heyoka 6.1.0

This is a quick release containing:

• a fix for a likely clang-17 bug which manifests itself with exceptions being thrown during (de)serialisation, and
• a fix for symbols from heyoka and its dependencies not being available to the JIT runtime when the heyoka shared library is dlopen()-ed with RTLD_LOCAL.

The minor version number has been bumped out of an abundance of caution, but this release does not contain any new user-facing features.

As usual, the full changelog is available here:

https://bluescarni.github.io/heyoka/changelog.html

heyoka 6.0.0

Improved support for mega-kernels ⚡

The main focus of this new heyoka release is improved support for very large computational graphs in both Taylor integrators and compiled functions. Specifically:

• when compact_mode is active, heyoka now splits the LLVM IR code in multiple modules rather than keeping it all in a single module - this leads to noticeable improvements in compilation time;
• the new parjit boolean flag (that can optionally be passed to the constructors of Taylor integrators and compiled functions) can be used to enable parallel compilation in compact_mode - this can lead to dramatically-reduced compilation times on multicore machines;
• it is now possible to pass the desired LLVM code model to the constructors of Taylor integrators and compiled functions. By default, the small code model is used, but very large computational graphs (which would error out in previous heyoka versions) might require the large model.

Warning

Due to several LLVM issues around parallel JIT compilation discovered during this latest heyoka development cycle, the parjit flag is currently off by default on Unix platforms and completely disabled on Windows. Turning on parjit on Unix platforms is considered safe but can very rarely result in a runtime exception being thrown. See the "known issues" page for more details:

https://bluescarni.github.io/heyoka/known_issues.html

We expect the parjit feature to become more stable in later LLVM releases, at which point it will be turned on by default.

Improvements to the integrator API 🔨

• It is now possible to initialise a Taylor integrator without providing a set of initial conditions - this will result in a zeroed-out initial state vector.
• The integrator constructor will now error out if a non-empty array of parameter values with the incorrect size is specified. If an empty array of parameter values is passed on construction, the parameter values in the integrator will be zero-inited.

pow() improvements 💥

Exponentiations with non-numerical exponents are now supported in the right-hand side of ODEs.

Update on supported LLVM versions 🔁

The minimum supported LLVM version is now 15. This release also adds support for the recently-released LLVM 19.

Miscellanea

• Fix build system warnings when using recent versions of CMake and Boost.
• Fix compilation on FreeBSD.
• Enable support for fmt 11.

As usual, the full changelog is available here:

https://bluescarni.github.io/heyoka/changelog.html

heyoka 5.1.0

SGP4 propagation 🌍

heyoka 5.1.0 adds an implementation of SGP4, a widely-used analytical propagator for Earth-orbiting objects.

SGP4 uses two-line elements sets (TLEs) (available from websites such as CelesTrak and Space-Track) to predict the future or past states of Earth-orbiting objects via a simplified perturbation model. The positional accuracy of SGP4 is in the order of kilometres for propagations up to a few days from the TLE reference epoch.

heyoka's SGP4 implementation is fully differentiable up to arbitrary order, thus enabling applications such as state covariance propagation, state transition matrix computation, gradient-based optimisation, orbit determination, etc.

SGP4 is available either as a low-level function that that produces the analytical formulae of SGP4 in heyoka's expression system, or a as a fast high-level propagator class accelerated via multithreaded parallelisation and SIMD vectorisation, providing state-of-the-art propagation performance. For more details, see the tutorial in the documentation of the Python bindings:

https://bluescarni.github.io/heyoka.py/notebooks/sgp4_propagator.html

Logical and relational operators, select() 📝

Another new feature in this release is support for logical and relational operators, as well as the select() primitive, in the heyoka expression system.

Relational operators allow to perform comparisons (such as "equal to", "less than", "greater than", etc.) during the evaluation of an expression (e.g., during a numerical integration), yielding a numerical value of 1 (true) or 0 (false). Logical operators allow to combine comparisons via logical AND/OR.

The select() primitive can be used to select one of two expressions based on the result of a comparison, thus providing a primitive form of if/then/else branching in the expression system. Note however that select() will always evaluate both the true and false branches, and thus it is unsuitable for complicated flow control.

The full changelog, as usual, is available here:

https://bluescarni.github.io/heyoka/changelog.html

heyoka 5.0.0

Variational equations 💫

With version 5.0.0, heyoka takes another big leap forward with built-in support for the variational equations - that is, the ability to compute not only the solution of an ODE system, but also its partial derivatives with respect to the initial conditions and/or parameters of the system.

The variational equations, which are automatically formulated by heyoka at any order via a process of efficient symbolic differentiation, enable a host of new applications, such as the solution of inversion problems (e.g., orbit determination), uncertainty propagation, Taylor maps and jet transport, the computation of chaos indicators, training of neural networks in NeuralODEs, etc.

A tutorial describing this new feature is available in the Python bindings.

Thermosphere models 🤖

Another big addition in this release is thermoNETs - a set of novel models for the calculation of the Earth's atmospheric density. These models, which have been recently unveiled at the ISSFD2024 conference, can be used to set up accurate and high-performance simulations of the LEO dynamical environment, accounting for the influence of air drag during orbital propagation. A tutorial describing this new feature is available in the Python bindings.

