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A Quantum Instruction Set Implemented on a Superconducting Quantum Processor

Morten Kjærgaard, Mollie E. Schwartz, Alex Greene, Gabriel Samach, Anders Bengtsson, Michael F. O’Keeffe, Christopher M. McNally, Jochen Braumüller, David K. Kim, Philip Krantz, Milad Marvian, Alexander J. Melville, Bethany M. Niedzielski, Yun‐Mo Sung, Roni Winik, Jonilyn Yoder, Danna Rosenberg, Kevin Obenland, Seth Lloyd, Terry P. Orlando, Iman Marvian, Simon Gustavsson, William D. Oliver

Published Jan 23, 2020• 10 citations
OpenAlex

Abstract

A quantum algorithm consists of a sequence of operations and measurements applied to a quantum processor. To date, the instruction set which defines this sequence has been provided by a classical computer and passed via control hardware to the quantum processor. Here, we demonstrate the first experimental realization of a quantum instruction set, in which a fixed sequence of classically-defined gates perform an operation that is fully determined only by a quantum input to the fixed sequence. Specifically, we implement the density matrix exponentiation algorithm, which consumes $N$ copies of the instruction state $\rho$ to approximate the operation $e^{-i \rho \theta}$ ($\theta$ an arbitrary angle). Our implementation relies on a 99.7% fidelity controlled-phase gate between two superconducting transmon qubits. We achieve an average algorithmic fidelity $\approx 0.9$, independent of the setting of $\rho$, to circuit depth nearly 90. This new paradigm for quantum instructions has applications to resource-efficient protocols for validating entanglement spectra, principal component analysis of large quantum states, and universal quantum emulation.

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Quantum computing utilizes quantum mechanics to perform computations with superconducting qubits being the more mature technology as of writing in realizing a quantum computer. In this thesis, we describe an implementation of a Quantum Processor Unit (QPU), which is used to execute instructions in the form of microwave pulses on a superconducting qubit device through the use of signal generators and to perform qubit readout. We further extend the QPU as a platform to perform qubit characterization tasks such as spectroscopy and decoherence measurements in order to determine and optimize the working parameters to perform quantum gate operations. We also demonstrate the use of the QPU in performing qubit experiments such as Gauss Sum Factorization in determining the factors of an integer and the Bell Inequality test in examining the entanglement strength between a pair of qubits. We bridge the divide of quantum computation and qubit hardware in the compilation of quantum circuits into microwave pulse sequences for the QPU to execute. The process of compilation, as well as hardware limitations and pre-compilation optimization procedures are discussed. Finally, we show an example of executing a variational quantum algorithm and break down this example in all layers from the quantum circuit provided by the user to the pulse sequence that will be executed on the QPU.

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A Programmable Five Qubit Quantum Computer Using Trapped Atomic Ions

Shantanu Debnath

Quantum computers can solve certain problems more efficiently compared to conventional classical methods. In the endeavor to build a quantum computer, several competing platforms have emerged that can implement certain quantum algorithms using a few qubits. However, the demonstrations so far have been done usually by tailoring the hardware to meet the requirements of a particular algorithm implemented for a limited number of instances. Although such proof of principal implementations are important to verify the working of algorithms on a physical system, they further need to have the potential to serve as a general purpose quantum computer allowing the flexibility required for running multiple algorithms and be scaled up to host more qubits. Here we demonstrate a small programmable quantum computer based on five trapped atomic ions each of which serves as a qubit. By optically resolving each ion we can individually address them in order to perform a complete set of single-qubit and fully connected two-qubit quantum gates and alsoperform efficient individual qubit measurements. We implement a computation architecture that accepts an algorithm from a user interface in the form of a standard logic gate sequence and decomposes it into fundamental quantum operations that are native to the hardware using a set of compilation instructions that are defined within the software. These operations are then effected through a pattern of laser pulses that perform coherent rotations on targeted qubits in the chain. The architecture implemented in the experiment therefore gives us unprecedented flexibility in the programming of any quantum algorithm while staying blind to the underlying hardware. As a demonstration we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms on the five-qubit processor and achieve average success rates of 95 and 90 percent, respectively. We also implement a five-qubit coherent quantum Fourier transform and examine its performance in the period finding and phase estimation protocol. We find fidelities of 84 and 62 percent, respectively. While maintaining the same computation architecture the system can be scaled to more ions using resources that scale favorably (O(N^2)) with the number of qubits N.

