Spin-qubits in silicon quantum dots are a promising platform for building a scalable quantum processor because they have a small footprint1, long coherence times2,3, and are compatible with advanced semiconductor manufacturing4. Furthermore, rudimentary quantum algorithms have been executed5 and quantum logic at high-fidelity performed6,7,8,9. As the qubit count is increasing, with a six-qubit processor demonstrated10, significant steps have been taken to couple silicon spin qubits at a distance, via microwave photons or spin shuttling11,12,13,14,15,16, towards networked spin-qubit tiles17. However, electrical fluctuations associated with charge noise in the host semiconductor can decrease qubit readout and control fidelity18. Reducing charge noise independently of the device location on a wafer is pivotal to achieving the ubiquitous high-fidelity of quantum operations, within and across qubit tiles, necessary to execute more complex quantum algorithms.

Charge noise is commonly associated with two-level fluctuators (TLF)19 in the semiconductor host. In gated heterostructures with buried quantum wells, TLF may arise from impurities in several locations: within the quantum well, the semiconductor barrier, the semiconductor/dielectric interface, and the dielectrics layers above20,21,22,23,24,25,26. Furthermore, previous work on strained-Si MOSFETs27,28,29, with strained-Si channels deposited on SiGe strain relaxed buffers, has associated charge noise with dislocations arising from strain relaxation, either deep in the SiGe buffer or at the quantum well/buffer interface. Since these impurities and dislocations are randomly distributed over the wafer and are also a main scattering source for electron transport in buried quantum wells30, a holistic approach to materials engineering should be taken to address disorder in two-dimensional electron gases and charge noise in quantum dots.

In this work, we demonstrate thin quantum wells in 28Si/SiGe heterostructures with low and uniform charge noise, measured over several gate-defined quantum dot devices. By linking charge noise measurements to the scattering properties of the two-dimensional electron gas, we show that a quiet environment for quantum dots is obtained by improving the semiconductor/dielectric interface and the crystalline quality of the quantum well. We feed the measured charge noise into a theoretical model, benchmark the model against recent experimental results6,10, and predict that these optimized heterostructures may support long-lived and high-fidelity spin qubits.


Description of 28Si/SiGe heterostructures

Figure 1a illustrates the undoped 28Si/SiGe heterostructures, grown by reduced-pressure chemical vapor deposition, and the gate-stack above. From bottom to top, the material stack comprises a 100 mm Si substrate, a strain-relaxed SiGe buffer layer, a strained 28Si quantum well, a 30 nm thick SiGe barrier, a Si cap oxidized in air to form a SiOx layer, an AlOx layer formed by atomic layer deposition, and metallic gates. The SiGe layers above and below the quantum well have a Ge concentration of 0.3 (Methods).

Fig. 1: Material stack and heterostructure field effect transistor characterization.
figure 1

a Schematics of the 28Si/SiGe heterostructure and dielectric stack above. z indicates the heterostructure growth direction. Circles represent remote impurities at the semiconductor/dielectric interface and perpendicular symbols represent misfit dislocations that might arise at the quantum well/buffer interface due to strain relaxation. b, c BF-STEM images from heterostructure C highlighting the semiconductor/dielectric interface and the 5 nm thick 28Si quantum well, respectively. d Mobility μ and e conductivity σxx measured as a function of density n at a temperature of 1.6 K in a Hall bar H-FET from heterostructure C. The red curve in e is a fit to percolation theory.

