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

Euler Equations of Motion01:19

Euler Equations of Motion

318
Imagine a rigid body that is rotating at an angular velocity of ω within an inertial frame of reference. Along with this, picture a second rotating frame that is attached to the body itself. This frame moves along with the body and possesses an angular velocity of Ω. The total moment about the center of mass is calculated by adding the rate of change of angular momentum about the center of mass in relation to the rotating frame and the cross-product of the body's angular velocity...
318
Kinematic Equations - II01:17

Kinematic Equations - II

10.3K
The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...
10.3K
Kinematic Equations - III01:18

Kinematic Equations - III

8.2K
The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
Using the kinematic equations,...
8.2K
Euler's Equations of Motion01:28

Euler's Equations of Motion

561
In fluid mechanics, shear stresses arise from viscosity, which represents a fluid's internal resistance to deformation. For low-viscosity fluids, like water, these stresses are minimal, simplifying flow analysis by allowing the fluid to be treated as inviscid, or frictionless. In an inviscid fluid, shear stresses are absent, leaving only normal stresses, which act perpendicularly to fluid elements. Notably, pressure — defined as the negative of the normal stress — remains...
561
Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

13.3K
When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
13.3K
Kinematic Equations - I01:26

Kinematic Equations - I

11.7K
When an object moves with constant acceleration, the velocity of the object changes at a constant rate throughout the motion. The kinematic equations of motions are derived for such cases where the acceleration of the object is constant. The first kinematic equation gives an insight into the relationship between velocity, acceleration, and time. We can see, for example:
11.7K

You might also read

Related Articles

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

Sort by
Same author

Interpretable machine learning model using peripheral blood for non-invasive detection of moderate-to-severe myelofibrosis in JAK2 V617F-positive MPNs: A multicentre pilot proof-of-concept study.

British journal of haematology·2026
Same author

RAD23A promotes multiple myeloma cell survival through DNA damage response, proteostasis and enhanced metabolic activity.

Toxicology and applied pharmacology·2026
Same author

Synthesis of amine-functionalized magnetic covalent organic framework for efficient magnetic solid-phase extraction and simultaneous determination of eleven mycotoxins in food by UPLC-MS/MS.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences·2026
Same author

Phonon-scattering-induced linear magnetoresistance in the quantum limit up to room temperature.

Nature communications·2026
Same author

Body mass index and early-onset colorectal cancer risk: a systematic review and cohort-based meta-analysis.

Scandinavian journal of gastroenterology·2026
Same author

Dominant TET2 mutations predict adverse prognosis in cytogenetically normal acute myeloid leukemia patients.

Frontiers in oncology·2026
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
See all related articles

Related Experiment Video

Updated: Sep 8, 2025

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.7K

Corrected Maslov index for complex saddle trajectories.

Huichao Wang1, Steven Tomsovic1

  • 1Department of Physics and Astronomy, Washington State University, Pullman, Washington 99164-2814, USA.

Physical Review. E
|June 16, 2022
PubMed
Summary
This summary is machine-generated.

Saddle-point approximations in quantum mechanics can have sign errors due to determinant zeros. A new method links complex saddles to real trajectories, avoiding complex time analysis for accurate phase correction.

More Related Videos

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K
Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

8.9K

Related Experiment Videos

Last Updated: Sep 8, 2025

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.7K
Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K
Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
08:19

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion

Published on: January 15, 2016

8.9K

Area of Science:

  • Quantum mechanics
  • Mathematical physics

Background:

  • Saddle-point approximations are vital in physics.
  • They require analytical continuation to complex variables.
  • Determinantal prefactors are crucial for phase correction in caustics.

Purpose of the Study:

  • To identify the cause of sign errors in saddle-point approximations.
  • To develop a more practical method for phase correction.
  • To avoid complex time contour deformation around determinant zeros.

Main Methods:

  • Analysis of determinant zeros at complex times.
  • Linking complex saddle points to real trajectories.
  • Developing a new prescription for phase correction.

Main Results:

  • Sign errors arise from determinant zeros crossing the real time axis.
  • A novel method connects complex saddles to real trajectories.
  • This approach bypasses the need to locate complex time zeros.

Conclusions:

  • The study resolves sign errors in saddle-point approximations.
  • A practical method for phase correction is presented.
  • The findings simplify calculations in quantum mechanics and related fields.