# Small Littlewood–Richardson coefficients

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## Abstract

We develop structural insights into the Littlewood–Richardson graph, whose number of vertices equals the Littlewood–Richardson coefficient \(c_{\lambda ,\mu }^{\nu }\) for given partitions \(\lambda \), \(\mu \), and \(\nu \). This graph was first introduced in Bürgisser and Ikenmeyer (SIAM J Discrete Math 27(4):1639–1681, 2013), where its connectedness was proved. Our insights are useful for the design of algorithms for computing the Littlewood–Richardson coefficient: We design an algorithm for the exact computation of \(c_{\lambda ,\mu }^{\nu }\) with running time \(\mathcal {O}\big ((c_{\lambda ,\mu }^{\nu })^2 \cdot {\textsf {poly}}(n)\big )\), where \(\lambda \), \(\mu \), and \(\nu \) are partitions of length at most *n*. Moreover, we introduce an algorithm for deciding whether \(c_{\lambda ,\mu }^{\nu } \ge t\) whose running time is \(\mathcal {O}\big (t^2 \cdot {\textsf {poly}}(n)\big )\). Even the existence of a polynomial-time algorithm for deciding whether \(c_{\lambda ,\mu }^{\nu } \ge 2\) is a nontrivial new result on its own. Our insights also lead to the proof of a conjecture by King et al. (Symmetry in physics. American Mathematical Society, Providence, 2004), stating that \(c_{\lambda ,\mu }^{\nu }=2\) implies \(c_{M\lambda ,M\mu }^{M\nu } = M+1\) for all \(M \in \mathbb {N}\). Here, the stretching of partitions is defined componentwise.

## Keywords

Littlewood–Richardson coefficient Hive model Efficient algorithms Flows in networks## Mathematics Subject Classification

05E10 22E46 90C27## Notes

### Acknowledgments

This research was conducted at the University of Paderborn. I benefitted tremendously from the long, intense, and invaluable discussions with my Ph.D. advisor Peter Bürgisser. I thank the Deutsche Forschungsgemeinschaft for their financial support (DFG-Grants BU 1371/3-1 and BU 1371/3-2). Furthermore, I thank an anonymous reviewer for his/her dedication to read this paper in detail and for giving valuable suggestions concerning its exposition.

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