From Quantum X Labs

Nuclear Quantum

Our research focuses on leveraging quantum computing to accelerate particle transport simulations and enable higher-fidelity modeling across a broad range of scientific and engineering applications.

Introduction

Nuclear engineering

Applications of Nuclear Engineering

Nuclear engineering applies principles of physics to understand and utilize nuclear processes in areas such as energy production, medicine, industry, and scientific research. It enables highly efficient energy generation, advanced medical imaging and cancer treatments, radiation-based technologies, and precise analysis of materials and physical systems.

Future Directions and Impact

Through continued development of safer reactor technologies, improved radiation applications, and advanced computational tools, nuclear engineering can contribute to reliable low-carbon energy, better healthcare, and technological innovation.

Utilizing radioactive tracers and radiation for medical imaging, diagnosis, and targeted treatment

Nuclear reactors generate large amounts of reliable electricity with very low greenhouse-gas emissions during operation. Nuclear power can contribute to reducing dependence on fossil fuels while supporting stable, large-scale electricity production.

Nuclear physics supports space exploration through spacecraft power systems, radiation shielding, and the study of energetic particles in space. These technologies are particularly important for long-duration missions and exploration far from the Sun.

The bottleneck

Every nuclear design today is a compromise with the compute budget.

Monte Carlo transport converges as 1/√N — halving the statistical error costs four times the compute. Add heterogeneous geometry and the wall arrives well before the physics demands it.

```xml AFFORDABLE COMPUTE Past this line, something gets cut MODEL FIDELITY → COMPUTE COST → ```

What gets cut

Cut 1

Coarser geometry

Heterogeneous structure gets homogenized away, directly affecting the fidelity.

Cut 2

Fewer histories

Statistical error stays higher than anyone wants, because halving it costs four times the compute.

Cut 3

Wider safety margins

Uncertainty gets absorbed by over-engineering: heavier shielding, higher radioactive dosage, more conservative limits.

Deep Tech

Quantum computing

The rapidly advancing field of quantum technologies, and quantum computing in particular, offers significant potential for addressing computationally demanding problems.

By exploiting quantum phenomena such as superposition and entanglement, quantum algorithms may provide substantial speedups for specific classes of calculations that are challenging for classical computers.

Emerging Potential

Quantum computing offers significant potential for solving computationally demanding problems.

Quantum Phenomena

Leverages superposition and entanglement — core quantum mechanical properties.

Computational Speedup

Enables substantial speedups for calculation types that challenge classical computers.

Our research focus

At Nuclear Quantum, we explore how these emerging capabilities can be applied to particle transport simulations. Our research focuses on developing:

Hybrid quantum-classical algorithms

Advanced random-walk schemes

both designed to reduce the computational burden of high-fidelity transport modeling.

Our goal

Develop an adaptive quantum oracle that combines efficient state preparation with transport calculations and can be integrated into Quantum Amplitude Estimation (QAE) — enabling high-precision estimates with reduced computational cost.

Work with Us

Get in Touch

Whether you're a reactor developer, national laboratory, quantum hardware partner, or investor — we'd like to hear from you. Fill out the form and our team will respond within 48 hours.