The advent of the computer has ushered in the fastest period of technological progress experienced by civilization. Quantum computing leverages the principles of quantum mechanics to process information in a fundamentally different paradigm, one that enables more efficient solving of computationally complex problems, including the factoring of large numbers, optimizing complex systems, and simulating molecular structures. In this new paradigm, information is encoded in quantum bits (qubits), which inherit the wave-like properties of superposition and interference to facilitate more efficient algorithms. However, to realize qubits experimentally, one must encode them into a quantum degree of freedom of a physical system. These are typically hard to control with very high accuracy. Interactions with the environment often lead to errors, limiting the number of operations one can perform reliably in these systems. Quantum error correction provides an alternative to protect quantum information from errors due to decoherence and operational imperfections at the cost of redundancy. Its core idea is to create a highly accurate logical qubit from many noisy physical qubits, ensuring that computational integrity is maintained despite the presence of errors.
This thesis studies experimental aspects of implementing quantum error correction with superconducting qubits: qubits encoded in quantum states of superconducting circuits operating at microwave frequencies and cooled down to cryogenic temperatures where they can exhibit coherent quantum behavior....@en

Quantum error correction enables the preservation of logical qubits with a lower logical error rate than the physical error rate, with performance depending on the decoding method. Traditional decoding approaches rely on the binarization ("hardening") of readout data, thereby ignoring valuable information embedded in the analog ("soft") readout signal. We present experimental results showcasing the advantages of incorporating soft information into the decoding process of a distance-3 (d=3) bit-flip surface code with flux-tunable transmons.@en

Artificial neural networks are becoming an integral part of digital solutions to complex problems. However, employing neural networks on quantum processors faces challenges related to the implementation of non-linear functions using quantum circuits. In this paper, we use repeat-until-success circuits enabled by real-time control-flow feedback to realize quantum neurons with non-linear activation functions. These neurons constitute elementary building blocks that can be arranged in a variety of layouts to carry out deep learning tasks quantum coherently. As an example, we construct a minimal feedforward quantum neural network capable of learning all 2-to-1-bit Boolean functions by optimization of network activation parameters within the supervised-learning paradigm. This model is shown to perform non-linear classification and effectively learns from multiple copies of a single training state consisting of the maximal superposition of all inputs.

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We present the use of a set of airbridges to trim the frequency of microwave coplanar-waveguide (CPW) resonators post-fabrication. This method is compatible with the fabrication steps of conventional CPW airbridges and crossovers and increases device yield by allowing compensation of design and fabrication uncertainty with 100 MHz range and 10 MHz resolution. We showcase two applications in circuit QED. The first is the elimination of frequency collisions between resonators intended to readout different transmons by frequency-division multiplexing. The second is frequency matching of readout and Purcell-filter resonator pairs. Combining this matching with transmon frequency trimming by laser annealing reliably achieves fast and high-fidelity readout across 17-transmon quantum processors.

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Minimizing leakage from computational states is a challenge when using many-level systems like superconducting quantum circuits as qubits. We realize and extend the quantum-hardware-efficient, all-microwave leakage reduction unit (LRU) for transmons in a circuit QED architecture proposed by Battistel et al. This LRU effectively reduces leakage in the second- and third-excited transmon states with up to 99% efficacy in 220 ns, with minimum impact on the qubit subspace. As a first application in the context of quantum error correction, we show how multiple simultaneous LRUs can reduce the error detection rate and suppress leakage buildup within 1% in data and ancilla qubits over 50 cycles of a weight-2 stabilizer measurement.

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Simple tuneup of fast two-qubit gates is essential for the scaling of quantum processors. We introduce the sudden variant (SNZ) of the net zero scheme realizing controlled-Z (CZ) gates by flux control of transmon frequency. SNZ CZ gates realized in a multitransmon processor operate at the speed limit of transverse coupling between computational and noncomputational states by maximizing intermediate leakage. Beyond speed, the key advantage of SNZ is tuneup simplicity, owing to the regular structure of conditional phase and leakage as a function of two control parameters. SNZ is compatible with scalable schemes for quantum error correction and adaptable to generalized conditional-phase gates useful in intermediate-scale applications.

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Future fault-tolerant quantum computers will require storing and processing quantum data in logical qubits. Here we realize a suite of logical operations on a distance-2 surface code qubit built from seven physical qubits and stabilized using repeated error-detection cycles. Logical operations include initialization into arbitrary states, measurement in the cardinal bases of the Bloch sphere and a universal set of single-qubit gates. For each type of operation, we observe higher performance for fault-tolerant variants over non-fault-tolerant variants, and quantify the difference. In particular, we demonstrate process tomography of logical gates, using the notion of a logical Pauli transfer matrix. This integration of high-fidelity logical operations with a scalable scheme for repeated stabilization is a milestone on the road to quantum error correction with higher-distance superconducting surface codes.

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