02275nas a2200193 4500008004100000245007200041210006900113260001500182490000600197520168200203100002401885700002101909700002601930700002301956700002301979700002302002700001902025856003702044 2021 eng d00aRay-based framework for state identification in quantum dot devices0 aRaybased framework for state identification in quantum dot devic c06/17/20210 v23 a

Quantum dots (QDs) defined with electrostatic gates are a leading platform for a scalable quantum computing implementation. However, with increasing numbers of qubits, the complexity of the control parameter space also grows. Traditional measurement techniques, relying on complete or near-complete exploration via two-parameter scans (images) of the device response, quickly become impractical with increasing numbers of gates. Here, we propose to circumvent this challenge by introducing a measurement technique relying on one-dimensional projections of the device response in the multi-dimensional parameter space. Dubbed as the ray-based classification (RBC) framework, we use this machine learning (ML) approach to implement a classifier for QD states, enabling automated recognition of qubit-relevant parameter regimes. We show that RBC surpasses the 82 % accuracy benchmark from the experimental implementation of image-based classification techniques from prior work while cutting down the number of measurement points needed by up to 70 %. The reduction in measurement cost is a significant gain for time-intensive QD measurements and is a step forward towards the scalability of these devices. We also discuss how the RBC-based optimizer, which tunes the device to a multi-qubit regime, performs when tuning in the two- and three-dimensional parameter spaces defined by plunger and barrier gates that control the dots. This work provides experimental validation of both efficient state identification and optimization with ML techniques for non-traditional measurements in quantum systems with high-dimensional parameter spaces and time-intensive measurements.

1 aZwolak, Justyna, P.1 aMcJunkin, Thomas1 aKalantre, Sandesh, S.1 aNeyens, Samuel, F.1 aMacQuarrie, E., R.1 aEriksson, Mark, A.1 aTaylor, J., M. uhttps://arxiv.org/abs/2102.1178401423nas a2200157 4500008004100000245006500041210006300106260001400169520093400183100002401117700002601141700002101167700002101188700001901209856003701228 2020 eng d00aRay-based classification framework for high-dimensional data0 aRaybased classification framework for highdimensional data c10/1/20203 a

While classification of arbitrary structures in high dimensions may require complete quantitative information, for simple geometrical structures, low-dimensional qualitative information about the boundaries defining the structures can suffice. Rather than using dense, multi-dimensional data, we propose a deep neural network (DNN) classification framework that utilizes a minimal collection of one-dimensional representations, called \emph{rays}, to construct the "fingerprint" of the structure(s) based on substantially reduced information. We empirically study this framework using a synthetic dataset of double and triple quantum dot devices and apply it to the classification problem of identifying the device state. We show that the performance of the ray-based classifier is already on par with traditional 2D images for low dimensional systems, while significantly cutting down the data acquisition cost.

1 aZwolak, Justyna, P.1 aKalantre, Sandesh, S.1 aMcJunkin, Thomas1 aWeber, Brian, J.1 aTaylor, J., M. uhttps://arxiv.org/abs/2010.0050001439nas a2200205 4500008004100000245005100041210005100092260001500143300001200158490000800170520087500178100001801053700002201071700001301093700001601106700001901122700001901141700001801160856005501178 2018 eng d00aResonantly driven CNOT gate for electron spins0 aResonantly driven CNOT gate for electron spins c2018/01/26 a439-4420 v3593 a

Single-qubit rotations and two-qubit CNOT operations are crucial ingredients for universal quantum computing. Although high-fidelity single-qubit operations have been achieved using the electron spin degree of freedom, realizing a robust CNOT gate has been challenging because of rapid nuclear spin dephasing and charge noise. We demonstrate an efficient resonantly driven CNOT gate for electron spins in silicon. Our platform achieves single-qubit rotations with fidelities greater than 99%, as verified by randomized benchmarking. Gate control of the exchange coupling allows a quantum CNOT gate to be implemented with resonant driving in ~200 nanoseconds. We used the CNOT gate to generate a Bell state with 78% fidelity (corrected for errors in state preparation and measurement). Our quantum dot device architecture enables multi-qubit algorithms in silicon.

1 aZajac, D., M.1 aSigillito, A., J.1 aRuss, M.1 aBorjans, F.1 aTaylor, J., M.1 aBurkard, Guido1 aPetta, J., R. uhttp://science.sciencemag.org/content/359/6374/43901080nas a2200193 4500008004100000245003200041210002800073260001400101490000800115520060900123100001600732700001300748700001900761700001900780700001100799700002000810700001900830856003700849 2013 eng d00aThe Resonant Exchange Qubit0 aResonant Exchange Qubit c2013/7/310 v1113 aWe introduce a solid-state qubit in which exchange interactions among confined electrons provide both the static longitudinal field and the oscillatory transverse field, allowing rapid and full qubit control via rf gate-voltage pulses. We demonstrate two-axis control at a detuning sweet-spot, where leakage due to hyperfine coupling is suppressed by the large exchange gap. A {\pi}/2-gate time of 2.5 ns and a coherence time of 19 {\mu}s, using multi-pulse echo, are also demonstrated. Model calculations that include effects of hyperfine noise are in excellent quantitative agreement with experiment. 1 aMedford, J.1 aBeil, J.1 aTaylor, J., M.1 aRashba, E., I.1 aLu, H.1 aGossard, A., C.1 aMarcus, C., M. uhttp://arxiv.org/abs/1304.3413v201375nas a2200181 4500008004100000245008800041210006900129260001400198490000700212520082100219100001901040700001801059700002001077700001501097700001901112700001801131856004401149 2007 eng d00aRelaxation, dephasing, and quantum control of electron spins in double quantum dots0 aRelaxation dephasing and quantum control of electron spins in do c2007/7/130 v763 aRecent experiments have demonstrated quantum manipulation of two-electron spin states in double quantum dots using electrically controlled exchange interactions. Here, we present a detailed theory for electron spin dynamics in two-electron double dot systems that was used to guide these experiments and analyze experimental results. The theory treats both charge and spin degrees of freedom on an equal basis. Specifically, we analyze the relaxation and dephasing mechanisms that are relevant to experiments and discuss practical approaches for quantum control of two-electron system. We show that both charge and spin dephasing play important roles in the dynamics of the two-spin system, but neither represents a fundamental limit for electrical control of spin degrees of freedom in semiconductor quantum bits. 1 aTaylor, J., M.1 aPetta, J., R.1 aJohnson, A., C.1 aYacoby, A.1 aMarcus, C., M.1 aLukin, M., D. uhttp://arxiv.org/abs/cond-mat/0602470v2