Scott Bair is a key voice at Intel Labs, sharing insights into innovative research for inventing tomorrow’s technology.
Highlights:
- The 2023 APS March Meeting will include an in-person conference held March 5-10 in Las Vegas, Nevada, as well as virtual meetings held on March 20-22.
- Intel Labs is excited to present seven papers on quantum computing, including one invited talk on Intel’s quantum computing system, with an emphasis on high-level qubit control.
- Intel’s Components Research and Intel Labs organizations have recently demonstrated the industry’s highest reported yield (95%) and uniformity to date of silicon spin qubit devices.
The 2023 APS March Meeting will have options for in-person attendance or virtual meetings. The in-person conference will be held March 5-10 in Las Vegas, Nevada. The virtual meetings will be held later on March 20-22. The APS March Meeting brings together professionals and students from the global physics community to connect and share groundbreaking physics research. Intel Labs is excited to present seven papers on quantum computing, including one invited talk on Intel’s quantum computing system, with an emphasis on high-level qubit control.
Quantum computing employs the properties of quantum physics, like superposition and entanglement, to perform computation. Traditional transistors use binary encoding of data represented electrically as “on” or “off” states. Quantum bits or “qubits” can simultaneously operate in multiple states enabling unprecedented levels of parallelism and computing efficiency. Today’s quantum systems only include tens or hundreds of entangled qubits, limiting them from solving real-world problems. However, Intel Labs is invested in achieving quantum practicality, and is actively working to overcome challenges with the help of industry and academic partners.
Intel Labs’ quantum research spans many areas. The works presented at this year’s APS March Meeting include information on the capabilities of the Intel Quantum Software Development Kit (SDK), as well as an overview of the Intel quantum computing system, with a focus on high-level qubit control. Another presentation will describe low-power, programmable, discrete-time pulse filtering techniques that eliminate leakage and thereby cross-talk at a victim qubit's Larmor Frequency.
Additionally, Intel’s Components Research and Intel Labs organizations have recently demonstrated the industry’s highest reported yield (95%) and uniformity to-date of silicon spin qubit devices. This achievement represents a major milestone for quantum chip fabrication and scaling on Intel’s transistor manufacturing processes line. Continue reading to learn more about all of Intel Labs’ efforts.
Intel Labs’ Contributions:
A Functional Approach to the Modular Construction of Quantum Logic: Part I
Many quantum languages use an object-oriented approach for the construction and manipulation of quantum circuits and logic. However, this approach is challenging for a compiled quantum binary in a NISQ accelerator model, as hardware-native instruction blocks must be determined and built at compile time. Thus, the compiler must reason about the structure of the quantum logic without runtime memory access, i.e., it must avoid side effects. Intel Labs’ solution is to introduce a quantum functional language extension to the C++-derived language of the Intel Quantum SDK. This work introduces a new built-in type that abstracts a quantum accelerator call, allowing it to be passed into and out of C++ functions before being passed to the quantum accelerator. It also includes several core built-in functions that users and libraries can use to build more elaborate transformations.
This talk introduces the basic concepts of this functional extension, different parts of its syntax and how it can be used alongside other C++ constructs to build modular quantum algorithms with the Intel Quantum SDK.
A Functional Approach to the Modular Construction of Quantum Logic: Part II
Many quantum languages use an object-oriented approach for the construction and manipulation of quantum circuits and logic. However, this approach is challenging for a compiled quantum binary in a NISQ accelerator model, as hardware-native instruction blocks must be determined and built at compile time. Thus, the compiler must reason about the structure of the quantum logic without runtime memory access, i.e., it must avoid side effects. Intel Labs’ solution is to introduce a quantum functional language extension to the C++-derived language of the Intel Quantum SDK. This work introduces a new built-in type that abstracts a quantum accelerator call, allowing it to be passed into and out of C++ functions before being passed to the quantum accelerator. It also includes several core built-in functions that users and libraries can use to build more elaborate transformations.
This talk will cover the basic methods used in the compilation of this functional language extension, including the use of the LLVM toolchain for parsing and generating an intermediate representation (IR) and the use of a Pauli-based representation to uniformly build the quantum logic from the call structure of the IR.
Efficient execution of quantum algorithms using the Intel Quantum SDK
Quantum computers are expected to be capable of solving certain classically intractable problems efficiently. A practical quantum computer will require high-quality physical qubits, dedicated control electronics, and a software stack capable of generating hardware-targeted quantum circuits as well as processing results from quantum circuit execution. The efficient transformation of quantum algorithms into practical quantum circuits is imperative in extracting the best performance from available quantum hardware.
This talk will describe the capabilities of the Intel Quantum SDK, which utilizes many optimizations within the quantum compiler as well as generates binary executables to enable tight integration during the execution of workloads -- especially for variational algorithms. Examples will be provided to demonstrate the benefits of a holistic optimization approach in contrast to a collection of discrete local optimizations. The tools available to examine the flow through the software toolchain will also be surveyed.
