Abstract
Singlespin qubits in semiconductor quantum dots hold promise for universal quantum computation with demonstrations of a high singlequbit gate fidelity above 99.9% and twoqubit gates in conjunction with a long coherence time. However, initialization and readout of a qubit is orders of magnitude slower than control, which is detrimental for implementing measurementbased protocols such as errorcorrecting codes. In contrast, a singlettriplet qubit, encoded in a twospin subspace, has the virtue of fast readout with high fidelity. Here, we present a hybrid system which benefits from the different advantages of these two distinct spinqubit implementations. A quantum interface between the two codes is realized by electrically tunable interqubit exchange coupling. We demonstrate a controlledphase gate that acts within 5.5 ns, much faster than the measured dephasing time of 211 ns. The presented hybrid architecture will be useful to settle remaining key problems with building scalable spinbased quantum computers.
Introduction
Initialization, singlequbit and twoqubit gate operations, and measurements are fundamental elements for universal quantum computation^{1}. Generally, they should all be fast and with high fidelity to reach the faulttolerance thresholds^{2}. So far, various encodings of spin qubits into one to threespin subspaces have been developed in semiconductor quantum dots^{3,4,5,6,7,8,9,10,11,12,13,14,15}. In particular, recent experiments demonstrated all of these elements including twoqubit logic gates for singlespin qubits proposed by Loss and DiVincenzo (LD qubits) and singlettriplet (ST) qubits^{6,7,8,14}. These qubits have different advantages depending on the gate operations, and combinations thereof can increase the performance of spinbased quantum computing. In LD qubits, the twoqubit gate is fast^{6,7} as it relies on the exchange interaction between neighboring spins. In contrast, the twoqubit gate in ST qubits is much slower as it is mediated by a weak dipole coupling^{14}. Concerning initialization and readout, however, the situation is the opposite: it is slow for LD qubits, relying on spinselective tunneling to a lead^{16,17}, while it is orders of magnitude faster in ST qubits relying on Pauli spin blockade^{12,13}. Therefore, a fast and reliable interface between LD and ST qubits would allow for merging the advantages of both realizations.
Here we present such an interface implementing a controlledphase (CPHASE) gate between a LD qubit and a ST qubit in a quantum dot array^{18,19}. The gate is based on the nearest neighbor exchange coupling and is performed in 5.5 ns. Even though we do not pursue benchmarking protocols here, the gate time being much shorter than the corresponding dephasing time (211 ns) indicates that the fidelity of this type of gates can be very high. Our results demonstrate that controlled coherent coupling of different types of gated spin qubits is feasible, and one can proceed to combining their advantages. Overall, our work pushes further the demonstrated scalability of spin qubits in quantum dot arrays.
Results
A LD qubit and a ST qubit formed in a triple quantum dot (TQD)
A hybrid system comprising a LD qubit and a ST qubit is implemented in a linearlycoupled gatedefined TQD shown in Fig. 1a. The LD qubit (Q_{LD}) is formed in the left dot while the ST qubit (Q_{ST}) is hosted in the other two dots. We place a micromagnet near the TQD to coherently and resonantly control Q_{LD} via electric dipole spin resonance (EDSR)^{20,21,22,23,26}. At the same time it makes the Zeeman energy difference between the center and right dots, \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}\), much larger than their exchange coupling J^{ST}, such that the eigenstates of Q_{ST} become ↑↓〉 and ↓↑〉 rather than singlet S〉 and triplet T〉. We apply an external inplane magnetic field B_{ext} = 3.166 T to split the Q_{LD} states by the Zeeman energy E_{Z} as well as to separate polarized triplet states ↑↑〉 and ↓↓〉 from the Q_{ST} computational states. The experiment is conducted in a dilution refrigerator with an electron temperature of approximately 120 mK. The qubits are manipulated in the (N_{L}, N_{C}, N_{R}) = (1,1,1) charge state while the (1,0,1) and (1,0,2) charge states are also used for initialization and readout (see Fig. 1b). Here, N_{L(C,R)} denotes the number of electrons inside the left (center, right) dot.
