Two-electron dephasing in single Si and GaAs quantum dots

Gamble, John King; Friesen, Mark; Coppersmith, S. N.; Hu, Xuedong

doi:10.1103/physrevb.86.035302

Cited by 42 publications

(68 citation statements)

References 59 publications

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“…In the GaAs charge qubit, both the Larmor oscillation and the Ramsey interference have been realized, but it remains challenging to use a complicated echo sequence [9]. In addition to high-frequency technics, compared with silicon, the stronger piezoelectric effect and electron-phonon interaction in GaAs will theoretically lead to the relatively shorter coherence time which may be another challenge to perform charge echo sequences [16]. Simultaneously, in turn, the realization of the echo processes in a GaAs system will be helpful to clarify the roles played by the different decoherence mechanisms.…”

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confidence: 99%

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Coherent control and charge echo in a GaAs charge qubit

Wang¹,

Chen²,

Cao³

et al. 2017

EPL

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In fulfilling the non-adiabatic requirement of pulse sequences, it is challenging to perform multi-pulse quantum control of a charge qubit. By optimizing our charge qubit and pulse parameters, we experimentally demonstrate the coherent control and echo process of a GaAs charge qubit. We firstly employed a single non-adiabatic voltage pulse to perform the Larmor oscillation experiment and determine the optimal operation pulses. Then, we produced Ramsey fringes using two pulses and extracted the decoherence time from the Ramsey fringes. More importantly, we successfully applied a charge echo pulse sequence to increase the extracted inhomogeneous dephasing time to ∼1360 ps. Our results show that the low-frequency noise is the important dephasing limiter of the coherence time of the charge qubit in the GaAs system.

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confidence: 99%

“…However, a serious challenge for charge qubits is the rapid loss of coherence caused by interactions with the environment. Mitigating environment noise is an important way to prolong the coherence time [15,16].…”

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confidence: 99%

Coherent control and charge echo in a GaAs charge qubit

Wang¹,

Chen²,

Cao³

et al. 2017

EPL

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“…We describe the physical mechanisms for implementing x-rotations (transitions between qubit states) and z-rotations (changes in the phase difference between the qubit states). We discuss the "slow" or "pure" spin-dephasing rate γ, arising from dephasing of the qubit states themselves, and the "fast" charge-dephasing rate Γ, involving the intermediate state (26,27). We then present the calculations and results for qubit fidelities, based on the master equations presented in Materials and Methods (see SI Text for further details).…”

Section: Significancementioning

confidence: 99%

High-fidelity gates in quantum dot spin qubits

Koh

Coppersmith

Friesen

2013

Proc. Natl. Acad. Sci. U.S.A.

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Several logical qubits and quantum gates have been proposed for semiconductor quantum dots controlled by voltages applied to top gates. The different schemes can be difficult to compare meaningfully. Here we develop a theoretical framework to evaluate disparate qubit-gating schemes on an equal footing. We apply the procedure to two types of double-dot qubits: the singlet-triplet and the semiconducting quantum dot hybrid qubit. We investigate three quantum gates that flip the qubit state: a DC pulsed gate, an AC gate based on logical qubit resonance, and a gate-like process known as stimulated Raman adiabatic passage. These gates are all mediated by an exchange interaction that is controlled experimentally using the interdot tunnel coupling g and the detuning e, which sets the energy difference between the dots. Our procedure has two steps. First, we optimize the gate fidelity (f) for fixed g as a function of the other control parameters; this yields an f opt (g) that is universal for different types of gates. Next, we identify physical constraints on the control parameters; this yields an upper bound f max that is specific to the qubit-gate combination. We show that similar gate fidelities (∼ 99:5%) should be attainable for singlet-triplet qubits in isotopically purified Si, and for hybrid qubits in natural Si. Considerably lower fidelities are obtained for GaAs devices, due to the fluctuating magnetic fields ΔB produced by nuclear spins.quantum computing | Heisenberg exchange | decoherence T he fundamental building block of a quantum information processor is a two-state quantum system, or qubit. Solid-state qubits based on electrons confined in top-gated quantum dots in semiconductor heterostructures (1) are promising, due to the promise of manipulability and the overall maturity of semiconductor technology. In a charge qubit, the information is stored in the location of an electron in a double quantum dot. Because charge qubits are subject to strong Coulomb interactions, they can be manipulated quickly, at gigahertz frequencies, using control electronics (2-5); however, they also couple strongly to environmental noise sources, such as thermally activated charges on materials defects, leading to short, subnanosecond decoherence times (6). Spin qubits, which couple more weakly to environmental noise, have much longer coherence times (1, 7-15). However, because magnetic couplings are weak, gate operations between spin qubits are slow. For this reason, in most gating protocols, spin qubits adopt a charge character briefly during gate operations. Successful gate operations generally entail a tradeoff: charge-like for faster gates vs. spin-like for better coherence.Several types of logical qubits have been designed to enable electrically controlled manipulation and measurement of qubits encoded in spin degrees of freedom formed of two or more electrons in two (7, 9, 16) or three (11) coupled dots. These logical qubits share experimental control knobs; however, their spin-charge characteristics vary widely, yielding ...

