430 9.6 The Impact of AI, ML, and Deep Learning on Biophysics and the Physics of Life
microscopy, it was found that the highly colored region was restricted to a distal region
of the scale which contained a series of vertical corrugations of thickness of ~175 nm,
which had localized optical characteristics like a simple thin film. When a 488 nm
wavelength laser was directed onto this region, back-reflected light was detected only
at specific angles with the brightest being at ~63° from the normal to the surface of the
corrugation. Estimate the refractive index of chitin.
Answers
a The optical path length (OPL) (i.e. the length that light needs to travel through air
to create the same phase difference it would have when traveling through another
homogenous medium) for the transmitted beam from the upper to the lower sur
face is dn1/cosθ1. Similarly, the OPL back-reflected from the lower surface to the
upper surface is dn1/cosθ1 so the total OPL for the transmitted beam to emerge
back into the air is 2dn1/cosθ1. The lateral displacement L between this emergent
beam and the incident beam is from trigonometry 2d tan θ1. Using trigonometry
again, the OPL for the equivalent incident beam in air of angle θ0 reflected from
the upper surface is L sin θ0 = 2d tan θ1sin θ0. Thus, the optical path difference
(OPD) between these two beams is:
OPD = 2dn1/cosθ1 – 2dtanθ1sinθ0
Using Snell’s law of refraction, n0sinθ0=n1sinθ1 so:
OPD = 2dn1/cosθ1 – 2dtanθ1n1sinθ1 = (2dn1/cosθ1)(1 – sin2θ1) = 2dn1cosθ1
Since n1>n0 the phase of the incident reflected beam is shifted by 180°, equivalent
to half a wavelength. Constructive interference will occur if the OPD is equiva
lent to some positive integer number (say m) minus a half (for this phase shift) of
wavelengths. Thus:
2dn1cosθ1 = (m – 1/2)λ
b The brightest back-reflection will be for the first order of m (i.e. m = 1). Thus for
488 nm wavelength, the refraction index of the chitin is:
n1 = ((1 – 1/2) × 488 × 10–9)/(175 × 10–9 × 2cos63°) ≈ 1.54
9.6 THE IMPACT OF AI, ML, AND DEEP LEARNING ON
BIOPHYSICS AND THE PHYSICS OF LIFE
Artificial Intelligence (AI) refers to the development and application of computer systems
that can perform tasks that would normally require human intelligence, such as mimicking
cognitive functions involved in learning, problem-solving, perception, and decision-making.
They are particularly powerful at processing large data sets, recognizing and categorizing
patterns in these, and using these patterns to make predictions. Machine learning (ML) is an
important subset of AI that focuses on developing algorithms and models that can learn from
data without being explicitly programmed. ML algorithms learn from patterns and gold-
standard examples (or training data sets) to classify objects, identify correlations, and make
predictions. Deep learning, a subset of ML, utilizes neural networks with multiple layers to
process complex data and extract hierarchical representations.