High-level control of spin qubits on an array with 12 quantum dots
Quantum computing promises to tackle exciting and computationally challenging problems. Intel is leveraging 50 years of semiconductor manufacturing experience to develop silicon-based spin qubit devices. Quantum chips are produced on the same advanced 300 mm semiconductor processing line as Intel’s next generation of computing technology. Owing to great process control and reliability, thousands of quantum devices are produced every week. With newly developed low-temperature wafer-scale characterization and measurement tools, statistically significant fabrication feedback is generated. This feedback enabled the development of high-quality 12-quantum dot samples that can be brought into the 1/1/…./1 electron occupation. After subjecting these electrons to a magnetic field, their degeneracy-lifted spin states are used as the qubit states. Single- and two-qubit gates are performed by electrically driving the spin resonance and voltage-pulsing the electrostatic barrier between qubits, respectively. Pauli spin blockade facilitates fast and high-fidelity readout of qubits. Control of the quantum chip is orchestrated with in-house built software and control electronics and is set up in a way that allows incorporation with the full algorithmic stack. This invited talk will include an overview of the above-mentioned aspects of the Intel quantum computing system, with a focus on high-level qubit control.
The Intel Quantum Software Development Kit (SDK) is a full-stack platform allowing programmers to design their applications on a system consisting of an LLVM-based compiler providing intuitive C++ language extensions to support the expression and optimizations of quantum circuits. The SDK provides a quantum runtime library to control the context switch between classical and quantum kernels to perform hybrid execution. The quantum runtime allows a set of quantum circuit parameters to be determined at runtime. With these capabilities, both quantum and classical procedures of a variational algorithm can be specified in the same program and only need to be compiled once for all iterations. This design reduces the execution latency of a variational algorithm significantly. A set of quantum simulators are integrated in the SDK, including a simulation of Intel quantum hardware (qubit control processor, control electronics, and quantum dot qubits). The Intel Quantum SDK is designed to provide a uniform interface to users to target ideal qubit simulators, realistic Intel quantum hardware simulators, as well as future Intel quantum hardware. The Intel Quantum SDK can efficiently perform optimization, compilation, and execution of scalable hybrid quantum-classical variational algorithms.
Linear Filtering of Pulses for Cross-Talk Elimination in Frequency-Multiplexed Qubit Control
Frequency multiplexed microwave driving of a large array of spin qubits is a potential solution to scalable control of a fault-tolerant quantum computer. The control of spin qubits closely spaced in frequency using a common interconnect is susceptible to cross-talk due to the leakage of energy outside the bandwidth of the driven qubit. While pulse shaping can reduce leakage to adjacent victim qubits, general pulse shapes are typically not easily programmable to accommodate varying qubit frequencies, particularly when implemented within low-power, mostly-digital integrated cryogenic controllers. This work shows that the loss of fidelity due to X and Y rotations of a victim qubit is approximately proportional to the spectral density of the pulse shape, thereby motivating the use of frequency domain linear filtering to eliminate cross-talk. It also describes low-power, programmable, discrete-time pulse filtering techniques that eliminate leakage and thereby cross-talk at a victim qubit's Larmor Frequency. A digital implementation of the filter is described that is easily scalable by cascading multiple programmable filters to eliminate cross-talk for several qubits. Finally, simulation results demonstrate that the cross-talk elimination technique restores fidelity to 99.9% for the victim qubit.
Si/SiGe Qubit Devices Enabled by Advanced Semiconductor Fabrication
Intel’s Components Research and Intel Labs organizations have recently demonstrated the industry’s highest reported yield (95%) and uniformity to date of silicon spin qubit devices. These devices are fabricated on a planar Si/SiGe heterostructure with extreme ultraviolet (EUV) lithography utilizing Intel’s advanced 300mm transistor research and development facility. This achievement represents a major milestone for quantum chip fabrication and scaling on Intel’s transistor manufacturing processes line. An overview of the process integration scheme, process parameters, and low temperature device characterization that led to these innovative advancements toward technology maturation and commercialization will be discussed.
Scott Bair is a Senior Technical Creative Director for Intel Labs, chartered with growing awareness for Intel’s leading-edge research activities, like AI, Neuromorphic Computing and Quantum Computing. Scott is responsible for driving marketing strategy, messaging, and asset creation for Intel Labs and its joint-research activities. In addition to his work at Intel, he has a passion for audio technology and is an active father of 5 children.
Scott has over 23 years of experience in the computing industry bringing new products and technology to market. During his 15 years at Intel, he has worked in a variety of roles from R&D, architecture, strategic planning, product marketing, and technology evangelism. Scott has an undergraduate degree in Electrical and Computer Engineering and a Masters of Business Administration from Brigham Young University.
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