Six-dimensional Manifold Engine cracks the quantum simulation problem of medium and large scale, Zhenyuan Software seeks RMB 10 million Angel round financing

Industry Pain Points: The "Impossible Triangle" in Quantum Simulation

Addressing the industry pain points of "small scale of accurate simulation and low precision of network simulation" in the current field of quantum entanglement simulation, Zhenyuan Software recently announced the successful development of a simulation engine for the "six - dimensional manifold - coupled entanglement network". This technology aims to fill the market gap in medium - and large - scale quantum network simulation. The verification of the core principle has been completed, and an angel round of financing of 10 million yuan is being launched.

With the rise of the quantum Internet and embodied intelligence, the industry's demand for the simulation of medium - and large - scale quantum entanglement networks is becoming increasingly urgent. However, existing technologies face severe challenges: Microscopic accurate simulation is limited by the memory wall of classical computing platforms and can only support small - scale simulations of less than 50 qubits; Macroscopic network simulation can support thousands of nodes but ignores core physical dynamics such as entanglement degree fluctuations and decoherence evolution. At the same time, the in - memory computing architecture lacks natively adapted scientific computing scenarios, and existing simulation algorithms cannot fully unleash the parallel energy - efficiency potential of in - memory computing chips.

Technological Breakthrough: A Self - Organizing Simulation Engine Driven by High - Dimensional Manifolds

The new simulation engine proposed by Zhenyuan Software breaks through the paradigm limitations of the traditional "static space container" and constructs a closed - loop dynamic mechanism of "spatiotemporal structure - energy coupling - entanglement generation and annihilation". This technology is based on a six - dimensional hyper - cubic spherical composite manifold as the system base, making the spatial structure a dynamic variable participating in the evolution rather than a static background.

The core technologies include a high - dimensional manifold base, self - organizing dynamics, dual - channel interaction, and a native in - memory computing architecture. Through orthogonal rotation transformation, the distance field between particles is reconstructed in real - time. The distance field directly regulates the entanglement coupling strength, and the entanglement distribution forms a global energy field, ultimately forming a complete dynamic closed - loop. Based on three physical constraints of decoherence dissipation, near - field coupling generation, and global energy conservation, the entanglement network autonomously completes generation, annihilation, and fluctuations, with typical living - state self - organizing characteristics.

In tests on a general - purpose home computing platform (CPU environment), the engine demonstrated excellent performance: It supports 576 particle nodes and maintains more than 130,000 active entanglement pairs in a steady state; The average time for a single - step complete evolution is about 290 ms, with a performance fluctuation of less than 1%, and the performance is improved by more than an order of magnitude compared with traditional simulation frameworks. After running continuously for more than 3000 steps, the total system energy, the number of entanglement pairs, and the system entropy all remain in a stable range, showing typical self - organizing critical state characteristics.

Application Prospects: Empowering Quantum Technology and Next - Generation Computing Power

This engine has significant paradigm - level application value and can provide underlying support for multiple cutting - edge fields. In the aspect of quantum Internet networking, it can serve as a numerical experiment platform for large - scale quantum entanglement networks, used for the location selection of relay stations in quantum metropolitan area networks and the optimization of entanglement distribution routing, reducing the trial - and - error cost of real networking. In the field of embodied intelligence motion planning, the high - dimensional manifold base can be directly mapped to the joint configuration space of humanoid robots, transforming complex inverse kinematics problems into geodesic searches and alleviating the Sim - to - Real migration gap.

At the same time, this technology can serve as a native scientific computing benchmark for the in - memory computing architecture, verify the energy - efficiency advantages of in - memory computing chips in the field of complex system simulation, promote their expansion from AI - specific to general - purpose scientific computing, and contribute to the industrial implementation of the next - generation computing power architecture. In addition, the engine can also provide a new numerical experiment platform for cutting - edge problems in complex systems such as dissipative structures, self - organizing criticality, and multi - body entanglement emergence.

Zhenyuan Software plans to use the funds from this round of financing mainly for the R & D of GPU/FPGA parallel acceleration, the development of special versions for quantum networks/embodied intelligence, and the adaptation and docking of in - memory computing hardware, aiming to build the next - generation scientific computing power base.