Backend
On composition and decomposition operations for vector spaces, graphs and matroids
arXiv eess.SY0 views
arXiv:2305.16354v3 Announce Type: replace-cross Abstract: In this paper, we study the ideas of composition and decomposition in the context of vector spaces, graphs and matroids. For vector spaces $\V_{AB},$ treated as collection of row vectors, with specified column set $A\uplus B,$ we define $\V_{SP}\lrarv \V_{PQ}, S\cap Q= \emptyset, $ to be the collection of all vectors $(f_S,f_Q)$ such that $(f_S,f_P)\in \V_{SP}, (f_P,f_Q)\in \V_{PQ}$. An analogous operation $\G_{SP}\lrarg \G_{PQ}\equivd \G_{PQ}$ can be defined in relation to graphs $\G_{SP}, \G_{PQ},$ on edge sets $S\uplus P, P\uplus Q,$ respectively in terms of an overlapping subgraph $\G_P$ which gets deleted in the right side graph (see for instance the notion of $k-sum$ \cite{oxley}). For matroids we define the `linking' $\M_{SP}\lrarm \M_{PQ} \equivd (\M_{SP}\vee \M_{PQ})\times (S\uplus Q)$, denoting the contraction operation by '$\times$'. In each case, we examine how to minimize the size of the `overlap' set $P,$ without affecting the right side entity. In the case of vector spaces, there is a polynomial time algorithm for achieving the minimum, which we present. Similar ideas work for graphs and for matroids under appropriate conditions. Next we consider the problem of decomposition. Here, in the case of vector spaces, the problem is to decompose $\V_{SQ}$ as $\V_{SP}\lrarv \V_{PQ},$ with minimum size $P.$ We give a polynomial time algorithm for this purpose. In the case of graphs and matroids we give a solution to this problem under certain restrictions.
Source:https://arxiv.org/abs/2305.16354PreviousProbe Sets for Nonlinear Kalman Filtering: Multi-Center Gains and Covariance RecalibrationNextCongestion-Aware Charging Coordination for Electric Ride-Hailing Fleets under Stochastic Demand
Related posts
The Building Is a System: What Software Engineers Can Learn from Construction Site Failures
0dev.to

Part 4: When the Screen Changes Silently: Live Regions, Headings and Focus in Compose
0dev.to
FlatCake: Why Tiered KV Cache Storage Is Holding LLM Serving Back
0dev.to
Why Scrum is Not a Silver Bullet: 5 Structural Drawbacks and Fixes
0dev.to
Agentic Frameworks Compared: LangGraph, CrewAI & More
0dev.to
The Real-World Pain
0dev.to