Presenting vqpu-sdk: an open-source quantum SDK with circuit knitting and a novel variational optimizer — tested live on IonQ
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vqpu-sdk has been developed as a quantum computing SDK that abstracts hardware differences. Users write a single circuit and execute it on CPU, Apple GPU, NVIDIA GPU, IonQ, IBM, or any supported backend using the same API without requiring rewrites. Two aspects may interest the community: Circuit knitting with exact results for controlled-gate cuts.** For CNOT/CZ gates cut at the control wire, the Z-basis decomposition achieves exact reconstruction with zero sampling overhead, avoiding any quasi-probability penalty. A 10-qubit GHZ state, when partitioned into two 5-qubit fragments, reconstructs perfectly, yielding only |0000000000⟩ and |1111111111⟩ outcomes, verified at 4096 shots. from vqpu import UniversalvQPU, CutFinder, CircuitKnitter qpu = UniversalvQPU() circuit = qpu.circuit(10, "ghz") circuit.h(0) for i in range(9): circuit.cnot(i, i + 1) plan = CutFinder.auto_partition(circuit, max_fragment_qubits=5) result = CircuitKnitter(plan).run(executor=qpu.run, shots=4096) print(result.counts) # {'0000000000': 2048, '1111111111': 2048} A new variational optimizer: Cryo-Canonical Basin Weaving.** Rather than relying on blind gradient descent, the CCBW optimizer explores the parameter landscape using a 3-3+1 motif (3 directions + 3 mirrors + center = 7 evaluations per candidate). Mirror-balance filtering rejects saddle points, and the algorithm preferentially refines flat, noise-tolerant basins. Testing on IonQ's cloud simulator involved 320 circuit evaluations, achieving an 89% approximation ratio on Max-Cut, with 72% of final shots hitting the optimal bitstring. Install: pip install vqpu-sdk - GitHub: https://github.com/sciencemaths-collab/vqpu - PyPI: https://pypi.org/project/vqpu-sdk/ All 33 validation tests pass across every module. Feedback is welcome, particularly from those experienced in circuit cutting or variational optimization. — Bernard Essuman submitted by /u/Substantial-Serve675 [link] [comments]