Bulletin of the American Physical Society•Jan 1, 2016•13 citations
A quantum algorithm consists of a sequence of operations and measurements applied to a quantum processor. To date, the instruction set which defines this sequence has been provided by a classical computer and passed via control hardware to the quantum processor. Here, we demonstrate the first experimental realization of a quantum instruction set, in which a fixed sequence of classically-defined gates perform an operation that is fully determined only by a quantum input to the fixed sequence. Specifically, we implement the density matrix exponentiation algorithm, which consumes NNN copies of the instruction state ρ\rhoρ to approximate the operation e−iρθe^{-i \rho \theta}e−iρθ (θ\thetaθ an arbitrary angle). Our implementation relies on a 99.7% fidelity controlled-phase gate between two superconducting transmon qubits. We achieve an average algorithmic fidelity ≈0.9\approx 0.9≈0.9, independent of the setting of ρ\rhoρ, to circuit depth nearly 90. This new paradigm for quantum instructions has applications to resource-efficient protocols for validating entanglement spectra, principal component analysis of large quantum states, and universal quantum emulation.
The equivalence between the instructions used to define programs and the input data on which the instructions operate is a basic principle of classical computer architectures and programming. Replacing classical data with quantum states enables fundamentally new computational capabilities with scaling advantages for many applications, and numerous models have been proposed for realizing quantum computation. However, within each of these models, the quantum data are transformed by a set of gates that are compiled using solely classical information. Conventional quantum computing models thus break the instruction-data symmetry: classical instructions and quantum data are not directly interchangeable. In this work, we use a density matrix exponentiation protocol to execute quantum instructions on quantum data. In this approach, a fixed sequence of classically-defined gates performs an operation that uniquely depends on an auxiliary quantum instruction state. Our demonstration relies on a 99.7% fidelity controlled-phase gate implemented using two tunable superconducting transmon qubits, which enables an algorithmic fidelity surpassing 90% at circuit depths exceeding 70. The utilization of quantum instructions obviates the need for costly tomographic state reconstruction and recompilation, thereby enabling exponential speedup for a broad range of algorithms, including quantum principal component analysis, the measurement of entanglement spectra, and universal quantum emulation.
We present the experimental implementation of two-qubit quantum algorithms in a superconducting circuit. Our processor incorporates local and fast flux biasing of two transmon qubits within a circuit QED architecture. An off-resonant cavity bus shields the qubits from the external environment and couples them to each other via virtual photon exchange. Meanwhile, integrated short-circuited coplanar waveguides proximal to each qubit allow nanosecond control of their frequencies. We demonstrate flux-controlled single-qubit z rotations and a qubit-qubit conditional phase (c-phase) interaction with a coupling strength tunable by two orders of magnitude. These operations are combined with frequency-multiplexed x and y rotations to form a set of gates universal for quantum computation. Dispersive frequency shifts of the cavity bus allow tomography of the two-qubit state, and accurate determination of state purity, fidelity and entanglement. The processor is first programmed to generate and detect entanglement on demand using sequences of five single-qubit operations and one c-phase. The four Bell states are generated with fidelities better than 90%, corresponding to a concurrence of 0.85 or an entanglement of formation of 0.8. Next, the Grover search algorithm is implemented by concatenating eight single-qubit and two c-phases operations. The fidelity of the algorithm output states to the theoretical ideal is ~ 80%, consistent with the observed T1 times ~ 1 us and the total duration ~ 130 ns of the algorithm sequence. We also program and execute the Deutsch-Jozsa algorithm, finding similar performance. Prospects for scaling the processor beyond two qubits will be discussed. Research supported by NSF, NSA and ARO.
Quantum algorithms on near-term quantum processors are typically executed using shallow quantum circuits composed of one- and two-qubit gates. However, as circuit depth and gate number increase, gate imperfections and qubit decoherence begin to dominate, limiting algorithmic complexity. An alternative approach is to explore gates involving more than two qubits. In previous work (X. Wu et al., Physical Review X 14, 041030 (2024)), we demonstrated a new superconducting qubit architecture with user-selectable two-qubit interactions via a reconfigurable router, used to connect pairs of qubits. Here, we leverage this novel architecture to realize programmable and efficient multi-qubit operations involving more than two qubits, resulting in faster preparation of multi-qubit entangled states with good fidelities. We also successfully apply model-free reinforcement learning to perform multi-qubit gates, including training a two-qubit controlled-Z gate as well as three-qubit controlled-SWAP and controlled-controlled-phase (Fredkin and Toffoli) gates. Higher nnnth-order gates may also be feasible, using our high-connectivity router design. This could provide a more efficient and higher-fidelity implementation of complex quantum algorithms and a more practical approach to quantum computation.
