Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session M34: Quantum Software and Compilers II  Compute Frameworks and Program RepresentationsFocus Live

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Sponsoring Units: DQI Chair: Lauren Capelluto, IBM TJ Watson Research Center 
Wednesday, March 17, 2021 11:30AM  11:42AM Live 
M34.00001: Quantify: An opensource framework for operating quantum computers in the NISQ era Michiel Adriaan Rol, Callum Attryde, Jules C. van Oven, Kelvin Loh, Jordy Gloudemans, Victor Negîrneac, Thorsten Last, Cornelis Christiaan Bultink Operating a quantum computer in the NISQ era is an oftenunderestimated challenge. Specifically, the tuneup and execution of quantum algorithms, which consist of physics experiments requiring access to control parameters and measured signals, as well as classical logic. Typically, these are defined at a higher level of abstraction and are not supported by current control architectures because they are limited to expressing experiments as either a series of classical pulses or variants of QASM. Here, we present Quantify, a robust and extensively documented opensource experiment platform inspired by PycQED (Rol et al. 10.5281/zenodo.160327). Quantify contains all the basic functionality to control experiments (e.g., instrument management, live plotting, data storage, etc.), as well as a novel scheduler featuring a unique hybrid control model allowing quantum gate and pulselevel descriptions to be combined in a clearly defined and hardwareagnostic way. The scheduler allows parameterized expressions and classical logic to make efficient use of hardware backends that support this. This opens up new avenues for efficient execution of calibration routines as well as variational quantum algorithms (VQA). 
Wednesday, March 17, 2021 11:42AM  11:54AM Live 
M34.00002: GeneralPurpose firmware for controlling quantum processors Mats Tholen, Riccardo Borgani, David Brant Haviland FPGAs are ideally suited to the classical, digital control of quantum hardware. However their lowlevel programming is time consuming making them inconvenient for laboratory exploration. We present a generalpurpose firmware for the Xilinx Zynq UltraScale+ RFSoC platform which allows for flexible implementation of quantum readout and control sequences through a Python API. Our approach allows for a wide variety of experiments with finetuning performed at runtime, without reloading large blocks of memory. 
Wednesday, March 17, 2021 11:54AM  12:06PM Live 
M34.00003: Exponential Information Compression with Quantum Contextual Redundancy Giancarlo Gatti, Daniel Huerga, Enrique Solano, Mikel Sanz We propose a protocol to store exponential amounts of classical information in the measurement statistics of a set of eigenstates of manybody Pauli observables. Fewer samples are required for bit retrieval if entanglement is allowed in the encoding, which is achieved by exploiting spontaneouslyoccurring redundancies in measurement contexts. This is applicable to store large quantities of data when only small portions of information need to be consulted at a time, e.g. decision trees. The present protocol showcases enhancement over classical methods using the same number of resources starting at 16 qubits and would outperform current HPC storage capacity starting at 38 qubits. To illustrate the power of this compression protocol, sets of states of ∼100 qubits are sufficient to store a bruteforce solution for chess. 
Wednesday, March 17, 2021 12:06PM  12:18PM Live 
M34.00004: Fast simulation of quantum algorithms using circuit optimization Gian Giacomo Guerreschi Classical simulators play a major role in the development and benchmark of quantum algorithms, and are an important component of most software frameworks for quantum computation. However, the development of simulators was substantially separated from the rest of the software frameworks which focus on usability and compilation. Here, we demonstrate the advantage of codeveloping and integrating simulators and compilers by proposing a specialized compiler pass to reduce the simulation time for arbitrary circuits. While the concept is broadly applicable, we present a concrete implementation based on the Intel Quantum Simulator, a highperformance distributed simulator. First, we extend its implementation with additional functionalities related to the representation of quantum states. The communication overhead is reduced by changing the order in which state amplitudes are stored in the distributed memory. Then, we implement a compiler pass to exploit the novel functionalities by introducing special instructions governing data movement as part of the quantum circuit. Those instructions target unique capabilities of simulators. To quantify the advantage, we compare the time required to simulate random circuits with and without our optimization. The simulation time is typically halved. 
Wednesday, March 17, 2021 12:18PM  12:30PM Live 
M34.00005: Qaintum: A Juliabased Simulation Framework for Quantum Circuits Qunsheng Huang, Ismael Medina, Esther Cruz, Shin Ho Cho, Christian Mendl We introduce “Qaintum”, a Juliabased software framework for quantum circuit simulation and optimization that can also be integrated into classical machine learning toolboxes. The core concept of Qaintum is flexibility of design: enabling the user to work with different representations, such as circuits or tensor networks. 
Wednesday, March 17, 2021 12:30PM  12:42PM Live 
M34.00006: Hamiltonian Open Quantum System Toolkit (HOQST) Huo Chen, Daniel Lidar We present an opensource 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 gatemodel of quantum computing. It features the key master equations (MEs) used in the field, suitable for describing the reduced system dynamics of an arbitrary timedependent Hamiltonian with either weak or strong coupling to infinitedimensional quantum baths. This package is ready to be deployed on high performance clusters (HPC) and aimed at providing reliable opensystem analysis tools for noisy intermediatescale quantum (NISQ) devices. 
