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arXiv:1704.06365 · npj Quantum Information

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

Davide Rotta, Fabio Sebastiano, Edoardo Charbon A, Enrico Prati

Published Jun 15, 2017• 53 citations
arXivHTMLPDF

Abstract

Abstract Even the quantum simulation of an apparently simple molecule such as Fe2S2requires a considerable number of qubits of the order of 106, while more complex molecules such as alanine (C3H7NO2) 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 fault-tolerant 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 time-division, 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/cm2for the 10 and 7-nm technology nodes, respectively, for the Steane code. The density is one and two orders of magnitude less for surface codes and for concatenated codes, respectively. Such values provide a benchmark for the development of fault-tolerant quantum algorithms by circuital quantum information based on silicon platforms and a guideline for other technologies in general.

DOI
10.1038/s41534-017-0023-5

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Abstract Even the quantum simulation of an apparently simple molecule such as Fe2S2requires a considerable number of qubits of the order of 106, while more complex molecules such as alanine (C3H7NO2) 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 fault-tolerant 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 time-division, 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/cm2for the 10 and 7-nm technology nodes, respectively, for the Steane code. The density is one and two orders of magnitude less for surface codes and for concatenated codes, respectively. Such values provide a benchmark for the development of fault-tolerant quantum algorithms by circuital quantum information based on silicon platforms and a guideline for other technologies in general.
Forthcoming CMOS technology nodes are in principle sufficient for achieving both the quantum information density and the speed that are critical for error-free logical qubits. Using data from the roadmap for semiconductor devices from ITRS and IEDM, we applied the standard CMOS design rules to a universal set of quantum logic gates to control silicon qubits. We consequently obtain a scaling law for quantum information density for Steane code, concatenated codes, and surface code, which represent the quantum information equivalent of Moore's law in terms of density scaling per node. By imposing the constraints due to both quantum error correction and the intrinsic operation speed limitation of a physical silicon qubit, we determine that technology nodes below 14 nm can in principle support error-free logical qubits manipulated at GHz frequency. We review the current state-of- the-art of silicon technology to assess the performance of different silicon qubit architectures based on CMOS single donors and double quantum dot devices. Our analysis demonstrates that silicon technology is compatible with the scalability requirements imposed by quantum error correction architectures for universal quantum computing. Such considerations provide a benchmark for the development of a silicon-based quantum computer and a general guideline for other quantum technology platforms.
Recent advances in quantum error correction codes for fault-tolerant quantum computing and physical realizations of high-fidelity qubits in multiple platforms 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 on complementary metal-oxide-semiconductor (CMOS) technology. 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 state of a single electron confined in quantum dots, coupled via exchange interactions, controlled using a microwave cavity, and measured via gate-based dispersive readout. We implement a spin qubit surface code, showing the prospects for universal quantum computation. We discuss the challenges and focus areas that need to be addressed, providing a path for large-scale quantum computing.
Abstract Recent advances in quantum error correction codes for fault-tolerant quantum computing and physical realizations of high-fidelity qubits in multiple platforms 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 on complementary metal-oxide-semiconductor (CMOS) technology. 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 state of a single electron confined in quantum dots, coupled via exchange interactions, controlled using a microwave cavity, and measured via gate-based dispersive readout. We implement a spin qubit surface code, showing the prospects for universal quantum computation. We discuss the challenges and focus areas that need to be addressed, providing a path for large-scale quantum computing.
As quantum processors grow in complexity, the focus is shifting towards the scaling of the entire quantum computing system, including the quantum hardware but as well the classical support electronics. Silicon-based quantum computing offers the enticing possibility that the quantum processor, the quantum-classical interface, and the classical layer can all, in principle, be manufactured using complementary metal-oxide semiconductor (CMOS) technology, creating an opportunity to move from distributed quantum-classical systems to integrated quantum computing solutions. Here, we review the state-of-the-art in spin-based quantum computing in silicon and present different approaches to help scale the technology using CMOS technology. We discuss the use of industry-manufactured silicon devices as the basic qubit element and present radio-frequency reflectometry techniques for fast high-fidelity spin readout. Finally, we show how quantum-classical co-integration can enable large-scale control and readout via frequency- and time-domain multiplexing.
Complementary metal-oxide semiconductor (CMOS) technology has radically reshaped the world by taking humanity to the digital age. Cramming more transistors into the same physical space has enabled an exponential increase in computational performance, a strategy that has been recently hampered by the increasing complexity and cost of miniaturization. To continue achieving significant gains in computing performance, new computing paradigms, such as quantum computing, must be developed. However, finding the optimal physical system to process quantum information, and scale it up to the large number of qubits necessary to build a general-purpose quantum computer, remains a significant challenge. Recent breakthroughs in nanodevice engineering have shown that qubits can now be manufactured in a similar fashion to silicon field-effect transistors, opening an opportunity to leverage the know-how of the CMOS industry to address the scaling challenge. In this article, we focus on the analysis of the scaling prospects of quantum computing systems based on CMOS technology.
Abstract The most promising quantum algorithms require quantum processors that host millions of quantum bits when targeting practical applications1. A key challenge towards large-scale quantum computation is the interconnect complexity. In current solid-state qubit implementations, an important interconnect bottleneck appears between the quantum chip in a dilution refrigerator and the room-temperature electronics. Advanced lithography supports the fabrication of both control electronics and qubits in silicon using technology compatible with complementary metal oxide semiconductors (CMOS)2. When the electronics are designed to operate at cryogenic temperatures, they can ultimately be integrated with the qubits on the same die or package, overcoming the ‘wiring bottleneck’3–6. Here we report a cryogenic CMOS control chip operating at 3 kelvin, which outputs tailored microwave bursts to drive silicon quantum bits cooled to 20 millikelvin. We first benchmark the control chip and find an electrical performance consistent with qubit operations of 99.99 per cent fidelity, assuming ideal qubits. Next, we use it to coherently control actual qubits encoded in the spin of single electrons confined in silicon quantum dots7–9 and find that the cryogenic control chip achieves the same fidelity as commercial instruments at room temperature. Furthermore, we demonstrate the capabilities of the control chip by programming a number of benchmarking protocols, as well as the Deutsch–Josza algorithm10, on a two-qubit quantum processor. These results open up the way towards a fully integrated, scalable silicon-based quantum computer.