A5046765031- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
- Advancements in Semiconductor Devices and Circuit Design
- Quantum and electron transport phenomena
- Parallel Computing and Optimization Techniques
- Cloud Computing and Resource Management
- Distributed and Parallel Computing Systems
- Quantum many-body systems
- Quantum Mechanics and Applications
- Defense, Military, and Policy Studies
- Complexity and Algorithms in Graphs
- Soil Moisture and Remote Sensing
- Neural Networks and Applications
- Atomic and Subatomic Physics Research
- Geophysical Methods and Applications
- Computability, Logic, AI Algorithms
- International Law and Aviation
- Numerical Methods and Algorithms
- Underwater Acoustics Research
- Blind Source Separation Techniques
- Low-power high-performance VLSI design
- Military and Defense Studies
- Image and Signal Denoising Methods
Michigan State University
2019-2024
École Polytechnique Fédérale de Lausanne
2022-2024
Unitary Fund
2022-2023
Los Alamos National Laboratory
2019-2023
Ames Research Center
2022
Michigan Technological University
2018
Data representation is crucial for the success of machine learning models. In context quantum with near-term computers, equally important considerations how to efficiently input (encode) data and effectively deal noise arise. this work, we study encodings binary classification investigate their properties both without noise. For common classifier consider, show that determine classes learnable decision boundaries as well set points which retain same in presence After defining notion a robust...
Zero-noise extrapolation (ZNE) is an increasingly popular technique for mitigating errors in noisy quantum computations without using additional resources. We review the fundamentals of ZNE and propose several improvements to noise scaling extrapolation, two key components technique. introduce unitary folding parameterized scaling. These are digital frameworks, i.e. one can apply them only gate-level access common most instruction sets. also study different methods, including a new adaptive...
Quantum computers are available to use over the cloud, but recent explosion of quantum software platforms can be overwhelming for those deciding on which use. In this paper, we provide a current picture rapidly evolving computing landscape by comparing four - Forest (pyQuil), Qiskit, ProjectQ, and Developer Kit (Q#) that enable researchers real simulated devices. Our analysis covers requirements installation, language syntax through example programs, library support, simulator capabilities...
Compiling quantum algorithms for near-term computers (accounting connectivity and native gate alphabets) is a major challenge that has received significant attention both by industry academia. Avoiding the exponential overhead of classical simulation dynamics will allow compilation larger algorithms, strategy this to evaluate an algorithm's cost on computer. To end, we propose variational hybrid quantum-classical algorithm called quantum-assisted compiling (QAQC). In QAQC, use overlap...
Previously proposed quantum algorithms for solving linear systems of equations cannot be implemented in the near term due to required circuit depth. Here, we propose a hybrid quantum-classical algorithm, called Variational Quantum Linear Solver (VQLS), on near-term computers. VQLS seeks variationally prepare <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow class="MJX-TeXAtom-ORD"><mml:mo stretchy="false">|</mml:mo></mml:mrow><mml:mi>x</mml:mi><mml:mo fence="false"...
We introduce Mitiq, a Python package for error mitigation on noisy quantum computers. Error techniques can reduce the impact of noise near-term computers with minimal overhead in resources by relying mixture sampling and classical post-processing techniques. Mitiq is an extensible toolkit different methods, including zero-noise extrapolation, probabilistic cancellation, Clifford data regression. The library designed to be compatible generic backends interfaces software frameworks. describe...
Abstract Variational hybrid quantum-classical algorithms are promising candidates for near-term implementation on quantum computers. In these algorithms, a computer evaluates the cost of gate sequence (with speedup over classical evaluation), and uses this information to adjust parameters sequence. Here we present such an algorithm state diagonalization. State diagonalization has applications in condensed matter physics (e.g., entanglement spectroscopy) as well machine learning principal...
Previously proposed quantum algorithms for solving linear systems of equations cannot be implemented in the near term due to required circuit depth. Here, we propose a hybrid quantum-classical algorithm, called Variational Quantum Linear Solver (VQLS), on near-term computers. VQLS seeks variationally prepare $|x\rangle$ such that $A|x\rangle\propto|b\rangle$. We derive an operationally meaningful termination condition allows one guarantee desired solution precision $\epsilon$ is achieved....
