CMOS charge qubits and qudits: entanglement entropy and mutual information as an optimization method to construct CNOT and SWAP Gates

Giounanlis, Panagiotis; Wu, Xutong; Sokolov, Andrii; Petropoulos, Nikolaos; Koskin, Eugene; Bashir, Imran; Leipold, Dirk; Staszewski, Robert Bogdan; Blokhina, Elena

doi:10.1088/1361-6641/abe550

Cited by 9 publications

(8 citation statements)

References 34 publications

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“…The discussed model can be easily extended to include dephasing phenomena by the use of the theory of open quantum systems [52]- [54]. However, the description of the system will have to be done through a density matrix rather than a state vector.…”

Section: Discussion On Incorporating Dephasing Phenomena and Temperature Dependencementioning

confidence: 99%

Towards the Co-Simulation of Charge Qubits: A Methodology Grounding on an Equivalent Circuit Representation

Blokhina

Sokolov

Giounanlis³

et al. 2021

IEEE Open J. Circuits Syst.

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Section: Discussion On Incorporating Dephasing Phenomena and Temperature Dependencementioning

confidence: 99%

Towards the Co-Simulation of Charge Qubits: A Methodology Grounding on an Equivalent Circuit Representation

Blokhina

Sokolov

Giounanlis³

et al. 2021

IEEE Open J. Circuits Syst.

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“…The weak interactions of the spin qubits with their environment, which is beneficial to their long decoherence times, make inter-qubit operations challenging. The charge qubits, however, can achieve stronger coupling to each other, enabling the realization of quantum gates through arrays of quantum dots [7], [10], [24], [55], as shown in Fig. 2.…”

Section: Overview Of Qda Structure For Charge Qubitsmentioning

confidence: 99%

“…This suggest roughly the same number of over 1000 gate operations per useful decoherence time. Therefore, despite their apparent imperfections when examined in isolation, the charge qubits generally appear as an attractive choice for integrated largescale quantum computing systems [7], [8], [10].…”

Section: Qubit Interface Circuitrymentioning

confidence: 99%

“…To address these challenges, we propose to leverage the unprecedented scalability of contemporary CMOS technology. Just like with a small IC chip, where a single nanometerscale transistor can be reliably replicated billions of times to build a digital or mixed-signal processor, a new positionbased charge qubit structure [7]- [10], realized as a CMOScompatible coupled quantum dot array (QDA), can be reliably replicated thousands (perhaps, millions) of times to construct a single-chip quantum processor operating at ∼4 K where the cooling requirements are modest.…”

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confidence: 99%

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Cryogenic Controller for Electrostatically Controlled Quantum Dots in 22-nm Quantum SoC

Staszewski

Esmailiyan²,

Wang

et al. 2022

IEEE Open J. Solid-State Circuits Soc.

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We present a fully integrated cryogenic controller for electrostatically controlled quantum dots (QDs) implemented in a commercial 22-nm FD-SOI CMOS process and operating in a quantum regime. The QDs are realized in local well areas of transistors separated by tunnel barriers controlled by voltages applied to gate terminals. The QD arrays (QDA) are co-located with the control circuitry inside each quantum experiment cell, with a total of 28 of such cells comprising this system-on-chip (SoC). The QDA structure is controlled by small capacitive digital-to-analog converters (CDACs) and its quantum state is measured by a single-electron detector.The SoC operates at a cryogenic temperature of 3.4 K. The occupied area of each QD array is 0.7×0.4 µm 2 , while each QD occupies only 20×80 nm 2 . The low power and miniaturized area of these circuits are an important step on the way for integration of a large quantum core with millions of QDs, required for practical quantum computers. The performance and functionality of the CDAC are validated in a loop-back mode with the detector sensing the CDAC-compelled electron tunneling from the quantum point contact (QPC) node into the quantum structure. Position of the injected charge inside the QD array is intended to be controlled through the CDAC codes and programmable pulse width. Quantum effects are shown by an experimental characterization of charge injection and quantization into the QD array consisting of three coupled QDs. The charge can be transferred to a QD and sensed at the QPC, and this process is controlled by the relevant voltages and CDACs.Index Terms-Capacitive DAC (CDAC), charge qubits, cryo-CMOS, fully depleted silicon-on-insulator (FD-SOI), imposer, positionbased qubits, quantum computer (QC), quantum dot (QD), single-electron detector, single-electron injector. I. INTRODUCTIONQ UANTUM computing is a new paradigm that utilizes the fundamental principles of quantum mechanics, such as superposition, interference and entanglement [1], [2]. The range of complex problems from mathematics, chemistry and material science that could be solved with quantum computing is far beyond the reach of today's most powerful supercomputers. The potential is thus immense. Quantum bits (qubits), basic units of quantum information, operate at a molecular/atomic level. They are extremely fragile and difficult to manipulate and read out. Some quantum computer technologies, such as based on trapped ions and photons, do not require the equipment to be cryogenically cooled [3], [4], but the majority of qubits must operate under extremely low Manuscript received

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“…After describing the hardware implementation, it is important to discuss the programming and resource allocation per quantum operation or, more specifically, an X Pauli rotation. The nature of the Pauli rotation exhibited by the charge qubit is a function of energy levels and well potential over the qubit array in addition to the waveform applied to the imposer 29 . The pattern shown in Fig.…”

Section: Pattern Generator (Patgen)mentioning

confidence: 99%

Monolithic Integration of Quantum Resonant Tunneling Gate on a 22nm FD-SOI CMOS Process

Bashir¹,

Leipold²,

Elena³

et al. 2021

Preprint

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The proliferation of quantum computing technologies has fueled the race to build a practical quantum computer. The spectrum of the innovation is wide and encompasses many aspects of this technology, such as the qubit, control and detection mechanism, cryogenic electronics, and system integration. A few of those emerging technologies are poised for successful monolithic integration of cryogenic electronics with the quantum structure where the qubits reside. In this work, we present a fully integrated Quantum Processor Unit in which the quantum core is co-located with control and detection circuits on the same die in a commercial 22-nm FD-SOI process from GlobalFoundries. The system described in this work comprises a two dimensional (2D) 240 qubits array integrated with 8 detectors and 32 injectors operating at 3 K and inside a two-stage Gifford -McMahon cryo-cooler. The power consumption of each detector and injector is 1 mW and 0.27 mW, respectively. The control sequence is programmed into an on-chip pattern generator that acts as a command and control block for all hardware in the Quantum Processor Unit. Using the aforementioned apparatus, we performed a quantum resonant tunneling experiment on two qubits inside the 2D qubit array. With supporting lab measurements, we demonstrate the feasibility of the proposed architecture in scaling-up the existing quantum core to thousands of qubits.

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CMOS charge qubits and qudits: entanglement entropy and mutual information as an optimization method to construct CNOT and SWAP Gates

Cited by 9 publications

References 34 publications

Towards the Co-Simulation of Charge Qubits: A Methodology Grounding on an Equivalent Circuit Representation

Towards the Co-Simulation of Charge Qubits: A Methodology Grounding on an Equivalent Circuit Representation

Cryogenic Controller for Electrostatically Controlled Quantum Dots in 22-nm Quantum SoC

Monolithic Integration of Quantum Resonant Tunneling Gate on a 22nm FD-SOI CMOS Process

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