Technical digest - International Electron Devices Meeting/Technical digest
Quantum computing within the framework of advanced semiconductor manufacturing
James S. Clarke, Nicole K. Thomas, J. Roberts, R. Pilliarisetty, Zachary Yoscovits, Román Caudillo, Hubert C. George, Kanwal Jit Singh, David J. Michalak, Payam Amin, Antonio B. Mei, Alessandro Bruno, Stefano Poletto, Jelmer M. Boter, Gabriel Droulers, Nima Kalhor, Nodar Samkharadze, Juan Pablo Dehollain, LaReine A. Yeoh, Amir Sammak, Giordano Scappucci, Menno Veldhorst, L. DiCarlo, Lieven M. K. Vandersypen
Quantum computing holds the promise of exponential speedup compared to classical computing for select algorithms and applications. Relatively small numbers of logical quantum bits or qubits could outperform the largest of supercomputers. Quantum dots in Si-based heterostructures and superconducting Josephson junctions are just two of the many approaches to construct the qubit. These, in particular, bear similarities to the transistors and interconnects used in advanced semiconductor manufacturing. While initial results on few-qubit systems are promising, advanced process control is expected to improve the qubit uniformity, coherence time, and gate fidelity needed for larger systems. This can be realized through the systematic characterization of film growth, interface control, and patterning.
Quantum computing holds the promise of exponential speedup compared to classical computing for select algorithms and applications. Relatively small numbers of logical quantum bits or qubits could outperform the largest of supercomputers. Quantum dots in Si-based heterostructures and superconducting Josephson junctions are just two of the many approaches to construct the qubit. These, in particular, bear similarities to the transistors and interconnects used in advanced semiconductor manufacturing. While initial results on few-qubit systems are promising, advanced process control is expected to improve the qubit uniformity, coherence time, and gate fidelity needed for larger systems. This can be realized through the systematic characterization of film growth, interface control, and patterning.
The integration of semiconductor technologies with quantum computing hardware holds immense promise in revolutionizing computation paradigms. This abstract delves into the pivotal role semiconductor materials play in advancing quantum computing hardware, focusing on their fabrication, implementation, and scalability. Silicon quantum dots emerge as frontrunners in this landscape, offering a robust platform for qubit realization. Through lithography, ion implantation, and etching processes, semiconductor-based qubits demonstrate remarkable potential for scalability and manufacturability. This abstract navigates through the fundamentals of quantum computing, elucidating the principles of qubits and quantum gates. It explores the historical evolution of semiconductor technologies in quantum computing hardware, highlighting silicon as a promising substrate for quantum dot-based architectures. Challenges such as coherence times and error rates are scrutinized alongside potential solutions.
Quantum computers have gained widespread interest as they can potentially solve problems that are intractable even for today’s supercomputers, such as the simulation of quantum systems as initially proposed by Feynman. To achieve such tremendous progress, a quantum computer relies on processing the information stored in quantum bits (qubits), the fundamental units of quantum computation, similar to the bits in a classical (i.e., non-quantum) processor. In general, a quantum processor comprising several qubits is connected through a quantum-to-classical interface consisting of classical electrical circuits for manipulating and reading out their quantum state. The accuracy of an operation on a qubit is characterized using the fidelity, which is 100 % in case of a perfect operation. In practice, a fidelity between 99 % and 99.9 % is typically achieved in today’s experiments with less than 100 qubits, limited by non-idealities in the control signals and by the implementation of the physical qubit itself. Since such qubit fidelities are too low to execute relevant quantum algorithms, quantum error correction schemes have been developed which rely on a much larger number of qubits to correct for possible errors, resulting in the need for quantum processors with thousands or millions of qubits. Solid-state qubits promise the largescale integration required to scale to millions of qubits, as they exploit the lithographic fabrication techniques borrowed from the semiconductor industry. However, state-of-theart solid-state qubits, such as transmons and single-electron spin qubits, must be typically cooled to cryogenic temperatures in a dilution refrigerator to exhibit quantum behavior. Because of the limited number of qubits (< 100) in state-of-theart solid-state quantum processors, the classical controller is currently implemented by general-purpose instruments or by tailor-made controllers operating at room temperature connected via several wires to the qubits in the cryogenic chamber. However, these systems must scale to support millions of qubits. While scaling up the underlying quantum processor is already exceptionally challenging, building the electronics required to interface such a large-scale processor is just as relevant and arduous.
