Datasets:

juliensimon
/

yarkovsky-nea-drifts

asteroid_number float64 1.57k 527k ⌀	name large_stringlengths 3 15	name_flag large_stringclasses 7 values	semimajor_axis_au float64 0.64 2.68	eccentricity float64 0.03 0.91	diameter_flag large_stringclasses 2 values	diameter_km float64 0.01 8.48	n_optical_observations int64 126 12.1k	n_radar_observations int64 0 51	drift_orbit_fit_au_per_myr float64 -381.69 56	drift_orbit_fit_uncertainty_au_per_myr float64 0.4 169	drift_orbit_fit_pvalue float64 0 1	drift_resampled_au_per_myr float64 -319.58 48.6 ⌀	drift_resampled_uncertainty_au_per_myr float64 0.1 157 ⌀	drift_resampled_pvalue float64 0 0.05 ⌀	drift_significance_sigma float64 -1 40	yarkovsky_efficiency float64 0.01 3.47	first_observation_year int64 1.93k 2.01k	last_observation_year int64 2k 2.02k
1,566	Icarus	null	1.08	0.83	null	1	2,372	16	-4.47	0.4	0	-4.84	0.4	0	37.1	0.03	1,949	2,019
1,620	Geographos	null	1.25	0.34	null	2.56	8,890	7	-0.68	0.5	0.003	-1.02	0.5	0.000002	18.7	0.05	1,951	2,019
1,685	Toro	null	1.37	0.44	null	3.4	5,050	9	-1.52	0.4	0	-1.57	0.4	0	33	0.1	1,948	2,019
1,864	Daedalus	S	1.46	0.61	null	3.7	4,368	1	-11.29	5.9	0.00006	-11.67	5.8	0.00003	3	0.56	1,971	2,019
1,865	Cerberus	null	1.08	0.47	null	1.2	3,396	0	-3.75	1.8	0.000003	null	null	null	11.5	0.07	1,971	2,019
1,866	Sisyphus	B	1.89	0.54	null	8.48	7,796	1	-2.26	2.5	0.02	-2.26	2.5	0.02	4.3	0.35	1,955	2,019
1,916	Boreas	null	2.27	0.45	null	3.5	2,892	0	-4.86	2.4	0.000007	null	null	null	7.7	0.39	1,953	2,019
2,062	Aten	null	0.97	0.18	null	1.1	1,922	7	-6.06	0.9	0	-5.34	0.7	0	24.1	0.1	1,955	2,019
2,063	Bacchus	null	1.08	0.35	null	1.02	1,292	12	-6.97	2.1	0	-6.22	1.9	0	17.3	0.14	1,977	2,016
2,100	Ra-Shalom	null	0.83	0.44	null	2.3	3,724	9	-3.27	0.9	0	-2.04	0.6	0	24.8	0.12	1,975	2,019
2,101	Adonis	null	1.87	0.76	null	0.6	238	5	-25.43	10.7	0.001	-17.51	9.3	0.01	6.5	0.1	1,936	2,018
2,201	Oljato	null	2.17	0.71	null	1.8	1,950	5	16.28	8.5	0.0001	15.11	7.2	0.00003	2.8	0.47	1,931	2,019
2,202	Pele	S	2.29	0.51	*	1.35	500	0	25.07	14.3	0.0003	null	null	null	3.5	0.65	1,972	2,018
2,340	Hathor	null	0.84	0.45	null	0.3	902	7	-17.39	0.7	0	-17.61	0.6	0	40	0.09	1,976	2,019
3,103	Eger	null	1.4	0.35	null	1.5	6,534	4	-0.76	2.3	0.5	-2.83	2.2	0.004	5.2	0.08	1,982	2,019
3,200	Phaethon	null	1.27	0.89	null	6.25	10,590	8	-9.01	2.8	0	-9.57	2.1	0	4.6	0.23	1,983	2,019
3,361	Orpheus	null	1.21	0.32	null	0.3	1,692	0	7.74	1.2	0	null	null	null	22.3	0.04	1,982	2,018
3,362	Khufu	null	0.99	0.47	null	0.7	518	0	-17.87	11.8	0.01	null	null	null	2.9	0.17	1,984	2,004
3,551	Verenia	null	2.09	0.49	null	0.9	928	0	-13.11	9.4	0.02	null	null	null	3.8	0.22	1,983	2,019
