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Register a new userQuantum information density scaling and qubit operation time constraints of CMOS silicon based quantum computer architectures
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Even the quantum simulation of simple molecules such as Fe$_2$S$_2$ requires more than 10$^6$ qubits. 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 provides the capability of nanometric, serial and industrial quality fabrication. The maximum amount of quantum information per unit surface and the consequent space constraints on qubit operations are key parameters towards fault-tolerant quantum information processing (QIP) with Si qubits. Such maximum density of quantum information is expressed for the compact exchange-only Si double quantum dot qubit architecture as a function of the CMOS technology node. The size scale optimizing both physical qubit operation time and quantum error correction (QEC) requirements is assessed by reviewing the physical and technological constraints. We determine the workable operation frequency range of a Si-CMOS quantum processor to be within 1 and 100 GHz, which limits its feasibility only to the most advanced nodes. The compatibility with classical control circuitry is discussed, focusing on the cryogenic CMOS 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. The operation time range prospected for cryogenic control electronics is found to be compatible with the qubit operation time. By combining the forecast of technology development 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-nm and 7-nm technology nodes respectively for the Steane code. The density is one and two orders of magnitude less for surface and concatenated codes respectively. Such values provide a benchmark for the development of Si-based fault tolerant QIP.
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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.
The most promising quantum algorithms require quantum processors hosting millions of quantum bits when targeting practical applications. A major challenge towards large-scale quantum computation is the interconnect complexity. In current solid-state qubit implementations, a major bottleneck appears between the quantum chip in a dilution refrigerator and the room temperature electronics. Advanced lithography supports the fabrication of both CMOS control electronics and qubits in silicon. When the electronics are designed to operate at cryogenic temperatures, it can ultimately be integrated with the qubits on the same die or package, overcoming the wiring bottleneck. Here we report a cryogenic CMOS control chip operating at 3K, which outputs tailored microwave bursts to drive silicon quantum bits cooled to 20mK. We first benchmark the control chip and find electrical performance consistent with 99.99% fidelity qubit operations, assuming ideal qubits. Next, we use it to coherently control actual silicon spin qubits and find that the cryogenic control chip achieves the same fidelity as commercial instruments. Furthermore, we highlight the extensive capabilities of the control chip by programming a number of benchmarking protocols as well as the Deutsch-Josza algorithm on a two-qubit quantum processor. These results open up the path towards a fully integrated, scalable silicon-based quantum computer.
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.
Quantum computing represents a radical departure from conventional approaches to information processing, offering the potential for solving problems that can never be approached classically. While large scale quantum computer hardware is still in development, several quantum computing systems have recently become available as commercial cloud services. We compare the performance of these systems on several simple quantum circuits and algorithms, and examine component performance in the context of each systems architecture.
When working to understand quantum systems engineering, there are many constraints to building a scalable quantum computer. Here I discuss a constraint on the qubit control system from an information point of view, showing that the large amount of information needed for the control system will put significant constraints on the control system. The size the qubits is conjectured to be an important systems parameter.
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