We first independently measure the coherent time evolution of each qubit to calibrate the initialization, control, and readout. We quench the interqubit exchange coupling by largely detuning the energies of the (1,1,1) and (2,0,1) charge states. For Q_{LD}, we observe Rabi oscillations^{4} with a frequency f_{Rabi} of up to 10 MHz (Fig. 1d) as a function of the microwave (MW) burst time t_{MW}, using the pulse sequence in Fig. 1e. For Q_{ST}, we observe the precession between S〉 and T〉 (ST precession) (Fig. 1f) as a function of the evolution time t_{e}, using the pulse sequence in Fig. 1g (see Supplementary Note 2 for full control of Q_{ST}). We use a metastable state to measure Q_{ST} with high fidelity^{13} (projecting to S〉 or T〉) in the presence of large \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}\) with which the lifetime of T〉 is short^{27}.
Calibration of the twoqubit coupling
The two qubits are interfaced by exchange coupling J^{QQ} between the left and center dots as illustrated in Fig. 1c. We operate the twoqubit system under the conditions of \(E_{\mathrm{Z}} \gg {\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}},{\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{QQ}}} \gg J^{{\mathrm{QQ}}} \gg J^{{\mathrm{ST}}}\) where \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{QQ}}}\) is the Zeeman energy difference between the left and center dots. Then, the Hamiltonian of the system is
where \(\hat \sigma _z^{{\mathrm{LD}}}\) and \(\hat \sigma _z^{{\mathrm{ST}}}\) are the Pauli zoperators of Q_{LD} and Q_{ST}, respectively^{18} (Supplementary Note 3). The last term in Eq. (1) reflects the effect of the interqubit coupling J^{QQ}: for states in which the spins in the left and center dots are antiparallel, the energy decreases by J^{QQ}/2 (see Fig. 2a). In the present work, we choose to operate Q_{LD} as a control qubit and Q_{ST} as a target, although these are exchangeable. With this interpretation, the ST precession frequency f^{ST} depends on the state of Q_{LD,} \(f_{\sigma _z^{{\mathrm{LD}}}}^{{\mathrm{ST}}} = \left( {{\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}  \sigma _z^{{\mathrm{LD}}}J^{{\mathrm{QQ}}}/2} \right)/h\). Here \(\sigma _z^{{\mathrm{LD}}}\) represents ↑〉 or ↓〉 and +1 or −1 interchangeably. This means that while J^{QQ} is turned on for the interaction time t_{int}, Q_{ST} accumulates the controlledphase ϕ_{C} = 2πJ^{QQ}t_{int}/h, which provides the CPHASE gate (up to singlequbit phase gates; see Supplementary Note 7) in t_{int} = h/2J^{QQ}. An important feature of this twoqubit gate is that it is intrinsically fast, scaling with J^{QQ}/h which can be tuned up to ~100 MHz, and is limited only by the requirement \(J^{{\mathrm{QQ}}}/h \ll {\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{QQ}}}/h \sim 500\,{\mathrm{MHz}}\) in our device.
Before testing the twoqubit gate operations, we calibrate the interqubit coupling strength J^{QQ}, and its tunability by gate voltages. The interqubit coupling in pulse stage F (Fig. 2b) is controlled by the detuning energy between (2,0,1) and (1,1,1) charge states (one of the points denoted E in Fig. 1b). To prevent leakage from the Q_{ST} computational states, we switch J^{QQ} on and off adiabatically with respect to \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{QQ}}}\) by inserting voltage ramps to stage F with a total ramp time of t_{ramp} = 24 ns (Fig. 2b)^{28}. The coherent precession of Q_{ST} is measured by repeating the pulse stages from D to H without initializing, controlling and measuring Q_{LD}, which makes Q_{LD} a random mixture of ↑〉 and ↓〉. Figure 2c shows the FFT spectra of the precession measured for various interaction points indicated in Fig. 1b. As we bring the interaction point closer to the boundary of (1,1,1) and (2,0,1), J^{QQ} becomes larger and we start to see splitting of the spectral peaks into two. The separation of the two peaks is given by J^{QQ}/h which can be controlled by the gate voltage as shown in Fig. 2d.
