Optimize statevector simulator preprocessing

.github/workflows/main.yml

@@ -180,8 +180,8 @@ jobs:
       - name: Install and Test wheel with extras
         run: |
           pip install setuptools
-          bash bin/install_wheel_extras.sh dist --type wheel --extra test --extra cli --extra pulse
-          python -m pytest --cov=pyqasm tests/ --cov-report=html --cov-report=xml --cov-report=term
+          bash bin/install_wheel_extras.sh dist --type wheel --extra test --extra test-sim --extra cli --extra pulse
+          python -m pytest --cov=pyqasm tests/ -m "not benchmark" --cov-report=html:build/coverage/html --cov-report=xml:build/coverage/coverage.xml --cov-report=term
 
       - name: Upload coverage to Codecov
         if: ${{ matrix.python == 311 }}
@@ -190,4 +190,4 @@ jobs:
           token: ${{ secrets.CODECOV_TOKEN }}
           fail_ci_if_error: false
           files: ./build/coverage/coverage.xml
-          verbose: true
+          verbose: true

.github/workflows/pre-release.yml

@@ -176,4 +176,4 @@ jobs:
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           user: __token__
-          password: ${{ secrets.PYPI_API_TOKEN }}
+          password: ${{ secrets.PYPI_API_TOKEN }}

.github/workflows/release.yml

@@ -167,4 +167,4 @@ jobs:
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           user: __token__
-          password: ${{ secrets.PYPI_API_TOKEN }}
+          password: ${{ secrets.PYPI_API_TOKEN }}

.github/workflows/test-release.yml

@@ -166,4 +166,4 @@ jobs:
         with:
           repository-url: https://test.pypi.org/legacy/
           user: __token__
-          password: ${{ secrets.TEST_PYPI_API_TOKEN }}
+          password: ${{ secrets.TEST_PYPI_API_TOKEN }}

.gitignore

@@ -8,6 +8,7 @@ __pycache__/
 
 # Cython build files
 src/pyqasm/accelerate/linalg.c
+src/pyqasm/accelerate/sv_sim.c
 
 # Distribution / packaging
 .Python

CHANGELOG.md

@@ -15,6 +15,7 @@ Types of changes:
 ## Unreleased
 
 ### Added
+- Added a statevector simulator as a new `pyqasm.simulator` subpackage, backed by a Cython/OpenMP-capable kernel (`pyqasm.accelerate.sv_sim`). `Simulator.run()` accepts an OpenQASM 3 string or an unrolled `QasmModule` and returns a `SimulatorResult` with the final statevector, probabilities, and sampled measurement counts. Ships with cross-validation tests against qiskit (`test-sim` extra), an optional `simulation` extra (numba-accelerated preprocessing helpers), and a `benchmarks/` suite. ([#316](https://github.com/qBraid/pyqasm/pull/316))
 - Added support for the `c3x` (3-controlled X) and `rc3x`/`rcccx` (relative-phase 3-controlled X) gates, decomposed into basis gates following qiskit's `C3XGate`/`RC3XGate` definitions. Also extended the `ctrl @` modifier chain so that 3- and 4-control stacks on `x` (e.g. `ctrl @ ctrl @ ctrl @ x`, `ctrl(4) @ x`) resolve to `c3x`/`c4x`. ([#320](https://github.com/qBraid/pyqasm/pull/320))
 
