Energy and computational complexity of atomic interactions

In summary, the conversation discusses the significant difference in energy requirements between modeling fluid dynamics on a computer and the physical process itself. It raises questions about estimating information content and calculating minimum energy requirements, as well as the potential of using a descriptive language for more efficient modeling. The speaker suggests that a better understanding of physical principles and laws of thermodynamics, as well as further research into potential alternatives, is needed to answer these questions.
  • #1
ktoz
171
12
Hi

Recently I've been pondering the causes of enormous difference in energy requirements between modeling a complex process like fluid dynamics on computer and the actual energy required in the physical fluid. In a computer, it takes hundreds or thousands of processors long periods of time to model even modestly complex fluid problems. If you took a simple bottle of water and shook it vigorously for a couple of seconds, the complexity would crush the combined power of every computer on earth. It would require huge amounts of energy and hundreds of years to exactly model what went on in the bottle in that two second span.

This brings up the following questions:
1. How would one estimate the total information content of a moderately complex problem?

2. How would one calculate the minimum energy requirements, using known mathematics, to exactly model a fluid problem?

3. It's a virtual certainty that nature doesn't use a single one of our quantum or physics equations to do what it does, so could the discrepancy between modeled and real processes lead unknown information? Or a descriptive language that yields more accurate and energy efficient models than math?
 
Physics news on Phys.org
  • #2
To answer these questions, I believe that a better understanding of the physical principles and the laws of thermodynamics must be obtained. By gaining a deeper insight into the underlying dynamics of fluid processes, we can better assess the complexity and energy requirements of modeling them. Additionally, further research into the potential of a descriptive language for more efficient modeling should also be explored.
 
  • #3


I find these questions very intriguing. The discrepancy between the computational complexity of atomic interactions and the actual energy requirements in physical processes is a fascinating topic to explore. This is a fundamental issue in the field of computational physics and has been a subject of research for many years.

To address the first question, estimating the total information content of a moderately complex problem is a challenging task. It involves understanding the underlying physical principles governing the process and the number of variables involved. It also requires a deep understanding of the computational methods being used and their limitations. This can be achieved through careful analysis and experimentation, but it is not a straightforward task.

The second question about calculating the minimum energy requirements to exactly model a fluid problem is also a complex one. It involves understanding the energy requirements of the individual atomic interactions and how they contribute to the overall energy of the system. This is a highly specialized area of research and requires advanced mathematical techniques and computational methods.

The third question is particularly interesting as it raises the possibility that there may be unknown information or alternative descriptive languages that could yield more accurate and energy-efficient models than traditional mathematics. This is a concept that has been explored in fields such as quantum computing and artificial intelligence. It is certainly possible that our current understanding of physics and mathematics may not fully capture the complexity of nature, and there may be alternative ways to describe and model physical processes.

In conclusion, the energy and computational complexity of atomic interactions is a complex and multifaceted topic that requires a deep understanding of physics, mathematics, and computational methods. It is an area of research that continues to be explored and may lead to new insights and breakthroughs in our understanding of the natural world.
 

1. What is the relationship between energy and computational complexity in atomic interactions?

The energy of atomic interactions refers to the amount of energy required to break or form bonds between atoms. Computational complexity, on the other hand, refers to the difficulty of solving a problem using a computer. In atomic interactions, the energy required to accurately simulate and predict the behavior of atoms increases with the complexity of the system, leading to a higher computational complexity.

2. How does the energy of atomic interactions affect the stability of molecules?

The energy of atomic interactions plays a crucial role in determining the stability of molecules. When the energy required to break bonds between atoms is higher than the energy released from forming new bonds, the molecule is considered stable. On the other hand, if the energy required is lower, the molecule is prone to breaking apart, making it less stable.

3. Can computational complexity be reduced in atomic simulations?

Yes, computational complexity can be reduced in atomic simulations by using more efficient algorithms and techniques. These can include simplifying the system being studied, using parallel computing, and optimizing the code used to run the simulations.

4. How do scientists measure the energy of atomic interactions?

The energy of atomic interactions can be measured using various experimental techniques, such as spectroscopy, calorimetry, and mass spectrometry. These methods involve measuring the changes in energy during different types of chemical reactions or interactions between atoms.

5. What are some real-world applications of understanding the energy and computational complexity of atomic interactions?

Understanding the energy and computational complexity of atomic interactions has numerous real-world applications. For example, it can help in the development of new materials with specific properties, such as strength and durability. It can also aid in the design of new drugs and catalysts, as well as improving our understanding of chemical reactions in various industrial processes.

Similar threads

  • Differential Equations
Replies
1
Views
658
  • Biology and Medical
Replies
15
Views
2K
  • Quantum Physics
Replies
4
Views
700
Replies
2
Views
792
  • Atomic and Condensed Matter
Replies
4
Views
1K
Replies
72
Views
5K
  • STEM Academic Advising
Replies
8
Views
822
  • Programming and Computer Science
Replies
29
Views
2K
Replies
17
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
996
Back
Top