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

Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
Modeling with Differential Equations01:25

Modeling with Differential Equations

Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
Open and closed-loop control systems01:17

Open and closed-loop control systems

Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal and...
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...

You might also read

Related Articles

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

Sort by
Same author

Downstream invasive coronary procedures following PET Versus SPECT myocardial perfusion imaging: a propensity-matched analysis.

European journal of nuclear medicine and molecular imaging·2026
Same author

Safety and Effectiveness of Saphenous Vein Graft Use for Retrograde Chronic Total Occlusion Percutaneous Coronary Intervention.

The American journal of cardiology·2026
Same author

Temporal trends in retrograde crossing of epicardial collaterals in chronic total occlusion percutaneous coronary intervention.

International journal of cardiology·2026
Same author

Ostial occlusion of all epicardial coronary arteries: Living off bypass grafts.

The Journal of thoracic and cardiovascular surgery·2026
Same author

Impact of Adherence to the Global Algorithm for Initial Crossing Strategy Selection in Chronic Total Occlusion Percutaneous Coronary Intervention.

The American journal of cardiology·2026
Same author

Optical Coherence Tomography for Recurrent Drug Eluting Stent-Related In-Stent Restenosis: Stepwise Intracoronary Imaging of Progressive Tissue and Calcium Modification.

Journal of the Society for Cardiovascular Angiography & Interventions·2026

Related Experiment Video

Updated: Jun 13, 2026

Bringing the Visible Universe into Focus with Robo-AO
10:35

Bringing the Visible Universe into Focus with Robo-AO

Published on: February 12, 2013

Deformable mirror model for open-loop adaptive optics using multivariate adaptive regression splines.

Dani Guzmán1, Francisco Javier de Cos Juez, Fernando Sánchez Lasheras

  • 1Physics Department, Durham University, South Road Laboratories, Durham, DH1 3LE, UK. dani@astroinventions.com

Optics Express
|April 15, 2010
PubMed
Summary

We developed a new method using multivariate adaptive regression splines (MARS) to model deformable mirrors in open-loop adaptive optics. This technique accurately controls mirror shape, achieving low positioning errors for any deformable mirror type.

More Related Videos

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter
05:14

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter

Published on: September 16, 2025

Related Experiment Videos

Last Updated: Jun 13, 2026

Bringing the Visible Universe into Focus with Robo-AO
10:35

Bringing the Visible Universe into Focus with Robo-AO

Published on: February 12, 2013

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter
05:14

Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter

Published on: September 16, 2025

Area of Science:

  • Optics
  • Control Systems Engineering
  • Computational Science

Background:

  • Open-loop adaptive optics corrects wavefront distortions before they reach optical components.
  • Accurate modeling of deformable mirrors is crucial for effective wavefront correction.
  • Existing models may be device-specific or rely on detailed physical parameters.

Purpose of the Study:

  • To present a novel, non-parametric modeling technique for deformable mirrors in open-loop adaptive optics.
  • To develop a model based on multivariate adaptive regression splines (MARS).
  • To demonstrate the model's applicability and accuracy across different deformable mirror types.

Main Methods:

  • Utilized multivariate adaptive regression splines (MARS), a non-parametric regression technique.
  • Developed a model where wavefront correction is the input and mirror voltages are the output.
  • Experimentally validated the model using an electrostrictive deformable mirror.

Main Results:

  • Achieved positioning errors of approximately 1.2% RMS of the peak-to-peak wavefront excursion.
  • The MARS-based model demonstrated high accuracy in predicting mirror voltages for wavefront correction.
  • The technique proved independent of specific physical device parameters.

Conclusions:

  • The MARS-based modeling technique offers a robust and generalizable approach for controlling deformable mirrors in open-loop adaptive optics.
  • This method can be integrated into the control schemes of various deformable mirror technologies.
  • The low positioning error indicates significant potential for improving adaptive optics system performance.