Related Experiment Video
Updated: Jul 13, 2026

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.
Abstract:
Quantum computation holds promise for the solution of many intractable problems. However, since many quantum algorithms are stochastic in nature they can find the solution of hard problems only probabilistically. Thus the efficiency of the algorithms has to be characterized by both the expected time to completion and the associated variance. In order to minimize both the running time and its uncertainty, we show that portfolios of quantum algorithms analogous to those of finance can outperform single algorithms when applied to the NP-complete problems such as 3-satisfiability.
Related Concept Videos
The Quantum-Mechanical Model of an Atom
Quantum Numbers
Ampere-Maxwell's Law: Problem-Solving
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
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Extended Versions of Green’s Theorem

