Reinventing Data Processing with Quantum Computing

Quantum computing is emerging from the theoretical realm towards real-world systems.

Intel Labs is producing quantum processors in Oregon and doing system-level engineering that targets production-level quantum computing within ten years.

What is Quantum Computing

Binary encoding of data is fundamental to computing, with bits comprising zeroes or ones represented electrically as “on” or “off” states. Quantum computing reimagines that approach, replacing bits with qubits that can simultaneously manifest multiple states as they are generally defined in classical physics. Quantum systems that represent data using qubits and quantum phenomena such as superposition and entanglement potentially enable computing at unprecedented levels of massive parallelism.

Work by Intel Labs on quantum computing draws on ongoing internal research, paired with collaborative relationships and investment across global academia and industry, as well as Intel’s leadership in silicon fabrication techniques. Research has been ongoing for decades, growing from a theoretical level with thought experiments throughout much of the 20th century, with the first functional hardware components for quantum computing developed only in the past several years.

A timeline of quantum computing.

Research at Intel Labs has led directly to the development of Tangle Lake, a superconducting quantum processor that incorporates 49 qubits in a package that is manufactured at Intel’s 300-millimeter fabrication facility in Hillsboro, Oregon. This device represents the third-generation of quantum processors produced by Intel, scaling upward from 17 qubits in its predecessor.

Tangle Lake is a step forward in the ongoing development of full quantum computing systems, which is still perhaps ten years in the future. Such systems promise unprecedented ability to simulate and analyze natural phenomena, leading to rapid answers to phenomenological questions that would require prohibitive amounts of time on today’s supercomputers. That capability is expected to power breakthroughs in areas as diverse as individualized genetic medicine, astrophysics, and solving environmental challenges.

The Tangle Lake 49-qubit quantum processor.

Ongoing Development in Partnership with Industry and Academia
The challenges in developing functioning quantum computing systems are manifold and daunting. For example, qubits themselves are extremely fragile, with any disturbance including measurement causing them to revert from their quantum state to a classical (binary) one, resulting in data loss. Tangle Lake also must operate at profoundly cold temperatures, within a small fraction of one kelvin from absolute zero. 

Moreover, there are significant issues of scale, with real-world implementations at commercial scale likely requiring at least one million qubits. Given that reality, the relatively large size of quantum processors is a significant limitation in its own right; for example, Tangle Lake is about three inches square. To address these challenges, Intel is actively developing design, modeling, packaging, and fabrication techniques to enable the creation of more complex quantum processors.

Intel began collaborating with QuTech, a quantum computing organization in the Netherlands, in 2015; that involvement includes a US$50M investment by Intel in QuTech to provide ongoing engineering resources that will help accelerate developments in the field. QuTech was created as an advanced research and education center for quantum computing by the Netherlands Organisation for Applied Research and the Delft University of Technology. Combined with Intel’s expertise in fabrication, control electronics, and architecture, this partnership is uniquely suited to the challenges of developing the first viable quantum computing systems.

Currently, Tangle Lake chips produced in Oregon are being shipped to QuTech in the Netherlands for analysis. QuTech has developed robust techniques for simulating quantum workloads as a means to address issues such as connecting, controlling, and measuring multiple, entangled qubits. In addition to helping drive system-level design of quantum computers, the insights uncovered through this work contribute to faster transition from design and fabrication to testing of future generations of the technology.

In addition to its collaboration with QuTech, Intel Labs is also working with other ecosystem members both on fundamental and system-level challenges on the entire quantum computing stack. Joint research being conducted with QuTech, the University of Toronto, the University of Chicago, and others builds upward from quantum devices to include mechanisms such as error correction, hardware- and software-based control mechanisms, and approaches and tools for developing quantum applications.

Beyond Superconduction: The Promise of Spin Qubits
One approach to addressing some of the challenges that are inherent to quantum processors such as Tangle Lake that are based on superconducting qubits is the investigation of spin qubits by Intel Labs and QuTech. Spin qubits function on the basis of the spin of a single electron in silicon, controlled by microwave pulses. Compared to superconducting qubits, spin qubits far more closely resemble existing semiconductor components operating in silicon, potentially taking advantage of existing fabrication techniques. In addition, this promising area of research holds the potential for advantages in the following areas:

• Operating temperature: Spin qubits require extremely cold operating conditions, but to a lesser degree than superconducting qubits (approximately one degree kelvin compared to 20 millikelvins); because the difficulty of achieving lower temperatures increases exponentially as one gets closer to absolute zero, this difference potentially offers significant reductions in system complexity.

• Stability and duration: Spin qubits are expected to remain coherent for far longer than superconducting qubits, making it far simpler at the processor level to implement them for algorithms.

• Physical size: Far smaller than superconducting qubits, a billion spin qubits could theoretically fit in one square millimeter of space. In combination with their structural similarity to conventional transistors, this property of spin qubits could be instrumental in scaling quantum computing systems upward to the estimated millions of qubits that will eventually be needed in production systems.

To date, researchers have developed a spin qubit fabrication flow using Intel’s 300-millimeter process technology that is enabling the production of small spin-qubit arrays in silicon. In fact, QuTech has already begun testing small-scale spin-qubit-based quantum computer systems. As a publicly shared software foundation, QuTech has also developed the Quantum Technology Toolbox, a Python package for performing measurements and calibration of spin-qubits.

Two-Step Approach to Scheduling Quantum Circuits

As the effort to scale up existing quantum hardware proceeds, it becomes necessary to schedule quantum gates in a way that minimizes the number of operations. This research presented an effective two-step approach to gate schedule for quantum circuits.

Read the paper

Partnerships

QuTech

QuTech is an advanced research center for quantum computing and quantum internet, a collaboration founded by TU Delft and TNO.

CQIQC

The Centre for Quantum Information and Quantum Counting promotes research collaboration within this rapidly evolving interdisciplinary field.

University of Chicago

The Institute for Molecular Engineering leads engineering research and education in new directions, promoting creative applications of molecular-level science.

In the News


Explore the latest news around Intel and Quantum Computing.

Join Intel Labs

Bring you passion for technology and problem solving to Intel Labs and help create something that’s never existed.

Explore opportunities

More from Intel Labs

About Intel Labs

Working with and sponsoring leading researchers around the world to develop the next breakthrough that transforms how machines think, learn, and adapt.

Learn more

Neuromorphic and Probabilistic Computing

The next revolution in AI is driving research that will make computing more closely emulate the biological brain.

Learn more

Emerging Innovations

Nascent technologies are driving and shaping the future of computing. Explore key areas of innovation that are at the forefront of the next technical revolution.

Learn more