3,753	Cruithne	null	1	0.51	null	2.07	1,500	0	-5.14	3.4	0.001	null	null	null	7.7	0.13	1,973	2,019
3,908	Nyx	null	1.93	0.46	null	1	3,408	16	6.59	2.6	0	7.1	1.6	0	6.3	0.1	1,980	2,019
4,034	Vishnu	null	1.06	0.44	null	0.42	960	1	-38.61	9.2	0	-33.04	7.9	0	4.9	0.2	1,986	2,015
4,179	Toutatis	null	2.54	0.63	null	5.4	12,070	51	-9.52	4	0	-2.15	0.3	0	2	0.19	1,934	2,019
4,197	Morpheus	null	2.3	0.77	null	1.8	1,584	6	12.81	8	0.003	13.35	8	0.002	3.2	0.35	1,954	2,019
4,581	Asclepius	null	1.02	0.36	*	0.26	660	4	-29.91	11.6	0	-20.37	5.4	0	3.2	0.08	1,989	2,019
4,660	Nereus	null	1.49	0.36	null	0.33	1,338	32	4.26	5	0.08	7.68	3.4	0.000003	7.3	0.05	1,981	2,019
4,688	1980 WF	null	2.24	0.51	null	0.6	416	0	-7	5.5	0.05	null	null	null	9.6	0.06	1,980	2,011
4,769	Castalia	null	1.06	0.48	null	1.4	574	15	-5.1	3	0.008	-6.14	2.8	0.0008	10.5	0.12	1,989	2,016
5,011	Ptah	null	1.64	0.5	*	1.86	1,198	0	-14.72	6.4	0.00005	null	null	null	6.3	0.45	1,960	2,018
5,131	1990 BG	S	1.49	0.57	T	3.44	3,024	0	-16.21	6.5	0.000001	null	null	null	2	0.87	1,978	2,019
5,189	1990 UQ	null	1.55	0.48	*	0.98	1,874	1	-12.22	9.4	0.002	-12.25	9.4	0.002	2.3	0.2	1,990	2,019
5,693	1993 EA	null	1.27	0.59	*	1.7	3,242	0	-6.35	4.3	0.004	null	null	null	3.4	0.14	1,984	2,019
5,869	Tanith	S	1.81	0.32	*	1.29	1,176	0	-19.22	14.5	0.008	null	null	null	2.1	0.51	1,977	2,019
6,239	Minos	null	1.15	0.41	*	0.71	1,762	3	6.79	3.7	0.0003	7.98	3.5	0.00001	7	0.09	1,983	2,015
6,456	Golombek	S	2.19	0.41	*	2.35	2,340	0	-14.08	4.9	0	null	null	null	4.7	0.7	1,979	2,019
6,489	Golevka	null	2.49	0.61	null	0.53	1,934	20	-13.44	12.1	0.06	-5.17	0.7	0	1.8	0.05	1,991	2,015
7,336	Saunders	null	2.31	0.48	T	0.52	1,786	0	12.44	3.3	0	null	null	null	6.8	0.18	1,982	2,018
7,341	1991 VK	null	1.84	0.51	null	0.98	3,040	13	-1.21	3.3	0.4	-2.57	0.8	0	4	0.06	1,981	2,018
7,482	1994 PC1	null	1.35	0.33	null	1.05	1,350	1	12.75	8.4	0.005	13.12	8.4	0.003	3.4	0.27	1,974	2,019
7,822	1991 CS	null	1.12	0.16	null	1.6	2,272	4	8.03	5.6	0.004	6.57	5.5	0.02	3.7	0.2	1,991	2,016
7,888	1993 UC	B, S	2.44	0.66	null	2.3	2,330	5	-37.71	26.6	0.005	-37.79	26.5	0.005	0.5	1.3	1,989	2,019
7,889	1994 LX	null	1.26	0.35	null	1.68	3,596	4	-3.92	5.3	0.1	-6.15	5.2	0.01	2.3	0.14	1,977	2,019
8,176	1991 WA	null	1.57	0.64	T	1.48	1,304	0	8.6	7.1	0.05	null	null	null	2.8	0.16	1,991	2,019
9,162	Kwiila	null	1.5	0.6	null	1.13	1,012	0	-7.06	7.2	0.05	null	null	null	5.6	0.11	1,987	2,019
9,856	1991 EE	null	2.24	0.63	null	1	1,536	4	11.84	10.2	0.005	11.46	10.1	0.006	2.2	0.18	1,991	2,019
10,302	1989 ML	null	1.27	0.14	T	0.49	1,026	0	19.49	3.7	0	null	null	null	4.4	0.14	1,989	2,019
10,563	Izhdubar	null	1.01	0.27	T	1.55	1,092	0	17.09	7.7	0.0004	null	null	null	3.4	0.42	1,991	2,019
