In preparation for the era of large-scale commercial quantum computers in the future, quantum computers for simulation that provide customized development environments for developers are appearing, and the provision of developer kits tailored to these environments is also expanding.

Intel announced on the 28th that it has released version 1.0 of its quantum software development kit (SDK), following the beta version released in September last year.

The SDK is a quantum computer for simulation that can also interface with Intel's quantum hardware, including Intel's quantum control chip, Horse Ridge II, which will be released this year, and Intel's quantum spin qubit chips.
The kit allows developers to program quantum algorithms in simulation, and features an intuitive programming interface written in C++ using the industry-standard LLVM (low-level virtual machine) compiler toolchain. As a result, Intel's SDK is more diverse and customizable, providing a seamless interface with C/C++ and Python applications.

“The Intel Quantum SDK helps programmers prepare for the future of large-scale commercial quantum computers,” said Anne Matsuura, director of quantum applications and architectures at Intel Labs. “Not only will it help developers learn how to create quantum algorithms and applications in simulations, it will also advance the industry by building a developer ecosystem that will accelerate application development so developers are ready when Intel’s quantum hardware arrives.”

The Intel Quantum SDK 1.0 includes an intuitive programming interface based on C++, a programming language familiar to classical computing developers, enabling collaboration between classical computing developers and quantum developers. The kit also provides a quantum runtime environment optimized for running quantum-classical hybrid algorithms, Intel explained.

Developers can choose between two target backends for simulating qubits representing larger numbers of generic qubits or Intel hardware.

The first backend is the Intel Quantum Simulator (IQS), a high-performance open-source general-purpose qubit simulator. IQS has a backend that can handle 32 qubits on a single node and more than 40 qubits on multiple nodes. The second is a target backend that simulates hardware with Intel quantum dot qubits and enables compact model simulation of Intel silicon spin qubits. Intel's qubits leverage Intel's expertise in manufacturing silicon transistors to build large-scale quantum computers.

The SDK allows users to develop small workloads to determine what features are required in the system architecture of a quantum computer to efficiently and accurately run algorithms on qubits. Intel uses the SDK internally to accelerate system development by co-designing quantum hardware and software.

The SDK is a customizable and extensible platform that provides greater flexibility in developing quantum applications. It supports comparing compiler files, a standard feature of traditional computing development, to determine how well the algorithm was optimized by the compiler. This allows users to view source code and abstract data at a lower level to gain insight into how the system stores data.

Additionally, Intel has developed a quantum runtime environment that extends the industry-standard LLVM with quantum extensions and is tailored for quantum computing, and IQS provides state-vector simulation of a universal quantum computer.

To enable efficient execution of quantum workflows, compiler extensions allow developers to integrate the results of quantum algorithms into C++ projects, starting the feedback loops required for hybrid quantum-classical algorithms such as quantum approximate optimization algorithms (QAOA) and variational quantum eigeninterpreters (VQE).

For high-performance simulations, Intel DevCloud users can build executables that can simulate applications and algorithms with up to 32 qubits on a single compute node, or 40 or more qubits on multiple nodes.

Intel is building a developer community to build a quantum ecosystem and advance the field of quantum computing. First, Intel provided grants to five universities, including the University of Pennsylvania, Technische Hochschule Deggendorf, Keio University, The Ohio State University, and Pennsylvania State University, to open quantum courses and share them with other universities and to spread the use of quantum computing across academia.

Deggendorf University of Technology in Munich, Germany, is using the SDK to explore fluid dynamics problems important for gas and liquid dynamics. In January 2023, Intel hosted the Intel Quantum Computing Challenge at Deggendorf University of Technology. Participants used the beta version of the Intel Quantum SDK to explore quantum use cases, including image denoising, generating realistic images, and solving unstructured search problems. Another beta user, Leidos, is working on applications such as quantum machine learning, materials simulation and teleportation, and astrophysics problems such as black holes and wormholes.

A number of testers have commented on the quantum SDK, including Gushu Li, an assistant professor in the Department of Computer and Information Sciences at the University of Pennsylvania. “The Intel Quantum SDK is easy to get started with. Everything is in the cloud, so all you need is a Secure Shell client, and the simulator generates a very detailed report that allows you to analyze and debug your kernels,” he said.

“The Intel Quantum SDK is a game-changer for quantum development because it allows developers to operate closer to the hardware for better resource utilization,” said Yaknan John Gambo, a student at Deggendorf School of Engineering.

“The Intel Quantum SDK provided a unique way to apply my knowledge of the C language to the quantum domain,” said Jeremy Pope, a computer science student at Penn State. “I was able to learn quantum programming almost like I was learning a classical language.”

“Leidos has enjoyed running a variety of hardware-free simulations for software development and comparative analysis,” said Elizabeth Iwasawa, research scientist and director of quantum technologies at Leidos Innovation Center. “Even in the beta version, we have explored a wide range of research topics, from materials modeling and quantum machine learning to thermofield dual-states.”