Wednesday, March 17, 2021 12:42PM  12:54PM Live 
M34.00007: QTensor: Fast QAOA Quantum Simulator Danylo Lykov, Yuri Alexeev, Cameron Ibrahim, Alexey Galda

Wednesday, March 17, 2021 12:54PM  1:06PM Live 
M34.00008: On the Quantum LINPACK Benchmark Yulong Dong, Lin Lin, Birgitta K Whaley The LINPACK benchmark reports the performance of a computer for solving systems of linear equations with pseudodense random matrices, and has been used to define the list of TOP500 supercomputers since the debut of the list in 1993. We propose that a quantum LINPACK benchmark could be used to measure the whole machine performance of quantum computers. We propose an input model called the RAndom Circuit BlockEncoded Matrix (RACBEM), which is a proper generalization of a dense random matrix in the quantum setting. The RACBEM model is efficient to be implemented on a quantum computer, and can be designed to optimally adapt to any given quantum architecture, with relying on a blackbox quantum compiler. The result of the quantum LINPACK benchmark demonstrates the performance of a quantum computer in solving scientific computing problems. 
Wednesday, March 17, 2021 1:06PM  1:42PM Live 
M34.00009: Universal Quantum Intermediate Representation Invited Speaker: Bettina Heim Quantum computing offers exciting promises regarding how it can benefit society. However, it is also still in its infancy. In many ways today’s environment is similar to the state of classical computing in the early 1950s: each system is different, and capabilities and resources are highly limited. We face several major technical challenges throughout the stack that yet need to be overcome, and it is not obvious which hardware technologies are likely to succeed and which applications will benefit society. To advance the field of quantum computing we need to make it possible to easily connect emerging technologies, and nurture the growth of an ecosystem that facilitates to develop and experiment with different approaches and analyze potential applications. 
Wednesday, March 17, 2021 1:42PM  1:54PM Live 
M34.00010: Parallel hybrid quantumclassical compute model Alexander J McCaskey, Daniel Claudino, Thien Nguyen, Dmitry Liakh Hybrid computing in which classical hardware is augmented with quantum processing units (QPUs) is widely adopted in the noisy intermediatescale quantum (NISQ) era, contending with many independent, often repetitive tasks in order to measure an observable comprised of many Pauli strings or to achieve reliable statistics in the presence of noise. Such computations are expected to greatly benefit from the simultaneous operation of an array of independent QPUs, akin to the parallel computing paradigm widespread in high performance computing (HPC). Here we report our findings in simulations with the variational quantum eigensolver algorithm, where different terms of the problem Hamiltonian are measured concurrently. The resulting groups of circuit instances are executed by virtual QPUs ran by standard message passing interface (MPI) processes, opening a door to parallel quantum computing based on the concerted operation of classical HPC nodes and virtual QPUs within a single hybrid virtual HPC platform, with potentially massive gains in efficiency and computational scale. 
Wednesday, March 17, 2021 1:54PM  2:06PM Live 
M34.00011: Booting a quantum computer: A QUAbased graph framework for automatic qubit calibration, measurement, and execution of hybrid classicalquantum algorithms Gal Winer, Spencer Tomarken, Ilan Mitnikov, Arthur Strauss, Steven Frankel, Jonathan L DuBois, Lior Ella, Yonatan Cohen Deploying algorithms on realworld quantum computers requires calibration and optimization steps, the complexity of which scales with the system’s size. These typically involve an interplay between quantum circuit execution on quantum hardware and classical processing of results on classical hardware. Interestingly, some of the most promising candidate algorithms for demonstrating quantum advantage in the next decade are, in fact, quantumclassical hybrid algorithms. Therefore, an automated framework for hybrid execution for efficiently running such protocols is highly desired. 
Wednesday, March 17, 2021 2:06PM  2:18PM Live 
M34.00012: Programming a Quantum Computer with Quantum Instructions (Part 1): Introduction and construction Morten Kjaergaard, Mollie Schwartz, Amy Greene, Gabriel O Samach, Andreas Bengtsson, Michael O'Keeffe, Chris McNally, Jochen Braumueller, David K Kim, Philip Krantz, Milad Marvian, Alexander Melville, Bethany Niedzielski, Youngkyu Sung, Roni Winik, Jonilyn Yoder, Danna Rosenberg, Kevin Obenland, Seth Lloyd, Terry Philip Orlando, Iman Marvian, Simon Gustavsson, William Oliver The equivalence between the instructions used to define programs and the input data on which they operate is a basic principle of classical computer architectures and programming. However, in all previous quantum computing models, quantum data are transformed by a set of gates compiled using solely classical information. In this work, we execute a quantum program–density matrix exponentiation (DME)–that uses quantum instructions to process quantum data. Here, a fixed sequence of gates performs an operation that depends on a quantum instruction state. Quantum instructions remove the need for state reconstruction in a broad range of algorithms, enabling exponential speedup. In Part 1, we introduce the DME algorithm and describe our experimental implementation of DME on a quantum processor using a 99.7% fidelity CPHASE gate between two superconducting transmons. 
Wednesday, March 17, 2021 2:18PM  2:30PM Live 
M34.00013: Programming a Quantum Computer with Quantum Instructions (Part 2): Demonstration and Characterization Mollie Schwartz, Morten Kjaergaard, Amy Greene, Gabriel O Samach, Andreas Bengtsson, Michael O'Keeffe, Chris McNally, Jochen Braumueller, David K Kim, Philip Krantz, Milad Marvian, Alexander Melville, Bethany Niedzielski, Youngkyu Sung, Roni Winik, Jonilyn Yoder, Danna Rosenberg, Kevin Obenland, Seth Lloyd, Terry Philip Orlando, Iman Marvian, Simon Gustavsson, William Oliver 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. However, in all previouslyrealized quantum computing models, quantum data have been transformed by a set of gates that are compiled using solely classical information. In this work, we execute a quantum program – density matrix exponentiation (DME) – that uses quantum instructions to process quantum data. In Part 2 of this talk, we benchmark an implementation of the DME algorithm in a twoqubit system. We demonstrate that the unitary implemented by DME depends uniquely on a quantum instruction state. We then explore tradeoffs between algorithmic error and coherence limitations in a noisy quantum processor, and characterize DME process via process tomography. 
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