11,398	1998 YP11	null	1.72	0.39	null	1.32	5,716	0	-5.17	3.6	0.0008	null	null	null	3	0.13	1,983	2,019
11,405	1999 CV3	S	1.46	0.39	null	3.62	4,692	0	7.54	5.3	0.004	null	null	null	2.6	0.66	1,978	2,019
11,500	Tomaiyowit	null	1.08	0.36	null	0.74	2,010	1	-5.18	2.3	0.000004	-5.45	2.3	0.000001	8	0.07	1,989	2,019
11,885	Summanus	null	1.7	0.47	null	1.3	542	0	-17.82	10.5	0.00002	null	null	null	3.7	0.4	1,990	2,019
14,402	1991 DB	null	1.71	0.4	null	0.6	1,214	0	-6.65	3.1	0.00002	null	null	null	9.3	0.04	1,991	2,019
15,745	Yuliya	null	1.72	0.26	T	1.04	2,144	0	-6	4.8	0.01	null	null	null	5	0.14	1,982	2,019
17,511	1992 QN	null	1.19	0.36	T	1.23	2,526	1	3.36	3.4	0.03	3.36	3.4	0.03	4.7	0.05	1,992	2,019
18,736	1998 NU	S	2.35	0.49	T	2.46	3,124	0	-15.42	8.3	0.000008	null	null	null	4.2	0.76	1,954	2,019
31,221	1998 BP26	null	1.72	0.26	*	1.29	1,912	0	-17.06	6.1	0	null	null	null	2.5	0.46	1,998	2,019
33,342	1998 WT24	null	0.72	0.42	null	0.43	3,528	16	-10.03	8.3	0.006	-16.02	2.4	0	2.2	0.08	1,998	2,019
37,655	Illapa	null	1.48	0.75	*	0.93	1,088	2	-11.67	3.6	0	-10.87	3.4	0	9	0.09	1,994	2,019
41,429	2000 GE2	null	1.59	0.56	null	0.2	670	0	-31.29	14.9	0.0008	null	null	null	2.5	0.1	1,998	2,018
52,387	Huitzilopochtli	null	1.28	0.19	null	0.89	1,086	3	-22.51	16.4	0.006	-22.18	16.3	0.006	3.3	0.37	1,993	2,019
54,509	YORP	D	1	0.23	*	0.1	1,084	5	-19.97	47.6	0.3	-33.85	13.3	0	0.7	0.06	2,000	2,005
65,679	1989 UQ	null	0.92	0.26	null	0.92	1,382	0	-19.16	4.9	0	null	null	null	5.9	0.26	1,954	2,017
65,690	1991 DG	null	1.43	0.36	*	0.56	518	0	-32.45	13.1	0.00003	null	null	null	3.7	0.32	1,991	2,018
65,706	1992 NA	null	2.4	0.56	T	2.92	1,066	0	11.29	10	0.03	null	null	null	2.5	0.33	1,992	2,019
65,733	1993 PC	null	1.15	0.47	*	0.78	1,394	0	-6.71	4.9	0.005	null	null	null	4.4	0.07	1,992	2,019
66,146	1998 TU3	null	0.79	0.48	null	2.86	2,270	1	-1.6	4.5	0.4	-5.6	3.9	0.002	4.1	0.19	1,982	2,019
66,391	Moshup	B	0.64	0.69	null	1.32	7,770	37	-5.23	2.9	0.000001	-5.73	2.2	0	2.7	0.04	1,998	2,019
66,400	1999 LT7	null	0.86	0.57	null	0.41	602	0	-38.25	5.3	0	null	null	null	5.4	0.17	1,987	2,018
68,950	2002 QF15	null	1.06	0.34	null	1.65	5,124	13	-6.18	5	0.006	-4.72	1.1	0	3	0.12	1,955	2,019
85,770	1998 UP1	null	1	0.35	*	0.28	976	0	-16.56	5.6	0.000001	null	null	null	5.2	0.07	1,990	2,016
85,774	1998 UT18	null	1.4	0.33	null	0.94	1,338	8	-3.21	3.8	0.1	-2.39	0.6	0	5.7	0.02	1,989	2,019
85,953	1999 FK21	null	0.74	0.7	null	0.59	2,272	0	-11.64	2.1	0	null	null	null	5.6	0.06	1,971	2,018
85,989	1999 JD6	null	0.88	0.63	null	1.46	5,412	15	-6.97	3.7	0.00001	-5.98	3.6	0.0002	3.8	0.12	1,990	2,019
