler energy levels, molecules possess additional rotational and vibrational energy levels.  Each energy level is separated by an energy gap, with the gaps between adjacent electronic, vibrational, and rotational levels varying significantly. The three types of energy levels in a diatomic molecule are shown in Figure 1.
2.4K

You might also read

Related Articles

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

Sort by
Same author

Experimental realization of para-particle oscillators.

Scientific reports·2025
Same author

Classically Estimating Observables of Noiseless Quantum Circuits.

Physical review letters·2025
Same author

Highly Efficient Noble-Metal Free Photocatalytic Hydrogen Generation Using Water-Stable 4,4'-Vinylenedipyridine-Based Halide Perovskites.

Small (Weinheim an der Bergstrasse, Germany)·2025
Same author

Does provable absence of barren plateaus imply classical simulability?

Nature communications·2025
Same author

Thermodynamic computing system for AI applications.

Nature communications·2025
Same author

Foveal vision reduces neural resources in agent-based game learning.

Frontiers in neuroscience·2025
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

Related Experiment Video

Updated: Aug 20, 2025

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source
12:19

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Published on: April 4, 2017

8.5K

Inference-Based Quantum Sensing.

C Huerta Alderete1,2,3, Max Hunter Gordon4,5, Frédéric Sauvage4

  • 1Information Sciences, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.

Physical Review Letters
|November 18, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an inference-based quantum sensing (QS) scheme. It enables accurate parameter estimation by characterizing system response with fewer measurements, improving quantum sensing performance.

More Related Videos

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.3K
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

636

Related Experiment Videos

Last Updated: Aug 20, 2025

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source
12:19

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Published on: April 4, 2017

8.5K
Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
10:42

Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

Published on: March 22, 2019

6.3K
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

636

Area of Science:

  • Quantum Information Science
  • Metrology
  • Quantum Sensing

Background:

  • Quantum sensing (QS) estimates unknown parameters encoded in quantum states.
  • Realistic QS scenarios lack a general closed-form expression for system response R(θ).
  • Characterizing R(θ) is crucial for accurate parameter estimation and performance evaluation.

Purpose of the Study:

  • To present a novel inference-based quantum sensing scheme.
  • To enable full characterization of system response R(θ) for a general class of unitary encodings.
  • To provide a framework for inferring unknown parameters and determining sensing sensitivity.

Main Methods:

  • Developed an inference-based scheme for quantum sensing.
  • Showcased that R(θ) can be characterized using only 2n+1 measurements for unitary families.
  • Analyzed inference error scaling with the number of measurements (shots).

Main Results:

  • Inference error is bounded with high probability for a number of shots scaling as Ω(log³(n)/δ²).
  • The framework is applicable to arbitrary probe states and measurement schemes.
  • The method remains valid even in the presence of quantum noise.

Conclusions:

  • The proposed inference-based scheme offers a robust and broadly applicable approach to quantum sensing.
  • It significantly reduces the measurement resources required for accurate parameter estimation.
  • The framework's validity under noise and for arbitrary states highlights its practical potential.