A Tutorial for Characterizing Transmon Qubits
- URL: http://arxiv.org/abs/2606.03815v1
- Date: Tue, 02 Jun 2026 15:57:47 GMT
- Title: A Tutorial for Characterizing Transmon Qubits
- Abstract summary: We present a comprehensive walkthrough for the characterization and optimization of tunable transmon qubits.<n>We detail in a straightforward manner the complete workflow, from cryogenic setup and wiring to parametric amplifier optimum operation.<n>This guide serves as a reference for experimentalists seeking to efficiently bring up transmon-based quantum devices.
- Score: 35.18016233072556
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Superconducting transmon qubits are a leading technology for quantum information processing, yet their reliable operation rests on meticulous calibration and characterization routines. These processes have been fine-tuned and are relatively well understood by the quantum computing community. Nevertheless, it is often challenging for newcomers to compile all the available information into a practical experimental flow. In this tutorial, we present a comprehensive walkthrough for the characterization and optimization of tunable transmon qubits, demonstrated on a commercial five-qubit processor. Moving beyond theoretical description, we detail in a straightforward manner the complete workflow, from cryogenic setup and wiring to parametric amplifier optimum operation, flux sweet-spot identification, pulse calibration, and readout optimization. We also demonstrate the characterization of qubit-qubit coupling, covering all steps before multiqubit operations. This guide serves as a reference for experimentalists seeking to efficiently bring up transmon-based quantum devices.
Related papers
- A Superconducting Qubit-Resonator Quantum Processor with Effective All-to-All Connectivity [44.72199649564072]
This architecture can be used as a test-bed for algorithms that benefit from high connectivity.<n>We show that the central resonator can be used as a computational element.<n>We achieve a genuinely multi-qubit entangled Greenberger-Horne-Zeilinger (GHZ) state over all six qubits with a readout-error mitigated fidelity of $0.86$.
arXiv Detail & Related papers (2025-03-13T21:36:18Z) - Optimizing Superconducting Qubit Performance: A Theoretical Framework for Design, Analysis, and Calibration [0.0]
Superconducting qubits have emerged as a frontrunner among many competing technologies.<n>We develop a comprehensive theoretical framework that spans the entire process - from design to the calibration of hardware.<n>This work provides a detailed and practical approach to the design, optimization, and calibration of superconducting qubits.
arXiv Detail & Related papers (2025-01-29T18:17:16Z) - Field-Based Formalism for Calculating Multi-Qubit Exchange Coupling Rates for Transmon Qubits [0.0]
Superconducting qubits are one of the most mature platforms for quantum computing.
Existing analysis approaches using eigenmode solvers are cumbersome, not robust, and computationally prohibitive if devices with more than a few qubits are to be analyzed.
This work begins the development of an alternative framework that we illustrate in the context of evaluating the qubit-qubit exchange coupling rate between transmon qubits.
arXiv Detail & Related papers (2024-06-08T13:31:18Z) - Learning-based Calibration of Flux Crosstalk in Transmon Qubit Arrays [0.1950600573389501]
Superconducting quantum processors comprising flux-tunable data and coupler qubits are a promising platform for quantum computation.
Magnetic flux crosstalk between the flux-control lines and the constituent qubits impedes precision control of qubit frequencies.
We introduce a learning-based calibration protocol and demonstrate its experimental performance by calibrating an array of 16 flux-tunable transmon qubits.
arXiv Detail & Related papers (2023-03-06T18:34:58Z) - Two qubits in one transmon -- QEC without ancilla hardware [68.8204255655161]
We show that it is theoretically possible to use higher energy levels for storing and controlling two qubits within a superconducting transmon.
The additional qubits could be used in algorithms which need many short-living qubits in error correction or by embedding effecitve higher connectivity in qubit networks.
arXiv Detail & Related papers (2023-02-28T16:18:00Z) - Universal qudit gate synthesis for transmons [44.22241766275732]
We design a superconducting qudit-based quantum processor.
We propose a universal gate set featuring a two-qudit cross-resonance entangling gate.
We numerically demonstrate the synthesis of $rm SU(16)$ gates for noisy quantum hardware.
arXiv Detail & Related papers (2022-12-08T18:59:53Z) - Gradient-descent quantum process tomography by learning Kraus operators [63.69764116066747]
We perform quantum process tomography (QPT) for both discrete- and continuous-variable quantum systems.
We use a constrained gradient-descent (GD) approach on the so-called Stiefel manifold during optimization to obtain the Kraus operators.
The GD-QPT matches the performance of both compressed-sensing (CS) and projected least-squares (PLS) QPT in benchmarks with two-qubit random processes.
arXiv Detail & Related papers (2022-08-01T12:48:48Z) - Dynamical learning of a photonics quantum-state engineering process [48.7576911714538]
Experimentally engineering high-dimensional quantum states is a crucial task for several quantum information protocols.
We implement an automated adaptive optimization protocol to engineer photonic Orbital Angular Momentum (OAM) states.
This approach represents a powerful tool for automated optimizations of noisy experimental tasks for quantum information protocols and technologies.
arXiv Detail & Related papers (2022-01-14T19:24:31Z) - Full-Wave Methodology to Compute the Spontaneous Emission Rate of a
Transmon Qubit [0.0]
The spontaneous emission rate (SER) is an important figure of merit for any quantum bit (qubit)
We show how this can be done with a recently developed field-based description of transmon qubits coupled to an electromagnetic environment.
We validate our model by computing the SER for devices similar to those found in the literature that have been well-characterized experimentally.
arXiv Detail & Related papers (2022-01-11T23:47:20Z) - Quantum-tailored machine-learning characterization of a superconducting
qubit [50.591267188664666]
We develop an approach to characterize the dynamics of a quantum device and learn device parameters.
This approach outperforms physics-agnostic recurrent neural networks trained on numerically generated and experimental data.
This demonstration shows how leveraging domain knowledge improves the accuracy and efficiency of this characterization task.
arXiv Detail & Related papers (2021-06-24T15:58:57Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.