We consider three 28Si/SiGe heterostructures (A, B, C) to improve, in sequence, the semiconductor/dielectric interface (from A to B) and the crystalline quality of the quantum well (from B to C). Heterostructure A has an 9 nm thick quantum well and is terminated with an epitaxial Si cap grown by dichlorosilane at 675 °C. This kind of heterostructure has already produced high performance spin-qubits6,10,31. Heterostructure B misses a final epitaxial Si cap but features an amorphous Si-rich layer obtained by exposing the SiGe barrier to dichlorosilane at 500 °C. Compared to A, heterostructure B supports a two-dimensional electron gas with enhanced and more uniform transport properties across a 100 mm wafer, owing to a more uniform SiOx layer with less scattering centers32. Finally, we introduce here heterostructure C, having the same amorphous Si-rich termination as in heterostructure B, but a thinner quantum well of 5 nm (Supplementary Fig. 1). This is much thinner than the Matthews-Blakeslee critical thickness33,34, which is 10 nm35 for the relaxation of tensile Si on Si0.7Ge0.3 via the formation of misfit dislocation at the bottom interface of the quantum well. In light of recent morphological characterization by electron channeling constrast imaging of Si/SiGe heterostructures with similar quantum well thickness and SiGe chemical composition36, we expect misfit dislocation segments in heterostructure B because the quantum well approaches the Matthews-Blakeslee critical thickness. Due to the much thinner quantum well, instead, the epitaxial planes may adapt to the SiGe buffer much better in heterostructure C than in heterostructure B, meaning that misfit dislocations are, in principle, suppressed.

Figure 1b, c shows bright-field scanning transmission electron microscopy (BF-STEM) images from heterostructure C after fabrication of a Hall bar shaped heterostructure field effect transistors (H-FET). We observe a sharp SiGe/SiOx semiconductor/dielectric interface (Fig. 1b), characterized by a minor Ge pile up (dark line) in line with ref. 32. The 5 nm thick quantum well (Fig. 1c, Supplementary Fig. 1) is uniform, has sharp interfaces to the nearby SiGe, and appears of high crystalline quality.

Electrical characterization of heterostructure field effect transistors

We evaluate the scattering properties of the two-dimensional electron gases by wafer-scale electrical transport measured on Hall-bar shaped H-FETs operated in accumulation mode (Methods). For each heterostructure, multiple H-FETs over a wafer are measured in the same cool-down at a temperature of 1.7 K in refrigerators equipped with cryo-multiplexers37. Figure 1d, e shows typical mobility-density and conductivity-density curves for heterostructure C, from which we extract the mobility measured at high density (n = 6 × 1011 cm−2) and the percolation density (np)38. The mobility rises steeply at low density due to progressive screening of scattering from remote impurities and flattens at higher density (n > 5 × 1011 cm−2), limited by scattering from impurities within or nearby the quantum well, for example uniform background charges, surface roughness, or crystalline defects such as threading or misfit dislocations30,39.

Charge noise measurements in quantum dots

For charge noise measurements, we use devices comprising a double quantum dot and a charge sensor quantum dot nearby, illustrated in Fig. 2a. Using the same device design, two-qubit gates with fidelity above 99% were demonstrated6, silicon quantum circuits were controlled by CMOS-based cryogenic electronics31, and energy splittings in 28Si/SiGe heterostructures were studied with statistical significance40.

Fig. 2: Quantum dots and charge noise measurements.
figure 2

a False colored SEM-image of a double quantum dot system with a nearby charge sensor. Charge noise is measured in the multi-electron quantum dot defined by accumulation gates SDLAcc and SDRAcc (blue), plunger P (blue), with the current going along the black arrow. In these experiments, the gates defining the double quantum dot (red) are used as screening gates. There is an additional global top gate (not shown) to facilitate charge accumulation when needed. b Source-drain current ISD through a charge sensor device fabricated on heterostructure C against the plunger gate voltage VP. Colored dots mark the position of the flank of the Coulomb peak where charge noise measurements are performed. The inset shows Coulomb diamonds from the same device, plotted as the differential of the current dI/dV as a function of VP and the source drain bias VSD. c Charge noise spectrum Sϵ measured at the Coulomb peak at VP 360.3 mV in b and extracted using the lever arm from the corresponding Coulomb diamond. The black trendline is proportional to 1/f. d Sϵ for the same device in b, plotted in 3D as a function of f and VP. The dark gray plane is a fit through the datasets, i.e. the collection of noise spectra as in c measured at different VP and each obtained using a unique lever arm from the corresponding Coulomb diamond. e Line cut through the data in d at f = 1 Hz, showing the experimental noise Sϵ (colored dots) and fit (dark gray line). The black circled data point (also in d) marks the minimum charge noise measured for this specific device (Sϵ,min) at f = 1 Hz.

