Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

The Quantum-Mechanical Model of an Atom

The Quantum-Mechanical Model of an Atom

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. Schrödinger...

Quantum Numbers

Quantum Numbers

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.

Ampere-Maxwell's Law: Problem-Solving

Ampere-Maxwell's Law: Problem-Solving

A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the problem,...

Theorems of Pappus and Guldinus: Problem Solving

Theorems of Pappus and Guldinus: Problem Solving

Pappus and Guldinus's theorems are powerful mathematical principles that are used for finding the surface area and volume of composite shapes. For example, consider a cylindrical storage tank with a conical top. Finding the surface area or volume can be challenging for such complex shapes. These theorems are particularly useful in calculating the volume and surface area of such systems. Here, the cylindrical storage tank with a conical top can be broken down into two simple shapes: a cylinder...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...

Extended Versions of Green’s Theorem

Extended Versions of Green’s Theorem

Green’s Theorem connects the circulation of a vector field around a closed curve with the behavior of the field across the region enclosed by that curve. It provides a way to replace a line integral around a boundary with a double integral over the interior region, making it especially useful in plane geometry, fluid flow, and vector calculus.Although Green’s Theorem is often introduced using simple regions without gaps, it can also be applied to regions made from several simple parts. This...

You might also read

Related Articles

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

Sort by

Same author

Foci of contamination of Listeria monocytogenes in different cheese processing plants.

International journal of food microbiology·2013

Same author

Wine phenolic compounds influence the production of volatile phenols by wine-related lactic acid bacteria.

Journal of applied microbiology·2011

Same author

Diverse geno- and phenotypes of persistent Listeria monocytogenes isolates from fermented meat sausage production facilities in Portugal.

Applied and environmental microbiology·2011

Same author

Consumer exposure to phthalates from paper packaging: an integrated approach.

Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment·2010

Same author

Distribution and characterization of Listeria monocytogenes clinical isolates in Portugal, 1994-2007.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology·2010

Same author

Characterization of microbial population of 'Alheira' (a traditional Portuguese fermented sausage) by PCR-DGGE and traditional cultural microbiological methods.

Journal of applied microbiology·2009

Search research articles

Related Experiment Video

Updated: Jul 13, 2026

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

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

Published on: May 30, 2014

Portfolios of quantum algorithms.

S M Maurer¹, T Hogg, B A Huberman

¹Physics Department, Stanford University, Stanford, California 94043, USA.

Physical Review Letters

|December 12, 2001

Summary

Quantum computation can probabilistically solve hard problems. Portfolios of quantum algorithms, like financial ones, can reduce running time and uncertainty for complex tasks like 3-satisfiability.

Area of Science:

Quantum Computing
Computational Complexity Theory
Algorithm Optimization

Background:

Quantum computation offers potential solutions for intractable problems.
Many quantum algorithms are inherently stochastic, providing probabilistic solutions.
Algorithm efficiency requires evaluation of both completion time and variance.

Purpose of the Study:

To investigate methods for minimizing running time and uncertainty in quantum algorithms.
To explore the application of portfolio strategies to quantum algorithm selection.
To assess the performance of quantum algorithm portfolios on NP-complete problems.

Main Methods:

Developed a portfolio approach for quantum algorithms, drawing parallels with financial portfolio theory.

More Related Videos

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

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

Published on: August 2, 2019

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Jul 13, 2026

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

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

Published on: May 30, 2014

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

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

Published on: August 2, 2019

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Applied the portfolio strategy to NP-complete problems, specifically 3-satisfiability.

Analyzed the expected completion time and variance of the portfolio approach compared to single algorithms.

Main Results:

Quantum algorithm portfolios demonstrated superior performance over single algorithms.
The portfolio approach effectively reduced both the expected running time and its uncertainty.
Significant improvements were observed when applied to NP-complete problems like 3-satisfiability.

Conclusions:

Portfolio strategies are a viable method for enhancing quantum algorithm efficiency.
This approach offers a promising direction for tackling complex computational problems using quantum computers.
Further research into quantum portfolio optimization could unlock new computational capabilities.