In this series, I'll start with a discussion of Hartnett's claims of redshift periodicities. The claim that extragalactic redshifts are distributed in fixed steps, i.e. quantized, is not new. William Tifft of the Steward Observatory at the University of Arizona is probably the originator of the modern redshift quantization movement back in the 1970s. If real, such periodicities or quantization would be very difficult to explain for conventional Big Bang cosmology. This is why you find redshift quantization supported by advocates of other alternative cosmologies such as the Electric Universe (see Electric Cosmos).

I choose to examine the redshift periodicities issue largely because my own graduate work focussed on time-series analysis of very noisy datasets and I accumulated a fair amount of experience working with Fourier series, transforms and power spectra.

Dr. Hartnett has published two papers on the Cornell Preprint server covering the topic of extragalactic redshift periodicities. I'll refer to them as Paper I and Paper II.

- Paper I:
*"Galaxy redshift abundance periodicity from Fourier analysis of number counts $N(z)$ using SDSS and 2dF GRS galaxy surveys"*by John G. Hartnett, Koichi Hirano (arXiv:0711.4885) - Paper II:
*"Redshift periodicity in quasar number counts from Sloan Digital Sky Survey"*by John G. Hartnett (arXiv:0712.3833)

It's interesting that the recently posted third version (v3) of paper I not only has an additional author, but seems to advocate a radically different cosmological model than the second version (v2). In the v2 paper, Hartnett advocated Moshe Carmeli's 5-dimensional cosmological model where the Hubble expansion was made part of the metric. Hartnett published several additional papers based on this model claiming it could explain Dark Matter as well. In paper v3, Hartnett has switched to another model developed by Hirano, Kawabata, and Komiya. This may be because the Hirano et al. cosmology explicitly tries to explain alleged redshift periodicities. This is another reason for me to examine the quantization claims first, as Hartnett appears to be in the process of changing his cosmological model, but quantization is a common component in both of them.

Hartnett is apparently using these works to gain him credibility in the creationist community as a professionally-published cosmologist. In his creationist publications, he has invoked redshift quantization as evidence of Galactocentrism, a feature of his young-universe cosmology. Some graphics similar to those from earlier versions of Hartnett's papers appear in his book Starlight, Time and the New Physics.

Since the advent of the Fast Fourier Transform and the availability of fast personal computers, the ability to compute the power spectral density (PSD) of a dataset has become much easier. Unfortunately, this increased ease of use does not come with an increased understanding of just what the PSD does. In cases with large amounts of low noise data, the PSD can identify well-defined frequencies in the data with relative ease. In other cases, such 'intuitive' understandings of the PSD can easily lead one astray.

Hartnett makes numerous erroneous statements on properties of PSD, suggesting he is relying on his 'intuition' on how the PSD works instead of actually testing the claim. Most researchers, myself included, must demonstrate that our test protocols work for datasets of

*known*content before making such grandiose claims when applying the test to datasets of

*unknown*content. In the abstract for Paper I, Hartnett states that his results "indicate that this is a real effect and not some observational artifact." Yet he has apparently conducted no tests to determine which characteristics of his results are

*analysis*artifacts.

In future entries in this series, I will present an overview of some of Dr. Hartnett's errors in these two papers. In later entries, I'll include some samples of how scientific

*tests*are themselves

*tested*. Some components may be difficult to communicate in this blog since there is limited support for graphics and mathematical notation. Some of these components may take a while to assemble as I may present code snippets (using Python, numpy, scipy, and similar tools) so the reader may explore the analysis themselves. Comments and feedback are certainly welcome.