4 ms·

None of the things you listed depend on explanations outside of the realm of physics that we already understand. Theoretically with a simulator powerful enough

None of the things you listed depend on explanations outside of the realm of physics that we already understand. Theoretically with a simulator powerful enough and using the principles we already know, all of the items you listed could be solved.

Thorentis 6y ago
I think there's a difference between understanding a system well enough to make predictions, and recreating a system (a simulation) and then seeing what it does. Many times in history before the physics was properly understood, the best scientists and engineers could do was create some kind of "dry run" and simulate/recreate whatever process they were testing, and use that to predict outcomes of the real one. But actually being able to look at the state of a live system and predict what it will do next accurately is quite different.
- antepodius 6y ago
  It seems to me to be more of a spectrum, where a 'well-understood' system is one we can simulate accurately with extremely pared-down models. (I.e., we can simulate it much more cheaply than running the whole atomic simulation) because we found symmetries/simplifications/shortcuts. Approximating ballistics arcs with parabolae, for example, is sort of a compression algorithm on the full simulation.
TheOtherHobbes 6y ago
Some systems are simply random. No amount of simulation will tell you exactly when an unstable atom will decay. We've spent the last century arguing about what this means for physics, and we still have no idea - even though quantum events can have macroscopic consequences. (To give a contrived example - a decaying atom may damage some human DNA and cause cancer in a historically important individual who dies decades earlier than they would have otherwise, changing the course of history.) It's more accurate to say that we can model a small selection of mathematically 'pure" system types that are neither random nor emergent, on timescales that are comprehensible to us.

Thorentis 6y ago

I think there's a difference between understanding a system well enough to make predictions, and recreating a system (a simulation) and then seeing what it does. Many times in history before the physics was properly understood, the best scientists and engineers could do was create some kind of "dry run" and simulate/recreate whatever process they were testing, and use that to predict outcomes of the real one. But actually being able to look at the state of a live system and predict what it will do next accurately is quite different.

antepodius 6y ago
It seems to me to be more of a spectrum, where a 'well-understood' system is one we can simulate accurately with extremely pared-down models. (I.e., we can simulate it much more cheaply than running the whole atomic simulation) because we found symmetries/simplifications/shortcuts. Approximating ballistics arcs with parabolae, for example, is sort of a compression algorithm on the full simulation.

TheOtherHobbes 6y ago

Some systems are simply random. No amount of simulation will tell you exactly when an unstable atom will decay. We've spent the last century arguing about what this means for physics, and we still have no idea - even though quantum events can have macroscopic consequences. (To give a contrived example - a decaying atom may damage some human DNA and cause cancer in a historically important individual who dies decades earlier than they would have otherwise, changing the course of history.) It's more accurate to say that we can model a small selection of mathematically 'pure" system types that are neither random nor emergent, on timescales that are comprehensible to us.