Researchers Crack the Code to Simulating Error-Proof Quantum Machines

Quantum Computer Simulation Method Could Speed Progress

Scientists have developed the first method to simulate error-corrected quantum computers using conventional machines—a critical advance that could accelerate the development of truly reliable quantum technologies. The technique, created by researchers at Chalmers University of Technology and international partners, tackles one of quantum computing’s biggest challenges: verifying that quantum calculations are correct when the systems themselves are prone to errors that conventional computers can barely track.

Published in Physical Review Letters, the research focuses on simulating quantum computers that use specialized error-correction codes called Gottesman-Kitaev-Preskill (GKP) states—a leading approach for building fault-tolerant quantum systems that major tech companies and research labs are actively pursuing.

The Verification Challenge

Quantum computers promise to solve complex problems beyond the reach of today’s supercomputers, with potential applications in medicine, energy, encryption, artificial intelligence, and logistics. However, these systems face a fundamental obstacle: quantum calculations are extraordinarily error-prone and those errors are difficult to detect and correct.

“We have discovered a way to simulate a specific type of quantum computation where previous methods have not been effective,” explains Cameron Calcluth, PhD in Applied Quantum Physics at Chalmers and first author of the study. “This means that we can now simulate quantum computations with an error correction code used for fault tolerance, which is crucial for being able to build better and more robust quantum computers in the future.”

To verify quantum computer accuracy, researchers must simulate the calculations using conventional computers—a task so computationally demanding that sometimes even the world’s most powerful supercomputers would need the age of the universe to reproduce quantum results.

Why Error Correction Matters

Quantum computers derive their power from qubits that can simultaneously hold multiple values through a phenomenon called superposition. This creates exponential computational capacity as more qubits are added, but also makes the systems extremely fragile.

“The slightest noise from the surroundings in the form of vibrations, electromagnetic radiation, or a change in temperature can cause the qubits to miscalculate or even lose their quantum state, their coherence, thereby also losing their capacity to continue calculating,” Calcluth notes.

The solution involves error correction codes that distribute quantum information across multiple systems, allowing errors to be detected and fixed without destroying the quantum computation. The GKP approach encodes information into the multiple energy levels of vibrating quantum systems—but this complexity has made simulation nearly impossible until now.

Mathematical Innovation Enables Simulation

The breakthrough required developing new mathematical tools specifically designed for the unique challenges of GKP systems. The research team’s key innovations include:

• Creating a specialized algorithm that can handle the infinite energy levels inherent in GKP codes
• Developing the Zak-Gross Wigner function that positively represents ideal quantum states while tracking problematic “negative” states
• Establishing efficient methods to simulate up to 1000 quantum modes with minimal computational overhead
• Proving that simulation complexity scales with the “negativity” of quantum states rather than system size

Practical Impact for Quantum Development

“The way it stores quantum information makes it easier for quantum computers to correct errors, which in turn makes them less sensitive to noise and disturbances,” explains Giulia Ferrini, Associate Professor of Applied Quantum Physics at Chalmers and co-author. “Due to their deeply quantum mechanical nature, GKP codes have been extremely difficult to simulate using conventional computers. But now we have finally found a unique way to do this much more effectively than with previous methods.”

The simulation method proves particularly powerful for highly “squeezed” quantum states—those with precisely controlled properties that are essential for fault-tolerant quantum computing. For states with 12 decibels of squeezing, considered necessary for practical quantum error correction, the algorithm can simulate circuits with up to 1000 modes using less than double the computational resources needed for a single mode.

This efficiency represents a dramatic improvement over existing approaches and could enable researchers to validate quantum computer designs before building expensive hardware. The method also provides a pathway for benchmarking early quantum processors and understanding how different error-correction strategies perform under realistic conditions.

“This opens up entirely new ways of simulating quantum computations that we have previously been unable to test but are crucial for being able to build stable and scalable quantum computers,” Ferrini emphasizes.

As quantum computing moves from laboratory curiosity toward practical application, tools like this simulation method become essential for ensuring these powerful machines work as intended—bringing reliable quantum computation closer to reality.