Noise fingerprints in quantum computers: Machine learning software tools
University of Florence（佛罗伦萨大学）；European Laboratory for Non-Linear Spectroscopy (LENS)（欧洲非线性光谱实验室（LENS））；University of Lisbon（里斯本大学）；Instituto de Telecomunicações（电信研究所）；CNR-INO（意大利国家研究委员会-国家光学研究所）；Scuola Internazionale Superiore di Studi Avanzati (SISSA)（国际高等研究院（SISSA））
Stefano Martina, Stefano Gherardini, Lorenzo Buffoni, Filippo Caruso
In this paper we present the high-level functionalities of a quantum-classical machine learning software, whose purpose is to learn the main features (the fingerprint) of quantum noise sources affecting a quantum device, as a quantum computer. Specifically, the software architecture is designed to classify successfully (more than 99% of accuracy) the noise fingerprints in different quantum devices with similar technical specifications, or distinct time-dependences of a noise fingerprint in single quantum machines.
Cloud-based quantum computers have become a reality with a number of companies allowing for cloud-based access to their machines with tens to more than 100 qubits. With easy access to quantum computers, quantum information processing will potentially revolutionize computation, and superconducting transmon-based quantum computers are among some of the more promising devices available. Cloud service providers today host a variety of these and other prototype quantum computers with highly diverse device properties, sizes, and performances. The variation that exists in today's quantum computers, e…
Quantum computing has the potential to revolutionize computing for certain classes of problems with exponential scaling, and yet this potential is accompanied by significant sensitivity to noise, requiring sophisticated error correction and mitigation strategies. Here we simulate the relaxations of stationary states at different frequencies on several quantum computers to obtain unique spectroscopic fingerprints of their noise. Response functions generated from the data reveal a clear signature of non-Markovian dynamics, demonstrating that each of the quantum computers acts as a non-Markovian …
University of Florence（佛罗伦萨大学）；European Laboratory for Non-Linear Spectroscopy (LENS)（欧洲非线性光谱实验室（LENS））；University of Lisbon（里斯本大学）；Instituto de Telecomunicações（电信研究所）；Scuola Internazionale Superiore di Studi Avanzati (SISSA)（国际高等研究学院（SISSA））
Noise sources unavoidably affect any quantum technological device. Noise's main features are expected to strictly depend on the physical platform on which the quantum device is realized, in the form of a distinguishable fingerprint. Noise sources are also expected to evolve and change over time. Here, we first identify and then characterize experimentally the noise fingerprint of IBM cloud-available quantum computers, by resorting to machine learning techniques designed to classify noise distributions using time-ordered sequences of measured outcome probabilities.
Spectral Fingerprints of Gauge Theories on a Quantum Computer
School of Physics and Astronomy, University of Southampton（南安普顿大学物理与天文学院）；Infleqtion UK（英飞克特英国公司）；Department of Physics and Center for Functional Materials, Wake Forest University（维克森林大学物理系和功能材料中心）
Noise affects the coherence of qubits and thereby places a bound on the performance of quantum computers. We theoretically study a generic two-level system with fluctuating control parameters in a photonic cavity and find that basic features of the noise spectral density are imprinted in the transient transmission through the cavity. We obtain analytical expressions for generic noise and proceed to study the cases of quasistatic, white and $1/f^α$ noise in more detail. Additionally, we propose a way of extracting the spectral density for arbitrary noise in a frequency band only bounded by the …
ArQTiC is an open-source, full-stack software package built for the simulations of materials on quantum computers. It currently can simulate materials that can be modeled by any Hamiltonian derived from a generic, one-dimensional, time-dependent Heisenberg Hamiltonain. ArQTiC includes modules for generating quantum programs for real- and imaginary-time evolution, quantum circuit optimization, connection to various quantum backends via the cloud, and post-processing of quantum results. By enabling users to seamlessly perform and analyze materials simulations on quantum computers by simply provi…
We present MISTIQS, a Multiplatform Software for Time-dependent Quantum Simulations. MISTIQS delivers end-to-end functionality for simulating the quantum many-body dynamics of systems governed by time-dependent Heisenberg Hamiltonians across multiple quantum computing platforms. It provides high-level programming functionality for generating intermediate representations of quantum circuits which can be translated into a variety of industry-standard representations. Furthermore, it offers a selection of circuit compilation and optimization methods and facilitates execution of the quantum circui…
Manipulating quantum computing hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers. Susceptibility to noise limits the performance and capabilities of noisy intermediate-scale quantum (NISQ) devices, as well as any future quantum computing technologies. Fortunately quantum control enables efficient execution of quantum logic operations and algorithms with built-in robustness to errors, without the need for complex logical encoding. In this manuscript we introduce software tools for the application and integration of qua…
RotorMap and Quantum Fingerprints of DNA Sequences via Rotary Position Embeddings
Institute of Mathematics of NAS of Ukraine（乌克兰国家科学院数学研究所）；Kyiv Academic University（基辅学术大学）；Institute of Physics of NAS of Ukraine（乌克兰国家科学院物理研究所）；Department of Computer Science, University of Oxford（牛津大学计算机科学系）
We introduce Mitiq, a Python package for error mitigation on noisy quantum computers. Error mitigation techniques can reduce the impact of noise on near-term quantum computers with minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Mitiq is an extensible toolkit of different error mitigation methods, including zero-noise extrapolation, probabilistic error cancellation, and Clifford data regression. The library is designed to be compatible with generic backends and interfaces with different quantum software frameworks. We …
Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based problems, point processes, and molecular vibronic spectra in chemistry. The development of dedicated quantum software is a key enabler in permitting users to program devices and implement algorithms. In this work, we introduce a new applications layer for the Strawberry Fields photonic quantum computing library. The applications layer provides users with the necessary tools to design and implement algorithms using GBS …
Quantum computers are becoming more mainstream. As more programmers are starting to look at writing quantum programs, they need to test and debug their code. In this paper, we discuss various use-cases for quantum computers, either standalone or as part of a System of Systems. Based on these use-cases, we discuss some testing and debugging tactics that one can leverage to ensure the quality of the quantum software. We also highlight quantum-computer-specific issues and list novel techniques that are needed to address these issues. The practitioners can readily apply some of these tactics to th…