 ### Improved / Modified
@@ -27,6 +28,7 @@ Types of changes:
 ### Fixed
 - Fixed `reset` on a physical qubit rewriting the operand to the internal pulse register, e.g. `reset $2;` unrolled to `reset __PYQASM_QUBITS__[2];`. That names a register the program never declares, so the unrolled output did not round-trip through `dumps()`/`loads()`, and the qubit was never registered (a program whose only operation was `reset $3;` reported `num_qubits == 0`). Physical qubits are now kept as-is in plain QASM programs, matching how gate and measurement operands already treat them; the rename is still applied for OpenPulse programs, where the pulse visitor expects it. ([#325](https://github.com/qBraid/pyqasm/pull/325))
 - Fixed `measure` and `reset` on a user register whose name merely starts with the reserved internal register name (e.g. `__PYQASM_QUBITS__foo`) being mistaken for the internal register itself. Such statements were short-circuited out of unrolling and emitted verbatim, so `c = measure __PYQASM_QUBITS__foo;` was never expanded per qubit and `reset __PYQASM_QUBITS__foo;` silently reset nothing. The register is now matched on its exact name, or on the name followed by an index or slice. ([#325](https://github.com/qBraid/pyqasm/pull/325))
+- Fixed the statevector simulator's `crz` fast path, which implemented a controlled-phase gate (`diag(1, 1, 1, e^{i*theta/2})`) instead of a true controlled-Rz (`diag(1, 1, e^{-i*theta/2}, e^{i*theta/2})`); it dropped the phase on the `|control=1, target=0>` amplitude. It now applies the full `Rz` to the target via the controlled-gate kernel. ([#316](https://github.com/qBraid/pyqasm/pull/316))
 - Fixed the `c4x` (4-controlled X) gate, which previously raised `TypeError: c4x_gate() takes 4 positional arguments but 5 were given` because it was declared with four parameters for a five-qubit gate. It is now implemented via qiskit's structured `rc3x`/`c3sx`/`cphaseshift` decomposition. ([#320](https://github.com/qBraid/pyqasm/pull/320))
 - Added `inv @` (inverse modifier) support for the multi-controlled-X family: `inv @ c3x` / `inv @ c4x` resolve to the (self-inverse) gate, and `inv @ rc3x` / `inv @ rcccx` resolve to the correct relative-phase dagger. These previously raised `Unsupported / undeclared QASM operation`. ([#320](https://github.com/qBraid/pyqasm/pull/320))
 - Fixed the `ctrl @` modifier not resolving gate aliases: `ctrl @ toffoli` / `ctrl @ ccnot` (aliases of `ccx`) and `ctrl @ cnot` / `ctrl @ CX` (aliases of `cx`) now escalate controls identically to their canonical gate instead of raising `Unsupported controlled QASM operation`. ([#320](https://github.com/qBraid/pyqasm/pull/320))

MANIFEST.in

@@ -2,4 +2,8 @@ include README.md
 recursive-include src/pyqasm *.py *.pyx
 include src/pyqasm/py.typed
 
-exclude tests/*
+# Never ship Cython-generated C: sdists compile from .pyx (Cython is a build
+# requirement), and stale generated C must not mask the .pyx sources.
+global-exclude *.c
+
+exclude tests/*

