  We propose a novel approach to detecting the elusive gravitational-wave
memory predicted by general relativity to accompany black hole mergers: direct
measurement of the permanent space-time strain offset. Compared to previous
techniques modeling and disentangling both the "chirp" and memory signals, this
approach has several advantages: it targets the feature of the signal carrying
nearly all its Shannon information, has great simplicity, circumvents the need
for precise modeling of the time evolution of all components of the
gravitational wave signal, and uses only data largely free of the more
complicated chirp signal. The frequency spectrum of the predicted memory signal
is roughly similar to that of the chirp signal. However its inclusion of lower
frequencies, where noise and data calibration are problematic, makes detection
difficult but not impossible. We applied this novel analysis, implemented with
a template-like algorithm, to a selection of 67 observations of 41 black hole
mergers in the LIGO/Virgo Gravitational Wave Transient Catalog. Statistical
significance was assessed by analyzing many time-shifted intervals. The result:
a few possible detections ($2\sigma-4\sigma$) and many upper limits. The
probability that a random ensemble of 67 strain time series, with the same
noise but no memory signals, will yield a particular figure-of-merit computed
for the actual data is approximately 0.1. Several validation checks proved
useless, partly due to large measurement and theoretical uncertainties, so
these results should be viewed with reservation. Appendices contain MatLab code
for various operations, including an algorithm for the complex Fourier
transform of arbitrarily spaced data.