Here, we electrostatically define a multi-electron quantum dot in the charge sensor by applying gate voltages to the accumulation gates SDRAcc and SDLAcc, the barriers SDLB and SDRB, and the plunger gate P. All other gates (red in Fig. 2a) are set to 0 V for measurements of heterostructure B and C, whereas they are positively biased in heterostructure A to facilitate charge accumulation in the sensor (Methods). Figure 2b shows typical Coulomb blockade oscillations of the source-drain current ISD for a charge sensor from heterostructure C measured at a dilution refrigerator base temperature of 50 mK. We follow the same tune-up procedure (Methods) consistently for all devices and we measure charge noise at the flank of each Coulomb peak within the VP range defined by the first peak observable in transport and the last one before onset of a background channel (Supplementary Figs. 24). For example, in Fig. 2b we consider Coulomb peaks within the VP range from 260 mV to 370 mV. The data collected in this systematic way is taken as a basis for comparison between the three different heterostructures in this study.

For each charge noise measurement at a given VP we acquire 60 s (heterostructure A) or 600 s (heterostructures B, C) long traces of ISD and split them into 10 (heterostructure A) or 15 windows (heterostructures B, C). We obtain the current noise spectrum SI by averaging over the 10 (15) windows the discrete Fourier transform of the segments (Methods). We convert SI to a charge noise spectrum Sϵ using, for each measurement at a given VP, the unique lever arm from the corresponding Coulomb diamonds and slope of the Coulomb peak to take into account a possible deformation of the charge sensor with the increasing electron number (inset Fig. 2b, Methods, and Supplementary Fig. 5). A representative charge noise spectrum Sϵ measured at VP = 360.3 mV is shown in Fig. 2c. We observe an approximate 1/f trend at low frequency, pointing towards an ensemble of TLF with a broad range of activation energies affecting charge noise around the charge sensor41,42. Figure 2e shows the charge noise Sϵ at 1 Hz as a function of VP. The charge noise decreases, with a linear trend, with increasing VP, suggesting that, similar to scattering in 2D, screening by an increased electron density shields the electronically active region from noise arising from the heterostructure and the gate stack43. From this measurement we extract, for a given device, the minimum measured charge noise at 1 Hz (Sϵ,min circled data point in Fig. 2e) upon variation of VP in our experimental range. We use Sϵ,min as an informative metric to compare charge noise levels from device to device in a given heterostructure. For a given device, all charge noise spectra Sϵ are plotted in 3D as a function of f and VP (Fig. 2d). To quantify our observations, we fit the data to the plane \(\log {S}_{\epsilon }=-\alpha \log f+\beta {V}_{P}+\gamma\) (Supplementary Note 4). Coefficient α = 0.84 ± 0.01 indicates the spectrum power law exponent and coefficient β = − 15.6 ± 0.1  mV−1 quantifies the change in noise spectrum with increasing plunger gate and, consequently, the susceptibility of charge noise to the increasing electron number in the sensor.

Distribution of transport properties and charge noise

We have introduced key metrics for 2D electrical transport (μ, np) and charge noise (α, β and Sϵ,min) from Hall bar and quantum dot measurements, respectively. In Fig. 3a–e we compare the distributions of all these metrics for the three heterostructures A, B, C. Each box-plot is obtained from the analysis of measurements in Figs. 1d, e, and 2d repeated on multiple H-FETs or quantum dots, on dies randomly selected from different locations across the 100 mm wafers (Methods). To facilitate a comparison with previous studies, the minimum charge noise at 1 Hz is plotted in Fig. 3e as \({S}_{\epsilon,min}^{1/2}\) and therefore in units of μeV/Hz½.