benchmarks/README.md

@@ -0,0 +1,78 @@
+# Benchmarks
+
+Scripts and reference results for the PyQASM statevector simulator
+(`pyqasm.simulator.Simulator`).
+
+## Contents
+
+| File | What it is |
+| --- | --- |
+| `bench_simulator.py` | Benchmarks PyQASM against Qiskit Aer, Cirq, and PennyLane Lightning on shared random and QFT circuits, with cross-simulator correctness checks. |
+| `plot_benchmarks.py` | Runs the same benchmarks and renders log-scale comparison plots (`bench_random.png`, `bench_qft.png`). |
+| `profile_simulator.py` | Profiles the PyQASM simulator itself: cProfile, section timing (preprocess vs simulation vs post-processing), or per-kernel timing. |
+| `bench_random.png`, `bench_qft.png` | Committed comparison plots produced by `plot_benchmarks.py`. |
+| `bench_evolved.json`, `bench_qft_evolved.png`, `bench_random_evolved.png` | Historical before/after results for the evolved preprocessing change (see provenance note below). |
+
+## Requirements
+
+All scripts need only `pyqasm` (installed from this repo) for the PyQASM
+paths. Additional dependencies:
+
+- `bench_simulator.py`: optionally `qiskit` + `qiskit-aer`, `cirq`, and
+  `pennylane` (Lightning) for the comparison columns, and `tabulate` for the
+  summary table. Every one of these is optional — missing simulators are
+  reported as `skipped: <name> not installed` and the script runs the
+  remaining backends (worst case, PyQASM only).
+- `plot_benchmarks.py`: `matplotlib`, plus the same optional simulators as
+  `bench_simulator.py`. Plots include only the installed backends.
+- `profile_simulator.py`: no extra dependencies.
+
+None of these are declared as a package extra; install them ad hoc, e.g.
+`pip install qiskit qiskit-aer cirq pennylane tabulate matplotlib`.
+
+## Running
+
+From the repository root:
+
+```bash
+# Full benchmark table (up to 22 qubits; minutes of runtime)
+python benchmarks/bench_simulator.py
+
+# Smoke test: small circuits, 2 repeats
+python benchmarks/bench_simulator.py --quick
+
+# Regenerate bench_random.png / bench_qft.png in benchmarks/
+python benchmarks/plot_benchmarks.py
+
+# Quick plot run, writing PNGs somewhere else
+python benchmarks/plot_benchmarks.py --quick --out-dir /tmp/bench-plots
+
+# Profile the simulator (modes: section | cprofile | kernel)
+python benchmarks/profile_simulator.py --mode section --qubits 16 --depth 200
+python benchmarks/profile_simulator.py --mode cprofile --qubits 12 --depth 100
+python benchmarks/profile_simulator.py --mode kernel --qubits 12 --depth 100
+```
+
+Timing covers simulation only; circuit construction/transpilation is done in
+each backend's `prepare_*` step and excluded from the measured time. Reported
+numbers are the median of `N_REPEATS` runs (default 5; `--quick` uses 2,
+`--repeats N` overrides).
+
+## Provenance of the `*_evolved` files
+
+`bench_evolved.json`, `bench_qft_evolved.png`, and `bench_random_evolved.png`
+were produced during development of the evolved no-cache preprocessing change
+(PR #316). They compare two states of this branch:
+
+- **baseline**: the branch state *before* the evolved-preprocessing commit
+  (the previous statevector preprocessing implementation);
+- **candidate**: the branch with the evolved no-cache preprocessing.
+
+They are retained for historical reference only. They are **not** regenerated
+by any script in this tree: the baseline implementation no longer exists in
+the working tree, so the before/after comparison cannot be reproduced from
+the current sources alone. To reproduce something comparable, check out the
+commit preceding the evolved-preprocessing commit and benchmark both
+revisions with `bench_simulator.py`. Current-code performance can always be
+re-measured with `bench_simulator.py` / `plot_benchmarks.py`, which
+regenerate `bench_random.png` and `bench_qft.png`.