We now demonstrate the controllability of the ST precession frequency by the input state of Q_{LD}, the essence of a CPHASE gate. We use the quantum circuit shown in Fig. 2b, which combines the pulse sequences for independent characterization of Q_{LD} and Q_{ST}. Here we choose the interaction point such that J^{QQ}/h = 90 MHz. By using either ↑〉 or ↓〉 as the Q_{LD} initial state (the latter prepared by an EDSR π pulse), we observe the ST precessions as shown in Fig. 2e, f. The data fit well to Gaussiandecaying oscillations giving \(f_{ \uparrow \rangle}^{{\mathrm{ST}}} = 434 \pm 0.5\,{\mathrm{MHz}}\) and \(f_{ \downarrow \rangle}^{{\mathrm{ST}}} = 524 \pm 0.4\,{\mathrm{MHz}}\) [These are consistent with the values determined by Bayesian estimation discussed in Methods]. This demonstrates the control of the precession rate of Q_{ST} by J^{QQ}/h depending on the state of Q_{LD}.
Demonstration of a CPHASE gate
To characterize the controlledphase accumulated during the pulse stage F, we separate the phase of Q_{ST} into controlled and singlequbit contributions as \(\phi _{\sigma _z^{{\mathrm{LD}}}} =  \pi \sigma _z^{{\mathrm{LD}}}J^{{\mathrm{QQ}}}\left( {t_{{\mathrm{int}}} + t_0} \right)/h\) and \(\phi ^{{\mathrm{ST}}} = 2\pi {\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}( {t_{{\mathrm{int}}} + t_{{\mathrm{ramp}}}} )/h + \phi _0\), respectively. Here t_{0 }(≪t_{ramp}) represents the effective time for switching on and off J^{QQ} (Supplementary Note 5). A phase offset ϕ_{0} denotes the correction accounting for nonuniform \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}\) during the ramp (Supplementary Note 5). Then the probability of finding the final state of Q_{ST} in singlet is modeled as
where a, b and \(T_2^ \ast\) represent the values of amplitude, mean and the dephasing time of the ST precession, respectively. We use maximum likelihood estimation (MLE) combined with Bayesian estimation^{29,30} to fit all variables in Eq. 2, that are \(a,b,t_0,J^{{\mathrm{QQ}}},T_2^ \ast ,\phi _0\), and \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}\), from the data (Methods). This allows us to extract the t_{int} dependence of \(\phi _{\sigma _z^{{\mathrm{LD}}}}\) (Fig. 3a) (Methods) and consequently ϕ_{C} = ϕ_{↓〉} − ϕ_{↑〉} (Fig. 3b). It evolves with t_{int} in the frequency of J^{QQ}/h = 90 MHz, indicating that the CPHASE gate time can be as short as h/2J^{QQ} = 5.5 ns (up to singlequbit phase). On the other hand, \(T_2^ \ast\) obtained in the MLE is 211 ns, much longer than what is observed in Fig. 2e, f because the shorter data acquisition time used here cuts off the lowfrequency component of the noise spectrum^{29}. We note that this \(T_2^ \ast\) is that for the twoqubit gate while J^{QQ} is turned on^{8}, and therefore it is likely to be dominated by charge noise rather than the nuclear field fluctuation (Supplementary Note 6). The ratio \(2J^{{\mathrm{QQ}}}T_2^ \ast /h\) suggests that 38 CPHASE operations would be possible within the twoqubit dephasing time. We anticipate that this ratio can be further enhanced by adopting approaches used to reduce the sensitivity to charge noise in exchange gates such as symmetric operation^{31,32} and operation in an enhanced field gradient^{33}.
Finally we show that the CPHASE gate operates correctly for arbitrary Q_{LD} input states. We implement the circuit shown in Fig. 4a in which t_{int} is fixed to yield ϕ_{C} = π, while a coherent initial Q_{LD} state with an arbitrary \(\sigma _z^{{\mathrm{LD}}}\) is prepared by EDSR. We extract the averaged \(\phi _{\sigma _z^{{\mathrm{LD}}}}\), \(\left\langle \phi _{\sigma _z^{{\mathrm{LD}}}} \right\rangle\) by Bayesian estimation^{29,30}, which shows an oscillation as a function of t_{MW} in agreement with the Rabi oscillation measured independently by reading out Q_{LD} at stage C as shown in Fig. 4b (see Methods for the estimation procedure and the origin of the low visibility, i.e., \({\mathrm{max}} {\langle {\phi _{\sigma _z^{{\mathrm{LD}}}}} \rangle }  < \pi /2\)). These results clearly demonstrate the CPHASE gate functioning for an arbitrary Q_{LD} input state.
