Abstract We present an open-source software package called “Hamiltonian Open Quantum System Toolkit" (HOQST), a collection of tools for the investigation of open quantum system dynamics in Hamiltonian quantum computing, including both quantum annealing and the gate-model of quantum computing. It features the key master equations (MEs) used in the field, suitable for describing the reduced system dynamics of an arbitrary time-dependent Hamiltonian with either weak or strong coupling to infinite-dimensional quantum baths. We present an overview of the theories behind the various MEs and provide examples to illustrate typical workflows in HOQST. We present an example that shows that HOQST can provide order of magnitude speedups compared to “Quantum Toolbox in Python" (QuTiP), for problems with time-dependent Hamiltonians. The package is ready to be deployed on high performance computing (HPC) clusters and is aimed at providing reliable open-system analysis tools for noisy intermediate-scale quantum (NISQ) devices.
Abstract We present an open-source software package called “Hamiltonian Open Quantum System Toolkit" (HOQST), a collection of tools for the investigation of open quantum system dynamics in Hamiltonian quantum computing, including both quantum annealing and the gate-model of quantum computing. It features the key master equations (MEs) used in the field, suitable for describing the reduced system dynamics of an arbitrary time-dependent Hamiltonian with either weak or strong coupling to infinite-dimensional quantum baths. We present an overview of the theories behind the various MEs and provide examples to illustrate typical workflows in HOQST. We present an example that shows that HOQST can provide order of magnitude speedups compared to “Quantum Toolbox in Python" (QuTiP), for problems with time-dependent Hamiltonians. The package is ready to be deployed on high performance computing (HPC) clusters and is aimed at providing reliable open-system analysis tools for noisy intermediate-scale quantum (NISQ) devices.
We present a quantum algorithm based on the generalized quantum master equation (GQME) approach to simulate open quantum system dynamics on noisy intermediate-scale quantum (NISQ) computers. This approach overcomes the limitations of the Lindblad equation, which assumes weak system-bath coupling and Markovity, by providing a rigorous derivation of the equations of motion for any subset of elements of the reduced density matrix. The memory kernel resulting from the effect of the remaining degrees of freedom is used as input to calculate the corresponding non-unitary propagator. We demonstrate how the Sz.-Nagy dilation theorem can be employed to transform the non-unitary propagator into a unitary one in a higher-dimensional Hilbert space, which can then be implemented on quantum circuits of NISQ computers. We validate our quantum algorithm as applied to the spin-boson benchmark model by analyzing the impact of the quantum circuit depth on the accuracy of the results when the subset is limited to the diagonal elements of the reduced density matrix. Our findings demonstrate that our approach yields reliable results on NISQ IBM computers.
Quantum optimal control can be used to shape the control pulses for realizing unitary and non-unitary transformations of quantum states. These control pulses provide the fundamental interface between the quantum compiler and the quantum hardware. Most current software for quantum optimal control (e.g. Qutip [1] or Krotov [2]) is restricted to run on shared memory platforms, limiting their applicability to smaller quantum systems, in particular if interactions with the environment are taken into account. This paper gives an overview of the open-source code Quandary, which is designed to solve quantum control problems in larger open quantum systems modelled by Lindblad’s master equation. Implemented in C++, Quandary uses the message passing paradigm for distributed memory computers that enables scalability to large numbers of compute cores. Accompanied by numerical examples, this paper presents an overview on existing theoretical developments for open optimal quantum control realizing state-to-state transfer, unitary gate optimization as well as state-preparation, and presents the numerical tools and implementation aspect as realized in Quandary, for deployment on modern high-performance computing platforms.
Simulating quantum dynamics at finite temperature in complex chemical systems remains a central challenge in quantum chemistry and materials science. In many cases, it is advantageous to focus on the dynamics of a subsystem of interest, represented by its reduced density matrix, whose interaction with the surrounding environment gives rise to open-system behavior. The Nakajima-Zwanzig generalized quantum master equation (GQME) provides a formally exact framework for capturing such non-Markovian dynamics, where memory effects play a defining role. Here, in Part VI of the QFlux tutorial series, we explore methods for simulating non-Markovian open quantum systems described by the GQME on quantum computers. The approach leverages the Sz.-Nagy dilation theorem to embed memory-dependent, non-unitary evolution into an enlarged unitary space suitable for quantum simulation. Using the spin-boson model as a prototypical example, we demonstrate how to formulate, implement, and analyze GQME dynamics within the QFlux open-source platform. This tutorial provides readers with both the theoretical foundation and practical tools required to study non-Markovian quantum dynamics, bridging fundamental concepts with executable workflows for quantum simulation.
Quantum optimal control can be used to shape the control pulses for realizing unitary and non-unitary transformations of quantum states.These control pulses provide the fundamental interface between the quantum compiler and the quantum hardware.Most current software for quantum optimal control (e.g.Qutip [1] or Krotov [2]) is restricted to run on shared memory platforms, limiting their applicability to smaller quantum systems, in particular if interactions with the environment are taken into account.This paper gives an overview of the open source code Quandary, which models open quantum systems using Lindblad's master equation.Quandary is designed to solve optimal control problems in larger open quantum systems using a message passing paradigm, implemented in C++ for distributed memory computers that enables scalability to large numbers of compute cores.
Abstract Effectively manipulating quantum computing (QC) hardware in the presence of imperfect devices and control systems is a central challenge in realizing useful quantum computers. Susceptibility to noise critically limits the performance and capabilities of today’s so-called noisy intermediate-scale quantum devices, as well as any future QC technologies. Fortunately, quantum control enables efficient execution of quantum logic operations and quantum algorithms with built-in robustness to errors, and without the need for complex logical encoding. In this manuscript we introduce software tools for the application and integration of quantum control in QC research, serving the needs of hardware R&D teams, algorithm developers, and end users. We provide an overview of a set of Python-based classical software tools for creating and deploying optimized quantum control solutions at various layers of the QC software stack. We describe a software architecture leveraging both high-performance distributed cloud computation and local custom integration into hardware systems, and explain how key functionality is integrable with other software packages and quantum programming languages. Our presentation includes a detailed mathematical overview of key features including a flexible optimization toolkit, engineering-inspired filter functions for analyzing noise susceptibility in high-dimensional Hilbert spaces, and new approaches to noise and hardware characterization. Pseudocode is presented in order to elucidate common programming workflows for these tasks, and performance benchmarking is reported for numerically intensive tasks, highlighting the benefits of the selected cloud-compute architecture. Finally, we present a series of case studies demonstrating the application of quantum control solutions derived from these tools in real experimental settings using both trapped-ion and superconducting quantum computer hardware.
We present QuTiP (http://www.qutip.org),an object-oriented, opensource framework for solving the dynamics of open quantum systems.Written in Python, and using a combination of Cython, NumPy, SciPy, and matplotlib, QuTiP provides an environment for computational quantum mechanics that is both easy and efficient to use.Arbitrary quantum systems, including timedependent systems, may be built up from operators and states defined by a quantum object class, and then passed on to a choice of unitary or dissipative evolution solvers.Here we give an overview of the basic structure for the framework, and the techniques used in its implementation.We also present a few selected examples from current research on quantum mechanics that illustrate the strengths of the framework, as well as the types of calculations that can be performed.This framework is particularly well suited to the fields of quantum optics, superconducting circuit devices, nanomechanics, and trapped ions, while also being ideal as an educational tool.