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What books are you currently reading?

Introduction to the Boost C++ Libraries Volume I – Foundations - Robert Demming, Daniel J. Duffy
Stochastic Calculus for Finance II: Continuous-Time Models - Steven E. Shreve
The 48 Laws of Power - Robert Greene
@jahaanrawat, mind if I DM you here? I am studying the same topics as you, might be worthwhile to have a chat.
 
Lucius Annaeus Seneca, Letters from the Stoic / Seneca's Moral Letter to Lucilius (translated by Richard Gummere) and
Paideia: the Ideals of Greek Culture by Werner Jaeger (Translated from the Second German Edition by Gilbert Highet) Volume 1 (Archaic Greece / the Mind of Athens)
 

Just in case Rust <-> C++ interop becomes the next hot topic.


Seems like a course is coming soon.

Let’s make it 2 more.

One more C++ course. Focused on building a robust application throughout the entirety of the course where each level of the course adds functionality to the application.

One Rust course.
 
Seems like a course is coming soon.

Let’s make it 2 more.

One more C++ course. Focused on building a robust application throughout the entirety of the course where each level of the course adds functionality to the application.

One Rust course.
My feeling is if you know C++ then learning Rust is easy.

e.g.

Rust is a multi-paradigm, general-purpose programming language that emphasizes performance, type safety, and concurrency. It enforces memory safety—meaning that all references point to valid memory—without a garbage collector. To simultaneously enforce memory safety and prevent data races, its "borrow checker" tracks the object lifetime of all references in a program during compilation. Rust was influenced by ideas from functional programming, including immutability, higher-order functions, and algebraic data types. It is popular for systems programming.[13][14][15]

These topics are discussed in QN Adv C++.
 
Seems like a course is coming soon.

Let’s make it 2 more.

One more C++ course. Focused on building a robust application throughout the entirety of the course where each level of the course adds functionality to the application.

One Rust course.
Firsy, we intend documenting it in book form. I get quite a number of requests for these kinds of application-oriented (for want of a better name) courses.
a lot of effort and work..:whistle:
 
Firsy, we intend documenting it in book form. I get quite a number of requests for these kinds of application-oriented (for want of a better name) courses.
a lot of effort and work..:whistle:
Would be happy to pay the fee. Obviously needs a decent return for you, but my feeling is that it’s created once and the residuals are long lived. You’ll know your market better than me, though.
 
Here is a nicely balanced book on SDE by two top numerical analysts

https://epubs.siam.org/doi/10.1137/1.9781611976434

i.e. continuous space to discrete space (as it should be).

Most books and articles on SDE give numerical methods short shrift... In fact, most books only tell half the story. That's why SDE can be so intimidating.
Paper models don't crash.

I recommend it to students, in combination with C++ and Python.

It is true that there is nothing in a stochastic differential equation that is not in a Fokker-Planck equation, but the stochastic differential equation is so much easier to write down and manipulate that only an excessively zealous purist would try to eschew the technique.

C.W. Gardiner (2004) Handbook of Stochastic Methods, for Physics, Chemistry and the Natural Sciences, Springer.

//
FPE (Fokker Planck) PDE Remarks
Daniel J. Duffy

Attention Points on current thinking
. Watertight mathematical formulation replaced by (ad-hoc) heuristics.
. Somewhat outdated finite difference schemes used.
Of course, extensive numerical experimental testing should ensure that it works in practice. But how does it work in theory?

Some possible Remedies

1. Domain transformation of PDE to unit interval/square (no ad-hoc domain truncation!).
2. Seamless Fichera/Feller/Green formula boundary conditions (mathematically robust). Well-posed PDE now.
3. Morph FPE into a conservative/self-adjoint PDE, which subsumes the pesky convective term and allowing elegant numerical schemes.
4. ADI/Craig Sneyd/Crank Nicolson are a bit alt-modisch; we have about 5 improvements in Duffy (2022).
5. No issues with Dirac BCs; integral evaluates to 1.
6. I use ADE, Marchuk, Strang, Yanenko schemes. Even Method of Lines (MOL).
Duffy, D.J. (2022) Numerical Methods in Computational Finance Wiley.
 
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Haven't read a new fiction book in 15 years or so. Last one was probably one of the Chrichton's as they were being published. Did re-read the original Foundation trilogy in this time span.

Did listen to few, while driving, most recently "SAS Rogue Heros" by Macintyre.
 
@Daniel Duffy Has a section on C++ interop with python and ruby. I hope it is good
 

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