For more information, see also the arxiv preprint https://arxiv.org/html/2405.19384v1.

Support for LLVM 18

heyoka 5.0.0 adds support for the recently-released version 18 of LLVM.

The full changelog, as usual, is available here:

https://bluescarni.github.io/heyoka/changelog.html

heyoka 4.0.3

This is a quick release that fixes a couple of build issues, one on FreeBSD and the other affecting the unit tests when building with GCC 13.

NOTE: heyoka 4.x introduces several breaking changes with respect to the 3.x series. Please see the following link for a list of breaking changes and explanations on how to adapt your code to the new API:

https://bluescarni.github.io/heyoka/breaking_changes.html#bchanges-4-0-0

heyoka 4.0.2

This is a quick release that fixes a build issue on MinGW.

NOTE: heyoka 4.x introduces several breaking changes with respect to the 3.x series. Please see the following link for a list of breaking changes and explanations on how to adapt your code to the new API:

https://bluescarni.github.io/heyoka/breaking_changes.html#bchanges-4-0-0

heyoka 4.0.1

This is a quick release that fixes a build issue on PPC64.

NOTE: heyoka 4.x introduces several breaking changes with respect to the 3.x series. Please see the following link for a list of breaking changes and explanations on how to adapt your code to the new API:

https://bluescarni.github.io/heyoka/breaking_changes.html#bchanges-4-0-0

heyoka 4.0.0

Breaking changes

Version 4 of heyoka introduces several backwards-incompatible changes, most of which have been prompted by user feedback. The updated heyoka API should be more streamlined, easier to use and more difficult to misuse.

The detailed list of breaking changes is available at the following page, along with instructions on how to update your code for the API modifications:

https://bluescarni.github.io/heyoka/breaking_changes.html#bchanges-4-0-0

If you have questions, please do not hesitate to ask.

New compiled functions class

A new class that facilitates the creation and use of compiled functions, called cfunc, has been introduced. This class has been available for a while in the Python bindings, and it now makes its official debut in the C++ API. A tutorial illustrating the use of this class is available here:

https://bluescarni.github.io/heyoka/tut_cfunc.html#tut-cfunc

Support for Lagrangian and Hamiltonian mechanics

heyoka is now able to automatically generate (and solve) the equations of motion from user-supplied Lagrangians and Hamiltonians. The Python bindings provide a tutorial illustrating this new feature:

https://bluescarni.github.io/heyoka.py/notebooks/lagrangian.html#lagham-tut

Enhancements to the step callback API

It is now possible to pass a range of step callbacks as an optional argument to the propagate_*() functions. The callbacks will be automatically composed into a callback set and they will be executed at the end of each integration step.

spack availability

Thanks to work by @agseaton, heyoka is now available in the spack package manager. See the updated installation instructions:

https://bluescarni.github.io/heyoka/install.html#spack

Performance improvements

The substitution primitive subs() has been substantially sped up.

The full changelog, as usual, is available here:

https://bluescarni.github.io/heyoka/changelog.html

heyoka 3.2.0

This new release of heyoka comes packed with several new features and enhancements.

Support for single-precision computations

In addition to extended and arbitrary precision computations, heyoka now supports also single-precision computations via the float type. Single-precision computations can lead to substantial performance benefits, especially in batch mode and/or low-accuracy applications. See the single-precision tutorial for a usage example.

ELP2000 model

heyoka now includes an implementation of the ELP2000 lunar theory. It is thus now possible to formulate systems of differential equations with the time-dependent geocentric lunar position appearing in the right-hand side. See the tutorial for an introduction.

Low-precision vector math

When the fast_math option is active, heyoka now employs lower-precision vector implementations of elementary functions, which can lead to substantial speedups in low-accuracy applications. The speedup is particularly visible when using single precision in AI and ML applications.

As usual, the full changelog is available here:

https://bluescarni.github.io/heyoka/changelog.html

heyoka 3.1.0

This new release of heyoka comes packed with several new features and enhancements.

Neural networks

It is now possible to create feed-forward neural networks in the expression system, and use them in the definition of ODEs. See the machine learning section in the documentation of the Python bindings for more information and examples.

Complementary to the introduction of neural networks is the addition of the (leaky) ReLU and its derivative to the expression system.

New anomalies

The eccentric longitude F and the delta eccentric anomaly DE have been added to the expression system. These transcendental functions are used in celestial mechanics and astrodynamics to implement Lagrangian propagation and in the definition of equinoctial orbital elements.

Thanks to the introduction of the eccentric longitude F, the analytical ephemeris VSOP2013 should now be more numerically stable for orbits with low eccentricity/inclination.

Performance improvements

Several operations involving the manipulation and differentiation of large symbolic expressions are now substantially faster, often by more than an order of magnitude.

Fixes

• Improve the behaviour of the in-memory cache by ensuring that global constants are always defined in a deterministic order in an LLVM module.
• Improve the numerical stability of the Kepler solvers.
• Fix compiler warning when building without SLEEF support.

As usual, the full changelog is available here:

https://bluescarni.github.io/heyoka/changelog.html