Quantum Elements and Planckian Partner on Digital Twins for Superconducting Quantum Processors

Insider Brief

• Quantum Elements and Planckian announced a development agreement to use AI-powered digital twins to support error correction research for Planckian’s superconducting quantum processors.
• Quantum Elements will develop architecture-specific noise models and simulation capabilities to help evaluate quantum error correction strategies for Planckian’s processor designs.
• The collaboration aims to improve understanding of hardware noise characteristics and support the development of scalable fault-tolerant quantum computing systems.

Press release – Quantum Elements, a provider of AI-powered digital twins for quantum computing developers, today announced a development agreement with Planckian, an Italian quantum computing company pioneering a novel superconducting quantum processor architecture, to support Planckian‘s error correction strategy.

Through this collaboration, Quantum Elements will develop architecture-specific noise models and digital twin capabilities to characterize the physical noise environment of Planckian‘s superconducting architectures, accounting for coherence, leakage and operation-level error sources. The work will support Planckian in evaluating QEC schemes’ performance across its unique processor designs.

“Our Digital Twins platform can accurately mirror quantum systems on classical computers, leading to a clear development path from system co-design to quantum error correction and all the way to fault tolerant quantum computing for Planckian and other quantum hardware companies,” said Izhar Madelsy, co-founder and CEO of Quantum Elements. “We’ve shown that both theoretically and practically.” 

“Our architecture removes the control complexity & infrastructure overhead that typically prevents conventional superconducting processors from scaling. However, a new approach also reshapes the errors the system has to contend with,” said Michele Dallari, co-founder and CEO of Planckian. “That makes architecture-specific characterization essential: we need a faithful picture of our own noise environment before we decide how to correct it. Quantum Elements‘ digital twins enable us to evaluate error-correction schemes against a realistic model of our processors, on classical hardware and well ahead of scaling, the kind of groundwork a credible path to fault tolerance actually depends on.”

While quantum processors are becoming increasingly sophisticated, they are still affected by environmental noise, crosstalk between qubits, and control imperfections. These effects are obstacles to developing fault-tolerant quantum computers. To study this behavior, researchers often simulate quantum systems on classical computers. One way to do this is direct density-matrix simulation, which tracks a noisy quantum system, including both its quantum state and its interaction with the environment. However, the amount of information required to represent the system becomes prohibitive as qubit counts grow.  

Quantum Elements’ Digital Twins technology allows researchers to model noisy quantum-circuit behavior with lower computational resources while preserving the dynamics needed to study quantum error correction, correlated noise, and decoder performance.

The practical application of this method was demonstrated in an AWS collaboration with Quantum Elements, USC, and Harvard, where researchers used a Quantum Monte Carlo-accelerated digital twin to simulate a 97-physical-qubit, distance-7 surface-code syndrome-extraction round on classical high-performance computing infrastructure. AWS reported that a brute force, full open-system simulation of the same system would require tracking 497 density-matrix entries, while the QMC-based method ran in about an hour on a single compute node.