201.9. MPCORB table

201.9. MPCORB table¶

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Last verified to run: 2025-09-02
Repository: github.com/lsst/tutorial-notebooks

Learning objective: To understand the contents of the MPCORB table and how to access it.

LSST data products: MPCORB

Packages: lsst.rsp

Credit: Originally developed by the Rubin Community Science team. Please consider acknowledging them if this notebook is used for the preparation of journal articles, software releases, or other notebooks.

Get Support: Everyone is encouraged to ask questions or raise issues in the Support Category of the Rubin Community Forum. Rubin staff will respond to all questions posted there.

1. Introduction¶

The MPCORB table contains orbit information from the Minor Planet Center (MPC) for all known solar system objects, including detections and discoveries made by Rubin. It includes the ssObjectId for each unique Solar System object and MPC-style orbit information.

• TAP table name: dp1.MPCORB
• columns: 10
• rows: 1,425,362

Related tutorials: The TAP data access services are demonstrated in the 100-level "How to" tutorials.

1.1. Import packages¶

Import standard python package numpy.

From the lsst package, import modules for the TAP service and the butler.

In [1]:

import matplotlib.pyplot as plt
from lsst.rsp import get_tap_service

1.2. Define parameters and functions¶

Create an instance of the TAP service, and assert that it exists.

In [2]:

service = get_tap_service("tap")
assert service is not None

2. Schema (columns)¶

To browse the table schema visit the Rubin schema browser, or use the TAP service via the Portal Aspect or as demonstrated in Section 2.1.

2.1. Retrieve table schema¶

To retrieve the table schema, define a query for the schema columns of the MPCORB table and run the query job.

In [3]:

query = "SELECT column_name, datatype, description, unit " \
        "FROM tap_schema.columns " \
        "WHERE table_name = 'dp1.MPCORB'"
job = service.submit_job(query)
job.run()
job.wait(phases=['COMPLETED', 'ERROR'])
print('Job phase is', job.phase)
if job.phase == 'ERROR':
    job.raise_if_error()

Job phase is COMPLETED

Retrieve the query results and display them as an astropy table with the to_table() attribute.

In [4]:

assert job.phase == 'COMPLETED'
results = job.fetch_result().to_table()
results

Out[4]:

Table length=10

column_name	datatype	description	unit
str64	str64	str512	str64
e	double	MPCORB: Orbital eccentricity
epoch	double	MPCORB: Epoch (in MJD, .0 TT)	d
incl	double	MPCORB: Inclination to the ecliptic, J2000.0 (degrees)	deg
mpcDesignation	char	MPCORB: Number or provisional designation (in packed form)
mpcH	float	MPCORB: Absolute magnitude, H	mag
node	double	MPCORB: Longitude of the ascending node, J2000.0 (degrees)	deg
peri	double	MPCORB: Argument of perihelion, J2000.0 (degrees)	deg
q	double	MPCORB: Perihelion distance (AU)	AU
ssObjectId	long	LSST unique identifier (if observed by LSST)
t_p	double	MPCORB: MJD of pericentric passage	d

The table displayed above has been truncated.

Option to print every column name as a list.

In [5]:

# for col in results['column_name']:
#     print(col)

Delete the job, but not the results.

In [6]:

del query
job.delete()

2.2. Key Columns¶

Of the 10 columns of the MPCORB table, a few are the most commonly used.

2.2.1. Solar System Object Id¶

The long integer that uniquely identifies each Solar System object.

• ssObjectId

2.2.2. MPC designation¶

The object number or provisional designation (unpacked format):

• mpcDesignation

2.2.3. Orbital elements¶

The osculating orbital elements:

• q, e, incl, peri, node

The semimajor axis does not appear as a column in the MPCORB table, but it can be computed using the perihelion and eccentricity with the following expression: a = q*(1-e).

3. Data access¶

The MPCORB table is only available via the TAP service.

3.1. TAP (Table Access Protocol)¶

The MPCORB table is stored in Qserv and accessible via the TAP services using ADQL queries.

3.1.1. Demo query¶

Define a query to return the three columns from Section 2.3.

In [7]:

query = "SELECT ssObjectId, mpcDesignation, q, e, incl "\
        "FROM dp1.MPCORB " \
        "ORDER BY ssObjectId ASC "
job = service.submit_job(query)
job.run()
job.wait(phases=['COMPLETED', 'ERROR'])
print('Job phase is', job.phase)
if job.phase == 'ERROR':
    job.raise_if_error()

Job phase is COMPLETED

Fetch the results as an astropy table.

In [8]:

assert job.phase == 'COMPLETED'
results = job.fetch_result().to_table()
print(len(results))

1425363

Option to display the table.

In [9]:

# results

In [10]:

job.delete()
del results

3.1.2. Joinable tables¶

The MPCORB table can be joined to the SSObject table on the column ssObjectId.

The SSObject table contains linked Solar System objects (groupings of difference image detections) from Rubin. The DP1 release SSObject table contains 430 unique Solar System objects detected by Rubin.

The following query joins the MPCORB and SSObject tables. Columns returned include the MPCORB and SSObject unique identifiers, the MPC designation, orbital elements, and the number of observations and discovery submission date from the SSObject table.

In [11]:

query = "SELECT mpc.ssObjectId, mpc.mpcDesignation, "\
        "mpc.q, mpc.e, mpc.incl, "\
        "sso.numObs, sso.discoverySubmissionDate "\
        "FROM dp1.MPCORB AS mpc " \
        "JOIN dp1.SSObject AS sso ON mpc.ssObjectId = sso.ssObjectId " \
        "ORDER BY mpc.ssObjectId ASC"
job = service.submit_job(query)
job.run()
job.wait(phases=['COMPLETED', 'ERROR'])
print('Job phase is', job.phase)
if job.phase == 'ERROR':
    job.raise_if_error()

Job phase is COMPLETED

In [12]:

assert job.phase == 'COMPLETED'
results = job.fetch_result().to_table()
print(len(results))

431

Option to display the table.

In [13]:

# results

Plot the semimajor axis versus eccentricity and a histogram of the number of observations for each DP1 Solar System object.

In [14]:

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(9, 4))

ax1.scatter((results['q']/(1-results['e'])), results['e'], s=0.5)
ax2.hist(results['numObs'])

ax1.set_xlabel('Semimajor axis (au)')
ax1.set_ylabel('Eccentricity')
ax2.set_xlabel('Number of observations')

plt.show()

Figure 1: Semimajor axis versus eccentricity and a histogram of the number of observations for each DP1 Solar System object.

Clean up.

In [15]:

job.delete()
del results

In [ ]: