Analog vs Digital: How Digital Representations Reflect the Analog Universe

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Discussion Overview

The discussion revolves around the representation of an analog universe through digital means, exploring the implications of measurement accuracy, the nature of mathematical constants like Pi, and the characteristics of neuron activity. It touches on theoretical, conceptual, and practical aspects of analog and digital representations.

Discussion Character

  • Exploratory
  • Debate/contested
  • Conceptual clarification
  • Technical explanation

Main Points Raised

  • Some participants question the belief that an analog universe can be accurately represented digitally, citing the approximation of Pi as a key example.
  • Others argue that the act of measurement inherently involves a digital representation due to limitations in accuracy and significant figures.
  • A participant notes that while Pi is transcendental and cannot be fully represented, scientific laws operate on the basis of limited measurement accuracy.
  • There is a suggestion that the universe's analog nature is still under debate, with a request for clarification on how approximations affect precision in calculations.
  • Some participants assert that neuron activity exhibits both analog and digital properties, although this topic is deemed more appropriate for a biology forum.
  • One participant emphasizes that all tools and measurements are approximations, which can still yield remarkable results despite their limitations.
  • Another participant highlights a distinction between "Analogue/Digital" and "Continuous/Discrete" variables, discussing the implications of measurement barriers in scientific practice.

Areas of Agreement / Disagreement

Participants express differing views on the nature of the universe (analog vs. digital) and the implications of using approximations in measurements. There is no consensus on whether digital representations can fully capture the analog universe, and the discussion remains unresolved.

Contextual Notes

Participants acknowledge the limitations of measurements, the dependence on definitions of analog and digital, and the unresolved nature of certain mathematical concepts like Pi. The discussion also reflects a variety of perspectives on the relationship between measurement accuracy and scientific representation.

GregoryC
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What makes us believe we can represent an analog universe with digital representations? We can only know the radius of a circle or it's circumference with precision because Pi is an approximation.
 
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GregoryC said:
What makes us believe we can represent an analog universe with digital representations?
We don't have to "believe", we do it.
We can only know the radius of a circle or it's circumference with precision because Pi is an approximation.
Yes. So what's wrong with that?
 
Whenever we write down a value that's been measured, we have 'gone digital'. In Science, all measurements have a limited accuracy and have a certain number of significant figures.
Pi is a transcendental number and, as you say, cannot be represented in a limited number of digits. There are other transcendental numbers (e) and also many familiar irrational numbers (√2) for instance.
We don't claim to represent the Universe perfectly - all our Scientific Laws are based on limited measurement accuracy. Everything is calculated 'near enough' to justify the many theories in which the Maths assumes a continuum of values.
No need to lose any sleep over this - unless you want to stray into the realms of Philosophy (third year work and beyond!)
 
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GregoryC said:
What makes us believe we can represent an analog universe with digital representations?

Is the universe analog? I thought the jury was still out on that.
We can only know the radius of a circle or it's circumference with precision because Pi is an approximation.

Can you explain why we can a only calculate the circumference with precision because pi is an approximation? Normally approximations reduce precision.
 
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Neuron activity seems pretty digital to me.
 
bsheikho said:
Neuron activity seems pretty digital to me.

I believe neurons have both analog and digital "properties", but that's a topic for the biology forum, not this thread.
 
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GregoryC said:
What makes us believe we can represent an analog universe with digital representations? We can only know the radius of a circle or it's circumference with precision because Pi is an approximation.
Pi is exact. Any real figure is only approximately a circle.
 
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There seems to be a bit of a confusion between "Analogue / Digital" (Types of electronic and other signal processing) and "Continuous / Discrete" (variables). Maths can handle integers, (the only discrete variables) rational, irrational and transcendental variables and all types turn up in Science.
Between Scientists and Science there is always the 'measurement barrier'. Every measurement has a certain resolution and accuracy and, as soon as we write it down or process it in a digital processor, it becomes a discrete quantity.
Before digital processors had sufficient capacity, we used to employ Analogue Computers which would take the analogue values from sensors and potential dividers and, with clever use of Op Amps, would produce an Analogue output signal. The whole information chain used continuous variables (Volts and current values). However, of course there was noise /hum / drift etc and the output value was not an 'exact' outcome. So you could not actually rely on a set of monotonic input variables giving you a monotonic answer.
 
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Drakkith said:
I believe neurons have both analog and digital "properties", but that's a topic for the biology forum, not this thread.
Actually they do, the chemical aspect is analog, and the patterns can be argued for digital. But yeah like you said, not in this thread's current location.
 
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  • #11
I'm an engineer not a scientist but I'll tell you what a professor told me once. "Every tool we have is an approximation". That doesn't mean that they are bad tools that cannot do remarkable things. Look at how we are communicating for instance. When the approximations fail that's where the interesting research starts.
 
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