Discussion
In summary, we have realized a fast quantum interface between a LD qubit and a ST qubit using a TQD. The CPHASE gate between these qubits is performed in 5.5 ns, much faster than its dephasing time of 211 ns and those ratio (~38) would be high enough to provide a highfidelity CPHASE gate (Supplementary Note 8). Optimizing the magnet design to enhance the field gradient would allow even faster gate time beyond GHz with larger J^{QQ}. At the same time, this technique is directly applicable to Sibased devices with much better singlequbit coherence^{5,6,7,8,9}. Our results suggest that the performance of certain quantum computational tasks can be enhanced by adopting different kinds of qubits for different roles. For instance, LD qubits can be used for highfidelity control and long memory and the ST qubit for fast initialization and readout. This combination is ideal for example, the surface code quantum error correction where a data qubit must maintain the coherence while a syndrome qubit must be measured quickly^{34}. Furthermore, the fast (~100 ns^{25}) ST qubit readout will allow the read out of a LD qubit in a quantumnondemolition manner^{35} with a speed three orders of magnitude faster than a typical energyselective tunneling measurement^{16,17}. Viewed from the opposite side, we envisage coupling two ST qubits through an intermediate LD qubit, which would boost the two ST qubit gate speed by orders of magnitude compared to the demonstrated capacitive coupling scheme^{14}. In addition, our results experimentally support the concept of the theoretical proposal of a fast twoqubit gate between two ST qubits based on direct exchange^{36} which shares the same working principle as our twoqubit gate. Our approach will further push the demonstrated scalability of spin qubits in quantum dot arrays beyond the conventional framework based on a unique spinqubit encoding.
Methods
Device design
Our device was fabricated on a GaAs/Al_{0.3}Ga_{0.7}As heterostructure wafer having a twodimensional electron gas 100 nm below the surface, grown by molecular beam epitaxy on a semiinsulating (100) GaAs substrate. The electron density n and mobility μ at a temperature of 4.2 K are n = 3.21 × 10^{15} m^{−2} and μ = 86.5 m^{2} V^{−1} s^{−1} in the dark, respectively. We deposited Ti/Au gate electrodes to define the TQD and the charge sensing single electron transistor. A piece of Co metal (micromagnet, MM) is directly placed on the surface of the wafer to provide a local magnetic field gradient in addition to the external magnetic field applied inplane (along z). The MM geometry is designed based on the numerical simulations of the local magnetic field^{23}. The field property is essentially characterized by the two parameters^{23}: dB_{x}/dz at the position of each dot and the difference in B_{z} between the neighboring dots, ΔB_{z} (see Fig. 1a for the definition of the x and z axes). dB_{x}/dz determines the spin rotation speed by EDSR and is as large as ~1 mT nm^{−1} at the left dot (Supplementary Fig. 5a) allowing fast control of Q_{LD} (f_{Rabi} > 10 MHz)^{20,23}. At the same time ΔB_{z} between the left and center dots, \({\mathrm{\Delta }}B_z^{{\mathrm{LC}}}\), is designed to be ~60 mT (Supplementary Fig. 5b) to guarantee the selective EDSR control of Q_{LD} without rotating the spin in the center dot^{20,23}. Furthermore, ΔB_{z} between the center and right dots, \({\mathrm{\Delta }}B_z^{{\mathrm{CR}}}\), is designed to be ~40 mT (Supplementary Fig. 5b) to make the eigenstates of Q_{ST} ↑↓〉 and ↓↑〉 rather than S〉 and T〉 by satisfying \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}} \gg J^{{\mathrm{ST}}}\). Note that \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}} = g\mu _{\mathrm{B}}{\mathrm{\Delta }}B_z^{{\mathrm{CR}}}\) where g ~ −0.4 and μ_{B} are the electron gfactor and Bohr magneton, respectively. From the design we expect a large variation of \({\mathrm{\Delta }}B_z^{{\mathrm{CR}}}\) when the electron in the center dot is displaced by the electric field. Indeed, we observe a strong influence of the gate voltages on \({\mathrm{\Delta }}B_z^{{\mathrm{CR}}}\), which reaches ~100 mT \(\left( {{\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}/h \sim 500\,{\mathrm{MHz}}} \right)\) in the configuration chosen for the twoqubit gate experiment.
