Abstract:

Can we detect primordial gravitational waves (i.e. tensor perturbations)? If so, what will they teach us about the early universe? These two questions are central to this two part thesis.

First, in chapters 2 and 3, we compute the gravitational wave spectrum produced by inflation. We argue that if inflation is correct, then the scalar spectral index ns should satisfy n s [Special characters omitted.] 0.98; and if ns satisfies 0.95 [Special characters omitted.]HASH(0x19c90f58)ns [Special characters omitted.] 0.98, then the tensor-to-scalar ratio r should satisfy r [Special characters omitted.] 0.01. This means that, if inflation is correct, then primordial gravitational waves are likely to be detectable. We compute in detail the "tensor transfer function" Tt (k, ?) which relates the tensor power spectrum at two different times ?1 and ? 2 , and the "tensor extrapolation function" Et ( k, k[low *] ) which relates the primordial tensor power spectrum at two different wavenumbers k and k [low *] . By analyzing these two expressions, we show that inflationary gravitational waves should yield crucial clues about inflation itself, and about the "primordial dark age" between the end of inflation and the start of big bang nucleosynthesis (BBN).

Second, in chapters 4 and 5, we compute the gravitational wave spectrum produced by the cyclic model. We examine a surprising duality relating expanding and contracting cosmological models that generate the same spectrum of gauge-invariant Newtonian potential fluctuations. This means that, if the cyclic model is correct, then it cannot be distinguished from inflation by observing primordial scalar perturbations alone. Fortunately, gravitational waves may be used to cleanly discriminate between the inflationary and cyclic scenarios: we show that BBN constrains the gravitational wave spectrum generated by the cyclic model to be so suppressed that it cannot be detected by any known experiment. Thus, the detection of a primordial gravitational wave signal would rule out the cyclic model.