High permormance symbolic computing

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In summary: Your Name]In summary, the person is asking if it is possible to obtain the expression for f using Maple or Mathematica. Both software have powerful symbolic computation capabilities and can handle differential equations and implicit functions. It is possible to use the "dsolve" command in Maple or the "DSolve" command in Mathematica to obtain an explicit expression for f. There are also free powerful codes available, such as SageMath, Maxima, and SymPy, which can be run on a workstation without any additional cost. However, they may not have the same level of user-friendly interface as Maple or Mathematica.
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landau_rules
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Dear all,

I have derived a set of differential equations. One is still missing and its left hand side is called f (as in the attachment). Unfortunately f is known only implicitly.

I am not very familiar with maple or mathematica. My question is:

Is it possible to obtain the expression for f with maple or mathematica? Can the problem be tackled with the mathematica commands "integrate" or "dsolve"?

What about symbolic computations in general. Are there free powerfull codes out there, which have certain advantages over the commercial products maple or mathematica, so that i can run them on a workstation?

Best greetings from Europe
K.
 

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Dear K.,

Thank you for reaching out with your question. It is certainly possible to obtain the expression for f using both Maple and Mathematica. Both software have powerful symbolic computation capabilities that can handle differential equations and implicit functions.

In Maple, you can use the "dsolve" command to solve the differential equation and obtain an explicit expression for f. For example, if your differential equation is represented as "f'(x) = x^2 + f(x)", you can use the command "dsolve(f'(x) = x^2 + f(x), f(x))" to obtain the solution for f.

In Mathematica, you can use the "DSolve" command in a similar manner to obtain the explicit expression for f. Both Maple and Mathematica also have the option to solve differential equations numerically if an explicit solution is not possible.

As for free powerful codes, there are several options available such as SageMath, Maxima, and SymPy. These codes have the advantage of being open-source and can be run on a workstation without any additional cost. However, they may not have the same level of user-friendly interface as Maple or Mathematica. It ultimately depends on your specific needs and preferences.

I hope this helps and best of luck with your research.


 

1. What is high performance symbolic computing?

High performance symbolic computing is a field of computer science that focuses on developing algorithms and software tools for performing symbolic computations, such as mathematical calculations and symbolic reasoning, at a high speed and with great accuracy.

2. How does high performance symbolic computing differ from traditional numerical computing?

Traditional numerical computing involves using numerical approximations to solve mathematical problems, while high performance symbolic computing utilizes symbolic manipulation to perform exact computations. This allows for more precise and reliable results, especially for complex calculations.

3. What are the applications of high performance symbolic computing?

High performance symbolic computing has a wide range of applications, including but not limited to: scientific computing, data analysis, machine learning, cryptography, and engineering design and optimization. It is also used in fields such as physics, chemistry, biology, and economics.

4. What are some common tools and languages used in high performance symbolic computing?

Some popular tools and languages for high performance symbolic computing include Mathematica, Maple, MATLAB, and Python with libraries such as SymPy and Sage. These tools provide a user-friendly interface for performing symbolic computations and offer a variety of algorithms and functions for different applications.

5. How is high performance symbolic computing advancing scientific research?

High performance symbolic computing has greatly advanced scientific research by providing powerful tools for solving complex equations and analyzing large datasets. It has also allowed for the development of more accurate models and simulations in various fields, leading to new discoveries and advancements in scientific knowledge.

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