85,990	1999 JV6	null	1.01	0.31	null	0.45	2,096	15	-11.4	3.9	0	-14.1	1	0	4.3	0.17	1,999	2,019
87,684	2000 SY2	null	0.86	0.64	*	2.14	1,310	0	-14.35	7.1	0.0003	null	null	null	4.5	0.29	1,977	2,019
88,254	2001 FM129	null	1.18	0.63	null	0.8	1,400	2	-10.55	5.8	0.0004	-11.1	5.6	0.0001	5.3	0.1	1,978	2,019
88,959	2001 TZ44	S	1.72	0.56	*	1.18	764	0	-29.45	15.1	0.0004	null	null	null	2.1	0.53	2,001	2,019
96,590	1998 XB	null	0.91	0.35	null	0.88	4,764	15	-0.05	4.2	1	2.3	1.1	0.000008	2.7	0.03	1,992	2,019
99,907	1989 VA	null	0.73	0.59	null	1.4	1,546	0	12.01	2.5	0	null	null	null	9	0.22	1,989	2,019
101,955	Bennu	null	1.13	0.2	null	0.49	1,148	29	-12.17	4.2	0	-19.03	0.1	0	6.7	0.08	1,999	2,018
136,582	1992 BA	null	1.34	0.07	*	0.37	460	0	-20.4	5.9	0	null	null	null	5.3	0.15	1,992	2,017
136,617	1994 CC	B	1.64	0.42	*	1.02	1,294	27	-10.92	14.2	0.2	-13.95	13.3	0.05	2.1	0.26	1,988	2,019
136,793	1997 AQ18	null	1.15	0.47	T	1.22	740	0	-22.79	5.3	0	null	null	null	3.8	0.21	1,997	2,019
136,818	Selqet	null	0.94	0.35	*	0.59	1,274	0	8.4	3.2	0.000006	null	null	null	8.3	0.07	1,997	2,018
136,993	1998 ST49	B	2.31	0.6	T	1.02	1,050	7	26.08	10.1	0.000001	27.22	9.9	0	2.4	0.47	1,998	2,019
137,084	1998 XS16	null	1.21	0.5	null	1.23	3,110	0	-17.79	7	0	null	null	null	2.2	0.31	1,994	2,019
137,125	1999 CT3	S	1.43	0.13	*	0.65	434	0	-56.44	20.9	0.000001	null	null	null	2.2	0.73	1,999	2,018
137,805	1999 YK5	null	0.83	0.56	null	2.24	2,188	0	-6.27	5.3	0.01	null	null	null	3.1	0.11	1,999	2,019
137,924	2000 BD19	null	0.88	0.89	null	0.97	1,304	5	-22.1	13.5	0.0003	-26.17	10.4	0	1.7	0.08	1,997	2,019
138,175	2000 EE104	null	1	0.29	*	0.31	1,870	3	-33.84	7.2	0	-34.59	7.1	0	4.3	0.17	1,999	2,019
138,404	2000 HA24	null	1.14	0.32	*	0.54	632	0	12.19	2.8	0	null	null	null	13.2	0.11	1,982	2,017
138,852	2000 WN10	null	1	0.3	*	0.32	1,920	0	16.25	3.7	0	null	null	null	5.6	0.08	2,000	2,019
138,911	2001 AE2	null	1.35	0.08	T	0.51	1,134	0	-12.3	5.8	0.0002	null	null	null	5.5	0.13	1,984	2,017
139,622	2001 QQ142	S	1.42	0.31	T	0.66	938	0	-31.92	14.4	0.000002	null	null	null	2.5	0.54	2,001	2,019
141,018	2001 WC47	null	1.4	0.24	*	0.59	2,962	4	-5.41	7.4	0.07	-7.49	7	0.007	2	0.08	1,991	2,019
141,498	2002 EZ16	null	0.92	0.57	*	0.74	624	0	-12.01	11.2	0.03	null	null	null	3.3	0.1	1,995	2,019
141,531	2002 GB	null	0.99	0.53	null	0.3	1,396	0	23.5	12.5	0.001	null	null	null	2.1	0.09	2,002	2,019
152,563	1992 BF	null	0.91	0.27	null	0.27	712	0	-13.99	1.3	0	null	null	null	20.3	0.11	1,953	2,018
152,671	1998 HL3	null	1.13	0.37	null	0.3	632	0	-31.92	9.3	0	null	null	null	3.9	0.15	1,998	2,018
152,742	1998 XE12	null	0.88	0.74	null	0.41	666	0	14.11	10.9	0.03	null	null	null	2.6	0.04	1,995	2,019

