A singlet-triplet hole spin qubit in planar Ge

Jirovec, Daniel; Hofmann, Andrea; Ballabio, Andrea; Mutter, Philipp M.; Tavani, Giulio; Botifoll, Marc; Crippa, Alessandro; Kukučka, Josip; Sági, O.; Martins, Frederico Rodrigues; Saez-Mollejo, Jaime; Prieto, Iván; Borovkov, Maksim; Arbiol, Jordi; Chrastina, Daniel; Isella, Giovanni; Katsaros, Georgios

doi:10.1038/s41563-021-01022-2

Cited by 119 publications

(97 citation statements)

References 53 publications

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“…These devices can leverage well-established industrial platforms [5,6], while also enabling rapid all-electric spin control [7][8][9][10]. Recent demonstrations have included single-qubit gate operations of holes in silicon devices [10] and up to four-qubit gate operations of holes in Ge devices [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Electrical control of the g tensor of the first hole in a silicon MOS quantum dot

et al. 2021

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Single holes confined in semiconductor quantum dots are a promising platform for spin-qubit technology, due to the electrical tunability of the g factor of holes. However, the underlying mechanisms that enable electric spin control remain unclear due to the complexity of hole-spin states. Here, we study the underlying hole-spin physics of the first hole in a silicon planar metal-oxide-semiconductor (MOS) quantum dot. We show that nonuniform electrode-induced strain produces nanometer-scale variations in the heavy-hole-light-hole (HH-LH) splitting. Importantly, we find that this nonuniform strain causes the HH-LH splitting to vary by up to 50% across the active region of the quantum dot. We show that local electric fields can be used to displace the hole relative to the nonuniform strain profile, allowing a mechanism for electric modulation of the hole g tensor. Using this mechanism, we demonstrate tuning of the hole g factor by up to 500%. In addition, we observe a potential sweet spot where dg (110) /dV = 0, offering a configuration to suppress spin decoherence caused by electrical noise. These results open a path towards a technology involving engineering of nonuniform strains to optimize spin-based devices.

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Section: Introductionmentioning

confidence: 99%

Electrical control of the g tensor of the first hole in a silicon MOS quantum dot

et al. 2021

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“…Hole-spin qubits, on the other hand, can circumvent this difficulty thanks to their intrinsically large spin-orbit coupling, which enables electric-dipole spin manipulation. Over the last five years a variety of hole spin qubits have been reported in both silicon 11,15 and germanium [16][17][18][19] quantum dots. In all these qubits, quantum operations are performed using high-frequency gate voltage excitations.…”

Section: Introductionmentioning

confidence: 99%

A single hole spin with enhanced coherence in natural silicon

Piot¹,

B.²,

Schmitt³

et al. 2022

Preprint

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Semiconductor spin qubits based on spin-orbit states are responsive to electric field excitation allowing for practical, fast and potentially scalable qubit control. Spinelectric susceptibility, however, renders these qubits generally vulnerable to electrical noise, which limits their coherence time. Here we report on a spin-orbit qubit consisting of a single hole electrostatically confined in a natural silicon metal-oxidesemiconductor device. By varying the magnetic field orientation, we reveal the existence of operation sweet spots where the impact of charge noise is minimized while preserving an efficient electric-dipole spin control. We correspondingly observe an extension of the Hahn-echo coherence time up to 88 µs, exceeding by an order of magnitude the best reported values for hole-spin qubits, and approaching the state-of-the-art for electron spin qubits with synthetic spin-orbit coupling in isotopically-purified silicon. This finding largely enhances the prospects of silicon-based hole spin qubits for scalable quantum information processing.

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“…Semiconductor quantum dot devices are a promising candidate technology for the development of scalable quantum computing architectures. Singlet-triplet qubits encoded in double quantum dots 22 have demonstrably long coherence times 23,24 , as well as high one- 25 and two-qubit [26][27][28] gate fidelities. Promising qubit performance was also demonstrated in single-spin qubits [29][30][31] , and exchange only qubits 32,33 .…”

Section: Introductionmentioning

confidence: 99%

Deep reinforcement learning for efficient measurement of quantum devices

et al. 2021

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Deep reinforcement learning is an emerging machine-learning approach that can teach a computer to learn from their actions and rewards similar to the way humans learn from experience. It offers many advantages in automating decision processes to navigate large parameter spaces. This paper proposes an approach to the efficient measurement of quantum devices based on deep reinforcement learning. We focus on double quantum dot devices, demonstrating the fully automatic identification of specific transport features called bias triangles. Measurements targeting these features are difficult to automate, since bias triangles are found in otherwise featureless regions of the parameter space. Our algorithm identifies bias triangles in a mean time of <30 min, and sometimes as little as 1 min. This approach, based on dueling deep Q-networks, can be adapted to a broad range of devices and target transport features. This is a crucial demonstration of the utility of deep reinforcement learning for decision making in the measurement and operation of quantum devices.

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A singlet-triplet hole spin qubit in planar Ge

Cited by 119 publications

References 53 publications

Electrical control of the g tensor of the first hole in a silicon MOS quantum dot

Electrical control of the g tensor of the first hole in a silicon MOS quantum dot

A single hole spin with enhanced coherence in natural silicon

Deep reinforcement learning for efficient measurement of quantum devices

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