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A COMPUTATIONAL APPROACH TO ODD CYCLE GRAPH ENTROPY {N OEMI G LAESER ,J OSHUA C OOPER ( MENTOR )} U NIVERSITY OF S OUTH C AROLINA D EPT OF M ATHEMATICS D EFINITIONS Coding theory concerns itself with commu- nication in noisy environments. A cycle graph is a graph consisting of ver- tices connected in a loop. Graph entropy (Shannon capacity) mea- sures the amount of information transmit- ted by the code modelled by a graph. An independent set is a set of vertices of a graph which are mutually non-adjacent. The strong product G H of graphs G and H has vertex set V = V (G) × V (H ) and edges between points (u, v ) and (u 0 ,v 0 ) ⇐⇒ at least one of the following holds: (1) u is adjacent u 0 or (2) v is adjacent to v 0 . An affine subspace is a vector subspace with a constant shift from the origin. I NTRODUCTION A cycle graph consists of a series of vertices con- nected in a loop. Such graphs can model a noisy communication channel, where each vertex represents a transmitted symbol and edges indi- cate confusability between symbols. What is the most efficient communication schema to transmit data with no errors and maximize precious band- width? This information density is encapsulated by the quantity known as graph entropy. Figure 1: An independent set in the graph C 5 . R IGIDITY &B OUNDS Theorem 1. Let the vertices of C 7 be the elements of F 7 and define the power C 5 7 (assuming the strong prod- uct) to have an edge between vertices x and y when x - y ∈B = {-1, 0, 1} 5 . Any maximal affine sub- space of C 5 7 = F 5 7 which is an independent set is rigid. Corollary 1. This characterization can in fact also be applied to the affine subspaces constructed in [1] for the lower α(G) bounds for G = C 4 11 , C 4 13 , and C 3 15 . Corollary 2. Furthermore, a similar argument can be utilized to show that constructions utilizing affine sub- spaces for C 5 5 , C 4 7 , and C 4 9 are also rigid. Note that this relies only upon the ring structure of these spaces, and so is also applicable for structures like C 2 9 . p\d 1 2 3 4 5 5 X 1 X 1 X 1 X 1 X 3 7 X 1 X 1 X 1 X 4 X 2,4 9 X 1 X 1 X 1 X 3 X 3 11 X 1 X 1 X 1 X 2,4 13 X 1 X 1 X 1 X 2,4 15 X 1 X 1 X 2,4 Table 1: Rigidity of lower bound independent set con- structions for C d p . Key: 1 α(G) known. 2 Corollary 1 (Theorem 1). 3 Corollary 2. 4 Computer proof. A CKNOWLEDGMENTS Many thanks to my advisor, Dr. Joshua Cooper, for his guidance, and the University of South Carolina Honors College for providing funding through the Science Undergraduate Research Fel- lowship (SURF). I also want to acknowledge the staff at the University of South Carolina’s Re- search Computing Institute (RCI) for providing me with access to and assistance with the univer- sity’s high performance computing clusters. B ACKGROUND Figure 2: A naïve independent set in C 2 5 , obtained by taking the Cartesian product of the independent set of C 5 with itself. Figure 3: The maximal independent set of C 2 5 , which increases the lower bound of the Shannon capacity to 5. The size of the independent set of a graph G to the power k , α(G k ), is bounded according to Equa- tion (1). The entropy, or Shannon capacity, is obtained by taking the k th root of the central quantity. α(G) k α(G k ) χ( ¯ G) k (1) G RAPH C YCLONE The Graph Cyclone package is available via PyPI at https://pypi.org/project/ graph-cyclone/. It can also be installed with pip install graph-cyclone. Features include: Create cycle graphs and their powers Add/remove points Check if a point is present Calculate size Count neighbors of a point F UTURE R ESEARCH This research can be extended by implementing some of the following approaches: Improve bounds with new methods (local search, annealing, “energy” characteriza- tion) More information about structure of sets in [1] (discrete Fourier transform) Smarter parallelization (e.g. genetic algo- rithm) Improvements to the current local improve- ment algorithm (bookkeeping and design) Optimize point removal R EFERENCES [1] K. A. Mathew and P. R. J. Östergård. New lower bounds for the Shannon capacity of odd cycles. De- signs, Codes and Cryptography, 84:13–22, 2017. [2] A. Vesel and J. Žerovnik. Improved lower bound on the Shannon capacity of c 7 . Information Processing Letters, 81:277–282, 2002. [3] L. D. et al. Baumert. A combinatorial packing prob- lem. Computers in Algebra and Number Theory, 4:97– 107, 1971. C ONTACT I NFORMATION Web nglaeser.github.io Email [email protected] GitHub @nglaeser

