Hamiltonian VQE Kit (hvk)
Hamiltonian VQE Kit (hvk) is an open-source, scientifically validated toolkit designed to take any molecular or qubit Hamiltonian and synthesize a diagnosed VQE / ADAPT-VQE workflow capable of achieving chemical accuracy ($\le 1.6,\text{mHa}$ vs. Full Configuration Interaction / FCI) with strict, verifiable accounting of quantum simulation cost.
📌 Core Modules
| Module | Purpose |
|---|---|
hvk.chemistry |
PySCF & OpenFermion Hamiltonian loaders, Jordan-Wigner transformation, Pauli parsing, FCI & HF reference solutions |
hvk.audit |
Hamiltonian 2-body interaction graph analysis and wasted CNOT audit vs. rigid hardware-efficient ansätze (HEA) |
hvk.adapt |
Exact ADAPT-VQE engine with fermionic/qubit operator pools, commutator gradients, and strict measurement tracking |
hvk.ansatz |
Deterministic, connected sparse ansatz generator derived directly from Hamiltonian interaction topology |
hvk.init |
Principled statevector initializers (Random, Hartree-Fock, Perturbation-Adjusted HF, Guarded Residual ML) |
hvk.diagnostics |
Barren plateau gradient variance analyzers and realistic NISQ energy-error-under-noise benchmarks |
hvk.exporters |
Zero-overhead circuit and operator export to Qiskit, PennyLane, and Cirq |
hvk.cli |
Unified command-line interface (`hvk audit |
⚖️ Non-Negotiable Honesty Rules
This repository operates under strict scientific reproducibility constraints:
- Zero Hardcoded Numbers: Every metric, iteration count, and energy reported in documentation or tables must be generated by verifiable scripts in
benchmarks/results/recording random seed, commit hash, and dependency versions. - FCI/PySCF Parity: All molecular test systems ($H_2$, $\text{LiH}$, $\text{BeH}_2$, $H_4$ chain) must be validated directly against PySCF Hartree-Fock and FCI exact ground states. Tests fail if reference energies diverge.
- Core is 100% Non-ML: The core toolkit operates with standard numerical computing dependencies (
numpy,scipy). Machine learning models are strictly optional extras (pip install hvk[ml]). - Honest Baseline Comparisons: ML components must be compared head-to-head against exact non-ML and simple heuristic methods. If ML does not win, the null or negative result will be reported plainly.
- Guarded Residual Initializer: The residual-ML initializer is explicitly guarded, not guaranteed: it evaluates energy at $\boldsymbol{\theta}{\text{HF}}$ and $\boldsymbol{\theta}{\text{HF}} + \Delta\boldsymbol{\theta}$, returns the lower energy, and falls back to PA-HF when an explicit out-of-distribution (OOD) criterion is triggered.
- Physical Noise Metric: Noise benchmarks measure ENERGY ERROR under noise vs. the exact ground state with confidence intervals. State fidelity vs. ideal state is only reported if explicitly labeled as such.
- Strict Measurement Accounting: ADAPT execution tracks every energy evaluation, commutator measurement, and appended operator using documented, deterministic counting conventions.
- Code Quality Standards: 100% type annotations, comprehensive docstrings, clean
ruffandmypyaudits, unit tests for every public function, and test coverage $> 85%$.
⚡ Quickstart
Installation
# Core package (zero ML overhead)
pip install hamiltonian-vqe-kit
# With optional chemistry and dev dependencies
pip install "hamiltonian-vqe-kit[chemistry,dev]"
# With optional machine learning extensions
pip install "hamiltonian-vqe-kit[ml]"
Command-Line Interface (CLI)
# 1. Audit Hamiltonian locality and interaction graph
hvk audit H2
# 2. Run exact ADAPT-VQE toward chemical accuracy (<= 1.6 mHa)
hvk adapt LiH --accuracy 0.0016
# 3. Build a sparse ansatz from the interaction graph
hvk build BeH2
# 4. Run barren plateau diagnostic
hvk diagnose H4
# 5. Execute full reproducible multi-molecule benchmark suite
hvk benchmark --output-dir benchmarks/results
⚠️ Limitations and Known Failures
This section is continuously updated as empirical benchmarks are evaluated.
- Phase 0 Status: Initial repository scaffolding and packaging phase. Core chemistry validation (Phase 1) is currently queued.
- Qubit Active Space Boundaries: Phase 1 through Phase 4 focus on small-molecule STO-3G active spaces ($N \le 8$ qubits). Systems exceeding 8 qubits require frozen-core approximations or extended basis set loaders.
- Physical Noise Assumptions: Energy-error-under-noise simulation in Phase 4 models quantum channels via stochastic Kraus operators; cross-talk and drift are not modeled in initial releases.
📜 Prior Work & Citation
If you use this toolkit in your research, please cite:
@software{khan2026hvk,
author = {Ashraf Khan},
title = {Hamiltonian VQE Kit: Validated, Honest VQE and ADAPT-VQE Toolkit},
year = {2026},
publisher = {GitHub},
version = {0.1.0},
url = {https://github.com/aashiq-parinda/hamiltonian-vqe-kit}
}
This project builds upon foundational theoretical and architectural insights pre-registered in:
- Ashraf Khan (2026). Rigorous Generalization Study: Transformer-Accelerated VQE Warm-Starting Across Multi-Molecule Families. Zenodo Record #22013110.
📄 License
Licensed under the Apache License, Version 2.0 (the "License"). See LICENSE for details.
Metadata
Release files for hamiltonian-vqe-kit 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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| hamiltonian_vqe_kit-0.1.1.tar.gz | 23.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hamiltonian_vqe_kit-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 45.6 kB
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