Estimation of the ST precession parameters
Here we describe the estimation of the ST precession parameters in Eq. 2 under the influence of a fluctuating singlequbit phase of Q_{ST}. Out of the parameters involved, \(\phi _{\sigma _z^{{\mathrm{LD}}}}\) is the only parameter assumed to be Q_{LD} statedependent, and the rest is classified into two types. One is the pulsecycleindependent parameters, \(a,b,J^{{\mathrm{QQ}}},T_2^ \ast\) and t_{0} which is constant during the experiment, and the other is the pulsecycledependent parameters, \(\sigma _z^{{\mathrm{LD}}},{\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}\) and ϕ_{0}, which can change cycle by cycle. Each pulse cycle consists of pulse stages from A to C as shown in Fig. 2b. We run the pulse cycle consecutively with a MW frequency fixed at 17.26 GHz and collect the data while Q_{LD} drifts between onresonances and offresonances with the MW burst due to the nuclear field fluctuation. To decrease the uncertainty of the estimated parameters, we choose the cycles during which the spin flip of Q_{LD} is unlikely in the following manner. The cycles throughout which Q_{LD} is likely to be ↓〉 are postselected by the condition that Q_{LD} is onresonance (i.e., Rabi oscillation of Q_{LD} is observed in ensembleaveraged data from nearby cycles) and the final state of Q_{LD} is measured to be ↓〉 at pulse stage C. Similarly, the cycles for Q_{LD} = ↑〉 are postselected by the condition that Q_{LD} is offresonance and the final state of Q_{LD} is measured to be ↑〉. The data structure and the index definitions for MLE are summarized in Supplementary Table 1. k is the index of the interaction time such that t_{int} = 0.83 × k ns with k ranging from 1 to 100. m is the pulsecycle index ranging from 1 (2001) to 2000 (4000) for Q_{LD} prepared in ↑〉 (↓〉). The estimation procedure is the following. From all the readout results of Q_{ST} (stage H) obtained in the cycles, we first estimate the five pulsecycleindependent parameters by MLE. Note that J^{QQ} may have a small pulsecycledependent component due to charge noise but this effect is captured as additional fluctuation in \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}\) and ϕ_{0} in our model. We apply MLE to 100 × 4000 readout results of Q_{ST}, \(r_m^k = 1\) (0) for Q_{ST} = S〉 (T〉). To this end, we first introduce the likelihood P_{m} defined in the eight dimensional parameter space as
where P_{S,model} is defined in Eq. (2). We calculate P_{m} on a discretized space within a chosen parameter range (Supplementary Table 2) using a single cycle data. Then we obtain P_{m} for the target five parameters as a marginal distribution by tracing out the pulsecycledependent parameters,
Repeating this process for all pulse cycles, we obtain the likelihood P as
We choose the maximum of P as the estimator for a, b, t_{0}, J^{QQ} and \(T_2^ \ast\), obtaining a = 0.218 ± 0.005, b = 0.511 ± 0.003, t_{0} = 1.53 ± 0.17 ns, J^{QQ}/h = 90.2 ± 0.3 MHz, \(T_2^ \ast = 211 \pm 37\) ns.
Once these values are fixed, we estimate the pulsecycledependent parameters, \(\sigma _z^{{\mathrm{LD}}},\phi _0\) and \({\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}\), for each cycle m. Note that \(\sigma _z^{{\mathrm{LD}}}\) could be prepared deterministically if the state preparation of Q_{LD} were ideal, but here we treat it as one of the parameters to be estimated because of a finite error in the Q_{LD} state preparation. We again evaluate the likelihood \(P_m\left( {\sigma _z^{{\mathrm{LD}}},\phi _0,{\mathrm{\Delta }}E_{\mathrm{Z}}^{{\mathrm{ST}}}} \right)\) defined in a discretized three dimensional space of its parameters using Eq. 3 and find their values that maximize the likelihood.
