We present HelioLinC, a novel approach to the minor planet linking problem. Our heliocentric transformation-and-propagation algorithm clusters tracklets at common epochs, allowing for the efficient identification of tracklets that represent the same minor planet. This algorithm scales as { \mathcal O }(N{log}N) with the number of tracklets N, a significant advance over standard methods, which scale as { \mathcal O }({N}3). This overcomes one of the primary computational bottlenecks faced by current and future asteroid surveys. We apply our algorithm to the Minor Planet Center’s Isolated Tracklet File, establishing orbits for more than 200,000 new minor planets. A detailed analysis of the influence of false detections on the efficiency of our approach, along with an examination of detection biases, will be presented in future work.