We simulate the excited states of Lipkin model using recently proposed Quantum Equation Motion (qEOM) method. The qEOM generalizes EOM on classical computers and gives access to collective excitations based quasi-boson operators $\hat{O}^\dagger_n(\alpha)$ increasing configuration complexity $\alpha$. show, in particular, that accuracy strongly depends fermion qubit encoding. Standard encoding leads large errors, but use symmetries Gray code reduces quantum resources improves significantly...
We apply quantum error mitigation techniques to a variety of benchmark problems and computers evaluate the performance in practice. To do so, we define an empirically motivated, resource-normalized metric improvement which call factor, calculate this for each experiment perform. The experiments perform consist zero-noise extrapolation probabilistic cancellation applied two run on IBM, IonQ, Rigetti computers, as well noisy computer simulators. Our results show that is average more beneficial...
Quantum technologies, such as communication, computing, and sensing, offer vast opportunities for advanced research development. While an open-source ethos currently exists within some quantum especially in computer programming, we argue that there are additional advantages developing open hardware (OQH). Open encompasses software the control of devices labs, blueprints, toolkits chip design other components, well openly accessible testbeds facilities allow cloud-access to a wider scientific...
Zero-noise extrapolation is a quantum error mitigation technique that has typically been studied under the ideal approximation noise acting on device not time correlated. In this paper, we investigate feasibility and performance of zero-noise in presence time-correlated noise. We show that, contrast to white noise, harder mitigate via because it difficult scale level without also modifying its spectral distribution. This limitation particularly strong if ``local'' gate-level methods are...
Quantum volume is a full-stack benchmark for near-term quantum computers. It quantifies the largest size of square circuit which can be executed on target device with reasonable fidelity. Error mitigation set techniques intended to remove effects noise present in computation noisy computers when computing an expectation value interest. Effective proposed metric that applies error protocol evaluate effectiveness not only but also algorithm. Digital zero-noise extrapolation technique estimates...
Abstract We introduce multiple parametrized circuit ansätze and present the results of a numerical study comparing their performance with standard Quantum Alternating Operator Ansatz approach. The are inspired by mixing phase separation in QAOA, also motivated compilation considerations aim running on near-term superconducting quantum processors. methods tested random instances quadratic binary constrained optimization problem that is fully connected for which space feasible solutions has...
We introduce Mitiq, a Python package for error mitigation on noisy quantum computers. Error techniques can reduce the impact of noise near-term computers with minimal overhead in resources by relying mixture sampling and classical post-processing techniques. Mitiq is an extensible toolkit different methods, including zero-noise extrapolation, probabilistic cancellation, Clifford data regression. The library designed to be compatible generic backends interfaces software frameworks. describe...
Quantum volume is a single-number metric which, loosely speaking, reports the number of usable qubits on quantum computer. While improvements to underlying hardware are direct means increasing volume, "full-stack" and has also been increased by software, notably compilers. We extend this latter direction demonstrating that error mitigation, type indirect compilation, increases effective several computers. Importantly, increase occurs while taking same overall samples. encourage adoption as...
We introduce a technique to estimate error-mitigated expectation values on noisy quantum computers. Our performs shadow tomography logical state produce memory-efficient classical reconstruction of the density matrix. Using efficient post-processing, one can mitigate errors by projecting general nonlinear function matrix into codespace. The subspace expansion and virtual distillation be viewed as special cases new framekwork. show our method is favorable in resources overhead. Relative which...
In this paper we describe, implement, and test the performance of distributed memory simulations quantum circuits on MSU Laconia Top500 supercomputer. Using OpenMP MPI hybrid parallelization, first use a matrix-vector multiplication with one-dimensional partitioning discuss shortcomings method due to exponential requirements in simulating computers. We then describe more efficient that stores only $2^n$ amplitudes $n$ qubit state vector $|\psi\rangle$ optimize its single node performance....
Estimating expectation values on near-term quantum computers often requires a prohibitively large number of measurements. One widely-used strategy to mitigate this problem has been partition an operator's Pauli terms into sets mutually commuting operators. Here, we introduce method that relaxes constraint commutativity, instead allowing for entirely arbitrary be grouped together, save locality constraint. The key idea is decompose the operator tensor products with bounded size, ignoring...
In this review article we summarize all experiments claiming quantum computational advantage to date. Our highlights challenges, loopholes, and refutations appearing in subsequent work provide a complete picture of the current statuses these experiments. addition, also discuss theoretical example problems such as approximate optimization recommendation systems. Finally, recent error correction -- biggest frontier reach experimental Shor's algorithm.