Quantum computers promise to solve certain problems that are intractable for classical computers, such as factoring large numbers and simulating quantum systems. To date, research in quantum computer engineering has focused primarily at opposite ends of the required system stack: devising high-level programming languages and compilers to describe and optimize quantum algorithms, and building reliable low-level quantum hardware. Relatively little attention has been given to using the compiler output to fully control the operations on experimental quantum processors. Bridging this gap, we propose and build a prototype of a flexible control microarchitecture supporting quantum-classical mixed code for a superconducting quantum processor. The microarchitecture is based on three core elements: (i) a codeword-based event control scheme, (ii) queue-based precise event timing control, and (iii) a flexible multilevel instruction decoding mechanism for control. We design a set of quantum microinstructions that allows flexible control of quantum operations with precise timing. We demonstrate the microarchitecture and microinstruction set by performing a standard gate-characterization experiment on a transmon qubit.
Quantum computing utilizes quantum mechanics to perform computations with superconducting qubits being the more mature technology as of writing in realizing a quantum computer. In this thesis, we describe an implementation of a Quantum Processor Unit (QPU), which is used to execute instructions in the form of microwave pulses on a superconducting qubit device through the use of signal generators and to perform qubit readout. We further extend the QPU as a platform to perform qubit characterization tasks such as spectroscopy and decoherence measurements in order to determine and optimize the working parameters to perform quantum gate operations. We also demonstrate the use of the QPU in performing qubit experiments such as Gauss Sum Factorization in determining the factors of an integer and the Bell Inequality test in examining the entanglement strength between a pair of qubits. We bridge the divide of quantum computation and qubit hardware in the compilation of quantum circuits into microwave pulse sequences for the QPU to execute. The process of compilation, as well as hardware limitations and pre-compilation optimization procedures are discussed. Finally, we show an example of executing a variational quantum algorithm and break down this example in all layers from the quantum circuit provided by the user to the pulse sequence that will be executed on the QPU.
Quantum computers can solve certain problems more efficiently compared to conventional classical methods. In the endeavor to build a quantum computer, several competing platforms have emerged that can implement certain quantum algorithms using a few qubits. However, the demonstrations so far have been done usually by tailoring the hardware to meet the requirements of a particular algorithm implemented for a limited number of instances. Although such proof of principal implementations are important to verify the working of algorithms on a physical system, they further need to have the potential to serve as a general purpose quantum computer allowing the flexibility required for running multiple algorithms and be scaled up to host more qubits. Here we demonstrate a small programmable quantum computer based on five trapped atomic ions each of which serves as a qubit. By optically resolving each ion we can individually address them in order to perform a complete set of single-qubit and fully connected two-qubit quantum gates and alsoperform efficient individual qubit measurements. We implement a computation architecture that accepts an algorithm from a user interface in the form of a standard logic gate sequence and decomposes it into fundamental quantum operations that are native to the hardware using a set of compilation instructions that are defined within the software. These operations are then effected through a pattern of laser pulses that perform coherent rotations on targeted qubits in the chain. The architecture implemented in the experiment therefore gives us unprecedented flexibility in the programming of any quantum algorithm while staying blind to the underlying hardware. As a demonstration we implement the Deutsch-Jozsa and Bernstein-Vazirani algorithms on the five-qubit processor and achieve average success rates of 95 and 90 percent, respectively. We also implement a five-qubit coherent quantum Fourier transform and examine its performance in the period finding and phase estimation protocol. We find fidelities of 84 and 62 percent, respectively. While maintaining the same computation architecture the system can be scaled to more ions using resources that scale favorably (O(N^2)) with the number of qubits N.