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“…36,43 We also note that, on scaling down to the most extreme technology nodes, a leading role in decoherence mechanism will be taken by electron-phonon interaction instead of charge noise. 97 Such phenomena must be effectively suppressed by limiting the material disorder and by cooling the system at temperatures of the order of 10 mK that are actually at hand in state-of-the-art dilution refrigerators. 35,46,87,88 As a final remark, the reduction of disorder and of charge noise are apparently among the main challenges to reach the ideal coherence time of~1 µs 37 enabling large-scale quantum computing within the stringent limits represented in Fig.…”

Section: Operation Time Constraints and Sources Of Decoherencementioning

confidence: 99%

Quantum information density scaling and qubit operation time constraints of CMOS silicon-based quantum computer architectures

et al. 2017

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Even the quantum simulation of an apparently simple molecule such as Fe 2 S 2 requires a considerable number of qubits of the order of 10 6 , while more complex molecules such as alanine (C 3 H 7 NO 2 ) require about a hundred times more. In order to assess such a multimillion scale of identical qubits and control lines, the silicon platform seems to be one of the most indicated routes as it naturally provides, together with qubit functionalities, the capability of nanometric, serial, and industrial-quality fabrication. The scaling trend of microelectronic devices predicting that computing power would double every 2 years, known as Moore's law, according to the new slope set after the 32-nm node of 2009, suggests that the technology roadmap will achieve the 3-nm manufacturability limit proposed by Kelly around 2020. Today, circuital quantum information processing architectures are predicted to take advantage from the scalability ensured by silicon technology. However, the maximum amount of quantum information per unit surface that can be stored in silicon-based qubits and the consequent space constraints on qubit operations have never been addressed so far. This represents one of the key parameters toward the implementation of quantum error correction for faulttolerant quantum information processing and its dependence on the features of the technology node. The maximum quantum information per unit surface virtually storable and controllable in the compact exchange-only silicon double quantum dot qubit architecture is expressed as a function of the complementary metal-oxide-semiconductor technology node, so the size scale optimizing both physical qubit operation time and quantum error correction requirements is assessed by reviewing the physical and technological constraints. According to the requirements imposed by the quantum error correction method and the constraints given by the typical strength of the exchange coupling, we determine the workable operation frequency range of a silicon complementary metal-oxide-semiconductor quantum processor to be within 1 and 100 GHz. Such constraint limits the feasibility of fault-tolerant quantum information processing with complementary metal-oxide-semiconductor technology only to the most advanced nodes. The compatibility with classical complementary metal-oxide-semiconductor control circuitry is discussed, focusing on the cryogenic complementary metal-oxide-semiconductor operation required to bring the classical controller as close as possible to the quantum processor and to enable interfacing thousands of qubits on the same chip via timedivision, frequency-division, and space-division multiplexing. The operation time range prospected for cryogenic control electronics is found to be compatible with the operation time expected for qubits. By combining the forecast of the development of scaled technology nodes with operation time and classical circuitry constraints, we derive a maximum quantum information density for logical qubits of 2.8 and 4 Mqb/cm 2 for the 10 and 7-...

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Two-electron dephasing in single Si and GaAs quantum dots

Cited by 42 publications

References 59 publications

Coherent control and charge echo in a GaAs charge qubit

Coherent control and charge echo in a GaAs charge qubit

High-fidelity gates in quantum dot spin qubits

Quantum information density scaling and qubit operation time constraints of CMOS silicon-based quantum computer architectures

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