Search Results for « Qiskit »

We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning. The API abstracts Qiskit's primitives to facilitate interactions with classical simulators and quantum hardware. Qiskit ML started as a proof-of-concept code in 2019 and has since been developed to be a modular, intuitive tool for non-specialist users while allowing extensibility and fine-tuning controls for quantum computational scientists and developers. The library is available as a public, open-source tool and is distributed under the Apache version 2.0 license.

We describe Qiskit, a software development kit for quantum information science. We discuss the key design decisions that have shaped its development, and examine the software architecture and its core components. We demonstrate an end-to-end workflow for solving a problem in condensed matter physics on a quantum computer that serves to highlight some of Qiskit's capabilities, for example the representation and optimization of circuits at various abstraction levels, its scalability and retargetability to new gates, and the use of quantum-classical computations via dynamic circuits. Lastly, we discuss some of the ecosystem of tools and plugins that extend Qiskit for various tasks, and the future ahead.

As interest in quantum computing grows, there is a pressing need for standardized API's so that algorithm designers, circuit designers, and physicists can be provided a common reference frame for designing, executing, and optimizing experiments. There is also a need for a language specification that goes beyond gates and allows users to specify the time dynamics of a quantum experiment and recover the time dynamics of the output. In this document we provide a specification for a common interface to backends (simulators and experiments) and a standarized data structure (Qobj --- quantum object) for sending experiments to those backends via Qiskit. We also introduce OpenPulse, a language for specifying pulse level control (i.e. control of the continuous time dynamics) of a general quantum device independent of the specific hardware implementation.

The practical benefits of hybrid quantum information processing hardware that contains continuous-variable objects (bosonic modes such as mechanical or electromagnetic oscillators) in addition to traditional (discrete-variable) qubits have recently been demonstrated by experiments with bosonic codes that reach the break-even point for quantum error correction and by efficient Gaussian boson sampling simulation of the Franck-Condon spectra of triatomic molecules that is well beyond the capabilities of current qubit-only hardware. The goal of this Co-design Center for Quantum Advantage (C2QA) project is to develop an instruction set architecture (ISA) for hybrid qubit/bosonic mode systems that contains an inventory of the fundamental operations and measurements that are possible in such hardware. The corresponding abstract machine model (AMM) would also contain a description of the appropriate error models associated with the gates, measurements and time evolution of the hardware. This information has been implemented as an extension of Qiskit. Qiskit is an opensource software development toolkit (SDK) for simulating the quantum state of a quantum circuit on a system with Python 3.7+ and for running the same circuits on prototype hardware within the IBM Quantum Lab. We introduce the Bosonic Qiskit software to enable the simulation of hybrid qubit/bosonic systems using the existing Qiskit software development kit. This implementation can be used for simulating new hybrid systems, verifying proposed physical systems, and modeling systems larger than can currently be constructed. We also cover tutorials and example use cases included within the software to study Jaynes- Cummings models, bosonic Hubbard models, plotting Wigner functions and animations, and calculating maximum likelihood estimations using Wigner functions.

We present QisMC, the first quantum model checker dedicated to debugging Qiskit programs. On the theoretical side, we introduce the notion of quantum-classical transition system and a quantum computation tree logic (qCTL) grounded in Birkhoff-von Neumann logic for modeling the behaviors and specifying the properties of Qiskit programs, respectively. On the implementation side, QisMC provides an end-to-end framework encompassing transition system generation, logical formula representation, and model checking algorithms, and it efficiently performs image computation based on decision diagrams. These methods and design principles give QisMC advantages over previous Qiskit program debuggers, including a unified property specification language, a fully automated and exhaustive verification process, and the ability to generate counterexamples. Extensive illustrative examples and benchmark evaluations demonstrate the practicality, efficiency, and scalability of QisMC in verifying realistic quantum programs.

qiskit-qudits is a Qiskit extension that simulates d-level qudits by encoding each one into m = ceil(log_2 d) qubits. Qudit gates are exposed as ordinary Qiskit Gate and ControlledGate subclasses, and operations that are not unitary gates (measurement, reset, barrier, state preparation) as dedicated Instruction subclasses dispatched through a dedicated apply() hook; every gate carries both a dense encoded unitary (via NumPy's array protocol) and a qubit-level definition. Because d need not be a power of two, the encoded Hilbert space is generally larger than the logical one; the library resolves this by the identity-padding convention, in which every gate acts as the identity on the unphysical part of the encoded space. When every operand dimension is a power of two, gates decompose into a fixed, transpiler-recognisable cascade of standard qubit gates; otherwise the library falls back to exact dense unitary synthesis, so that dimensions 2 <= d <= 16 are supported exactly, not only powers of two. This paper describes the software's circuit model, gate hierarchy, decomposition strategy, and measurement/decoding machinery, states its limitations, and verifies the implementation numerically: the qudit QFT against the discrete Fourier transform for both power-of-two and non-power-of-two d, extending the check of the underlying theory paper, which could only be run for d = 2^m, and every gate's emitted decomposition against its dense unitary across the whole gate set.

Qiskit is one of the common quantum computing frameworks and and the qiskit-aer package can accelerating quantum circuit simulation using NVIDIA GPU with the help of THRUST. AMD ROCm framework similar to CUDA, a heterogeneous computing framework supporting both the NVIDIA and AMD GPUs provides the possibility to porting Qiskit/Qiskit-Aer from CUDA platform to its own. We present the porting progress of Qiskit/QiskitAer and preliminary performance test on both NVIDA and AMD GPUs. Our results show that Qiskit/Qiskit-Aer cand work well on AMD GPUs with the help of ROCm/HIP, and has comparable performance on AMD platform.