qibo-final/qibojit-benchmarks/scripts/quimb

Quimb Benchmark Suite

Local (single-process) tensor network simulation benchmarking using quimb backend.

Files

• quimb_local.sh — Main benchmark sweep script (no MPI)
• expectation_mps.json — Expectation mode with MPS (default for expectation)
• expectation_dense.json — Expectation mode, dense tensor network
• dense_vector_mps.json — State extraction with MPS (default for state)
• dense_vector_dense.json — State extraction, dense tensor network

Configuration Files

Expectation Modes (computing Hamiltonian expectation values)

• expectation_mps.json: Uses Matrix Product State (MPS) tensor network ansatz; good for larger systems with limited bond dimension
• expectation_dense.json: Uses dense tensor network; full contraction without MPS truncation

State Modes (full state vector computation)

• dense_vector_mps.json: Extracts full state using MPS contraction (faster, bounded memory)
• dense_vector_dense.json: Extracts full state using dense tensor (maximum memory usage)

Usage

cd /ssd_data/tankya2/code/ASC_2026_prism/ASC-2026/qibojit-benchmarks/scripts/quimb

# Run with defaults (all matching dense_vector*.json and expectation*.json configs)
./quimb_local.sh

# Test only expectation mode, custom qubit sizes
modes="expectation" nqubits_list="8 10 12" ./quimb_local.sh

# Test dense vector only with one explicit config
state_cfg=dense_vector_dense.json modes="dense_vector" ./quimb_local.sh

# Restrict the sweep to a chosen subset of configs
EXPECTATION_CONFIGS="expectation_mps.json expectation_dense.json" ./quimb_local.sh

# Test variational and BV circuits
circuits="variational bv" nqubits_list="6 8 10" nreps=3 ./quimb_local.sh

Supported Circuits

✓ Fully Supported (Numerically Validated)

Circuit	Alias	Parameters	Status	Notes
qft	—	none	✓ Works	Quantum Fourier Transform; aligned with qibojit
supremacy	—	depth, seed	✓ Works	Verified locally after environment repair; requires Cirq import path to be healthy
variational	—	nlayers	✓ Works	Parameterized circuit; aligned with qibojit
bv	bernstein-vazirani	none	✓ Works	Bernstein-Vazirani algorithm; aligned with qibojit
hs	hidden-shift	none	✓ Works	Hidden-shift problem; aligned with qibojit
qaoa	—	nlayers	✓ Works	QAOA with RZZ gate support; aligned with qibojit

❌ Not Supported

Circuit	Issue	Notes
qv	Qiskit API compatibility	quantum-volume uses deprecated qiskit .qasm() method (v3.0+); not specific to quimb

Implementation Notes

• RZZ Gate: Full support for QAOA and algorithms using two-qubit Ising rotations
• cu1 Gate: Fully supported in expectation value mode (QFT compatible)
• Numerical Alignment: All benchmarks automatically include qibojit (numba) reference with identical observable for validation

Environment Variables

Variable	Default	Description
nqubits_list	6 8 10	Space-separated qubit counts to benchmark
circuits	supremacy qft variational bv qaoa	Space-separated circuit names
modes	dense_vector expectation	Benchmark modes (dense_vector, expectation)
nlayers	2	Layers for layered circuits (variational, qaoa)
nreps	1	Repetitions per benchmark
filename	quimb_benchmark_local.dat	Output log file
precision	complex128	NumPy dtype (complex128 or complex64)
exp_cfg	unset	Optional single expectation config; when unset, all expectation*.json files are swept
state_cfg	unset	Optional single dense-vector config; when unset, all dense_vector*.json files are swept
EXPECTATION_CONFIGS	unset	Optional space-separated subset of expectation configs to run
STATE_CONFIGS	unset	Optional space-separated subset of dense-vector configs to run

Results

Results are logged to /qibojit-benchmarks/benchmarks/results/ with filename quimb_benchmark_local.dat (configurable).

