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To push gate performance to levels beyond the thresholds for quantum error correction, it is important to characterize the error sources occurring on quantum gates. However, the characterization of non-Markovian error poses a challenge to current quantum process tomography techniques. Fast Bayesian Tomography (FBT) is a self-consistent gate set tomography protocol that can be bootstrapped from earlier characterization knowledge and be updated in real-time with arbitrary gate sequences. Here we demonstrate how FBT allows for the characterization of key non-Markovian error processes. We introduce two experimental protocols for FBT to diagnose the non-Markovian behavior of two-qubit systems on silicon quantum dots. To increase the efficiency and scalability of the experiment-analysis loop, we develop an online FBT software stack. To reduce experiment cost and analysis time, we also introduce a native readout method and warm boot strategy. Our results demonstrate that FBT is a useful tool for probing non-Markovian errors that can be detrimental to the ultimate realization of fault-tolerant operation on quantum computing.

Quantum technology is exploding. Computing, communication, and sensing are just a few areas likely to see breakthroughs in the next few years. Worldwide, national governments, industries, and universities are moving to create a new class of workforce - the Quantum Engineers. Demand for such engineers is predicted to be in the tens of thousands within a five-year timescale. However, how best to train this next generation of engineers is far from obvious. Quantum mechanics - long a pillar of traditional physics undergraduate degrees - must now be merged with traditional engineering offerings. This paper discusses the history, development, and first year of operation of the world's first undergraduate degree in quantum engineering. The main purpose of the paper is to inform the wider debate, now being held by many institutions worldwide, on how best to formally educate the Quantum Engineer., Comment: Comments welcome

Silicon spin qubits promise to leverage the extraordinary progress in silicon nanoelectronic device fabrication over the past half century to deliver large-scale quantum processors. Despite the scalability advantage of using silicon technology, realising a quantum computer with the millions of qubits required to run some of the most demanding quantum algorithms poses several outstanding challenges, including how to control so many qubits simultaneously. Recently, compact 3D microwave dielectric resonators were proposed as a way to deliver the magnetic fields for spin qubit control across an entire quantum chip using only a single microwave source. Although spin resonance of individual electrons in the globally applied microwave field was demonstrated, the spins were controlled incoherently. Here we report coherent Rabi oscillations of single electron spin qubits in a planar SiMOS quantum dot device using a global magnetic field generated off-chip. The observation of coherent qubit control driven by a dielectric resonator establishes a credible pathway to achieving large-scale control in a spin-based quantum computer.

Benchmarking and characterising quantum states and logic gates is essential in the development of devices for quantum computing. We introduce a Bayesian approach to self-consistent process tomography, called fast Bayesian tomography (FBT), and experimentally demonstrate its performance in characterising a two-qubit gate set on a silicon-based spin qubit device. FBT is built on an adaptive self-consistent linearisation that is robust to model approximation errors. Our method offers several advantages over other self-consistent tomographic methods. Most notably, FBT can leverage prior information from randomised benchmarking (or other characterisation measurements), and can be performed in real time, providing continuously updated estimates of full process matrices while data is acquired., Comment: 10 pages + 6 page appendix, 6 figures, comments welcome

Physical processes, camera movement, and unpredictable environmental conditions like the presence of dust can induce noise and artifacts in video feeds. We observe that popular unsupervised MOT methods are dependent on noise-free inputs. We show that the addition of a small amount of artificial random noise causes a sharp degradation in model performance on benchmark metrics. We resolve this problem by introducing a robust unsupervised multi-object tracking (MOT) model: AttU-Net. The proposed single-head attention model helps limit the negative impact of noise by learning visual representations at different segment scales. AttU-Net shows better unsupervised MOT tracking performance over variational inference-based state-of-the-art baselines. We evaluate our method in the MNIST-MOT and the Atari game video benchmark. We also provide two extended video datasets: ``Kuzushiji-MNIST MOT'' which consists of moving Japanese characters and ``Fashion-MNIST MOT'' to validate the effectiveness of the MOT models., Comment: Accepted to IEEE ICIP 2021

