Toward Axion Signal Extraction in Semiconductor Spin Qubits Via Spectral Engineering

Abstract

Recent advances in quantum sensing and computational technologies indicate the possibility of improving the precision of measurements aimed at detecting cosmological particles and weakly interacting massive particles using various qubit platforms. While recent progress has been made, mitigating environmental noise remains a challenge in extracting particle parameters with high fidelity. Addressing these challenges requires efforts on two levels. At the device level, the qubit and its array acting as a probe, must be isolated from electrical and magnetic noise through optimized device geometry. At the signal-processing level, it is necessary to develop filtering methods targeting specific noise spectra based on different qubit architectures. In this work, we explore the possibility of using semiconductor quantum dot spin qubits as a platform to search for quantum chromodynamics axions and, more broadly, axion like particles (ALPs). Starting by deriving an effective Hamiltonian for electron-axion interactions, we identify an axion-induced effective magnetic field and determine the characteristic axion oscillation frequency. To suppress charge noise in the devices and environmental noise, we first analyze the charge noise spectrum and then develop a dedicated filtering and noise-reduction protocol, paving the way for exploring feasible axion mass ranges. Our preliminary study holds promise for enhancing the screening of various axion signals using quantum technologies. We expect that our analysis and filtering protocol can help advance the use of semiconductor quantum dot spin qubit arrays in axion detection.

Figures (7)

• Figure 1: Schematic planar silicon quantum dot. In this specific design, we focus on a quantum dot array in the silicon layer. By applying a gate electric field $F_z$ via gate P1, holes accumulate in silicon and are confined vertically against the silicon oxide (indicated at the location of the two-dimensional hole gas). The single quantum dot is formed using gates P2--P5. The gates P2 and P4 provide confinement in the $\hat{x}$-direction, while gate P5 provides confinement in the $y$-direction. P3 is used as the top gate of the quantum dot, accumulating a single hole in the potential well beneath. The resulting potential is indicated schematically below the gates. Then the quantum dot array repeats the set-up for P2--P4.
• Figure 2: A possible workflow combining FFT analysis and lock-in detection. The LNA outputs signals to both the FFT module for global frequency analysis and the Lock-in Amplifier for specific frequency detection.
• Figure 3: Projected search sensitivity for the axion--electron coupling constant $g_{ae}$ as a function of axion mass $m_a$ (bottom axis) and corresponding frequency (top axis). The shaded purple region indicates the detectable parameter space with next-generation devices ($Q=10^{6}$, $N=10^{6}$, $T_{2}=100$ ms), bounded by the dashed red line. The green region shows the space of current devices ($Q=10^{4}$, $N=16$, $T_{2}=1$ ms). The purple band denotes the DFSZ model range ($0.1<\tan\beta_a<50$), with the solid purple line corresponding to $\tan\beta_a=1$. The red dotted line indicates current stellar cooling limits Oda2020.
• Figure 4: Power spectral density (PSD) of the received signal with an input SNR of $2.73$ dB before filtering. A prominent carrier peak appears at 14 GHz, with symmetric sidebands at 13.27 and 14.73 GHz, consistent with axion-induced modulation. The noise floor is shown as a reference for signal integrity and spectral purity.
• Figure 5: Time-dependent SNR of the filtered transverse spin response $\langle\sigma_x\rangle$, computed over sliding windows of size 100. The SNR fluctuates between about $-60$ dB and 20 dB due to oscillations, spectral leakage, and drift, while remaining above 8.36 dB, demonstrating robust detectability of axion-induced modulation. The best-case simulated SNR reaches 22.5 dB according to $\text{SNR}=20\log_{10}(Q N \sqrt{t} B_{\text{eff}} / \eta_B)$.