Based on the values of \(a,b,T_2^ \ast\) and ϕ^{ST} determined above, we can directly estimate \(\phi _{\sigma _z^{{\mathrm{LD}}}}\) controlled by Q_{LD} for each t_{int} without presumptions on the value of J^{QQ}. To this end, we search for the parameter \(\phi _{\sigma _z^{{\mathrm{LD}}}}\) that maximizes the likelihood
The obtained estimators for ϕ_{↓〉} and ϕ_{↑〉} are consistent with the expected values ±πJ^{QQ}(t_{int} + t_{0})/h calculated from J^{QQ}/h and t_{0} found above (see Fig. 3a).
The ensembleaveraged phase \(\left\langle {\phi _{\sigma _z^{{\mathrm{LD}}}}} \right\rangle\) is obtained based on a similar estimation protocol. Here we estimate \(\phi _{\sigma _z^{{\mathrm{LD}}}}\) for each m with fixed k = 5 (t_{int} = 4.2 ns) to yield ϕ_{C} ≈ π from the likelihood \(P_m^{k = 5} = r_m^{k = 5}P_{{\mathrm{S}},{\mathrm{model}}} + \left( {1  r_m^{k = 5}} \right)\left( {1  P_{{\mathrm{S}},{\mathrm{model}}}} \right)\) and then take the average of the estimated values for 800 pulse cycles. The oscillation visibility of \(\left\langle {\phi _{\sigma _z^{{\mathrm{LD}}}}} \right\rangle\) in Fig. 4b is limited by three factors, low preparation fidelity of the input Q_{LD} state, estimation error of \(\phi _{\sigma _z^{{\mathrm{LD}}}}\) and CPHASE gate error. The first contribution is likely to be dominant as the visibility of the oscillation in P_{↓} is correspondingly low. Note that the effect of those errors is not visible in Fig. 3 because the most likely values of \(\phi _{\sigma _z^{{\mathrm{LD}}}}\) are plotted.
Data availability
The data that support the findings of this study are available from the corresponding authors upon reasonable request.
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Acknowledgements
Part of this work is financially supported by the ImPACT Program of Council for Science, Technology and Innovation (Cabinet Office, Government of Japan), the GrantinAid for Scientific Research (No. 26220710), CREST (JPMJCR15N2, JPMJCR1675), JST, Incentive Research Project from RIKEN. A.N. acknowledges support from Advanced Leading Graduate Course for Photon Science (ALPS). T.N. acknowledges financial support from JSPS KAKENHI Grant Number 18H01819. T.O. acknowledges financial support from GrantsinAid for Scientific Research (No. 16H00817, 17H05187), PRESTO (JPMJPR16N3), JST, The Telecommunications Advancement Foundation Research Grant, Futaba Electronics Memorial Foundation Research Grant, Hitachi Global Foundation Kurata Grant, The Okawa Foundation for Information and Telecommunications Research Grant, The Nakajima Foundation Research Grant, Japan Prize Foundation Research Grant, Iketani Science and Technology Foundation Research Grant,Yamaguchi Foundation Research Grant, Kato Foundation for Promotion of Science Research Grant. A.D.W. and A.L. acknowledge gratefully support of DFGTRR160, BMBF  Q.Link.X 16KIS0867, and the DFH/UFA CDFA0506.
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Contributions
A.N. and J.Y. conceived the experiment. A.N. and T.N. performed the measurement with the assistance of K.K., Y.K., M.R.D., T.O., K.T., S.A., and G.A. A.N. and T.N. conducted data analysis with the inputs from J.Y., P.S., and D.L. A.N. and T.N. fabricated the device on the heterostructure grown by A.L. and A.D.W. A.N. and T.N. wrote the manuscript with inputs from other authors. All authors discussed the results. The project was supervised by S.T.
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Noiri, A., Nakajima, T., Yoneda, J. et al. A fast quantum interface between different spin qubit encodings. Nat Commun 9, 5066 (2018). https://doi.org/10.1038/s41467018075221
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DOI: https://doi.org/10.1038/s41467018075221
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Nature Nanotechnology (2019)
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