Fig. 3: Distribution of transport properties and charge noise.
figure 3

a, b Distributions of mobility μ measured at n = 6 × 1011 cm−2 and percolation density np for heterostructure A (red, 20 H-FETs measured, of which 16 reported in ref. 32), B (blue, 16 H-FETs measured of which 14 reported in ref. 32), and C (green, 22 H-FETs measured). ce Distributions of noise spectrum power law exponent α, coefficient β indicating the change in noise spectrum with increasing VP, and minimum charge noise \({S}_{\epsilon,min}^{1/2}\) within the range of VP investigated for heterostructure A (red, 4 devices measured), B (blue, 7 devices measured), and C (green, 5 devices measured). Quartile box plots, mode (horizontal line), means (diamonds), 99% confidence intervals of the mean (dashed whiskers), and outliers (circles) are shown.

As reported earlier in ref. 32, the improvement in both mean values and spread for μ and np was associated with a reduction of remote impurities when replacing the epitaxial Si cap in heterostructure A with a Si-rich passivation layer in heterostructure B. Moving to heterostructure C, we measure a high mean mobility of (2.10 ± 0.08) × 105 cm2/Vs and a low mean percolation density of (7.68 ± 0.37) × 1010 cm−2, representing an improvement by a factor 1.4 and 1.3, respectively (compared to heterostructure A). Most strikingly, the 99% confidence intervals of the mean for μ and np are drastically reduced by a factor 9.8 and 4.8, respectively. We speculate that these improvements in heterostructure C are associated with the suppression of misfit dislocations at the quantum well/buffer interface, thereby reducing short range scattering and increasing uniformity on a wafer-scale. This interpretation is supported by previous studies of mobility limiting mechanisms as a function of the quantum well thickness in strained Si/SiGe heterostructures39. We speculate that further reducing the quantum well thickness could increase surface roughness scattering from the bottom interface, and therefore disorder. Instead, fine-tuning the quantum well thickness between 5 nm and 9 nm might minimize surface roughness scattering whilst still avoiding the formation of misfit dislocations.

We now shift our attention to the results of charge noise measurements. First, the power law exponent α (Fig. 3c) shows a mean value 1, however the 99% confidence interval and interquartile range increase when moving from heterostructure A to B and C. Next, we observe a decreasing trend for the absolute mean value of coefficient β (Fig. 3d), meaning that the noise spectrum is less susceptible to changes in VP. Finally, Fig. 3e shows the distributions for \({S}_{\epsilon,min}^{1/2}\), the minimum charge noise at 1 Hz upon varying VP. We find in heterostructure C an almost order of magnitude reduction in mean \({S}_{\epsilon,min}^{1/2}\) to 0.29 ± 0.02 μeV/Hz½. This trend is confirmed by plotting the distributions of maximum charge noise at 1 Hz upon varying VP (Supplementary Fig. 4). Furthermore, within the distribution of \({S}_{\epsilon,min}^{1/2}\) for heterostructure C, the minimum value of the measured charge noise as a function of VP and across quantum dots is 0.15 μeV/Hz½. These charge noise values are on par or compare favorably to the best values reported previously at 1 Hz in gate defined quantum dots. In multi-electron quantum dots, charge noise of 0.47 μeV/Hz½ was reported for Si/SiGe44, 0.6 μeV/Hz½ (average value, with a minimum of ≤0.2 μeV/Hz½) for Ge/SiGe45, 0.49 ± 0.1 μeV/Hz½ for Si/SiO246, and 1 μeV/Hz½ for InSb47. In single-electron quantum dots, charge noise of 0.33 μeV/Hz½ was reported for Si/SiGe48 and 7.5 μeV/Hz½ for GaAs49.

We understand the charge noise trends in Fig. 3c–e by relating them to the evolution of the disorder landscape moving from heterostructures A to B and C, as inferred by the electrical transport measurements in Fig. 3a, b. The narrow distribution of α in heterostructure A points to charge noise being dominated from many TLFs possibly located at the low quality semiconductor/dielectric interface and above, albeit other sources of charge noise in the surrounding environment of the quantum dot may be present, such as highly localized misfit dislocations arising from partial strain relaxation in the quantum well or other nearby fluctuators. With a better semiconductor/dielectric interface, the effect of these other nearby fluctuators emerges in heterostructure B and C as a larger spread of the frequency exponent α, indicating a nonuniform distribution of activation energies according to the Dutta-Horn model50. Yet, the noise spectra still follow a 1/f-like behavior (Supplementary Fig. 3), suggesting that TLFs also experience slow temperature fluctuations42. The electrical transport measurements support this interpretation: scattering from many remote impurities is dominant in heterostructure A, whereas with a better semiconductor/dielectric interface remote scattering has less impact in the transport metrics of heterostructures B and C.

