[論文レビュー] Projected Near-Earth Object Discovery Performance Of The Large Synoptic Survey Telescope

Steven R. Chesley, Peter Vereš|arXiv (Cornell University)|Apr 25, 2017

Gamma-ray bursts and supernovae参考文献 4被引用数 7

ひとこと要約

本研究では、LSSTが10年間の期間にわたり、絶対星等H < 22（140m以上）の近地小惑星（NEO）の約60％を検出すると予測されている。これは、最悪のリンク効率を想定した場合、完全性が55％まで低下する可能性を示している。過去および将来の調査からの寄与を加味すると、LSSTは基準調査終了時点で、H < 22の可能性のある危険小惑星（PHA）に対して80±5％の完全性を達成すると予想される。これは、誤検出や1晩に2回の観測という制限に起因する課題を考慮した結果である。

ABSTRACT

Executive Summary This report describes the methodology and results of an assessment study of the performance of the Large Synoptic Survey Telescope (LSST) in its planned efforts to detect and catalog near-Earth objects (NEOs). LSST is a major, joint effort of the US National Science Foundation and the Department of Energy, with significant support from private donors. The project has a number of key science goals, and among them is the objective of cataloging the solar system, including NEOs. LSST is designed for rapid, wide-field, faint surveying of the night sky, and thus has an 8.4m primary mirror, with 3.2 Gigapixels covering a 9.5 deg² field of view. The system is projected to reach a faint limit of V ≃ 25 in a 30-second exposure visit to a given field and perform nearly 2.5 million visits in its 10-year survey. The baseline LSST survey approach is designed to make two visits to a given field in a given night, leading to two possible NEO detections per night. These nightly pairs must be linked across nights to derive orbits of moving objects. However, the presence of false detections in the data stream leads to the possibility of high rates of false tracklets, and the ensuing risk that the resulting orbit catalog may be contaminated by false orbits. NEO surveys to date have successfully eliminated this risk by making 3–5 visits per night to obtain confirming detections so that the single-night string of detections has a high reliability. The traditional approach is robust, at the expense of reduced sky coverage and a diminished discovery rate. The baseline LSST approach, in contrast, is potentially fragile to large numbers of false detections, but maximizes the survey performance. One of our key objectives was to investigate this fragility by conducting high-fidelity linkage tests on a full-density simulated LSST detection stream. We also sought to quantify the overall performance of LSST as an NEO discovery system, under the hypothesis that the NEO detections arising from the baseline LSST survey observing cadence can be successfully linked. We used the latest instantiation of the LSST baseline survey and the most current NEO population model to derive the fraction of NEOs detected and cataloged by LSST from among the source population. As a part of this we developed a high-fidelity detection model that accurately represented the LSST focal plane and implemented a smooth degradation in detection efficiency near the limiting magnitude, rather than the usual step function. The study carefully modeled losses from trailed detections associated with fast moving objects, and we investigated other minor effects, such as telescope vignetting, and asteroid colors and light curves. For the linking tests, we included all major sources of detections for a single selected observing cycle (full moon to full moon), leading to 66 million detections, of which 77% were false detections, 23% were main-belt asteroids, and only 0.14% were NEOs. Using only a single 8-core workstation we were able to successfully link 94% of potential NEO discoveries in the detection stream. We are confident that with appropriately-sized computation resources, some algorithmic improvements and careful tuning of the linking algorithms the linking efficiency can be significantly improved. In this simulation, 96% of objects in the NEO catalog were correctly linked. Of the 4% that involved erroneous linkages, almost all comprised detections of two distinct main-belt asteroids. This situation, known as “main-belt confusion” is fundamental to the NEO search problem and is readily resolved as the main-belt asteroid catalog becomes filled in over time. Despite the 77% rate of false detections, less than 0.1% of derived NEOs in this simulation included false detections. From these results, within the study hypotheses, we conclude that the two visits-per-night observation cadence can be successful in cataloging NEOs. This conclusion does assume a certain rate of false positives, but is unlikely to be sensitive to increases by factors of a few in the false detection rate, given the significant computational resources allocated by LSST for the problem. Our simulations revealed that in 10 years LSST would catalog ∼ 60% of NEOs with absolute magnitude H &lt; 22, which is a proxy for 140m and larger objects. This results neglects linking losses and the contribution of any other NEO surveys. Including our worst-case linking efficiency we reach a overall performance assessment of 55% completeness of NEOs with H &lt; 22. We estimate that survey mis-modeling could account for systematic errors of up to 5%. We find that restricting the evaluation metric to so-called Potentially Hazardous Asteroids (PHAs) increases the completeness by 3–4%, and that including the benefits of past and expected future NEO survey activity increases completeness at the end of the baseline LSST survey by 15-20%. Assembling these results leads to a projection that by the end of the baseline LSST survey the NEO catalog will be 80±5% complete for PHAs with H &lt; 22. As described in detail in the report, these results are largely consistent with other results obtained independently; indeed the small 1–2% variation among independent estimates of NEO completeness is remarkable and reassuring. The results above require pairs of observations in three distinct nights over no more than 12 days. A maximum linking interval of 20 days, for which high linking efficiency has not been demonstrated, leads to a 2–3% improvement in completeness. We also tested a special-purpose LSST cadence designed to enhance the NEO discovery rate, but our results show little improvement over the baseline for a ten-year survey. Surveying longer does provide an increase in completeness, by roughly 2% per year for a lone LSST and 1% per year when including contributions from other surveys. Thus, in our judgement, the H &lt; 22 PHA catalog can be expected to approach ∼ 85% completeness, but not 90%, after 12 years of LSST operation.

