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At least 109 records · Page 6

Quantum-Inspired Power System Reliability Assessment

To enable an in-depth study of power system operation and planning, the assessment of standard reliability indices is inevitable. The Monte Carlo Simulation (MCS) approach is a broadly used method in replacing the analytical methods in reliability indices assessment. The accuracy of MCS, however, highly depends on the sampling size, and hence, a complicated system with large number of components requires a large sampling size and daunting computational effort. To address this shortcoming, we, in this paper attempt to take advantage of potentials of the quantum computing (QC) for power system reliability assessment by realizing the following contributions: 1) an innovative quantum model designed for reliability assessment; 2) a quantum circuit that achieves the quadratic speed up compared to the classical MCS method; 3) an efficient quantum amplitude estimation (QAE) algorithm to accurately evaluate the reliability indices. The accuracy and efficacy of the quantum reliability method are extensively verified and demonstrated on both radial and mesh distribution systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A QUBO formulation for top-τ eigencentrality nodes

The efficient calculation of the centrality or “hierarchy” of nodes in a network has gained great relevance in recent years due to the generation of large amounts of data. The eigenvector centrality (aka eigencentrality) is quickly becoming a good metric for centrality due to both its simplicity and fidelity. In this work we lay the foundations for solving the eigencentrality problem of ranking the importance of the nodes of a network with scores from the eigenvector of the network, using quantum computational paradigms such as quantum annealing and gate-based quantum computing. The problem is reformulated as a quadratic unconstrained binary optimization (QUBO) that can be solved on both quantum architectures. The results focus on correctly identifying a given number of the most important nodes in numerous networks given by the sparse vector solution of our QUBO formulation of the problem of identifying the top- τ highest eigencentrality nodes in a network on both the D-Wave and IBM quantum computers.

97 MATHEMATICS AND COMPUTING↗

Error mitigation with Clifford quantum-circuit data

Achieving near-term quantum observables despite significant hardware noise. For this purpose, we propose a novel, scalable error-mitigation method that applies to gate-based quantum computers. The method generates training data { X i noisy , X i exact } via quantum circuits composed largely of Clifford gates, which can be efficiently simulated classically, where X i noisy and X i exact are noisy and noiseless observables respectively. Fitting a linear ansatz to this data then allows for the prediction of noise-free observables for arbitrary circuits. We analyze the performance of our method versus the number of qubits, circuit depth, and number of non-Clifford gates. Here, we obtain an order-of-magnitude error reduction for a ground-state energy problem on 16 qubits in an IBMQ quantum computer and on a 64-qubit noisy simulator.

97 MATHEMATICS AND COMPUTING↗

Resonant dipole – dipole interaction of Rydberg atoms for realisation of quantum computations

We report the application of the resonant dipole – dipole interaction of Rydberg atoms for the realisation of quantum computations with ultracold neutral atoms. Coherent population oscillations between the collective states of systems consisting of two interacting atoms make it possible to implement two-qubit phase gates, which are necessary for universal quantum computations. The schemes studied are alternatives to two-qubit gates based on the Rydberg dipole blockade effect. In contrast, the schemes we propose do not require large dipole – dipole interaction energies and can be realised for atoms that are at a considerable distance from each other. The bibliography includes 27 references. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimal Design and Control of Qubits

Research interest in developing computing systems that represent logic states using quantum mechanical observables has only increased in the few decades since its inception. While quantum computers, with Josephson junction based qubits, have now been commercially available in the last three years, there is also significant research initiative to develop scalable quantum computers with so-called donor qubits. B.E. Kane first published on a device implementation of a silicon-based quantum computer in 1998, which sparked a wave of follow-on advances due to the attractive nature of silicon-based computing[7]. Nearly all commercial computing systems using classical binary logic are fabricated using a silicon substrate and it is inarguably the most mature material system for semiconductor devices, so that coupling classical and quantum bits on a single substrate is possible. The process of growing and processing silicon crystals into wafers is extremely robust and leads to minimal impurities or structural defects.