Spin-based silicon quantum electronic circuits offer a scalable platform for quantum computation, combining the manufacturability of semiconductor devices with the long coherence times afforded by spins in silicon. Advancing from current few-qubit devices to silicon quantum processors with upwards of a million qubits, as required for fault-tolerant operation, presents several unique challenges, one of the most demanding being the ability to deliver microwave signals for large-scale qubit control. Here we demonstrate a potential solution to this problem by using a three-dimensional dielectric resonator to broadcast a global microwave signal across a quantum nanoelectronic circuit. Critically, this technique utilizes only a single microwave source and is capable of delivering control signals to millions of qubits simultaneously. We show that the global field can be used to perform spin resonance of single electrons confined in a silicon double quantum dot device, establishing the feasibility of this approach for scalable spin qubit control.

A fault-tolerant quantum processor may be configured using stationary qubits interacting only with their nearest neighbours, but at the cost of significant overheads in physical qubits per logical qubit. Such overheads could be reduced by coherently transporting qubits across the chip, allowing connectivity beyond immediate neighbours. Here we demonstrate high-fidelity coherent transport of an electron spin qubit between quantum dots in isotopically-enriched silicon. We observe qubit precession in the inter-site tunnelling regime and assess the impact of qubit transport using Ramsey interferometry and quantum state tomography techniques. We report a polarization transfer fidelity of 99.97% and an average coherent transfer fidelity of 99.4%. Our results provide key elements for high-fidelity, on-chip quantum information distribution, as long envisaged, reinforcing the scaling prospects of silicon-based spin qubits.

Quantum computers are expected to outperform conventional computers for a range of important problems, from molecular simulation to search algorithms, once they can be scaled up to large numbers of quantum bits (qubits), typically millions. For most solid-state qubit technologies, e.g. those using superconducting circuits or semiconductor spins, scaling poses a significant challenge as every additional qubit increases the heat generated, while the cooling power of dilution refrigerators is severely limited at their operating temperature below 100 mK. Here we demonstrate operation of a scalable silicon quantum processor unit cell, comprising two qubits confined to quantum dots (QDs) at $\sim$1.5 Kelvin. We achieve this by isolating the QDs from the electron reservoir, initialising and reading the qubits solely via tunnelling of electrons between the two QDs. We coherently control the qubits using electrically-driven spin resonance (EDSR) in isotopically enriched silicon $^{28}$Si, attaining single-qubit gate fidelities of 98.6% and coherence time $T_2^*$ = 2$\mu$s during `hot' operation, comparable to those of spin qubits in natural silicon at millikelvin temperatures. Furthermore, we show that the unit cell can be operated at magnetic fields as low as 0.1 T, corresponding to a qubit control frequency of 3.5 GHz, where the qubit energy is well below the thermal energy. The unit cell constitutes the core building block of a full-scale silicon quantum computer, and satisfies layout constraints required by error correction architectures. Our work indicates that a spin-based quantum computer could be operated at elevated temperatures in a simple pumped $^4$He system, offering orders of magnitude higher cooling power than dilution refrigerators, potentially enabling classical control electronics to be integrated with the qubit array.

Once the periodic properties of elements were unveiled, chemical bonds could be understood in terms of the valence of atoms. Ideally, this rationale would extend to quantum dots, often termed artificial atoms, and quantum computation could be performed by merely controlling the outer-shell electrons of dot-based qubits. Imperfections in the semiconductor material, including at the atomic scale, disrupt this analogy between atoms and quantum dots, so that real devices seldom display such a systematic many-electron arrangement. We demonstrate here an electrostatically-defined quantum dot that is robust to disorder, revealing a well defined shell structure. We observe four shells (31 electrons) with multiplicities given by spin and valley degrees of freedom. We explore various fillings consisting of a single valence electron -- namely 1, 5, 13 and 25 electrons -- as potential qubits, and we identify fillings that yield a total spin-1 on the dot. An integrated micromagnet allows us to perform electrically-driven spin resonance (EDSR). Higher shell states are shown to be more susceptible to the driving field, leading to faster Rabi rotations of the qubit. We investigate the impact of orbital excitations of the p- and d-shell electrons on single qubits as a function of the dot deformation. This allows us to tune the dot excitation spectrum and exploit it for faster qubit control. Furthermore, hotspots arising from this tunable energy level structure provide a pathway towards fast spin initialisation. The observation of spin-1 states may be exploited in the future to study symmetry-protected topological states in antiferromagnetic spin chains and their application to quantum computing.