The decreasing trend in β is in line with the observation from electrical transport. As the impurity density decreases from heterostructure A to B and C, charge noise is less affected by an increasing VP, since screening of electrical noise through adding electrons to the charge sensor becomes less effective. While we are not able to measure directly the electron number in the charge sensor, we deem unlikely the hypothesis that charge sensors in heterostructure A are operated with considerably fewer electrons than in heterostructure C. This is because all operation gate voltages in heterostructure A are consistently larger than in heterostructure C (Supplementary Fig. 4), due to the higher disorder.

Finally, the drastic reduction in mean value and spread of \({S}_{\epsilon,min}^{1/2}\) mirrors the evolution of mean value and spread of np and μ. From heterostructure A to B, a reduction in scattering from remote impurities is likely to result in less charge noise from long-range TLFs. From heterostructure B to C, the reduction in the possible number of dislocations at the quantum well/buffer interface, further reduces the charge noise picked up by quantum dots. This explanation is based on earlier studies of charge noise in strained Si-MOSFETs27,28,29, which showed a correlation between low-frequency noise spectral density and static device parameters. Dislocations at the bottom of the strained channel may act as scattering centers that degrade mobility and as traps for the capture and release of carriers, which causes noise similarly to traps at the dielectric interface.

Calculated dephasing time and infidelity

To emphasize the improvement of the electrical environment in the semiconductor host, we calculate the dephasing time \({T}_{2}^{\star }\) of charge and spin qubits assuming these qubits experience the same fluctuations as our 28Si/SiGe quantum dots. The dephasing time of a qubit (in the quasistatic limit and far-off from a sweet spot) is given by51,52

$${T}_{2}^{\star }=\frac{h}{\sqrt{2}\pi \sigma }$$

with the Planck constant h and the standard deviation

$${\sigma }^{2}={\left | \frac{\partial {{{{{{{\mathcal{E}}}}}}}}}{\partial \mu }\right | }^{2}\times 2\int\nolimits_{{f}_{{{{{{{{\rm{low}}}}}}}}}}^{{f}_{{{{{{{{\rm{high}}}}}}}}}}\frac{{S}_{\epsilon }^{2}}{{f}^{\alpha }}df.$$

Importantly, both the charge noise amplitude \({S}_{\epsilon }^{2}(f)\) and the noise exponent α have a strong impact on the dephasing time while the low and high frequency cut-off, flow and fhigh, given by the duration of the experiment have a weaker impact. The prefactor \(\left|\frac{\partial {{{{{{{\mathcal{E}}}}}}}}}{\partial \mu }\right|\) translates shifts in chemical potential of the charge sensor into energy shifts of the qubit and depends on many parameters such as the type of qubit and the device itself. We find \(\left|\frac{\partial {{{{{{{\mathcal{E}}}}}}}}}{\partial \mu }\right |=1\) for a charge qubit53 and \(\left|\frac{\partial {{{{{{{\mathcal{E}}}}}}}}}{\partial \mu }\right|\approx 1{0}^{-5}\) for an uncoupled spin- qubit44 (see Supplementary Note 7 for a derivation of these numbers and the used frequency bandwidths).

