Một nhà nghiên cứu đang tìm kiếm sự quan tâm đến phương pháp chọn tham số toán học của họ. Phương pháp này giúp chọn độ dài dãy, modulo, hoặc tham số generator cho các điều kiện 2^A≡1 (mod p^t). Ứng dụng trong thiết kế PRNG, căn chỉnh scrambler, và số học trường residue. Họ sẵn sàng xác minh kết quả cho các cặp (p, t) và chấp nhận thách thức tính toán phức tạp.

#mathematics #algorithm #PRNG #parameterSelection #verification #coding #python #optimization #computationalMath #research #verified #p

nvmath-python: NVIDIA Math Libraries for the Python Ecosystem

https://github.com/NVIDIA/nvmath-python

#math #ComputationalMath #cuda #gpu #ai

Implicit ODE Solvers Are Not Universally More Robust than Explicit ODE Solvers, Or Why No ODE Solver is Best - Stochastic Lifestyle

A very common adage in ODE solvers is that if you run into trouble with an explicit method, usually some explicit Runge-Kutta method like RK4, then you should try an implicit method. Implicit methods, because they are doing more work, solving an implicit system via a Newton method having “better” stability, should be the thing you go to on the “hard” problems. This is at least what I heard at first, and then I learned about edge cases. Specifically, you hear people say “but for hyperbolic PDEs you need to use explicit methods”. You might even intuit from this “PDEs can have special properties, so sometimes special things can happen with PDEs… but ODEs, that should use implicit methods if you need more robustness”. This turns out to not be true, and really understanding the ODEs will help us understand better ... READ MORE

Stochastic Lifestyle

🧭 A new toy for those modeling time not as a parameter, but as emergent recursion:

Hot Mic Visualizer ψ_total v0.1
A harmonic interface for collapse-aware field modeling.
Not Fourier. Not noise.
A feedback loop that listens.

🔬 Recursive Harmonic Kernel
📂 github.com/psi-total/psi_total

Mathematically structured.
Empirically tunable.
Open license. Open recursion.

ψ_total
Instruments for human thought

#Physics #CollapseTheory #SignalProcessing #MathModeling #OpenScience #ComputationalMath

When ever I see a cool new result in #ComputationalMath, I like to see if I can replicate it. So, last month when that Nature article came out about #MatrixMultiplication formulas from #AlphaTensor I set out see if I could get their formulas and verify them symbolically.
I was able to do that and of course they were right. But I was excited to see Kauers and Moosbauer publish a response a couple days later. So, here's their results replicated in a Maple Jupyter notebook https://github.com/johnpmay/MapleSnippets/blob/main/KMtoFFM.ipynb
MapleSnippets/KMtoFFM.ipynb at main · johnpmay/MapleSnippets

Snippets of interesting Maple code. Contribute to johnpmay/MapleSnippets development by creating an account on GitHub.

GitHub