Assessment of a Silicon Quantum Dot Spin Qubit Environment via Noise Spectroscopy

Abstract

Preserving coherence long enough to perform meaningful calculations is one of the major challenges on the pathway to large scale quantum computer implementations. Noise coupled in from the environment is the main contributing factor to decoherence but can be mitigated via engineering design and control solutions. However, this is only possible after acquiring a thorough understanding of the dominant noise sources and their spectrum. In this paper, we employ a silicon quantum dot spin qubit as a metrological device to study the noise environment experienced by the qubit. We compare the sensitivity of this qubit to electrical noise with that of an implanted silicon donor qubit in the same environment and measurement set-up. Our results show that, as expected, a quantum dot spin qubit is more sensitive to electrical noise than a donor spin qubit due to the larger Stark shift, and the noise spectroscopy data shows pronounced charge noise contributions at intermediate frequencies (2-20 kHz).

Low-frequency charge noise in Si/SiGe quantum dots

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Electron spins in silicon have long coherence times [1][2][3][4][5][6] and are a promising qubit platform [7,8]. However, electric field noise in semiconductors poses a challenge for most single-and multi-qubit operations in quantum-dot spin qubits [4,9,10]. Here, we investigate the dependence of lowfrequency charge noise spectra on temperature and aluminum-oxide gate dielectric thickness in Si/SiGe quantum dots with overlapping gates.

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Non-Gaussian noise spectroscopy with a superconducting qubit sensor

“…Quantum noise spectroscopy (QNS) leverages the fact that open-loop control modulation is akin to shaping the filter function that determines the sensor's response in frequency space [8][9][10][11][12] and, in it simplest form, aims to characterize the spectral properties of environmental noise as sensed by a single qubit sensor. By now, QNS protocols employing both pulsed and continuous control modalities have been explored, and experimental implementations have been reported across a wide variety of qubit platforms -including NMR [13], superconducting quantum circuits [14][15][16][17], semiconductor quantum dots [18][19][20][21], diamond nitrogen vacancy centers [22,23], and trapped ions [24]. Notably, knowledge of the underlying noise spectrum has already enabled unprecedented coherence times to be achieved via tailored error suppression [25].…”

Extending comb-based spectral estimation to multiaxis quantum noise

“…On the experimental side, we expect that our results will open new avenues for high quality control of quantum systems, as they give access to all the noise information relevant to the dynamics of a qubit. Indeed, similar experiments to the ones performed in platforms where dephasing noise is dominant [22,24,29], should now also possible in platforms where both T 1 and T 2 processes are significant. As one can see from the above equations, the expectation value of any given observable, given an arbitrary initial state, manifestly depends on both G + and G − filters.…”

“…In both cases, the basic idea is to shape the control modulation so that the frequency response of the driven qubit sensor is altered in a desired way [20]. To date, experimental application of QNS has enabled successful reconstructions of dephasing noise spectra in physical settings as diverse as nuclear magnetic resonance [3,19], superconducting qubits [2,21], spin qubits in semiconductors [22][23][24], trapped ions [25,26], and NV centers in diamond [27,28]. QNS protocols for high-order dephasing spectra resulting from non-Gaussian statistics have also been validated experimentally, using engineered noise on a superconducting qubit sensor operated outside of a linear-response regime [29].…”