Figure 4a shows the computed dephasing times of charge qubits (circle) and spin qubits (star) for all three heterostructures. These calculations represent a best case scenario, since we use the distribution of measured Sϵ,min from Fig. 3 as input parameter for each heterostructure. The improvements in our material can be best seen by investigating \({T}_{2}^{\star }\) of the charge qubit since it is directly affected by charge noise. Our theoretical extrapolation shows two orders of magnitude improvement in \({T}_{2}^{\star }\) by switching from heterostructures A to heterostructures B and C. One order is gained from the reduced charge noise amplitude and another order is gained through a more beneficial noise exponent α > 1. Note, that the integration regimes differ for spin and charge qubits due to the different experimental setups and operation speeds44,53. For potential spin qubits in heterostructure A the calculated \({T}_{2}^{\star }\) shows an average \({\overline{T}}_{2}^{\star }=8.4\pm 5.6\) μs. This distribution compares well with the distribution \({\overline{T}}_{2}^{\star }=6.7\pm 5.6\) μs of experimental \({T}_{2}^{\star }\) data from state-of-the-art semiconductor spin qubits in materials with similar stacks as in heterostructure A6,10. Note that while such comparisons oversimplify actual semiconductor spin-qubit devices by reducing them to a single number, they fulfill two aims. They allow us to benchmark the computed performance of heterostructure A to past experiments and provide a prognosis on the qubit quality in novel material stacks. Heterostructures B and C, in this case, may support average dephasing times of \({\overline{T}}_{2}^{\star }=24.3\pm 12.5\) μs and \({\overline{T}}_{2}^{\star }=36.7\pm 18\) μs, respectively. The highest values \({T}_{2}^{\star }=70.1\) μs hints towards a possible long dephasing time for spin qubits, previously only reported in ref. 2.

Fig. 4: Calculated dephasing times and infidelity.
figure 4

a Computed dephasing times \({T}_{2}^{\star }\) of a charge qubit (circle) and of a spin-qubit (star) using Sϵ,min from heterostructure A (red), B (blue), C (green). Eq. (1) was used to compute \({T}_{2}^{\star }\) as a function of Sϵ and α from Fig. 3 with frequency cutoffs (fmin, fmax) = (1.6 mHz, 33 GHz) and (fmin, fmax) = (1.6 mHz, 10 kHz). Literature values (squares) are taken from refs. 6,10. b Simulated infidelity of a CZ-gate between two spin qubits following the ref. 6 using Sϵ and α from heterostructure A (red), B (blue), C (green) in Fig. 3 as input for barrier fluctuations.

Figure 4b shows the simulated infidelity, a metric to measure the closeness to the ideal operation, of a universal CZ-gate between two spin qubits following ref. 6 and Supplementary Note 7. Note that the device used in ref. 6 has the same architecture as our test devices. In the CZ-gate simulation, noise couples in dominantly via barrier voltage fluctuations which affects the interaction between the electron spins. Again, we use the charge noise amplitude Sϵ,min and exponent α from the quantum dot experiments in Fig. 3 as input for the simulations. The simulations show an averaged average gate infidelity \(1-{\overline{F}}_{{\scriptstyle{{{{{\rm{CZ}}}}}}}}=0.02\pm 0.01\%\) which means on average a single error every 5000 runs. We also observe a saturation value close to 1 − F = 10−4 which arises from single-qubit dephasing \({T}_{2}^{\star }=20\) μs used in the simulations estimated from nuclear spin noise due to a 800 ppm concentration of the 29Si silicon isotope which has a non-zero nuclear spin44.


In summary, we have measured electron transport and charge noise in 28Si/SiGe heterostructures where we improve the semiconductor/dielectric interface, by adopting an amorphous Si-rich passivation, and the structural quality of the quantum well, by reducing the quantum well thickness significantly below the Matthew-Blakeslee critical thickness for strain relaxation. We relate disorder in 2D to charge noise in quantum dots by following a statistical approach to measurements. A reduction of remote impurities and dislocations nearby the quantum well is connected with the key improvements in the scattering properties of the 2D electron gas, such as mobility and percolation density, and their uniformity across a 100 mm wafer. The trend observed from electron transport in 2D is compatible with the observations from measurements of charge noise in quantum dots. As remote impurities are reduced, charge noise becomes more sensitive to local fluctuators nearby the quantum well and less subject to screening by an increased number of electrons in the dot. Furthermore, with this materials optimization, we achieve a statistical improvement of nearly one order of magnitude in the charge noise supported by quantum dots. Using the charge noise distribution as input parameter and benchmarking against published spin-qubit data, we predict that our optimized semiconductor host could support long-lived and high-fidelity spin qubits. We envisage that further materials improvements in the structural quality of the quantum well, in addition to the commonly considered semiconductor/dielectric interface, may lead systematically to quantum dots with less noise and to better qubit performance.