Single-electron spin qubits employ magnetic fields on the order of 1 Tesla or above to enable quantum state readout via spin-dependent-tunnelling. This requires demanding microwave engineering for coherent spin resonance control and significant on-chip real estate for electron reservoirs, both of which limit the prospects for large scale multi-qubit systems. Alternatively, singlet-triplet (ST) readout enables high-fidelity spin-state measurements in much lower magnetic fields, without the need for reservoirs. Here, we demonstrate low-field operation of metal-oxide-silicon (MOS) quantum dot qubits by combining coherent single-spin control with high-fidelity, single-shot, Pauli-spin-blockade-based ST readout. We discover that the qubits decohere faster at low magnetic fields with $T_{2}^{Rabi}=18.6$~$\mu$s and $T_2^*=1.4$~$\mu$s at 150~mT. Their coherence is limited by spin flips of residual $^{29}$Si nuclei in the isotopically enriched $^{28}$Si host material, which occur more frequently at lower fields. Our finding indicates that new trade-offs will be required to ensure the frequency stabilization of spin qubits and highlights the importance of isotopic enrichment of device substrates for the realization of a scalable silicon-based quantum processor.

Implementing high-fidelity quantum control and reducing the effect of the coupling between a quantum system and its environment is a major challenge in developing quantum information technologies. Here, we show that there exists a geometrical structure hidden within the time-dependent Schr\"odinger equation that provides a simple way to view the entire solution space of pulses that suppress noise errors in a system's evolution. In this framework, any single-qubit gate that is robust against quasistatic noise to first order corresponds to a closed three-dimensional space curve, where the driving fields that implement the robust gate can be read off from the curvature and torsion of the space curve. Gates that are robust to second order are in one-to-one correspondence with closed curves whose projections onto three mutually orthogonal planes each enclose a vanishing net area. We use this formalism to derive new examples of dynamically corrected gates generated from smooth pulses. We also show how it can be employed to analyze the noise-cancellation properties of pulses generated from numerical algorithms such as GRAPE. A similar geometrical framework exists for quantum systems of arbitrary Hilbert space dimension., Comment: published version

Electron spins in silicon quantum dots provide a promising route towards realising the large number of coupled qubits required for a useful quantum processor. At present, the requisite single-shot spin qubit measurements are performed using on-chip charge sensors, capacitively coupled to the quantum dots. However, as the number of qubits is increased, this approach becomes impractical due to the footprint and complexity of the charge sensors, combined with the required proximity to the quantum dots. Alternatively, the spin state can be measured directly by detecting the complex impedance of spin-dependent electron tunnelling between quantum dots. This can be achieved using radio-frequency reflectometry on a single gate electrode defining the quantum dot itself, significantly reducing gate count and architectural complexity, but thus far it has not been possible to achieve single-shot spin readout using this technique. Here, we detect single electron tunnelling in a double quantum dot and demonstrate that gate-based sensing can be used to read out the electron spin state in a single shot, with an average readout fidelity of 73%. The result demonstrates a key step towards the readout of many spin qubits in parallel, using a compact gate design that will be needed for a large-scale semiconductor quantum processor.

Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. Based on the fact that fundus structure and vascular disorders are the main characteristics of retinal diseases, we propose a novel visual-assisted diagnosis hybrid model mixing the support vector machine (SVM) and deep neural networks (DNNs). Furthermore, we present a new clinical retina dataset, called EyeNet2, for ophthalmology incorporating 52 retina diseases classes. Using EyeNet2, our model achieves 90.43\% diagnosis accuracy, and the model performance is comparable to the professional ophthalmologists., Comment: A extension work of a workshop paper arXiv admin note: substantial text overlap with arXiv:1806.06423

The performance requirements for fault-tolerant quantum computing are very stringent. Qubits must be manipulated, coupled, and measured with error rates well below 1%. For semiconductor implementations, silicon quantum dot spin qubits have demonstrated average single-qubit Clifford gate error rates that approach this threshold, notably with error rates of 0.14% in isotopically enriched $^{28}$Si/SiGe devices. This gate performance, together with high-fidelity two-qubit gates and measurements, is only known to meet the threshold for fault-tolerant quantum computing in some architectures when assuming that the noise is incoherent, and still lower error rates are needed to reduce overhead. Here we experimentally show that pulse engineering techniques, widely used in magnetic resonance, improve average Clifford gate error rates for silicon quantum dot spin qubits to 0.043%,a factor of 3 improvement on previous best results for silicon quantum dot devices. By including tomographically complete measurements in randomised benchmarking, we infer a higher-order feature of the noise called the unitarity, which measures the coherence of noise. This in turn allows us to theoretically predict that average gate error rates as low as 0.026% may be achievable with further pulse improvements. These fidelities are ultimately limited by Markovian noise, which we attribute to charge noise emanating from the silicon device structure itself, or the environment.

Networks are abundant in biological systems. Small sized over-represented network motifs have been discovered, and it has been suggested that these constitute functional building blocks. We ask whether larger dynamical network motifs exist in biological networks, thus contributing to the higher-order organization of a network. To end this, we introduce a gradient descent machine learning (ML) approach and genetic algorithms to learn larger functional motifs in contrast to an (unfeasible) exhaustive search. We use the French Flag (FF) and Switch functional motif as case studies motivated from biology. While our algorithm successfully learns large functional motifs, we identify a threshold size of approximately 20 nodes beyond which learning breaks down. Therefore we investigate the stability of the motifs. We find that the size of the real negative eigenvalues of the Jacobian decreases with increasing system size, thus conferring instability. Finally, without imposing learning an input-output for all the components of the network, we observe that unconstrained middle components of the network still learn the desired function, a form of homogeneous team learning. We conclude that the size limitation of learnability, most likely due to stability constraints, impose a definite requirement for modularity in networked systems while enabling team learning within unconstrained parts of the module. Thus, the observation that community structures and modularity are abundant in biological networks could be accounted for by a computational compositional network structure., Comment: Accepted at the Joint ICML and IJCAI Workshop on Computational Biology (ICML-IJCAI WCB) to be held in Stockholm SWEDEN, 2018. Referring to https://sites.google.com/view/wcb2018/accepted-papers?authuser=0 update the team-learning figure

Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. We propose a novel visual-assisted diagnosis hybrid model based on the support vector machine (SVM) and deep neural networks (DNNs). The model incorporates complementary strengths of DNNs and SVM. Furthermore, we present a new clinical retina label collection for ophthalmology incorporating 32 retina diseases classes. Using EyeNet, our model achieves 89.73% diagnosis accuracy and the model performance is comparable to the professional ophthalmologists., Comment: Accepted at the Joint ICML and IJCAI Workshop on Computational Biology (ICML-IJCAI WCB) to be held in Stockholm SWEDEN, 2018. Referring to https://sites.google.com/view/wcb2018/accepted-papers?authuser=0

