Quantum Computing Optimzations, Q# and Ninja Trader 8

[yoleven]

Quantum computing for optimization has now become affordable, and the cost for renting processing time on a quantum computer will continuously drop.

Is there an development underway for quantum computing optimizations for Ninja Trader or other charting platforms?

Microsoft is promoting Q# for their Azure platform.

It is time for a serious and enlightening discussion.

[bltdavid]

Are there no bindings to call your Q# code from C#?

If not, when such bindings do become available, isn't that enough?

[yoleven]

Are there no bindings to call your Q# code from C#?

If not, when such bindings do become available, isn't that enough?

There is a developer kit available:

https://azure.microsoft.com/en-us/services/quantum/

There is a tutorial on how to create a Q# library with a dot NET host. So this is likely possible.

"A primary distinction is that Q# can be run:

• as a standalone application, where Q# is the only language involved and the program is invoked directly. Two methods actually fall in this category:
  • the command-line interface
  • Q# Jupyter Notebooks
• with an additional host program, written in Python or a .NET language (e.g. C# or F#), which then invokes the program and can further process returned results."

WORTH READING:

https://docs.microsoft.com/en-us/qua...s=tabid-python

[bettingweb33]

Quantum computing for optimization has now become affordable, and the cost for renting processing time on a quantum computer will continuously drop.

Is there an development underway for quantum computing optimizations for Ninja Trader or other charting platforms?

Microsoft is promoting Q# for their Azure platform.

It is time for a serious and enlightening discussion.

Quantum computing for optimization is quickly becoming more accessible, and the potential it holds for trading platforms like NinjaTrader is exciting. While specific quantum computing optimizations for NinjaTrader may not be widespread yet, the trend is moving in that direction, especially as costs for renting quantum processing time continue to drop.

Microsoft's Q# on Azure is indeed a strong example of how major tech companies are pushing quantum computing into practical use cases. AI tools, already widely used in trading for pattern recognition and predictive analysis, could be combined with quantum computing to create incredibly powerful optimizations. Imagine using AI for data-driven insights and then applying quantum algorithms for even faster, more precise optimization.

It’s certainly time for a serious discussion on how both AI and quantum computing could revolutionize trading platforms in the near future.