Gravitational Waves from Colliding Black Holes Prove Einstein’s Theory Right Again


The LIGO team officially announced at a media conference in the US that gravitational waves from a binary black hole merger were detected by two US-based Laser Interferometer Gravitational-wave Observatory (LIGO) detectors in September last year, and later in December 26.

A hundred years after Albert Einstein’s prediction, we have found evidence for the same twice. LIGO research is carried out by the LIGO Scientific Collaboration (LSC), a group of more than 1,000 scientists from universities around the United States and in 14 other countries, including India.

LIGO detectors at Hanford in Washington and at Livingston in Louisiana on December 26th, detected a signal from the coalescence of two black holes, with masses 14 and eight times the mass of Sun. They merged into a single, more massive, rapidly rotating black hole that is about 21 times the mass of Sun. The event took place 1.4 billion years ago, lasted in LIGO’s frequency band for about a second, and released about 1 solar mass worth of energy in that short period. For comparison, only a tiny fraction of the Sun’s mass gets converted to light in its entire lifetime, which is enough to keep the earth warm for billions of years, according to an official release issued by the LIGO scientists.

Many scientists in IPR, IUCAA and RRCAT are currently engaged in building a third LIGO detector in India, LIGO-India, that will significantly help detection of such events and dramatically improve the accuracy in estimating the location of binaries in the sky.

Compared to the first binary black hole merger event announced in February 2016, however, the present one is less massive — 65 solar mass versus 21 solar mass. Dr Somak Roychoudhury, director, IUCAA, said detection of another binary black hole merger, coming barely two months after the first one was detected, will put an end to scepticism in scientific circles.

Unlike the first event, the signal in the second instance does not stand out of the noise like a short-duration burst. One needs to use sophisticated data analysis techniques — matched filtering —to find such signals.

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