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Page 1: COMPUTATIONAL APPROACH TO ODD CYCLE GRAPH ENTROPY

A COMPUTATIONAL APPROACH TO ODD CYCLE GRAPH ENTROPY{ NOEMI GLAESER, JOSHUA COOPER (MENTOR) } UNIVERSITY OF SOUTH CAROLINA DEPT OF MATHEMATICS

DEFINITIONS• Coding theory concerns itself with commu-

nication in noisy environments.• A cycle graph is a graph consisting of ver-

tices connected in a loop.• Graph entropy (Shannon capacity) mea-

sures the amount of information transmit-ted by the code modelled by a graph.• An independent set is a set of vertices of a

graph which are mutually non-adjacent.• The strong product G�H of graphs G andH has vertex set V = V (G) × V (H) andedges between points (u, v) and (u′, v′) ⇐⇒at least one of the following holds: (1) u isadjacent u′ or (2) v is adjacent to v′.• An affine subspace is a vector subspace

with a constant shift from the origin.

INTRODUCTIONA cycle graph consists of a series of vertices con-nected in a loop. Such graphs can model anoisy communication channel, where each vertexrepresents a transmitted symbol and edges indi-cate confusability between symbols. What is themost efficient communication schema to transmitdata with no errors and maximize precious band-width? This information density is encapsulatedby the quantity known as graph entropy.

Figure 1: An independent set in the graph C5.

RIGIDITY & BOUNDS

Theorem 1. Let the vertices of C7 be the elements ofF7 and define the power C5

7 (assuming the strong prod-uct) to have an edge between vertices x and y whenx − y ∈ B = {−1, 0, 1}5. Any maximal affine sub-space of C5

7 = F57 which is an independent set is rigid.

Corollary 1. This characterization can in fact also beapplied to the affine subspaces constructed in [1] for thelower α(G) bounds for G = C4

11, C413, and C3

15.

Corollary 2. Furthermore, a similar argument can beutilized to show that constructions utilizing affine sub-spaces for C5

5 , C47 , and C4

9 are also rigid. Note that thisrelies only upon the ring structure of these spaces, andso is also applicable for structures like C2

9 .

p\d 1 2 3 4 5

5 X1 X1 X1 X1 X3

7 X1 X1 X1 X4 X2,4

9 X1 X1 X1 X3 X3

11 X1 X1 X1 X2,4

13 X1 X1 X1 X2,4

15 X1 X1 X2,4

Table 1: Rigidity of lower bound independent set con-structions for Cd

p .

Key:1α(G) known.2Corollary 1 (Theorem 1).3Corollary 2.4Computer proof.

ACKNOWLEDGMENTS

Many thanks to my advisor, Dr. Joshua Cooper,for his guidance, and the University of SouthCarolina Honors College for providing fundingthrough the Science Undergraduate Research Fel-lowship (SURF). I also want to acknowledge the

staff at the University of South Carolina’s Re-search Computing Institute (RCI) for providingme with access to and assistance with the univer-sity’s high performance computing clusters.

BACKGROUND

Figure 2: A naïve independent set in C25 , obtained by

taking the Cartesian product of the independent set ofC5 with itself.

Figure 3: The maximal independent set of C25 , which

increases the lower bound of the Shannon capacity to√5.

The size of the independent set of a graphG to thepower k, α(G�k), is bounded according to Equa-tion (1).The entropy, or Shannon capacity, is obtained by

taking the kth root of the central quantity.

α(G)k ≤ α(G�k) ≤ χ(G)k (1)

GRAPH CYCLONE

The Graph Cyclone package is available viaPyPI at https://pypi.org/project/graph-cyclone/. It can also be installedwith pip install graph-cyclone.Features include:

• Create cycle graphs and their powers• Add/remove points• Check if a point is present• Calculate size• Count neighbors of a point

FUTURE RESEARCH

This research can be extended by implementingsome of the following approaches:

• Improve bounds with new methods (localsearch, annealing, “energy” characteriza-tion)

• More information about structure of sets in[1] (discrete Fourier transform)

• Smarter parallelization (e.g. genetic algo-rithm)

• Improvements to the current local improve-ment algorithm (bookkeeping and design)

• Optimize point removal

REFERENCES

[1] K. A. Mathew and P. R. J. Östergård. New lowerbounds for the Shannon capacity of odd cycles. De-signs, Codes and Cryptography, 84:13–22, 2017.

[2] A. Vesel and J. Žerovnik. Improved lower bound onthe Shannon capacity of c7. Information ProcessingLetters, 81:277–282, 2002.

[3] L. D. et al. Baumert. A combinatorial packing prob-lem. Computers in Algebra and Number Theory, 4:97–107, 1971.

CONTACT INFORMATION

Web nglaeser.github.ioEmail [email protected] @nglaeser