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Kinetic width

Kinetic width is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Kinetic width rather than just read about it. In short: A kinetic width data structure is a kinetic data structure which maintains the width of a set of moving points. In 2D, the width of a point set is the minimum distance between two parallel lines that contain the point set in the strip between them.

Key takeaways

  • Kinetic width belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Kinetic width to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Kinetic width from memory before moving on to harder problems.

Reference excerpt

A kinetic width data structure is a kinetic data structure which maintains the width of a set of moving points. In 2D, the width of a point set is the minimum distance between two parallel lines that contain the point set in the strip between them. For the two dimensional case, the kinetic data structure for kinetic convex hull can be used to construct a kinetic data structure for the width of a point set that is responsive, compact and efficient.

2D case Consider the parallel lines which contain the point set in the strip between them and are of minimal distance apart. One of the lines must contain an edge a b {\displaystyle ab} of the convex hull, and the other line must go through a point c of the convex hull such that (a,c) and (b,c) are antipodal pairs. ab and c are referred to as an antipodal edge-vertex pair. Consider the dual of the point set. The points dualize to lines and the convex hull of the points dualizes to the upper and lower envelope of the set of lines. The vertices of the upper convex hull dualize to segments on the upper envelope. The vertices of the lower convex hull dualize to segments on the lower envelope. The range of slopes of the supporting lines of a point on the hull dualize to the x-interval of segment that point dualizes to. When viewed in this dualized fashion the antipodal pairs, are pairs of segments, one from the upper envelope, one from the lower, with overlapping x ranges. Now, the upper and lower envelopes can be viewed as two different x-ordered lists of non overlapping intervals. If these two lists are merged, the antipodal pairs are the overlaps in the merged list. If a pair a b {\displaystyle ab} and c is an antipodal edge-vertex pair, then the x-interval for a and b must both intersect the x-interval for c. This means that the common endpoint of the x intervals for a and b must lie within the x-interval for c. The endpoints of both of the sets of x-intervals can be maintained in a kinetic sorted list. When points swap, the list of antipodal edge-point pairs are updated appropriately. The upper and lower envelopes can be maintained using the standard data structure for kinetic convex hull. The minimum distance between edge-point pairs can be maintained with a kinetic tournament. Thus, using kinetic convex hull to maintain the upper and lower envelopes, a kinetic sorted list on these intervals to maintain the antipodal edge-vertex pairs, and a kinetic tournament to maintain the pair of minimum distance apart, the diameter of a moving point set can be maintained. This data structure is responsive, compact and efficient. The data structure uses O ( n ) {\displaystyle O(n)} space because the kinetic convex hull, sorted list, and tournament data structures all use O ( n ) {\displaystyle O(n)} space. In all of the data structures, events, inserts, and deletes can be handled in O ( log 2 ⁡ n ) {\displaystyle O(\log ^{2}n)} time, so the data structure are responsive, requiring O ( log 2 ⁡ n ) {\displaystyle O(\log ^{2}n)} per event. The data structure is efficient because the total number of events is O ( n 2 + ϵ ) {\displaystyle O(n^{2+\epsilon })} for all ϵ > 0 {\displaystyle \epsilon >0} and the width of a point set can change Ω ( n 2 ) {\displaystyle \Omega (n^{2})} times, even if the points are moving linearly. This data structure is not local because one point may be in many antipodal edge-vertex pairs, and thus appear many times in the kinetic tournament. The existence of a local kinetic data structure for width is open.

Higher Dimensions Efficiently maintaining the kinetic width of a point set in dimensions higher than 2 is an open problem. Efficient kinetic convex hull in dimensions higher than 2 is also an open problem.

Related Problems Kinetic diameter Kinetic minimum box

References

Further reading P. K. Agarwal, L. J. Guibas, J. Hershberger, and E. Verach. Maintaining the extent of a moving set of points.

Worked examples

Example 1 — a first encounter with Kinetic width

Start with the simplest possible case. Write down what Kinetic width claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Kinetic width before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Kinetic width ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Kinetic width

In research
Kinetic width appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Kinetic width in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Kinetic width is common in secondary-school and first-year university syllabi. It links to neighbouring topics Geometric data structures, Kinetic data structures, so understanding it makes those chapters shorter.
In everyday life
Look for Kinetic width outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Kinetic width in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Kinetic width means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Kinetic width out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Kinetic width in simple terms?

A kinetic width data structure is a kinetic data structure which maintains the width of a set of moving points. In 2D, the width of a point set is the minimum distance between two parallel lines that contain the point set in the strip between them.

Why does Kinetic width matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Kinetic width?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Kinetic width.

Tags

  • Geometric data structures
  • Kinetic data structures

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