benchmarks/bench_evolved.json

@@ -0,0 +1,183 @@
+{
+  "benchmark": "statevector preprocessing no-cache comparison",
+  "baseline": "PyQASM sv branch before evolved preprocessing commit",
+  "candidate": "PyQASM sv branch with evolved no-cache preprocessing",
+  "n_repeats": 5,
+  "pyqasm_num_threads": 1,
+  "notes": [
+    "No QASM string memoization is included in the candidate.",
+    "Both series use pre-unrolled QasmModule inputs, matching the branch benchmark convention."
+  ],
+  "series": {
+    "random": [
+      {
+        "num_qubits": 4,
+        "depth": 20,
+        "pyqasm_sv_ms": 0.06092991679906845,
+        "evolved_no_cache_ms": 0.06546999793499708,
+        "speedup": 0.9306540204807044,
+        "correct": true
+      },
+      {
+        "num_qubits": 6,
+        "depth": 40,
+        "pyqasm_sv_ms": 0.1580890966579318,
+        "evolved_no_cache_ms": 0.1151899341493845,
+        "speedup": 1.372421104546456,
+        "correct": true
+      },
+      {
+        "num_qubits": 8,
+        "depth": 60,
+        "pyqasm_sv_ms": 0.16204908024519682,
+        "evolved_no_cache_ms": 0.14194007962942123,
+        "speedup": 1.1416724625509327,
+        "correct": true
+      },
+      {
+        "num_qubits": 10,
+        "depth": 80,
+        "pyqasm_sv_ms": 0.24963996838778257,
+        "evolved_no_cache_ms": 0.21547905635088682,
+        "speedup": 1.1585347208002805,
+        "correct": true
+      },
+      {
+        "num_qubits": 12,
+        "depth": 100,
+        "pyqasm_sv_ms": 0.458328053355217,
+        "evolved_no_cache_ms": 0.41990901809185743,
+        "speedup": 1.0914937131808757,
+        "correct": true
+      },
+      {
+        "num_qubits": 14,
+        "depth": 150,
+        "pyqasm_sv_ms": 1.5235739992931485,
+        "evolved_no_cache_ms": 1.3638049131259322,
+        "speedup": 1.117149516495739,
+        "correct": true
+      },
+      {
+        "num_qubits": 16,
+        "depth": 200,
+        "pyqasm_sv_ms": 7.1852849796414375,
+        "evolved_no_cache_ms": 5.937180016189814,
+        "speedup": 1.210218480835721,
+        "correct": true
+      },
+      {
+        "num_qubits": 18,
+        "depth": 250,
+        "pyqasm_sv_ms": 35.15114798210561,
+        "evolved_no_cache_ms": 28.548280941322446,
+        "speedup": 1.231287728124666,
+        "correct": true
+      },
+      {
+        "num_qubits": 20,
+        "depth": 300,
+        "pyqasm_sv_ms": 162.53185598179698,
+        "evolved_no_cache_ms": 126.72401999589056,
+        "speedup": 1.282565499319447,
+        "correct": true
+      },
+      {
+        "num_qubits": 22,
+        "depth": 400,
+        "pyqasm_sv_ms": 1289.0826460206881,
+        "evolved_no_cache_ms": 1231.460615992546,
+        "speedup": 1.0467916141854843,
+        "correct": true
+      }
+    ],
+    "qft": [
+      {
+        "num_qubits": 4,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 0.20883907563984394,
+        "evolved_no_cache_ms": 0.16430008690804243,
+        "speedup": 1.2710831720784765,
+        "correct": true
+      },
+      {
+        "num_qubits": 6,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 0.4983479157090187,
+        "evolved_no_cache_ms": 0.315018929541111,
+        "speedup": 1.5819618091997316,
+        "correct": true
+      },
+      {
+        "num_qubits": 8,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 0.9089269442483783,
+        "evolved_no_cache_ms": 0.5902479169890285,
+        "speedup": 1.5399070764789728,
+        "correct": true
+      },
+      {
+        "num_qubits": 10,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 1.5004950109869242,
+        "evolved_no_cache_ms": 1.0477059986442327,
+        "speedup": 1.4321718238977499,
+        "correct": true
+      },
+      {
+        "num_qubits": 12,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 2.5123610394075513,
+        "evolved_no_cache_ms": 1.782613922841847,
+        "speedup": 1.409369133279482,
+        "correct": true
+      },
+      {
+        "num_qubits": 14,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 5.448751035146415,
+        "evolved_no_cache_ms": 4.14173596072942,
+        "speedup": 1.3155718005226993,
+        "correct": true
+      },
+      {
+        "num_qubits": 16,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 18.029507948085666,
+        "evolved_no_cache_ms": 15.524596092291176,
+        "speedup": 1.1613511772482323,
+        "correct": true
+      },
+      {
+        "num_qubits": 18,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 77.3717820411548,
+        "evolved_no_cache_ms": 68.92851099837571,
+        "speedup": 1.1224931587885028,
+        "correct": true
+      },
+      {
+        "num_qubits": 20,
+        "depth": "QFT",
+        "pyqasm_sv_ms": 382.6392919290811,
+        "evolved_no_cache_ms": 349.38782698009163,
+        "speedup": 1.0951706452866319,
+        "correct": true
+      }
+    ]
+  },
+  "summary": {
+    "random": {
+      "geomean_speedup": 1.1521318658620598,
+      "min_speedup": 0.9306540204807044,
+      "max_speedup": 1.372421104546456,
+      "all_correct": true
+    },
+    "qft": {
+      "geomean_speedup": 1.3147632402156637,
+      "min_speedup": 1.0951706452866319,
+      "max_speedup": 1.5819618091997316,
+      "all_correct": true
+    }
+  }
+}