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Loupekine snark

Loupekine snark is a 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 Loupekine snark rather than just read about it. In short: In graph theory, the Loupekine snarks are an infinite family of snarks, graphs with three edges per vertex that cannot be partitioned into three perfect matchings. Their construction is credited to Féodor Loupekine in a 1976 technical report published by Rufus Isaacs.

Loupekine snark — main illustration
Loupekine snark — illustration

Key takeaways

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

Reference excerpt

In graph theory, the Loupekine snarks are an infinite family of snarks, graphs with three edges per vertex that cannot be partitioned into three perfect matchings. Their construction is credited to Féodor Loupekine in a 1976 technical report published by Rufus Isaacs. Loupekine's 1992 doctoral dissertation includes the construction, and attaches Isaac's technical report as an appendix, but this appendix has been redacted from the online version of the dissertation.

Construction It involves forming an odd number of blocks by removing three-vertex paths from smaller snarks, and arranging the blocks into a cycle. Consecutive pairs of blocks in this cycle are connected by pairs of edges, attached in each block to two degree-two vertices in the block, the two neighbors of one endpoint of the removed path. These connections leave one remaining degree-two vertex in each block, a neighbor of the central vertex of the removed path. These remaining vertices are connected by adding to them a "central graph", attached to each degree-two vertex by a single edge and having degree three at its other vertices. This construction produces a graph that has no 3-color edge coloring, regardless of the central graph. This is because in any 3-edge-coloring of a block and its connecting edges, one pair of edges connecting to an adjacent block in the cycle of blocks must have a single color and the other pair must have two different colors. This alternation between edge pairs with one or two colors cannot be maintained consistently around an odd cycle of blocks. When the central graph is chosen in a way that maintains the connectivity requirements of a snark, the result is a snark.

Examples The simplest Loupekine snarks are obtained by constructing three blocks from three copies of the Petersen graph, connecting them by pairs of edges into a cycle of three blocks, and using a central graph consisting of a three-leaf star. There are two graphs of this type, depending on how the pairs of edges connecting consecutive blocks are chosen. They both have 22 vertices and 33 edges, and have an order-6 dihedral group of symmetries. Both graphs are 1-planar.

References

External links No. 263, Isaacs: "Loupekine's Snarks: A Bifamily of Non-Tait- Colorable Graphs," 1976, catalog record of a printed copy of Isaac's original 1976 publication in the special collections of the Johns Hopkins University libraries

Illustrations

Loupekine snark illustration
Loupekine snark illustration

Worked examples

Example 1 — a first encounter with Loupekine snark

Start with the simplest possible case. Write down what Loupekine snark claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In 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 Loupekine snark 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 Loupekine snark 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 Loupekine snark

In research
Loupekine snark appears in 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 Loupekine snark 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
Loupekine snark is common in secondary-school and first-year university syllabi. It links to neighbouring topics Individual graphs, Regular graphs, so understanding it makes those chapters shorter.
In everyday life
Look for Loupekine snark 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 Loupekine snark in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Loupekine snark 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 Loupekine snark out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Loupekine snark in simple terms?

In graph theory, the Loupekine snarks are an infinite family of snarks, graphs with three edges per vertex that cannot be partitioned into three perfect matchings. Their construction is credited to Féodor Loupekine in a 1976 technical report published by Rufus Isaacs.

Why does Loupekine snark matter?

Because it connects several 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 Loupekine snark?

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 Loupekine snark.

Tags

  • Individual graphs
  • Regular graphs

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