A two-qubit controlled-NOT (CNOT) gate, realized by a controlled-phase (C-phase) gate combined with single-qubit gates, has been experimentally implemented recently for quantum-dot spin qubits in isotopically enriched silicon, a promising solid-state system for practical quantum computation. In the experiments, the single-qubit gates have been demonstrated with fault-tolerant control-fidelity, but the infidelity of the two-qubit C-phase gate is, primarily due to the electrical noise, still higher than the required error threshold for fault-tolerant quantum computation (FTQC). Here, by taking the realistic system parameters and the experimental constraints on the control pulses into account, we construct experimentally realizable high-fidelity CNOT gates robust against electrical noise with the experimentally measured $1/f^{1.01}$ noise spectrum and also against the uncertainty in the interdot tunnel coupling amplitude. Our optimal CNOT gate has about two orders of magnitude improvement in gate infidelity over the ideal C-phase gate constructed without considering any noise effect. Furthermore, within the same control framework, high-fidelity and robust single-qubit gates can also be constructed, paving the way for large-scale FTQC., Comment: 6 pages, 2 figures

Universal quantum computation will require qubit technology based on a scalable platform, together with quantum error correction protocols that place strict limits on the maximum infidelities for one- and two-qubit gate operations. While a variety of qubit systems have shown high fidelities at the one-qubit level, superconductor technologies have been the only solid-state qubits manufactured via standard lithographic techniques which have demonstrated two-qubit fidelities near the fault-tolerant threshold. Silicon-based quantum dot qubits are also amenable to large-scale manufacture and can achieve high single-qubit gate fidelities (exceeding 99.9%) using isotopically enriched silicon. However, while two-qubit gates have been demonstrated in silicon, it has not yet been possible to rigorously assess their fidelities using randomized benchmarking, since this requires sequences of significant numbers of qubit operations ($\gtrsim 20$) to be completed with non-vanishing fidelity. Here, for qubits encoded on the electron spin states of gate-defined quantum dots, we demonstrate Bell state tomography with fidelities ranging from 80% to 89%, and two-qubit randomized benchmarking with an average Clifford gate fidelity of 94.7% and average Controlled-ROT (CROT) fidelity of 98.0%. These fidelities are found to be limited by the relatively slow gate times employed here compared with the decoherence times $T_2^*$ of the qubits. Silicon qubit designs employing fast gate operations based on high Rabi frequencies, together with advanced pulsing techniques, should therefore enable significantly higher fidelities in the near future.

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 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 phosphorus donor in silicon 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).

The spin states of electrons confined in semiconductor quantum dots form a promising platform for quantum computation. Recent studies of silicon CMOS qubits have shown coherent manipulation of electron spin states with extremely high fidelity. However, manipulation of single electron spins requires large oscillatory magnetic fields to be generated on-chip, making it difficult to address individual qubits when scaling up to multi-qubit devices. The spin-orbit interaction allows spin states to be controlled with electric fields, which act locally and are easier to generate. While the spin-orbit interaction is weak for electrons in silicon, valence band holes have an inherently strong spin-orbit interaction. However, creating silicon quantum dots in which a single hole can be localised, in an architecture that is suitable for scale-up to a large number of qubits, is a challenge. Here we report a silicon quantum dot, with an integrated charge sensor, that can be operated down to the last hole. We map the spin states and orbital structure of the first six holes, and show they follow the Fock-Darwin spectrum. We also find that hole-hole interactions are extremely strong, reducing the two-hole singlet-triplet splitting by 90% compared to the single particle level spacing of 3.5 meV. These results provide a route to single hole spin quantum bits in a planar silicon CMOS architecture., Comment: 7 pages, 3 figures

Silicon quantum dot spin qubits provide a promising platform for large-scale quantum computation because of their compatibility with conventional CMOS manufacturing and the long coherence times accessible using $^{28}$Si enriched material. A scalable error-corrected quantum processor, however, will require control of many qubits in parallel, while performing error detection across the constituent qubits. Spin resonance techniques are a convenient path to parallel two-axis control, while Pauli spin blockade can be used to realize local parity measurements for error detection. Despite this, silicon qubit implementations have so far focused on either single-spin resonance control, or control and measurement via voltage-pulse detuning in the two-spin singlet-triplet basis, but not both simultaneously. Here, we demonstrate an integrated device platform incorporating a silicon metal-oxide-semiconductor double quantum dot that is capable of single-spin addressing and control via electron spin resonance, combined with high-fidelity spin readout in the singlet-triplet basis., Comment: 10 pages, 4 figures

