  A boson sampling device is a specialised quantum computer that solves a
problem which is strongly believed to be computationally hard for classical
computers. Recently a number of small-scale implementations have been reported,
all based on multi-photon interference in multimode interferometers. In the
hard-to-simulate regime, even validating the device's functioning may pose a
problem . In a recent paper, Gogolin et al. showed that so-called symmetric
algorithms would be unable to distinguish the experimental distribution from
the trivial, uniform distribution. Here we report new boson sampling
experiments on larger photonic chips, and analyse the data using a scalable
statistical test recently proposed by Aaronson and Arkhipov. We show the test
successfully validates small experimental data samples against the hypothesis
that they are uniformly distributed. We also show how to discriminate data
arising from either indistinguishable or distinguishable photons. Our results
pave the way towards larger boson sampling experiments whose functioning,
despite being non-trivial to simulate, can be certified against alternative
hypotheses.