97 MATHEMATICS AND COMPUTING↗

Analysis of RF Surface Loss in a Planar 2D Qubit

The Josephson junction and shunt capacitor form a transmon qubit, which is the cornerstone of modern quantum computing platforms. For reliable quantum computing, it is important how long a qubit can remain in a superposition of quantum states, which is determined by the coherence time (T1). The coherence time of a qubit effectively sets the "lifetime" of usable quantum information, determining how long quantum computations can be performed before errors occur and information is lost. There are several sources of decoherence in transmon qubits, but the predominant one is generally considered to be dielectric losses in the natural oxide layer formed on the surface of the superconductor. In this paper, we present a numerical study of microwave surface losses in planar superconducting antennas of different transmon qubit designs. An asymptotic method for estimating the energy participation ratio in ultrathin films of nanometer scales is proposed, and estimates are given for the limits of achievable minimum RF losses depending on the electrical properties of the surface oxide and the interface of the qubit with the substrate material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Automatic Qubit Characterization and Gate Optimization with QubiC

As the size and complexity of a quantum computer increases, quantum bit (qubit) characterization and gate optimization become complex and time-consuming tasks. Current calibration techniques require complicated and verbose measurements to tune up qubits and gates, which cannot easily expand to the large-scale quantum systems. We develop a concise and automatic calibration protocol to characterize qubits and optimize gates using QubiC, which is an open source FPGA (field-programmable gate array) based control and measurement system for superconducting quantum information processors. We propose multi-dimensional loss-based optimization of single-qubit gates and full XY-plane measurement method for the two-qubit CNOT gate calibration. We demonstrate the QubiC automatic calibration protocols are capable of delivering high-fidelity gates on the state-of-the-art transmon-type processor operating at the Advanced Quantum Testbed at Lawrence Berkeley National Laboratory. Finally, the single-qubit and two-qubit Clifford gate infidelities measured by randomized benchmarking are of 4.9(1.1) × 10 -4 and 1.4(3) × 10 -2 , respectively.

97 MATHEMATICS AND COMPUTING↗

Efficient, Predictive Tomography of Multi-Qubit Quantum Processors

After decades of R&D, quantum computers comprising more than 2 qubits are appearing. If this progress is to continue, the research community requires a capability for precise characterization (“tomography”) of these enlarged devices, which will enable benchmarking, improvement, and finally certification as mission-ready. As world leaders in characterization -- our gate set tomography (GST) method is the current state of the art – the project team is keenly aware that every existing protocol is either (1) catastrophically inefficient for more than 2 qubits, or (2) not rich enough to predict device behavior. GST scales poorly, while the popular randomized benchmarking technique only measures a single aggregated error probability. This project explored a new insight: that the combinatorial explosion plaguing standard GST could be avoided by using an ansatz of few-qubit interactions to build a complete, efficient model for multi-qubit errors. We developed this approach, prototyped it, and tested it on a cutting-edge quantum processor developed by Rigetti Quantum Computing (RQC), a US-based startup. We implemented our new models within Sandia’s PyGSTi open-source code, and tested them experimentally on the RQC device by probing crosstalk. We found two major results: first, our schema worked and is viable for further development; second, while the Rigetti device is indeed a “real” 8-qubit quantum processor, its behavior fluctuated significantly over time while we were experimenting with it and this drift made it difficult to fit our models of crosstalk to the data.

97 MATHEMATICS AND COMPUTING↗

Ancilla-driven quantum computation for qudits and continuous variables

Although qubits are the leading candidate for the basic elements in a quantum computer, there are also a range of reasons to consider using higher-dimensional qudits or quantum continuous variables (QCVs). In this paper, we use a general “quantum variable” formalism to propose a method of quantum computation in which ancillas are used to mediate gates on a well-isolated “quantum memory” register and which may be applied to the setting of qubits, qudits (for d>2), or QCVs. More specifically, we present a model in which universal quantum computation may be implemented on a register using only repeated applications of a single fixed two-body ancilla-register interaction gate, ancillas prepared in a single state, and local measurements of these ancillas. In order to maintain determinism in the computation, adaptive measurements via a classical feed forward of measurement outcomes are used, with the method similar to that in measurement-based quantum computation (MBQC). We show that our model has the same hybrid quantum-classical processing advantages as MBQC, including the power to implement any Clifford circuit in essentially one layer of quantum computation. In some physical settings, high-quality measurements of the ancillas may be highly challenging or not possible, and hence we also present a globally unitary model which replaces the need for measurements of the ancillas with the requirement for ancillas to be prepared in states from a fixed orthonormal basis. In conclusion, we discuss settings in which these models may be of practical interest.