We identify the presence of monoatomic steps at the Si/SiGe or Si/SiO$_2$ interface as a dominant source of variations in the dephasing time of Si quantum dot (QD) spin qubits. First, using atomistc tight-binding calculations we show that the g-factors and their Stark shifts undergo variations due to these steps. We compare our theoretical predictions with experiments on QDs at a Si/SiO$_2$ interface, in which we observe significant differences in Stark shifts between QDs in two different samples. We also experimentally observe variations in the $g$-factors of one-electron and three-electron spin qubits realized in three neighboring QDs on the same sample, at a level consistent with our calculations. The dephasing times of these qubits also vary, most likely due to their varying sensitivity to charge noise, resulting from different interface conditions. More importantly, from our calculations we show that by employing the anisotropic nature of the spin-orbit interaction (SOI) in a Si QD, we can minimize and control these variations. Ultimately, we predict that the dephasing times of the Si QD spin qubits will be anisotropic and can be improved by at least an order of magnitude, by aligning the external DC magnetic field towards specific crystal directions., Comment: 5 pages, 3 figures, Supplemental Material (3 pages, 2 figures)

Silicon-based metal-oxide-semiconductor quantum dots are prominent candidates for high-fidelity, manufacturable qubits. Due to silicon's band structure, additional low-energy states persist in these devices, presenting both challenges and opportunities. Although the physics governing these valley states has been the subject of intense study, quantitative agreement between experiment and theory remains elusive. Here, we present data from a new experiment probing the valley states of quantum dot devices and develop a theory that is in quantitative agreement with both the new experiment and a recently reported one. Through sampling millions of realistic cases of interface roughness, our method provides evidence that, despite radically different processing, the valley physics between the two samples is essentially the same. This work provides the first evidence that valley splitting can be deterministically predicted and controlled in metal oxide semiconductor quantum dots, a critical requirement for such systems to realize a reliable qubit platform., Comment: 7 pages, 4 figures

Recent advances in quantum error correction (QEC) codes for fault-tolerant quantum computing \cite{Terhal2015} and physical realizations of high-fidelity qubits in a broad range of platforms \cite{Kok2007, Brown2011, Barends2014, Waldherr2014, Dolde2014, Muhonen2014, Veldhorst2014} give promise for the construction of a quantum computer based on millions of interacting qubits. However, the classical-quantum interface remains a nascent field of exploration. Here, we propose an architecture for a silicon-based quantum computer processor based entirely on complementary metal-oxide-semiconductor (CMOS) technology, which is the basis for all modern processor chips. We show how a transistor-based control circuit together with charge-storage electrodes can be used to operate a dense and scalable two-dimensional qubit system. The qubits are defined by the spin states of a single electron confined in a quantum dot, coupled via exchange interactions, controlled using a microwave cavity, and measured via gate-based dispersive readout \cite{Colless2013}. This system, based entirely on available technology and existing components, is compatible with general surface code quantum error correction \cite{Terhal2015}, enabling large-scale universal quantum computation.

We define single electron spin qubits in a silicon MOS double quantum dot system. By mapping the qubit resonance frequency as a function of gate-induced electric field, the spectrum reveals an anticrossing that is consistent with an inter-valley spin-orbit coupling. We fit the data from which we extract an inter-valley coupling strength of 43 MHz. In addition, we observe a narrow resonance near the primary qubit resonance when we operate the device in the (1,1) charge configuration. The experimental data is consistent with a simulation involving two weakly exchanged-coupled spins with a g-factor difference of 1 MHz, of the same order as the Rabi frequency. We conclude that the narrow resonance is the result of driven transitions between the T- and T+ triplet states, using an ESR signal of frequency located halfway between the resonance frequencies of the two individual spins. The findings presented here offer an alternative method of implementing two-qubit gates, of relevance to the operation of larger scale spin qubit systems.

