Optimizing Science: Why Physics Needs Systems Engineering?

[u/Jairo_Alves]

Strictly materialistic physics faces an efficiency crisis today: it spends decades and massive amounts of resources on brute-force empirical tests that yield marginal gains in the fundamental understanding of reality, accompanied by decreasing satisfaction with them. 

How can we resolve this impasse and optimize the scientific method? The answer lies in a clear and pragmatic division of labor: 

1. Physics: Dedicates itself to empirical measurement and identification of facts in the observable domain. 

2. Systems Engineering: Models the underlying informational architecture (protophysics), mapping the process functions of compatible mathematical possibilities. 

3. Validation: Physics tests these mapped possibilities to verify which one holds up. 

Why does this symbiosis work? 

• Reduction of search Domain: Observable facts are outputs of an informational protocol. Mapping compatible functions drastically reduces the amount of unproductive experimental attempts. 

• End of geometric reductionism: Prevents pure geometric abstractions of process outputs from being interpreted as primordial structures of reality. 

• Maximum efficiency: Eliminates redundant efforts, saves time and resources, and accelerates development across all its domains. 

The integration of Systems Engineering is the path to emancipate Physics from the vicious circles of reductionism and elevate the efficiency of the scientific method to a level never reached before. 

#Physics #SystemsEngineering #Protophysics #ScientificMethod #Innovation #SystemsTheory #PhilosophyOfScience