# Building the computer of the future

**Quantum computers have the potential to perform extremely complex calculations, by encoding information into quantum states. This opens the way for revolutionary applications, such as complex optimization challenges or prediction, simulation and modelling of the behaviour of molecules, catalysts and new materials.**

**Realizing the promise of quantum computing requires the development of different layers of hardware and software. Together, these layers are referred to as the quantum computing stack, and this is what we explore at QuTech. The base of the stack – the ‘quantum processor’ – contains the qubits. We are investigating different types of qubits, along with the system architecture that translates quantum algorithms into electronic signals that operate on the qubits.**

## Spin qubits

Long-term goal:

To build a modular spin-qubit processor for scalable quantum information processing.

### Highlights:

- In the
^{28}Si/SiGe quantum dot platform, we made progress on three fronts: we achieved bettercontrol, control of more qubits, and coupling between distantqubits. Specifically, we demonstrated a**record two-qubit gate fidelity**for electron spin qubits of 99.65% and used it to implement a variational quantum eigensolver algorithm (Nature), well above the prototypical 99% error threshold for fault-tolerance. Next, we achieved universal control of a record six spin qubits in a linear array, maintaining high fidelity (arXiv). Finally, we achieved a coherent coupling between two distant electron spins, separated by about 200 micron on the chip, mediated by virtual photons in a superconducting resonator (arXiv). These results built on methods for efficient RF readout of spins in quantum dots (Phys. Rev. Appl.). - In the Ge/SiGe platform, we developed extremely low-noise heterostructures (Mat. Quant. Tech.) on which we advanced semiconductor qubits beyond two-qubit logic and by scaling in two dimensions. We demonstrated a four-qubit germanium quantum processor (Nature), where all qubits can be controllably entangled and disentangled. Additionally, we demonstrated a record single-qubit fidelity for semiconductor qubits approaching 99.99% (arXiv).
- We proposed and analyzed in much detail a spin qubit architecture consisting of qubit dots spaced about 10 micron apart and networked together through shuttling channels, aimed at overcoming the wiring bottleneck (arXiv).
- In our work on quantum simulations, we simulated the antiferromagnetic Heisenberg spin chain (Phys. Rev. X). After earlier quantum simulations where the dominant energy scale was the on-site interaction (2017) or the hopping (2020), here the weaker spin exchange term dominated the physics.

## Transmon qubits

Long-term goal:

To realize an error-protected logical qubit with a superconducting circuit and a flexible control stack, enabling NISQ applications.

### Highlights:

- In the realm of NISQ applications, we demonstrated (in collaboration with Intel Labs) the possibility to simulate a quantum system at finite temperature using a hybrid quantum-classical variational algorithm and only unitary control (NPJ Quantum Information).
- In the realm of quantum error correction, we demonstrated a universal set of logical-qubit operations (including initialization, gates and measurement) in the small (distance-2) surface code Surface-7, while also achieving unprecedented logical-state stabilization by multi-round quantum error detection (Nature Physics).
- We took significant strides toward realizing a fully error-corrected logical qubit in the distance-3 surface code Surface-17. We developed reliable post-fabrication trimming techniques to achieve frequency targeting of transmons and resonators in our circuit QED quantum architecture, yielding operational 17-qubit devices. We developed highly parallelized characterization and calibration routines, and increased the robustness of interfaces, programmability and self-testing of the electronics control stack (together with TNO). These developments place us in excellent position to achieve logical-state stabilization and logical-qubit computation with Surface-17 in the coming year. These efforts have contributed to the admission of the QuSurf consortium (left by TU Delft) to a new phase of the IARPA LogiQ programme with additional funding through March 2023.

## Quantum computing architecture stack

Long-term goal:

To develop a scalable quantum computing control system stack that bridges the gap between quantum applications and quantum devices.

### Highlights:

- We developed a context-aware version of the gate set tomography protocol that, due to refined sequence selection, allows for a higher accuracy of error characterization validated using simulated QPUs as well as Quantum Inspire's Starmon-5 chip (arXiv).
- We improved the quantum programming framework OpenQL (ACM JETCS) by adding a mapper that is now timing- and resource-aware (IEEE TCAD).
- We proposed the application of Design Space Exploration methodologies to optimally architect full-stack quantum systems in the NISQ era (DATE), but also to analyze the scalability of quantum processors based on a distributed multi-core approach (IEEE Micro, in collaboration with UPC).
- We introduced a noise-aware heuristic mapping algorithm and analyzed how the topological structure of the interaction graph underlying the quantum circuit affects the performance of the algorithm (arXiv).

## Cryogenic electronics

Long-term goal:

To replace room-temperature electronics that control quantum processors with integrated cryogenic electronics, operating in close proximity to the qubits, in order to facilitate large-scale quantum computers.

### Highlights:

- To enable the reliable design of high-performance circuits, we advanced the understanding and modelling of cryo-CMOS devices, including the self-heating of cryo-CMOS devices (JEDS), and got first results on compact models for EDA simulators (WOLTE).
- We demonstrated the first cryo-CMOS PLL (phase-locked loop) to be used as frequency generator in the cryogenic interface for quantum processors (CICC 2021).
- We demonstrated the first high-speed (1 GSa/s) cryo-CMOS analog-to-digital converter (ISSCC 2021), able to acquire a large number of frequency-multiplexed qubit readout channels over a 500-MHz bandwidth.
- We successfully performed the RF readout of a double quantum dot with a cryo-CMOS I/Q RF receiver operating at 4 K (ISSCC 2021).
- We showed, for the first time, universal two-qubit control and execution of quantum algorithms on silicon spin qubits with a cryo-CMOS controller (Nature). The cryo-CMOS controller, implemented as a 22-nm FinFET
**cryo-CMOS microwave driver**operating at 3 K controller, was awarded the ISSCC 2020 Jan van Vessem award for outstanding European paper.

## Theory for assessing the performance of quantum processors employing superconducting and spin qubits

Long-term goal:

To provide analyses and ideas towards implementing and assessing the performance of quantum error correction for superconducting and spin qubits

### Highlights:

- We demonstrated how to reach the so-called Heisenberg limit in estimating multiple eigenvalues in an input state by using a hybrid quantum/classical algorithm (arXiv)based on quantum phase estimation.
- We developed a hardware-efficient scalable leakage reduction scheme for superconducting qubits to actively remove excitations of the higher energy state of the qubit. Our scheme is geared towards the surface-code hardware architecture implemented and developed at QuTech. Leakage on data qubits of the code is removed by actively enabling an energy exchange with the read-out resonator of each qubit through which the excitation can dissipate. Leakage on ancilla qubits is removed by detection and applying a leakage-reducing pulse if necessary (Physical Review X).
**We provided theory support, analysis and decoding for experiments on:**

A logical qubit (5 nuclear spins) at a diamond NV-centre (collaboration with Taminiau at QuTech, arXiv)

Repetitive error detection and error correction in superconducting qubits (collaboration with DiCarlo at QuTech, *Nature Physics* and ongoing work)

Phase flip code in spin qubits (collaboration with Menno Veldhorst at QuTech, ongoing work)