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Related Concept Videos

Vector Operations01:20

Vector Operations

Vectors are physical quantities that have both magnitude and direction. The vector operations include addition, subtraction, and scalar multiplication.
A vector multiplied by a scalar value is called scalar multiplication. The result obtained is a new vector with a different magnitude. If the scalar is positive, the direction of the vector remains the same, but if it is negative, the direction of the vector is reversed. For example, the product of the mass and velocity yields the momentum.
Vector Components in the Cartesian Coordinate System01:29

Vector Components in the Cartesian Coordinate System

Vectors are usually described in terms of their components in a coordinate system. Even in everyday life, we naturally invoke the concept of orthogonal projections in a rectangular coordinate system. For example, if someone gives you directions for a particular location, you will be told to go a few km in a direction like east, west, north, or south, along with the angle in which you are supposed to move. In a rectangular (Cartesian) xy-coordinate system in a plane, a point in a plane is...
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
Scalar and Vector Triple Products01:06

Scalar and Vector Triple Products

Two vectors can be multiplied using a scalar product or a vector product. The resultant of a scalar product is scalar, while with vector products, the resultant is a vector. These rules of the scalar or vector product between two vectors can be applied to multiple vectors to obtain meaningful combinations. The scalar triple product is the dot product of a vector with the cross product of two vectors.
The scalar triple product is the dot product of a vector with the cross product of two vectors.
Vectors in Engineering Applications01:30

Vectors in Engineering Applications

A steel beam supported by two identical cables provides a practical example of static equilibrium. The beam has a downward weight of 5000 N, while the two cables support it from opposite sides. Because the arrangement is symmetric, each cable makes the same angle of 60° with the horizontal beam and carries the same tension.In equilibrium, the beam remains completely at rest. This means that the total horizontal and vertical forces must both be zero. Each cable pulls along its own direction, so...
Vector or Cross Product01:17

Vector or Cross Product

Vector multiplication of two vectors yields a vector product, with the magnitude equal to the product of the individual vectors multiplied by the sine of the angle between both the vectors and the direction perpendicular to both the individual vectors. As there are always two directions perpendicular to a given plane, one on each side, the direction of the vector product is governed by the right-hand thumb rule.
Consider the cross product of two vectors. Imagine rotating the first vector about...

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A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
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Published on: September 5, 2019

Linear vector operations in coherent optical data processing systems.

R G Eguchi, F P Carlson

    Applied Optics
    |January 16, 2010
    PubMed
    Summary
    This summary is machine-generated.

    This study demonstrates a novel method for generating a two-dimensional vector space in optical data processing. This technique enables the direct computation of the transverse gradient operator using coherent optical systems.

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    Published on: January 28, 2019

    Area of Science:

    • Coherent Optics
    • Optical Data Processing
    • Vector Space Generation

    Background:

    • Traditional optical data processing systems often face limitations in handling complex mathematical operations.
    • The transverse gradient is a fundamental operation in image processing and physics, but its direct implementation in optical systems is challenging.

    Purpose of the Study:

    • To theoretically and experimentally demonstrate the generation of a two-dimensional linear vector space in a coherent optical data processing system.
    • To apply this vector space to the computation of the transverse gradient operator.

    Main Methods:

    • Creating a vector space by superposing outputs from two Fourier optical systems with orthogonal polarizations.
    • Utilizing each system to perform partial derivative operations of the transverse gradient.
    • Employing identical inputs for both systems to achieve a vector sum of partial derivatives.

    Main Results:

    • Successfully generated a two-dimensional linear vector space.
    • Demonstrated the computation of the transverse gradient operation by summing partial derivatives.
    • Focused on optimal approximation of specific filters (jomega(x)î and jomega(y)j) over binary filters.

    Conclusions:

    • The proposed method provides a viable approach for implementing the transverse gradient operator in coherent optical systems.
    • The experimental realization highlights the potential for advanced optical data processing applications.
    • Addressed practical challenges such as film and lens noise in the experimental setup.