Si/SiGe heterostructure growth

The 28Si/SiGe heterostructures are grown on a 100-mm n-type Si(001) substrate using an Epsilon 2000 (ASMI) reduced pressure chemical vapor deposition reactor. The reactor is equipped with a 28SiH4 gas cylinder (1% dilution in H2) for the growth of isotopically enriched 28Si. The 28SiH4 gas was obtained by reducing 28SiF4 with a residual 29Si concentration of 0.08%54. Starting from the Si substrate, the layer sequence of all heterostructures comprises a 3 μm step-graded Si(1−x)Gex layer with a final Ge concentration of x = 0.3 achieved in four grading steps (x = 0.07, 0.14, 0.21, and 0.3), followed by a 2.4 μm Si0.7Ge0.3 strain-relaxed buffer. The heterostructures differ for the active layers on top of the strain-relaxed buffer. Heterostructure A has a 9 nm tensile strained 28Si quantum well, a 30 nm Si0.7Ge0.3 barrier, and a sacrificial 1 nm epitaxial Si cap. Heterostructure B has an 9 nm tensile strained 28Si quantum well, a 30 nm Si0.7Ge0.3 barrier, and a sacrificial passivated Si cap grown at 500 °C. Heterostructure C has a 5 nm tensile strained 28Si quantum well, a 30 nm Si0.7Ge0.3 barrier, and a sacrificial passivated Si cap grown at 500 °C. A typical secondary ions mass spectrometry of our heterostructures is reported in Supplementary Fig. S13 of ref. 40 and the Ge concentration in the SiGe layers is confirmed by quantitative electron energy loss spectroscopy (EELS).

Device fabrication

The fabrication process for Hall-bar shaped heterostructure field effect transistors (H-FETs) involves: reactive ion etching of mesa-trench to isolate the two-dimensional electron gas; P-ion implantation and activation by rapid thermal annealing at 700 °C; atomic layer deposition of a 10-nm-thick Al2O3 gate oxide; deposition of thick dielectric pads to protect gate oxide during subsequent wire bonding step; sputtering of Al gate; electron beam evaporation of Ti:Pt to create ohmic contacts to the two-dimensional electron gas via doped areas. All patterning is done by optical lithography. Double quantum dot devices are fabricated on wafer coupons from the same H-FET fabrication run and share the process steps listed above. Double-quantum dot devices feature a single layer gate metallization and further require electron beam lithography, evaporation of Al (27 nm) or Ti:Pd (3:17 nm) thin film metal gate, lift-off, ALD of a 5 nm thick Al2O3 insulating layer, and a global top-gate.

Electrical characterization of H-FETs

Hall-bar H-FETs measurements are performed in an attoDRY2100 variable temperature insert refrigerator at a base temperature of 1.7 K32. We apply a source-drain bias of 100 μV and measure the source-drain current ISD, the longitudinal voltage Vxx, and the transverse Hall voltage Vxy as function of the top gate voltage Vg and the external perpendicular magnetic field B. From here we calculate the longitudinal resistivity ρxx and transverse Hall resistivity ρxy. The Hall electron density n is obtained from the linear relationship ρxy = B/en at low magnetic fields. The carrier mobility μ is extracted from the relationship σxx = neμ, where e is the electron charge. The percolation density np is extracted by fitting the longitudinal conductivity σxx to the relation \({\sigma }_{xx}\propto {(n-{n}_{p})}^{1.31}\). Here σxx is obtained via tensor inversion of ρxx at B = 0. The box plots in Fig. 3a, b for heterostructure A (red) and B (blue) expand previously published data in Fig. 2f, e of ref. 32 by considering measurements of 4 additional H-FETs for heterostructure A (20 H-FETs in total) and of 2 additional H-FETs for heterostructure B (16 H-FETs in total).