Each benchmark includes:

• import_time — Backend initialization time
• creation_time — Circuit creation time
• dry_run_time — First execution time (warm-up)
• simulation_times — Execution times for nreps runs
• expectation_result — Observable expectation values (for expectation mode)

Observable

By default, expectation uses:

• X on qubit 0, identity on remaining qubits
• Configurable via pauli_pattern in JSON config (e.g., "XIIII" for 5 qubits)

Reference Validation

Each benchmark run automatically includes a qibojit (numba) reference with the same observable configuration, enabling direct numerical comparison for validation.

Example:

[expectation MPI] quimb + qft @ 6q:     0.2019...
[qibojit ref]     numba + qft @ 6q:     0.2019...  ✓ aligned

MPI Support

For MPI-enabled benchmarking (multiple processes), see the parallel suite in /scripts/quimb_mpi/:

cd /ssd_data/tankya2/code/ASC_2026_prism/ASC-2026/qibojit-benchmarks/scripts/quimb_mpi
./quimb_mpi.sh  # runs with mpirun -np 2

Tensor Network Options

Quimb supports both MPS (Matrix Product State) and dense tensor network contractions. By default the script sweeps every matching JSON file in this folder, or you can target individual configs:

# Compare MPS vs dense at same nqubits
exp_cfg=expectation_mps.json nqubits_list="12" ./quimb_local.sh
exp_cfg=expectation_dense.json nqubits_list="12" ./quimb_local.sh

MPS is typically faster and uses bounded memory, while dense provides full accuracy without truncation.

Installation

Preferred path: create a fresh environment from the benchmark spec.

cd /ssd_data/tankya2/code/ASC_2026_prism/ASC-2026/qibojit-benchmarks
conda env create -f environment.yml
conda activate benchmarks

If you are using an existing environment instead of recreating it, check that it is aligned with the benchmark stack:

python -c "import numpy, qibo, qibojit; print('numpy', numpy.__version__); print('qibo', qibo.__version__); print('qibojit', qibojit.__version__)"

Dependency Recovery

pip install cirq==0.8.2

This is the recovery path that eventually made ./quimb_local.sh work for supremacy in the existing qibotn-py311-test environment.

Symptom 1: cirq failed with ModuleNotFoundError: No module named 'pkg_resources'

Cause:

• the existing environment had setuptools 82.0.1
• that install did not expose pkg_resources
• the installed cirq package still imported pkg_resources during startup

Fix:

/home/tankya2/miniforge3/envs/qibotn-py311-test/bin/python -m pip install "setuptools<81"

Working result:

• setuptools was changed to 80.10.2
• import pkg_resources worked again
• the Quimb supremacy path could construct the Cirq-generated circuit

Symptom 2: qibojit reference crashed with TypeError: asarray() got an unexpected keyword argument 'copy'

Cause:

• the same environment had numpy 1.26.4
• but qibo 0.3.1 requires numpy >= 2.0.0
• the qibojit reference backend was therefore running against an incompatible NumPy version

Fix:

/home/tankya2/miniforge3/envs/qibotn-py311-test/bin/python -m pip install numpy==2.2.6

Working result:

• numpy was changed to 2.2.6
• the qibojit reference backend started working again
• both the Quimb and qibojit sides of the supremacy benchmark completed successfully

Final verified state

The existing repaired environment was verified with:

cd /ssd_data/tankya2/code/ASC_2026_prism/ASC-2026/qibojit-benchmarks/scripts/quimb
nqubits_list="6" circuits="supremacy" nreps=1 modes="dense_vector expectation" ./quimb_local.sh

That smoke test completed all three stages:

• Quimb dense_vector
• Quimb expectation
• qibojit reference

Notes:

• environment.yml remains the preferred source of truth for a clean install
• the repaired environment may still emit a pkg_resources deprecation warning from the older Cirq stack, but the benchmark run succeeds
• if an environment has drifted far from environment.yml, recreating it is usually safer than incremental repair

Notes

• Intel MPI Fabric: On Prism cluster, shared-memory fabric (I_MPI_FABRICS=shm) is automatically enabled for single-node runs
• QFT Support: Fixed cu1 gate compatibility in quimb backend; no platform-specific gate limitations
• Bond Dimension: MPS modes use max_bond_dimension=20 by default; adjust in JSON for memory/accuracy tradeoff