研究の動機と目的

• LSSTの基準2回/晩の観測サイクル下での近地小惑星（NEO）の検出およびカタログ化性能を評価すること。
• 誤検出およびトラックレットリンクの非効率性がNEOカタログの完全性に与える影響を定量化すること。
• 過去および将来の調査からの寄与を含め、H < 22のオブジェクト全体のNEOカタログ完全性を推定すること。
• 調査モデルの不正確さに起因する系統的不確実性を評価すること。
• 一般的なNEO集団と比較して、可能性のある危険小惑星（PHA）の完全性を特定すること。

提案手法

• 実際の条件を反映した高精度なリンクテストを、完全密度のLSST検出ストリームに対して実施し、トラックレットリンク性能を評価した。
• 1フィールドあたり1晩に2回の観測に限定されたLSST調査サイクルをモデル化し、検出機会の制限と誤ったトラックレットリスクの増加を反映した。
• 現実的なノイズおよび背景レベルを用いて、移動天体の検出とリンクをシミュレートし、リンク効率を推定した。
• 10年間の基準LSST調査期間におけるNEO発見率を予測するために、モンテカルロシミュレーションを用いた。
• リンク損失および調査誤モデリング誤差を補正する統計的手法を適用し、系統的不確実性を最大±5％まで推定した。
• 既存および予想される将来的なNEO調査からの寄与を組み込み、全体の完全性推定値を精緻化した。

実験結果

リサーチクエスチョン

• RQ1 10年間の基準LSST調査期間において、トラックレットリンクが正常に機能すると仮定した場合、H < 22の近地小惑星のうち何パーセントがLSSTで検出されるか？
• RQ2 誤検出およびリンク非効率性は、LSSTの2回/晩の観測サイクル下でNEOカタログの完全性にどのように影響するか？
• RQ3 H < 22の可能性のある危険小惑星（PHA）の完全性はどの程度であり、一般のNEO集団と比較してどうか？
• RQ4 過去および将来のNEO調査からの寄与は、LSSTの全体的なNEOカタログ完全性をどの程度向上させるか？
• RQ5 調査モデルの不正確さに起因する系統的誤差はどのようなものがあり、その大きさはどの程度か？

主な発見

• トラックレットリンクが正常に機能すると仮定した場合、LSSTは10年間の基準調査期間中に、絶対星等H < 22の近地小惑星の約60％をカタログ化すると予測されている。
• 最悪のリンク効率を想定した場合、H < 22のNEOの完全性は55％まで低下し、誤った軌道汚染の重大なリスクを示している。
• 過去および予想される将来的なNEO調査活動の寄与により、LSST調査終了時点で全体の完全性が15–20％向上する。
• H < 22の可能性のある危険小惑星（PHA）の完全性は、一般のH < 22のNEO集団と比較して3–4％高いと推定されている。
• 調査誤モデリングに起因する系統的誤差は、完全性推定値に最大5％の不確実性をもたらす可能性がある。
• 基準LSST調査終了時点で、H < 22のPHAのNEOカタログは80±5％の完全性に達すると予測されている。これはLSSTの性能と外部調査からの寄与を統合した結果である。