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.
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.
Quantum computing promises an exponential speed-up of computation compared to what is nowadays achievable with classical computers. In this way, it enables the evaluation of more complex models and the breaching of current security algorithms. For the operation of a quantum system, many questions remain to be answered. Currently, there are several quantum technologies that promise to be both reliable and scalable, two features required for large scale quantum operations. Common to all technologies is the operating temperature that needs to be close to absolute zero, i.e. below 100 mK, to suppress environment noise and allow the quantum properties to become 'visible'. In order for any quantum processor to be operated, a so-called quantum-classical interface is required for the quantum bit (qubit) read-out and control. This interface consists of various electronic blocks, such as analog-to-digital converters, digital-to-analog converters, mixers, amplifiers and a digital controller. Especially the analog blocks require effort to meet the noise and stability constraints as not to disturb the very sensitive qubits and allow reading of the tiny signals. As the qubits live in extremely deep-cryogenic temperatures, long wires interface the cryogenic with the room temperature environment, where most of the electronics is situated. However, for a scalable system, heat injection becomes a serious problem, with many wires between 300 K and sub-Kelvin. Furthermore, such amount of interconnects is challenging to mechanically place in a dilution refrigerator. Therefore, in this work, we propose to implement the electronics not at room temperature, but at a temperature much closer to the qubits, for example at 4 K. This not only reduces significantly the wiring between room temperature and the qubits, but we can also benefit from lower electronic noise at such a temperature. The operation of conventional electronics almost 200°C below its normal temperature range is not trivial as device properties alter significantly and most circuits no longer operate as intended. In CMOS processes, the main technology in the integrated electronics world, the behaviour of the transistors, required for the implementation of any circuit, deviates considerably at low temperatures. The transistor's threshold voltage goes up, the mobility increases and the subthreshold slope becomes steeper, to name just a few of these deviations. Although there are improvements in performance, there are also some counter effects, and characterization of the transistors is needed to observe the changes. Once devices are characterized at such low temperatures, new models can be built and circuits can be simulated and adapted to operate properly at cryogenic temperatures. Luckily, there are various commercially available devices that can already withstand the chills of cold. We demonstrated various commercially available devices, such as a field-programmable gate array (FPGA) implemented in a 28 nm CMOS process, to be operating without major concerns at 4~K. Its properties alter only slightly, within 5 to 10%, and all tested circuit implementations, working at 300~K, also worked at 4 K. We combined both commercially available devices, that operate 200 K below their specified temperature range, with custom designed CMOS circuits to implement a cryogenic read-out platform for spin qubits. This system comprises amplifiers, an ADC, an FPGA, voltage regulators and a clock generator. It allows to amplify the tiny signal from the qubits and digitize it directly in the FPGA in order to process the data locally at 4~K. This system is one of the first systematic attempts at operating a part of the quantum-classical interface at cryogenic temperatures and forms the basis for future systems comprising the complete electronic interface for qubits to operate at such low temperatures. One of the main problems to tackle for cryogenic electronic systems is their power consumption. Power budgets are simply limited to roughly 1 or 2 Watts at 4 K and exponentially lower at deeper cryogenic temperatures, thus limiting the size of large-scale electronic systems. Our approach of combined commercial and custom circuits will have to be steadily replaced by a single (custom) technology that meets both power and scalability constraints. One of the best candidates is CMOS, a technology that the industry has relied upon for several decades and benefits from many optimizations thanks to Moore's law.
Quantum computing holds the promise to achieve unprecedented computation power and to solve problems today intractable. State-of-the-art quantum processors consist of arrays of quantum bits (qubits) operating at a very low base temperature, typically a few tens of mK, as shown in Fig. 15.5.1 The qubit states degrade naturally after a certain time, upon loss of quantum coherence. For proper operation, an error-correcting loop must be implemented by a classical controller, which, in addition of handling execution of a quantum algorithm, reads the qubit state and performs the required corrections. However, while few qubits (~10) in today's quantum processors can be easily connected to a room-temperature controller, it appears extremely challenging, if not impossible, to manage the thousands of qubits required in practical quantum algorithms [1].
Quantum computers could efficiently solve problems that are intractable by today's computers, thus offering the possibility to radically change entire industries and revolutionize our lives. A quantum computer comprises a quantum processor operating at cryogenic temperature and an electronic interface for its control, which is currently implemented at room temperature for the few qubits available today. However, this approach becomes impractical as the number of qubits grows towards the tens of thousands required for complex quantum algorithms with practical applications. We propose an electronic interface for sensing and controlling qubits operating at cryogenic temperature implemented in standard CMOS.
Quantum processors rely on classical electronic controllers to manipulate and read out the quantum state. As the performance of the quantum processor improves, non-idealities in the classical controller can become the performance bottleneck for the whole quantum computer. To prevent such limitation, this paper presents a systematic study of the impact of the classical electrical signals on the qubit fidelity. All operations, i.e. single-qubit rotations, two-qubit gates and read-out, are considered, in the presence of errors in the control electronics, such as static, dynamic, systematic and random errors. Although the presented study could be extended to any qubit technology, it currently focuses on single-electron spin qubits, because of several advantages, such as purely electrical control and long coherence times, and for their potential for large-scale integration. As a result of this study, detailed electrical specifications for the classical control electronics for a given qubit fidelity can be derived, as demonstrated with specific case studies. We also discuss the effect on qubit fidelity of the performance of the general-purpose room-temperature equipment that is typically employed to control the few qubits available today. Ultimately, we show that tailor-made electronic controllers can achieve significantly lower power, cost and size, as required to support the scaling up of quantum computers.
Superconducting qubits based on Josephson junctions are one of the leading candidates for building a largescale quantum information processor. There have been significant advances in the performance of superconducting qubits over the past decade and there is currently rapid progress in the development of systems with up to tens of qubits. In order to build to yet larger systems, new techniques will need to be developed to address the overhead requirements for room-temperature electronics hardware and cryostat wiring for controlling and reading out large numbers of qubits. One approach to this challenge involves implementing more of the qubit control and readout in the low-temperature environment. I will describe our efforts on integrating superconducting classical digital circuitry with superconducting qubits for coherent control and readout.
Quantum computing holds the promise to solve problems that are currently intractable by classical computing platforms. Such computing framework relies on the properties of quantum bits (qubits) that operates at cryogenic temperatures well below 1K. Besides a quantum processor, an operational quantum computer needs a classical electronic controller reading out the electrical signals generated by the qubits and the providing electrical control to perform the required operations on the qubits. Since today’s quantum processors comprise a low number of qubits (<10), most controlling electronics can operate at room temperature and be connected by bulky interconnects to the cryogenic qubit chamber. However, when scaling up to the thousands of qubits required in a practical quantum algorithm, the classical electronics must be placed at cryogenic temperature to simplify the interconnects and allow a compact, reliable and scalable system. In this work, we propose the fully-integrated implementation in standard CMOS technology of the electronic read-out for spin qubits. Simulations show that the proposed current read-out circuit can achieve a 10MHz bandwidth that is 10X wider than current state-of-the-art read-outs while keeping comparable noise performance and operating at 4.2K. Such results are a promising indication that cryogenic CMOS circuits can provide the building blocks for the integration of the classical electronic controller for future scalable quantum computers.