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arXiv:2503.10607 · Physical review. B./Physical review. B

Utilizing discrete variable representations for decoherence-accurate numerical simulation of superconducting circuits

Brittany Richman, Christopher J. Lobb, Jacob M. Taylor

Published Jan 8, 2026• 0 citations
arXivHTMLPDF

Abstract

Given the prevalence of superconducting platforms for uses in quantum computing and quantum sensing, the simulation of quantum superconducting circuits has become increasingly important for identifying system characteristics and modeling their relevant dynamics. Various numerical tools and software packages have been developed with this purpose in mind, typically utilizing the harmonic oscillator basis or the charge basis to represent a Hamiltonian. In this work, we instead consider the use of discrete variable representations (DVRs) to model superconducting circuits. In particular, we use `sinc DVRs' of both charge number and phase to approximate the eigenenergies of several prototypical examples, exploring their use and effectiveness in the numerical analysis of superconducting circuits. We find that not only are these DVRs capable of achieving decoherence-accurate simulation, i.e., accuracy at the resolution of experiments subject to decay, decoherence, and dephasing, they also demonstrate improvements in efficiency with smaller basis sizes and better convergence over standard approaches, showing that DVRs are an advantageous alternative for representing superconducting circuits.

DOI
10.1103/2zqn-6r1k

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Given the prevalence of superconducting platforms for uses in quantum computing and quantum sensing, the simulation of quantum superconducting circuits has become increasingly important for identifying system characteristics and modeling their relevant dynamics. Various numerical tools and software packages have been developed with this purpose in mind, typically utilizing the harmonic oscillator basis or the charge basis to represent a Hamiltonian. In this work, we instead consider the use of discrete variable representations (DVRs) to model superconducting circuits. In particular, we use `sinc DVRs' of both charge number and phase to approximate the eigenenergies of several prototypical examples, exploring their use and effectiveness in the numerical analysis of superconducting circuits. We find that not only are these DVRs capable of achieving decoherence-accurate simulation, i.e., accuracy at the resolution of experiments subject to decay, decoherence, and dephasing, they also demonstrate improvements in efficiency with smaller basis sizes and better convergence over standard approaches, showing that DVRs are an advantageous alternative for representing superconducting circuits.
Building on the established methods for superconducting circuit quantization, we present a new theoretical framework for approximate numerical simulation of Josephson quantum circuits. Simulations based on this framework provide access to a degree of complexity and circuit size heretofore inaccessible to quantitative analysis, including fundamentally new kinds of superconducting quantum devices. This capability is made possible by two improvements over previous methods: first, physically-motivated choices for the canonical circuit modes and physical basis states which allow a highly-efficient matrix representation; and second, an iterative method in which subsystems are diagonalized separately and then coupled together, at increasing size scales with each iteration, allowing diagonalization of Hamiltonians in extremely large Hilbert spaces to be approximated using a sequence of diagonalizations in much smaller spaces.
Abstract The development of new superconducting circuits and the improvement of existing ones rely on the accurate modeling of spectral properties which are key to achieving the needed advances in qubit performance. Systematic circuit analysis at the lumped-element level, starting from a circuit network and culminating in a Hamiltonian appropriately describing the quantum properties of the circuit, is a well-established procedure, yet cumbersome to carry out manually for larger circuits. We present work utilizing symbolic computer algebra and numerical diagonalization routines versatile enough to tackle a variety of circuits. Results from this work are accessible through a newly released module of the scqubits package.
Abstract We introduce CircuitQ, an open-source toolbox for the analysis of superconducting circuits implemented in Python. It features the automated construction of a symbolic Hamiltonian of the input circuit and a dynamic numerical representation of the Hamiltonian with a variable basis choice. The software implementation is capable of choosing the basis in a fully automated fashion based on the potential energy landscape. Additional features include the estimation of the T 1 lifetimes of the circuit states under various noise mechanisms. We review previously established circuit quantization methods and formulate them in a way that facilitates the software implementation. The toolbox is then showcased by applying it to practically relevant qubit circuits and comparing it to specialized circuit solvers. Our circuit quantization is applicable to circuit inputs from a large design space, and the software is open-sourced. We thereby add an important resource for the design of new quantum circuits for quantum information processing applications.
The theory of superconducting phase qubits---also known as current-biased Josephson junctions---is presented. In the first part of this thesis, I introduce quantum computation, quantum simulation, and their deep connection with symplectic integration. I then consider the fundamental many-body theory of superconductivity and Josephson junctions and show how the quantum dynamics of a single macroscopic degree of freedom, the gauge invariant phase difference, emerges. A complete study of the Hilbert space structure of such a variable is performed for the current-biased junction. The resulting resonance structure is studied in detail, using various formalisms including the WKB approximation, instanton methods, the complex scaling transformation, basis set stabilization, numerical integration, and dynamical simulation using Lie algebraic wave-packet propagation. The second part of this thesis explores how the current-biased junction can be used as an element of a quantum computer---a quantum bit (qubit). Single qubit operations are studied, followed by the presentation of the theory of coupled qubit devices. My key result is the design and optimization of quantum logic gates with high fidelity (F ~ 0.9999) for capacitively coupled phase qubits with short gate times (~ 10 ns). Finally, I examine an advanced qubit-coupling scheme, a resonant coupling method utilizing a harmonic oscillator as the auxiliary degree of freedom. The models and methods presented here have been developed in direct collaboration with an experimental program. These experiments are the first to show spectroscopic evidence for entanglement between two and three macroscopic degrees of freedom in a superconducting circuit.
As the number of qubits in quantum computing increases, the scalability of existing qubit circuit structures and control systems may become insufficient for large-scale expansion and high-fidelity control. To address this challenge, we propose a behavioral-level model of a superconducting qubit and its control electronics, followed by a co-simulation to evaluate their performance. In this paper, we present the modeling process, simulation procedure, and resulting design specifications for the qubit control system. Our co-simulation approach utilizes MATLAB and Simulink, enabling us to derive critical circuit design specifications, such as the required Digital-to-Analog Converter (DAC) resolution, which should be 8 bits or higher, to achieve high-fidelity control. By taking into account factors such as DAC sampling rates, integral and differential nonlinearities, and filter characteristics, we optimize the control system for efficient and accurate qubit manipulation. Our model and simulation approach offer a promising solution to the scalability challenges in quantum computing, providing valuable insights for the design of large-scale superconducting quantum computing systems.
Fluxonium qubits, designed to mitigate charge noise and enhance anharmonicity, are among the most promising superconducting platforms for quantum computing. To understand and exploit their quantum properties and design novel fluxonium-based architectures with improved functionalities, these systems require an accurate Hamiltonian formulation to capture their energy level structure and quantum dynamics. This work presents a systematic method for constructing the Hamiltonian for multi-loop circuits that partitions the system into a set of uncoupled harmonic oscillators and a coupled anharmonic part originating from the Josephson circuit elements, allowing clear identification of independent modes and isolating the nonlinearity in the Josephson terms. While demonstrated for fluxonium-type multi-loop circuits, this method can be generalized to other superconducting qubit architectures within the broader context of circuit QED, making it a versatile tool for exploring different circuit configurations. Our systematic and flexible modeling approach forms the theoretical basis for the qubit measurement and control experiments validating multi-loop fluxonium architectures.