“The Universe is a big place” is easily the biggest understatement of the century.
If you could travel seven and a half times around the Earth in one second and with that same speed travel in one direction for 13.6 billion years, you would have reached the place where the furthest objects that we can see today were when the light we receive now, left those objects.
Finding distance to stars and other celestial bodies has been a challenge throughout the history of astronomy. Some methods go back a long way in time, such as the ones developed by the Greek astronomer Hipparchus (around 150 BCE), who determined the distance to the Moon with a method we now call parallax.
Within our Solar system the most common technique to measure distance nowadays is radar in various frequencies in the Electro-Magnetic spectrum. We know the orbits of planets, moons and even asteroids so accurately that we do not have many problems in knowing how far away any object is at any given time. That is why we can fly spacecraft into the far corners of our Solar system without too much of a problem as far as navigation is concerned.
In this EBook we will concentrate on distances outside our Solar system. We will find out that measuring distance at various scales of the Universe is far from trivial. Actually, measuring distance in deep space is arguably the biggest practical problem in astronomy today.
Most methods that we use, have been developed over the last two centuries and are the result of countless nights of systematic observations by many astronomers, and what we could call old-fashioned detective work, to find relationships and physical properties that somehow relate to distance. That research is on-going and we still cannot say that we have a consistent and accurate picture of the true scale of the Universe.
Contemporary methods to determine distance outside our Solar system can be separated in three main groups:
- geometrical methods based on parallax,
- optical methods based on the star’s luminosity,
- cosmological redshift and independent techniques.
In this module we will discuss the most commonly used methods in each of these groups.