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Register a new userScaling silicon-based quantum computing using CMOS technology: State-of-the-art, Challenges and Perspectives
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Added by
M. Fernando Gonzalez-Zalba
Publication date
2020
fields
Physics
and research's language is
English
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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.
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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.
This is a brief review of the experimental and theoretical quantum computing. The hopes for eventually building a useful quantum computer rely entirely on the so-called threshold theorem. In turn, this theorem is based on a number of assumptions, treated as axioms, i.e. as being satisfied exactly. Since in reality this is not possible, the prospects of scalable quantum computing will remain uncertain until the required precision, with which these assumptions should be approached, is established. Some related sociological aspects are also discussed. .
The past few years have witnessed the concrete and fast spreading of quantum technologies for practical computation and simulation. In particular, quantum computing platforms based on either trapped ions or superconducting qubits have become available for simulations and benchmarking, with up to few tens of qubits that can be reliably initialized, controlled, and measured. The present review aims at giving a comprehensive outlook on the state of art capabilities offered from these near-term noisy devices as universal quantum simulators, i.e. programmable quantum computers potentially able to calculate the time evolution of many physical models. First, we give a pedagogic overview on the basic theoretical background pertaining digital quantum simulations, with a focus on hardware-dependent mapping of spin-type Hamiltonians into the corresponding quantum circuit model as a key initial step towards simulating more complex models. Then, we review the main experimental achievements obtained in the last decade regarding the digital quantum simulation of such spin models, mostly employing the two leading quantum architectures. We compare their performances and outline future challenges, also in view of prospective hybrid technologies, towards the ultimate goal of reaching the long sought quantum advantage for the simulation of complex many body models in the physical sciences.
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.
In this paper a commercial 28-nm FDSOI CMOS technology is characterized and modeled from room temperature down to 4.2 K. Here we explain the influence of incomplete ionization and interface traps on this technology starting from the fundamental device physics. We then illustrate how these phenomena can be accounted for in circuit device-models. We find that the design-oriented simplified EKV model can accurately predict the impact of the temperature reduction on the transfer characteristics, back-gate sensitivity, and transconductance efficiency. The presented results aim at extending industry-standard compact models to cryogenic temperatures for the design of cryo- CMOS circuits implemented in a 28 nm FDSOI technology.
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