97 MATHEMATICS AND COMPUTING↗

Qubit Regularization and Qubit Embedding Algebras

Qubit regularization is a procedure to regularize the infinite dimensional local Hilbert space of bosonic fields to a finite dimensional one, which is a crucial step when trying to simulate lattice quantum field theories on a quantum computer. When the qubit-regularized lattice quantum fields preserve important symmetries of the original theory, qubit regularization naturally enforces certain algebraic structures on these quantum fields. We introduce the concept of qubit embedding algebras (QEAs) to characterize this algebraic structure associated with a qubit regularization scheme. We show a systematic procedure to derive QEAs for the O(N) lattice spin models and the SU(N) lattice gauge theories. While some of the QEAs we find were discovered earlier in the context of the D-theory approach, our method shows that QEAs are far richer. A more complete understanding of the QEAs could be helpful in recovering the fixed points of the desired quantum field theories.

97 MATHEMATICS AND COMPUTING↗

Orchestrated trios: compiling for efficient communication in Quantum programs with 3-Qubit gates

Current quantum computers are especially error prone and require high levels of optimization to reduce operation counts and maximize the probability the compiled program will succeed. These computers only support operations decomposed into one- and two-qubit gates and only two-qubit gates between physically connected pairs of qubits. Typical compilers first decompose operations, then route data to connected qubits. We propose a new compiler structure, Orchestrated Trios, that first decomposes to the three-qubit Toffoli, routes the inputs of the higher-level Toffoli operations to groups of nearby qubits, then finishes decomposition to hardware-supported gates. This significantly reduces communication overhead by giving the routing pass access to the higher-level structure of the circuit instead of discarding it. A second benefit is the ability to now select an architecture-tuned Toffoli decomposition such as the 8-CNOT Toffoli for the specific hardware qubits now known after the routing pass. Furthermore, we perform real experiments on IBM Johannesburg showing an average 35% decrease in two-qubit gate count and 23% increase in success rate of a single Toffoli over Qiskit. We additionally compile many near-term benchmark algorithms showing an average 344% increase in (or 4.44x) simulated success rate on the Johannesburg architecture and compare with other architecture types.

compiler↗

Angle-robust two-qubit gates in a linear ion crystal

In trapped-ion quantum computers, two-qubit entangling gates are generated by applying spin-dependent force which uses phonons to mediate interaction between the internal states of the ions. To maintain high-fidelity two-qubit gates under fluctuating experimental parameters, robust pulse-design methods are applied to remove the residual spin-motion entanglement in the presence of motional mode-frequency drifts. Here we propose an improved pulse-design method that also guarantees the robustness of the two-qubit rotation angle against uniform mode-frequency drifts by concatenating pulses with opposite sensitivity of the angle to mode-frequency drifts. Here we experimentally verify significantly improved robustness of the rotation angle against uniform mode-frequency drifts, as well as observe an improvement in gate fidelity from 97.84(10)% to 98.11(11)%, compared to a single frequency-modulated pulse.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Using IBM-Q to Study and Visualize the Ground State Properties of the Su-Schrieffer-Heeger Model

Quantum computing takes advantage of quantum mechanical properties such as superposition and entanglement in order to perform calculations that are too intensive for a classical computer. Richard Feynmann came up with the idea of quantum computers in 1982, where it was only theoretically motivated until the creation of Shor’s algorithm. This algorithm involves the factorization of large numbers, which in turn makes it possible to break encryption keys. Quantum computers would be capable of using Shor’s algorithm to crack encryptions at a significantly faster speed than a classical computer, which provided the motivation to start developing quantum computers to run Shor’s algorithm and discover other uses. In the present day, companies such as Google, Microsoft, D-Wave Systems, Rigetti Computing, and IBM are building quantum computers using different techniques and racing to achieve quantum supremacy. The purpose of quantum computing is to perform calculations that are too difficult to be executed on classical computers. But before we are able to use these computers, we must first prove that they are able to use quantum mechanics that will in turn be used to perform the calculations. As a proof of principle we use algorithms that can be done classically and compare those results to that of the quantum computer. In theory, if the quantum computer works for small qubit systems, larger qubit systems can be implemented and run on quantum computers.

97 MATHEMATICS AND COMPUTING↗