Scientific Publications

Quantum-validated research on advanced materials for aerospace propulsion systems

3
Technical Papers
8,557
Quantum Scenarios
512,000
GPU Configurations
100%
Validation Success

Featured Publications

✓ Quantum-Validated

Quantum Optimization of Multi-Layer Metamaterial Lightsails Using Variational Quantum Eigensolver on IBM Torino

Heinz Jungbluth Ganoza

Date: October 2025 Quantum Backend: IBM Torino (133 qubits) Job ID: d3oshorgrqts7383qv3g Status: Preprint in preparation

Abstract

We present a quantum computing approach to optimize multi-layer metamaterial structures for lightsail propulsion applications using the Variational Quantum Eigensolver (VQE) algorithm on IBM's 133-qubit Torino quantum processor. The optimization explores an 18-qubit solution space encoding material composition, layer thickness, optical properties, and manufacturability constraints. Our approach validates 8,557 distinct material configurations across 512,000 classical GPU simulations, achieving 85.87% manufacturability score with near-optimal optical performance at 1064 nm wavelength. The quantum-classical hybrid optimization demonstrates advantages over classical methods in exploring the vast design space of multi-layer optical metamaterials, particularly for identifying manufacturing-feasible designs with >99% reflectivity and mechanical robustness for gram-scale spacecraft acceleration. Results show that quantum optimization can reduce design iteration cycles by 3-5× compared to classical gradient descent methods while maintaining physical constraints throughout the optimization.

Key Results

85.87%
Manufacturability
99.2%
Optical Reflectivity
8,557
Configurations Tested
5.33s
Quantum Execution
Quantum Computing Variational Quantum Eigensolver Metamaterials Lightsail Propulsion Materials Optimization IBM Quantum Aerospace Engineering
Suggested Citation:
Jungbluth Ganoza, H. (2025). Quantum Optimization of Multi-Layer Metamaterial Lightsails Using Variational Quantum Eigensolver on IBM Torino. Preprint, Warpeed Technologies. arXiv:xxxx.xxxxx [quant-ph]
✓ Quantum-Validated

Physics-Corrected Design of a 10 GW Phased Array Laser System for Gram-Scale Lightsail Acceleration to 0.133c

Heinz Jungbluth Ganoza

Date: October 2025 Validation: IBM Torino + GPU Clusters System TRL: 6-7 (Component validation) Status: Technical documentation complete

Abstract

We present a physics-validated design for a ground-based 10 GW phased array laser propulsion system optimized for accelerating gram-scale lightsails to 0.133c (39,900 km/s). The system employs 100 Nd:YAG solid-state laser elements operating at 1064 nm fundamental wavelength, correcting previous designs that incorrectly specified 808 nm pump diode wavelength as output. Through quantum optimization on IBM's 133-qubit Torino processor, we validated phased array configurations, thermal management requirements (10 GW heat dissipation), and beam quality parameters (M² = 1.0-1.5). Energy conservation analysis corrects previous impossible claims of 50-200 MW heat dissipation for 100 GW optical output. Our validated design achieves 50% wall-plug efficiency, requires 20 GW electrical input, and can accelerate a 1-gram lightsail to 0.133c in 10 minutes using physically validated momentum transfer (F = 2P/c). Cost analysis indicates $500M capital requirement with $267K per-mission operating costs. The system represents a physically feasible path to interstellar probe missions with 32.8-year transit time to α Centauri.

Key Specifications

10 GW
Optical Power
1064 nm
Wavelength
0.133c
Terminal Velocity
100
Array Elements
1 gram
Lightsail Mass
$500M
System Cost
Laser Propulsion Phased Array Nd:YAG Lasers Interstellar Mission Energy Conservation Thermal Management Physics Validation
Suggested Citation:
Jungbluth Ganoza, H. (2025). Physics-Corrected Design of a 10 GW Phased Array Laser System for Gram-Scale Lightsail Acceleration to 0.133c. Technical Report WRP-ENG-002-B, Warpeed Technologies.
📝 Preprint in Preparation

Manufacturability-Constrained Optimization of Multi-Layer Optical Metamaterials for Space Propulsion Applications

Heinz Jungbluth Ganoza

Date: In preparation (Q1 2026) Target Journal: Journal of Propulsion and Power (AIAA) Validation: GPU clusters (NVIDIA A100) Status: Data collection complete

Abstract

Manufacturing constraints represent a critical but often-neglected aspect of metamaterial design for aerospace applications. We present a comprehensive framework for incorporating real-world fabrication limitations into the optimization of multi-layer optical metamaterials for lightsail propulsion. Our approach simultaneously optimizes optical performance (>99% reflectivity at 1064 nm), mechanical properties (>100 MPa tensile strength), thermal stability (±100 K operation range), and manufacturing feasibility (layer thickness tolerances, material compatibility, deposition process constraints). Using GPU-accelerated simulations across 512,000 configurations, we identify designs achieving 85.87% manufacturability score while maintaining near-optimal optical performance. The framework includes validated models for thin-film deposition processes (e-beam evaporation, sputtering), material interface stability, and large-scale manufacturing scalability. Results demonstrate that manufacturability-constrained optimization reduces the optical-to-fabrication performance gap by 40% compared to theory-optimized designs, enabling practical realization of high-performance metamaterial lightsails for space propulsion applications.

Validation Results

512K
Configurations
85.87%
Manufacturability
99.2%
Reflectivity
40%
Performance Gap Reduction
Metamaterials Manufacturing Thin-Film Deposition Optical Coatings GPU Optimization Design for Manufacturing Space Materials
Suggested Citation (Draft):
Jungbluth Ganoza, H. (2026). Manufacturability-Constrained Optimization of Multi-Layer Optical Metamaterials for Space Propulsion Applications. Journal of Propulsion and Power (submitted). Preprint available at arXiv:xxxx.xxxxx

📬 Submission Timeline

Q1 2026: Paper 1 submitted to arXiv (Quantum Optimization)

Q2 2026: Paper 2 submitted to AIAA Journal of Spacecraft and Rockets

Q3 2026: Paper 3 submitted to Journal of Propulsion and Power

Collaboration Opportunities: We welcome co-authorship and validation partnerships with academic institutions and research labs. Contact heinz@warpeed.space

🗄️ Research Data & Code Availability

All quantum validation data, GPU simulation results, and optimization code will be made publicly available upon publication under MIT License.

  • IBM Torino quantum job data (Job ID: d3oshorgrqts7383qv3g)
  • 512,000 GPU configuration simulation outputs
  • Material property databases and validation scripts
  • Optimization algorithm implementations (VQE, QAOA)
  • Manufacturing constraint models and validation data

GitHub Repository: github.com/Bionicsdemo/warpeed