We demonstrate the microscopic role of oxygen vacancies spatially confined within nanometer inter-spacing (about 1 nm) in BiFeO3, using resonant soft X-ray scattering techniques and soft X-ray spectroscopy measurements. Such vacancy confinements and total number of vacancy are controlled by substitution of Ca2+ for Bi3+ cation. We found that by increasing the substitution, the in-plane orbital bands of Fe3+ cations are reconstructed without any redox reaction. It leads to a reduction of the hopping between Fe atoms, forming a localized valence band, in particular Fe 3d-electronic structure, around the Fermi level. This band localization causes to decrease the conductivity of the doped BiFeO3 system., Comment: 24 pages, 4 figures, and 4 supplementary figures

Spin qubits composed of either one or three electrons are realized in a quantum dot formed at a Si/SiO_2-interface in isotopically enriched silicon. Using pulsed electron spin resonance, we perform coherent control of both types of qubits, addressing them via an electric field dependent g-factor. We perform randomized benchmarking and find that both qubits can be operated with high fidelity. Surprisingly, we find that the g-factors of the one-electron and three-electron qubits have an approximately linear but opposite dependence as a function of the applied dc electric field. We develop a theory to explain this g-factor behavior based on the spin-valley coupling that results from the sharp interface. The outer "shell" electron in the three-electron qubit exists in the higher of the two available conduction-band valley states, in contrast with the one-electron case, where the electron is in the lower valley. We formulate a modified effective mass theory and propose that inter-valley spin-flip tunneling dominates over intra-valley spin-flips in this system, leading to a direct correlation between the spin-orbit coupling parameters and the g-factors in the two valleys. In addition to offering all-electrical tuning for single-qubit gates, the g-factor physics revealed here for one-electron and three-electron qubits offers potential opportunities for new qubit control approaches.

We show that non-exponential fidelity decays in randomized benchmarking experiments on quantum dot qubits are consistent with numerical simulations that incorporate low-frequency noise. By expanding standard randomized benchmarking analysis to this experimental regime, we find that such non-exponential decays are better modeled by multiple exponential decay rates, leading to an instantaneous control fidelity for isotopically-purified-silicon MOS quantum dot qubits which can be as high as 99.9% when low-frequency noise conditions and system calibrations are favorable. These advances in qubit characterization and validation methods underpin the considerable prospects for silicon as a qubit platform for fault-tolerant quantum computation., Comment: 6 pages, 4 figures

Quantum computation requires qubits that can be coupled and realized in a scalable manner, together with universal and high-fidelity one- and two-qubit logic gates \cite{DiVincenzo2000, Loss1998}. Strong effort across several fields have led to an impressive array of qubit realizations, including trapped ions \cite{Brown2011}, superconducting circuits \cite{Barends2014}, single photons\cite{Kok2007}, single defects or atoms in diamond \cite{Waldherr2014, Dolde2014} and silicon \cite{Muhonen2014}, and semiconductor quantum dots \cite{Veldhorst2014}, all with single qubit fidelities exceeding the stringent thresholds required for fault-tolerant quantum computing \cite{Fowler2012}. Despite this, high-fidelity two-qubit gates in the solid-state that can be manufactured using standard lithographic techniques have so far been limited to superconducting qubits \cite{Barends2014}, as semiconductor systems have suffered from difficulties in coupling qubits and dephasing \cite{Nowack2011, Brunner2011, Shulman2012}. Here, we show that these issues can be eliminated altogether using single spins in isotopically enriched silicon\cite{Itoh2014} by demonstrating single- and two-qubit operations in a quantum dot system using the exchange interaction, as envisaged in the original Loss-DiVincenzo proposal \cite{Loss1998}. We realize CNOT gates via either controlled rotation (CROT) or controlled phase (CZ) operations combined with single-qubit operations. Direct gate-voltage control provides single-qubit addressability, together with a switchable exchange interaction that is employed in the two-qubit CZ gate. The speed of the two-qubit CZ operations is controlled electrically via the detuning energy and we find that over 100 two-qubit gates can be performed within a two-qubit coherence time of 8 \textmu s, thereby satisfying the criteria required for scalable quantum computation.