Maximum Length Sequence Phase Encoding for Quantum Sensor Readout

Quantum sensors can detect extremely small electromagnetic and magnetic signatures, which makes them powerful tools for geophysical analysis, materials detection, environmental monitoring, and scientific research. Their sensitivity also makes them vulnerable to interference from ambient RF sources, electrical noise, and outdoor or industrial environments. Traditional readout methods attempt to preserve the phase of the sensor or allow it to evolve uniformly, but these approaches can produce ambiguous results or false positives when exposed to strong interference. Los Alamos researchers developed a pseudorandom phase-encoding method that allows a quantum sensor to distinguish true target signals from substantial background noise. By applying a maximum length sequence, also called an msequence, the sensor's phase is flipped by 180 degrees according to a designed pattern. The resulting measurement is analyzed using correlation against the known sequence, enabling accurate extraction of the intended signal even when conventional methods fail to differentiate between interference and true sensor output. Advantages Improves quantum sensor performance in noisy outdoor and industrial settings Distinguishes true sensor signals from interfering or spurious noise Reduces false positives without added shielding or multichannel detection Integrates into existing measurement protocols with minimal modification Compatible with a range of quantum sensing platforms, including magnetic and electromagnetic systems Technology Description The method embeds a defined sequence of phase inversions into the quantum sensor. Target signals track this imposed pattern because they arise from the controlled experiment, while interfering signals do not. This inherent separation allows correlation-based processing to highlight coherent responses and suppress background noise. Demonstrations using low field nuclear magnetic resonance (NMR) show that both traditional CPMG-style readouts and the m-sequence-based readout detect the intended signal under ideal conditions. However, when only interference is present, the traditional readout cannot reliably separate interference from the target signal, while the m-sequence method correctly rejects the interferer. Experimental data also show strong correlation peaks for the encoded measurement and minimal correlation for AM or broadband interferers, confirming the method's robustness in realistic outdoor and industrial noise environments. Market Applications This phase-encoded readout method supports sensing platforms in which interference can obscure weak or transient signals. Its characteristics make it relevant to a wide range of technologies, including: subsurface imaging and resource characterization in geophysical exploration quantum sensing systems deployed near infrastructure such as roads, power lines, or industrial equipment environmental and geophysical platforms that integrate seismic, muon, magnetic, or other sensing modalities detection systems that require high confidence in distinguishing real signatures from environmental noise These and related applications benefit from enhanced robustness and improved discrimination of true signals in field environments. TRL 3 U.S. Patent pending LA-UR-25-31925 LANL Tech Partnerships: Unlock the Innovative Potential Los Alamos National Laboratory offers a wide range of cutting-edge technologies and capabilities that may provide your company with a competitive edge in the market and unlock the innovative potential that can enhance, refine, and revolutionize your products. LANL's licensing program focuses on moving inventions developed by our researchers to commercial innovations. Patented and patent pending inventions and copyrighted software are available to existing and start-up companies through exclusive and non-exclusive licensing agreements. For specific discussions, please contact [email removed]. Note: This is not a call for external services for the development of this technology. https://www.lanl.gov/engage/collaboration/feynman-center/partner-with-us/licensing-technology m.lanl.gov/tech-search