Features

NeoPDF is designed to be a modern, extensible, and high-performance library for generic non-perturbative functions. This page details the physics and technical features, design rationale, and future plans.

Summary of the Current Supported Features

Physics Features

Hadron Types and PDF Classification

Proton + Proton -> π + π + X

Particle: 2212/212/... # Hadron PID
Polarized: true/false
SetType: SpaceLike/TimeLike

Supported distributions

NeoPDF supports generic classes of distributions that are functions of different combinations of the kinematic variables. Examples of known distribution functions are given in the diagram below with their simplified relationships.

graph TD

A["**Generalized Tranverse Momentum Distribution** <br> GTMD(x, ξ, Δ, kT​​, Q²)"]

A -->|∫ dkT| B["**Generalized Parton Distributions** <br> GPD(x, ξ, Δ, Q²)"]
A -->|ξ → 0, Δ → 0| C["**Transverse Momentum Distributions** <br> TMD(x, kT, Q²)"]

B -->|ξ → 0, Δ → 0| D["**Collinear Parton Distribution Functions** <br> PDF(x, Q²)"]
C -->|∫ dkT| D

style A fill:#8B4513,stroke:#D2691E,stroke-width:2px
style B fill:#1E3A5F,stroke:#4169E1,stroke-width:2px
style C fill:#2F4F2F,stroke:#3CB371,stroke-width:2px
style D fill:#8B2F2F,stroke:#CD5C5C,stroke-width:2px

In order to support these distributions, NeoPDF provides Hermite Cubic Spline and Chebyshev interpolation strategies for up to 6D data.

Multi-Flavor Grids (Planned)

NeoPDF will support grids with varying numbers of active flavors \(n_f\), providing a consistent treatment of heavy quark effects across all scales. Advanced schemes like FONLL and ACOT require careful handling of flavor thresholds and mass effects. NeoPDF's multi-flavor support will enable:

• Precision predictions for heavy flavor production
• Proper matching across flavor thresholds
• Consistent treatment of charm and bottom quark effects

Analytical Interpolation (Planned)

Future versions will support DGLAP-based analytical interpolation. Such an analytical-based interpolation will provide:

• Consistent treatment of scale evolution
• Reduced interpolation artifacts
• More accurate extrapolation beyond the grid boundaries

Technical Features

Language Interoperability

NeoPDF provides native APIs across multiple programming languages, enabling seamless integration into diverse computational workflows:

• Native Rust API: The core library is written in Rust, providing zero-cost abstractions, memory safety, and high performance. Rust's ownership system ensures thread safety and prevents common programming errors that could lead to incorrect physics results.

• Python Bindings: Comprehensive Python interface using PyO3, enabling integration with the rich ecosystem of scientific Python libraries (NumPy, etc.). This is crucial for data analysis, visualization, and integration with existing physics analysis frameworks.

• C/C++ Bindings: Direct C and C++ interfaces for integration with legacy codes and high-performance computing applications. The C API provides a stable ABI for long-term compatibility, while the C++ API offers object-oriented convenience.

No-Code Migration

NeoPDF maintains API compatibility with LHAPDF, enabling seamless migration:

• Drop-in Replacement: Existing LHAPDF code can often be migrated by simply changing import statements, with no modifications to the core physics logic required.

• Preserved Function Signatures: Key functions like xfxQ2(), alphasQ2(), and mkPDF() maintain the same signatures as LHAPDF, ensuring compatibility with existing analysis codes.

This compatibility is crucial for the physics community, as it allows for immediate adoption without requiring extensive code rewrites or validation efforts.

Extensible Interpolation

NeoPDF's modular architecture enables easy extension and customization:

• Pluggable Interpolation Strategies: The library supports multiple interpolation algorithms (linear, cubic, Chebyshev) for up to 6D data and can be extended with custom interpolation schemes.

• Custom Grid Types: The framework can accommodate new grid formats and data structures, enabling support for emerging PDF sets and specialized applications.

• Performance Tuning: Different interpolation strategies can be selected based on the specific requirements of accuracy vs. speed, allowing optimization for different use cases.

Performance Optimization

NeoPDF is designed for high-performance computing environments:

• Zero-Cost Abstractions: Rust's compilation model ensures that high-level abstractions don't incur runtime overhead, providing both safety and performance.

• Cache-Friendly Design: Data structures are optimized for modern CPU cache hierarchies, reducing memory access latency and improving performance for large-scale calculations.

• SIMD Optimization: The library can leverage CPU vector instructions for parallel evaluation of multiple points, crucial for Monte Carlo event generation and large-scale simulations.

• Benchmarking: Comprehensive benchmarking against LHAPDF ensures that performance improvements don't come at the cost of accuracy, maintaining the precision required for physics calculations.

Thread and Memory Safety

NeoPDF leverages Rust's safety guarantees for robust multi-threaded applications:

• Memory Safety: Rust's ownership system prevents common memory errors (use-after-free, double-free, data races) that could lead to incorrect physics results or program crashes.

• Thread Safety: Built-in support for safe concurrent access to PDF objects, essential for parallel event generation and Monte Carlo simulations.

• FFI Safety: Careful design of the foreign function interface ensures that safety guarantees extend to Python, C, and C++ code, preventing crashes and undefined behavior.