The future of quantum surgery is now

Variational Quantum Path Planning

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Kryptur Research presents an end-to-end VQPP pipeline — from GPU-accelerated 3D anatomy to QUBO formulation and one-layer QAOA on IBM's 156-qubit Kingston processor.

10.5281/zenodo.20672535Raja RamGitHub
GPU speedup
5.8×
CuPy vs. SciPy on 256³ volume
Pre-processing
2.86 s
256³ volume · 200 waypoints
IBM Kingston
156
Qubits · 14-qubit QAOA circuit
Safe margin 6 mm
0/10
Classical reachability — graphs disconnected

Research highlights

Variational Quantum Path Planning for Robotic Surgery: Experimental Validation on IBM Kingston and GPU-Accelerated Anatomy

Research Paper
Raja Ram · Muskan S · Vipul Jain · Kalinga Swain

NISQ hardware can participate in surgical path planning. A 14-qubit QAOA circuit on IBM Kingston sampled a valid path through an 8-node surgical graph, while GPU distance transforms enable sub-3 s intra-operative replanning on 256³ anatomical volumes.

QAOASurgical RoboticsQUBO

GPU-accelerated pre-processing scales to 200 waypoints

Figure 1
2× RTX 5090 cluster · Vast.ai
GPUCuPy

Vascular phantom — realistic branching anatomy

Figure 2
6.1× GPU speedup on complex obstacles
PhantomTopology

IBM Kingston QAOA-planned surgical path

Figure 3
4096 shots · p = 1 QAOA layer
Quantum HardwareNISQ
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Results & figures

Table 1. Distance-transform runtime (256³ obstacle mask)
MethodTime (s)Relative speed
GPU (CuPy)0.327Baseline (fastest)
CPU (SciPy)1.8851.0×
GPU speedup—5.8×
Table 2. Classical vs. quantum solver (8-node surgical graph)
SolverPathCostExecution time
Classical SA[0, 3, 5, 7]70.20< 0.1 s
IBM Kingston QAOA[0, 7]1109.24≈ 3.5 s (QPU)
Pre-processing time vs volume size and waypoints
Figure 1a. Pre-processing time vs. volume size and waypoint count.
GPU vs CPU distance transform bar chart
Figure 1b. GPU vs. CPU distance transform on 256³.
Axial vascular phantom slice at z-index with vessel structure
Figure 2. Axial slice of the synthetic vascular phantom (white = vessels).
3D IBM Kingston QAOA-planned surgical path
Figure 3. Three-dimensional visualisation of the IBM Kingston QAOA-planned surgical path through the obstacle volume.

Full paper, datasets & API

Research Paper: https://doi.org/10.5281/zenodo.20672535 · Open access · Zius Research Center · Kryptur OU

Research Paper

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