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Yarkovsky Drift Catalog for Near-Earth Asteroids

NASA's DART spacecraft approaching the Didymos asteroid system

Credit: NASA/Johns Hopkins APL

Part of a dataset collection on Hugging Face.

Dataset description

Direct measurements of the Yarkovsky semimajor-axis drift for 247 Near-Earth Asteroids — VizieR J/AJ/159/92 from Greenberg et al. (2020), AJ 159, 92.

The Yarkovsky effect is a thermal radiation force that slowly modifies an asteroid's orbit: sunlight absorbed on the dayside and reradiated from the rotating afternoon side produces a small net thrust. Over millions of years this drift accumulates to many millions of kilometers, delivering main-belt asteroids onto Earth-crossing orbits, dispersing collisional families, and shifting impact-probability calculations for hazardous NEAs (Bennu, Apophis, and 1950 DA are the canonical operationally critical cases). Direct detection requires high-precision orbit fits over decades of optical astrometry, ideally anchored by radar ranging at multiple apparitions; only a few hundred NEAs currently meet this threshold.

Each row in this dataset records one NEA with its orbital elements, diameter, observation count (optical + radar), and two independent drift estimates — a direct least-squares orbit fit and a bootstrap-resampled fit that cross-checks against systematic astrometric bias — together with their uncertainties, p-values, detection significance, and an empirical Yarkovsky efficiency parameter that flags physically implausible solutions.

This dataset complements juliensimon/jpl-small-body-database (orbital elements for the full small-body population), juliensimon/sentry-impact-risk (NEAs with non-zero Earth impact probability where Yarkovsky drift matters most), juliensimon/neowise-asteroid-properties (NEOWISE thermal-IR diameters that anchor Yarkovsky efficiency estimates), and juliensimon/nesvorny-asteroid-families (Yarkovsky-driven family dispersion).

This dataset is suitable for tabular classification, tabular regression tasks.