The understanding of quantum mechanics enabled the development of technology such as transistors and has been the foundation of today’s information age. Actively using quantum mechanics to build quantum technology may cause a second revolution in handling information. However, to execute meaningful algorithms, largescale quantum computers have to be built. Such systems are constructed from many qubits, the quantum version of the classical bit. While exciting progress is being made across a range of different qubit platforms, achieving the radical scalability that is necessary to build a largescale processor could be a roadblock. Huge challenges are put on reproducibility, inand output connectivity and material quality. Qubits based on the spins of electrons and holes confined in semiconductor quantum dots may have an important advantage in constructing quantum processors. This platform can profit from the advanced semiconductor industry that was responsible for the first computing revolution. Group IV semiconductors such as silicon and germanium have a high compatibility with industrial semiconductor manufacturing and contain stable isotopes with zero nuclear spin. The materials can be isotopically purified and serve as excellent hosts for spins with long quantum coherence. In Chapter 3 we present quantum dot arrays in silicon metaloxidesemiconductor (SiMOS), strained silicon (Si/SiGe) and strained germanium (Ge/SiGe). A nearly identical integration scheme based on an overlapping gate structure can be used to define quantum dots in each platform. Each platform has its own opportunities, which are carefully assessed. By employing charge sensing we confirm that all quantum dots can be depleted to the singleelectron regime. We compare capacitive crosstalk and find it to be the smallest in SiMOS, relevant for the tuning of quantum dot arrays. Using this crossplatform integration, we can study qubits in each platform with minimal overhead. Long coherence times, excellent singlequbit gate fidelities and twoqubit logic have been demonstrated with SiMOS spin qubits, making it one of the leading platforms for quantum information processing. However, due to the high disorder at the Si/SiO2 interface compared to Ge/SiGe and Si/SiGe interface, quantum dots defined in SiMOS are small and achieving sufficient control over single electrons has been a long standing challenge. In Chapter 5 we show experiments on a double quantum dot that can be isolated from its reservoir. We demonstrate a tunable tunnel coupling between single electrons up to 13 GHz and tunable tunnel rates down to below 1 Hz. These results mark an important step towards the required degree of control over the location of and coupling between quantum dots, necessary for the operation of a large array.
Quantum computers are based on the theory of quantum mechanics, and their powerful parallel data processing capability is expected to solve many mathematical problems that too are difficult to be handled by classical computers. Especially with the increase of data processing volume, the quantum advantage is more obvious. Among the many physical systems for quantum computers, superconducting quantum circuit and semiconductor quantum dot computers show amazing potential due to their compatibility with traditional integrated circuit process technology and ultrashort gating time of nanoseconds. Superconducting qubits consisting of Josephson junctions and superconducting coplanar capacitors are easily integrated into a large scale for their simple circuit structure and conventional semiconductor process compatibility. Semiconductor qubits made from isotopically purified silicon (Si)-based materials greatly suppress nuclear spin noise, and decoherence times of ultralong milliseconds can be achieved. In this article, we systematically describe the challenges faced by superconducting qubits and semiconductor qubits in hot issues such as error correction and decoherence and look into the future development of superconducting quantum computers and Si-based semiconductor quantum computers.
There is a growing demand for quantum computing across various sectors, including finance, materials, and studying chemical reactions. A promising implementation involves semiconductor qubits utilizing quantum dots within transistors. While academic research labs currently produce their own devices, scaling this process is challenging, requires expertise, and results in devices of varying quality. Some initiatives are exploring the use of commercial transistors, offering scalability, improved quality, affordability, and accessibility for researchers. This paper delves into potential realizations and the feasibility of employing off-the-shelf commercial devices for qubits. It addresses challenges such as noise, coherence, limited customizability in large industrial fabs, and scalability issues. The exploration includes discussions on potential manufacturing approaches for early versions of small qubit chips. The use of state-of-the-art transistors as hosts for quantum dots, incorporating readout techniques based on charge sensing or reflectometry, and methods like electron shuttling for qubit connectivity are examined. Additionally, more advanced designs, including 2D arrays and crossbar or DRAM-like access arrays, are considered for the path toward accessible quantum computing.
Quantum computing is one of the grand challenges of the 21st century and promises to transform almost every industry. As quantum computing technology exits the academic research phase into manufacturing, the goal is not to build single, unique qubits, but millions of interconnected, identical qubits capable of performing fully error corrected, general purpose calculations. Photon-based qubits offer a path to such a general-purpose machine by leveraging the mature silicon photonics high-volume manufacturing ecosystem. Creating quantum devices from silicon photonics components requires patterning innovation to bring leading-edge nanolithography to near macroscopic scale, a unique challenge for an industry where the future relies on progressive device shrink.