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

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

2.1K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
2.1K
The Uncertainty Principle04:08

The Uncertainty Principle

34.5K
Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
34.5K
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

631
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
631
Quantum Numbers02:43

Quantum Numbers

53.8K
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.
53.8K
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

61.3K
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.
61.3K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.6K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.6K

You might also read

Related Articles

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

Sort by
Same author

Equivalence of Discrete and Continuous Otto-like Engines Assisted by Catalysts: Mapping Catalytic Advantages from the Discrete to the Continuous Framework.

Physical review letters·2026
Same author

How to Use Quantum Computers for Biomolecular Free Energies.

Journal of chemical theory and computation·2026
Same author

Iterative construction ofSp×Spgroup-adapted irreducible matrix units for the walled Brauer algebra.

Reports on progress in physics. Physical Society (Great Britain)·2026
Same author

Efficient quantum thermal simulation.

Nature·2025
Same author

Hardware-efficient quantum error correction via concatenated bosonic qubits.

Nature·2025
Same author

Catalytic enhancement in the performance of the microscopic two-stroke heat engine.

Physical review. E·2024
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: Mar 21, 2026

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

15.1K

Efficient Quantum Pseudorandomness.

Fernando G S L Brandão1,2, Aram W Harrow3, Michał Horodecki4

  • 1Quantum Architectures and Computation Group, Microsoft Research, Redmond 11728, Washington, USA.

Physical Review Letters
|May 14, 2016
PubMed
Summary
This summary is machine-generated.

Random quantum circuits offer a new way to create pseudorandomness efficiently. This breakthrough allows for polynomial-time constructions of quantum unitary designs, useful in quantum information science and cryptography.

More Related Videos

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

1.2K
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

9.1K

Related Experiment Videos

Last Updated: Mar 21, 2026

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

15.1K
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

1.2K
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

9.1K

Area of Science:

  • Quantum Information Science
  • Quantum Computing
  • Theoretical Physics

Background:

  • Randomness is crucial for modeling natural systems and for engineered applications like computation and control.
  • While classical pseudorandom operations are well-understood, constructing similar pseudorandomness in quantum systems is challenging.
  • Fully random quantum transformations are computationally expensive, requiring exponential time.

Purpose of the Study:

  • To demonstrate that random quantum unitary time evolutions (circuits) can serve as a powerful source of quantum pseudorandomness.
  • To provide the first polynomial-time construction for quantum unitary designs.
  • To show that generic quantum dynamics are indistinguishable from truly random processes.

Main Methods:

  • Utilizing random quantum unitary time evolutions (circuits) as a method for generating pseudorandomness.
  • Developing a polynomial-time construction for quantum unitary designs.
  • Analyzing the properties of generic quantum dynamics.

Main Results:

  • Established random quantum circuits as a source of quantum pseudorandomness.
  • Achieved the first polynomial-time construction of quantum unitary designs.
  • Demonstrated that generic quantum dynamics cannot be distinguished from truly random processes.

Conclusions:

  • Random quantum circuits provide an efficient method for creating quantum pseudorandomness.
  • The developed quantum unitary designs can substitute for fully random operations in many applications.
  • The findings have implications for quantum information science, cryptography, and the study of quantum system self-equilibration.