Schema

Column	Type	Description	Sample	Null %
`asteroid_number`	float64	Permanent IAU minor-planet number (e.g. 1566 for Icarus, 1620 for Geographos); only numbered NEAs are included since orbit determination requires long-baseline astrometry	1566.0	1.2%
`name`	str	Asteroid name where assigned (e.g. 'Icarus', 'Geographos', 'Bennu'); blank for numbered-but-unnamed objects	Icarus	0.0%
`name_flag`	str	Reference flag indicating the source of the name designation	S	74.5%
`semimajor_axis_au`	float64	Heliocentric semimajor axis (au); osculating orbital element at the epoch of the underlying orbit solution	1.08	0.0%
`eccentricity`	float64	Orbital eccentricity (dimensionless, 0 to <1); the population includes the Apollo, Amor, Aten, and Atira NEA classes	0.83	0.0%
`diameter_flag`	str	Reference flag indicating the source of the diameter estimate	*	44.1%
`diameter_km`	float64	Equivalent spherical diameter (km); compiled from albedo-corrected absolute magnitudes or direct radar/IR measurements where available	1.0	0.0%
`n_optical_observations`	int64	Number of optical astrometric observations used in the orbit fit	2372	0.0%
`n_radar_observations`	int64	Number of radar astrometric observations used in the orbit fit; radar measurements anchor the orbit at the 10-meter range-precision level	16	0.0%
`drift_orbit_fit_au_per_myr`	float64	Yarkovsky semimajor-axis drift rate da/dt from the direct orbit fit (10^-4 au per million years); negative for retrograde rotators (drift inward), positive for prograde (drift outward)	-4.47	0.0%
`drift_orbit_fit_uncertainty_au_per_myr`	float64	1-sigma uncertainty on the orbit-fit drift rate (10^-4 au/Myr)	0.4	0.0%
`drift_orbit_fit_pvalue`	float64	Two-tailed p-value for the orbit-fit drift detection; lower values indicate higher detection significance	1e-16	0.0%
`drift_resampled_au_per_myr`	float64	Yarkovsky drift rate from the bootstrap-resampled orbit fit (10^-4 au/Myr); cross-check against orbit-fit value to mitigate astrometric bias	-4.84	63.2%
`drift_resampled_uncertainty_au_per_myr`	float64	1-sigma uncertainty on the resampled drift rate (10^-4 au/Myr)	0.4	63.2%
`drift_resampled_pvalue`	float64	Two-tailed p-value for the resampled drift detection	1e-16	63.2%
`drift_significance_sigma`	float64	Detection significance of the Yarkovsky drift in standard deviations; values >= 3 are considered confident detections	37.1	0.0%
`yarkovsky_efficiency`	float64	Empirical Yarkovsky efficiency xi (dimensionless), the ratio of observed drift to the maximum drift achievable by a perfectly absorbing-and-reradiating asteroid of the same size; xi values >> 1 are unphysical and flag candidate non-Yarkovsky perturbations	0.03	0.0%
`first_observation_year`	int64	Year of the earliest astrometric observation used in the fit; longer baselines yield more precise drift estimates	1949	0.0%
`last_observation_year`	int64	Year of the latest astrometric observation used in the fit	2019	0.0%

Quick stats

247 Near-Earth Asteroids with direct Yarkovsky drift measurements
167 confident detections at >= 3 sigma (88 at >= 5 sigma)
175 retrograde rotators (inward-drifting) + 72 prograde rotators (outward-drifting)
Diameter span: 0.01 to 8.5 km
Observation baselines extend up to 88 years — necessary for unambiguous Yarkovsky detection

Usage

from datasets import load_dataset

ds = load_dataset("juliensimon/yarkovsky-nea-drifts", split="train")
df = ds.to_pandas()

from datasets import load_dataset
import matplotlib.pyplot as plt

df = load_dataset("juliensimon/yarkovsky-nea-drifts", split="train").to_pandas()

# Drift rate vs diameter — Yarkovsky scales as 1/diameter for spherical bodies
mask = (df["diameter_km"].notna()
        & df["drift_orbit_fit_au_per_myr"].notna()
        & (df["drift_significance_sigma"] >= 3))
fig, ax = plt.subplots(figsize=(8, 6))
ax.errorbar(df.loc[mask, "diameter_km"],
            df.loc[mask, "drift_orbit_fit_au_per_myr"],
            yerr=df.loc[mask, "drift_orbit_fit_uncertainty_au_per_myr"],
            fmt="o", alpha=0.6)
ax.axhline(0, color="grey", linestyle="--")
ax.set_xscale("log")
ax.set_xlabel("Diameter (km)")
ax.set_ylabel("da/dt (10$^{-4}$ au / Myr)")
ax.set_title("Yarkovsky drift inversely scales with NEA size")
plt.tight_layout()
plt.show()

# Highest-confidence inward drifters — most relevant to long-term impact risk
top = df[df["drift_significance_sigma"] >= 5].nsmallest(15, "drift_orbit_fit_au_per_myr")
print(top[["asteroid_number", "name", "diameter_km",
           "drift_orbit_fit_au_per_myr", "drift_significance_sigma"]])

Data source

https://cdsarc.cds.unistra.fr/viz-bin/cat/J/AJ/159/92

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About the author

Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.

Citation

@dataset{yarkovsky_nea_drifts,
  title = {Yarkovsky Drift Catalog for Near-Earth Asteroids},
  author = {juliensimon},
  year = {2026},
  url = {https://huggingface.co/datasets/juliensimon/yarkovsky-nea-drifts},
  publisher = {Hugging Face}
}

License

VizieR Scientific-Use Terms

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Collection including juliensimon/yarkovsky-nea-drifts

Asteroids and Small Bodies

Collection

JPL SBDB, NEO close approaches, Sentry impact risk, asteroid taxonomy, families, lightcurves, mining, comets, and meteoroids. • 20 items • Updated 26 days ago