Quantum X Labs' QuantumQ Security Achieves Technological Milestone On Three Operational IBM Quantum Processors

Quantum X Labs Inc. (NASDAQ:QXL) ("Quantum X Labs" or the "Company"), a quantum technology company developing solutions across quantum computing, quantum software, quantum cybersecurity and quantum sensing, today announced a technological milestone achieved by its quantum cybersecurity operation, QuantumQ Security, through the experimental validation of its LayerQake technology on three operational IBM quantum processors.

The Company completed a pre-registered, reproducible experimental test of LayerQake's quantum calibration methodology on three IBM quantum processors: ibm_fez, ibm_kingston and ibm_marrakesh. The Company believes the experiment demonstrated substantial improvements in computational accuracy and reductions in cumulative errors caused by quantum hardware noise, and the results met both of the Company’s predefined success criteria on all three processors.

According to the Company’s results, prior to applying LayerQake's calibration methodology, hardware-induced noise introduced measurement bias ranging from approximately 11% to 15%. Following the application of LayerQake, the observed bias was reduced to below 6% on each of the three processors.

In addition, the experiments demonstrated a 15- to 21-fold reduction in maximum cumulative error, representing a substantial improvement in the reliability of the tested quantum computational results.

Importantly, these improvements were achieved using LayerQake's problem-independent calibration approach, which is designed to mitigate hardware-induced inaccuracies without requiring a calibration methodology tailored to each individual computational problem.

Experimental Results Demonstrate Consistent Performance Across Multiple Quantum Processors. The experimental program was designed to assess whether LayerQake could systematically reduce the effects of quantum hardware noise across different physical quantum computing devices.

Before conducting the experiments, the Company established two predefined success criteria: (i) a reduction in measurement bias and (ii) a reduction in maximum cumulative error.

The Company believes these findings provide initial experimental evidence that LayerQake's calibration methodology can improve the accuracy and consistency of results obtained from existing quantum computing hardware.