Electrical characterization of quantum dots

Measurements of the multi-electron quantum dots defined in the charge sensor are performed in a Leiden cryogenic dilution refrigerator with a mixing chamber base temperature TMC = 50 mK40. The devices are tuned systematically with the following procedure. We sweep all gate voltages (VSDRAcc, VSDRB, VP, VSDLB, and VSDLAcc) from 0 V towards more positive bias, until a source-drain current ISD of ≈1 nA is measured, indicating that a conductive channel has formed in the device. We then reduce the barrier voltages to find the pinch-off voltages for each barrier. Subsequently, we measure ISD as a function of VSDLB and VSDRB and from this 2D map we find a set of gate voltage parameters so that Coulomb blockade peaks are visible. We then fix the barrier voltages and sweep VP to count how many clearly defined Coulomb peaks are observed before onset of a background current. The quantum dot is tuned to show at least 9 Coulomb peaks, so that noise spectra may be fitted as in Fig. 2d with meaningful error bars. If we see less than 9 Coulomb peaks we readjust the accumulation gate voltages VSDRAcc, and VSDLAcc, and repeat the 2D scan of VSDLB against VSDRB. In one case (device 2 of heterostructure A), we tuned device to show past 5 Coulomb peaks and still performed the fit of the charge noise spectra similar to the one shown in Fig. 2d. Further details on the extraction of the lever arms and operation gate voltages of the devices are provided in Supplementary Figs 4 and 5. We estimate an electron temperature of 190 mK by fitting Coulomb blockade peaks (see Supplementary Fig. 2 in ref. 32) measured on quantum dot devices.

For heterostructure A we apply a source drain bias of 100 μV (1 device) or 150 μV (3 devices) across the quantum dot, finite gate voltages across the operation gates of the dot, and finite gate voltages across the screening gates. We measure the current ISD and the current noise spectrum SI on the left side of the Coulomb peak where dI/dVP is largest. We use a sampling rate of 1 kHz for 1 min using a Keithley DMM6500 multimeter. The spectra are then divided into 10 segments of equal length and we use a Fourier transform to convert from time-domain to frequency-domain for a frequency range of 167 mHz–500 Hz. We set the upper limit of the frequency spectra at 10 Hz, to avoid influences from a broad peak at around 150 Hz coming from the setup (Supplementary Fig. 3). A peak in the power spectral density at 9 Hz is removed from the analysis since it is an artifact of the pre-amplifier. To convert the current noise spectrum to a charge noise spectrum, we use the formula20

$${S}_{\epsilon }=\frac{{a}^{2}{S}_{I}}{|dI/d{V}_{P}{|}^{2}}$$

where a is the lever arm and dI/dVP is the slope of the Coulomb peak at the plunger voltage used to acquire the time trace.

The charge noise measurements conditions have been slightly modified from sample A to sample B, C to extend the probed frequency range from 100 μHz to 10 μHz. For heterostructures B and C we apply a source drain bias of 150 μV across the quantum dot, finite gate voltages across the operation gates of the quantum dot, and we apply 0 V to all other gates. We measure the current ISD and the current noise spectrum SI on the left side of the Coulomb peak where dI/dVP is largest. We use a sampling rate of 1 kHz for 10 min using a Keithley DMM6500 multimeter. The spectra are then divided into 15 segments of equal length and we use a Fourier transform to convert from time-domain to frequency-domain for a frequency range of 25 mHz–500 Hz. We set the upper limit of the frequency spectra at 10 Hz, to avoid influences from a broad peak at around 150 Hz coming from the setup. We use Eq. (3) to convert the current noise spectrum to a charge noise spectrum.

(Scanning) Transmission Electron Microscopy

For structural characterization with (S)TEM, we prepared cross-sections of the quantum well heterostructures by using a Focused Ion Beam (Helios 600 dual beam microscope). Atomically resolved HAADF STEM data was acquired in a probe corrected TITAN microscope operated at 300 kV. Quantitative EELS was carried out in a TECNAI F20 microscope operated at 200 kV with approximately 2 eV energy resolution and 1 eV energy dispersion. Principal Component Analysis (PCA) was applied to the spectrum images to enhance S/N ratio.