Article
Biochemical Research Methods
Nolan H. Hamilton, Terrence S. Furey
Summary: ROCCO is a novel method that determines consensus open chromatin regions across multiple samples simultaneously. It utilizes robust summary statistics and solves a constrained optimization problem to consider both the enrichment and spatial dependence of open chromatin signal data. We demonstrate that this method has attractive theoretical and conceptual properties and shows superior empirical performance compared to current methodology.
Article
Computer Science, Interdisciplinary Applications
Aras Selvi, Aharon Ben-Tal, Ruud Brekelmans, Dick den Hertog
Summary: This research investigates the problem of maximizing a convex function over convex constraints and proves that it can be reformulated as an adjustable robust optimization problem. By using ARO techniques, approximate solutions to the convex maximization problem can be obtained. The research provides approximate solution methods for both cases of having one nonlinear constraint and multiple linear constraints.
INFORMS JOURNAL ON COMPUTING
(2022)
Article
Automation & Control Systems
Jianchen Hu, Baocang Ding, Meng Zhang, Jun Zhao, Zuhua Xu, Hongguang Pan
Summary: This article proposes a novel approach for hierarchical implementation of output feedback robust model predictive control for linear polytopic uncertain models. It addresses the optimization problem of minimizing the performance index followed by assessing the estimation error set (EES). These two problems are posed in a lexicographic order. The new approach improves control performance significantly compared to earlier schemes without lexicographic optimization. The proposed approach is shown to be recursively feasible and the closed-loop stability is ensured by quadratic boundedness. The results are validated through two numerical examples.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Physics, Multidisciplinary
Edward H. Chen, Theodore J. Yoder, Youngseok Kim, Neereja Sundaresan, Srikanth Srinivasan, Muyuan Li, Antonio D. Corcoles, Andrew W. Cross, Maika Takita
Summary: Arbitrarily long quantum computations require quantum memories that can be repeatedly measured without being corrupted. In this study, the researchers were able to preserve the state of a quantum memory by using flagged error events. Fast, midcircuit measurements and resets of the physical qubits were used to extract all error events. A perfect matching decoder was introduced for comparison with other error decoders, and it was calibrated using measurements containing up to size-four correlated events. The researchers observed logical errors per round that surpass the physical measurement error, demonstrating the potential for repeated logical measurements.
PHYSICAL REVIEW LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Alireza Arab, Joseph Euzebe Tate
Summary: This paper proposes a distributionally robust joint chance-constrained AC optimal power flow to manage the risk of operational limits violations caused by uncertain renewable generation. The uncertainty is modeled as a distributionally robust ellipsoidal bound based on the Wasserstein metric, and this bound is adopted within a semidefinite relaxation of the optimal power flow. Numerical experiments demonstrate the validity and scalability of the proposed method, as well as its effectiveness in meeting probabilistic guarantees, cost-effectiveness and computational time.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Multidisciplinary Sciences
William P. Livingston, Machiel S. Blok, Emmanuel Flurin, Justin Dressel, Andrew N. Jordan, Irfan Siddiqi
Summary: Continuous quantum error correction using direct parity measurements in a resource-efficient manner is demonstrated, achieving high detection efficiency and increasing the relaxation time of protected logical qubits.
NATURE COMMUNICATIONS
(2022)
Article
Automation & Control Systems
Monimoy Bujarbaruah, Ugo Rosolia, Yvonne R. Sturz, Xiaojing Zhang, Francesco Borrelli
Summary: We propose a novel approach to design a robust Model Predictive Controller (MPC) for constrained uncertain linear systems. The approach models the uncertain system as linear parameter varying with an additive disturbance and formulates a constraint tightening strategy based on these bounds. With appropriately designed terminal cost function and constraint set, the resulting MPC satisfies the imposed constraints in closed-loop with the uncertain system and exhibits Input to State Stability of the origin.
Article
Engineering, Electrical & Electronic
Sharmin Kibria, Jinsub Kim, Raviv Raich
Summary: This study focuses on joint nonlinear state estimation with multi-period measurement vectors potentially corrupted by sparse gross errors. A nonlinear sparse optimization formulation is used for joint sparse error correction and robust state estimation, exploiting the sparsity and short-term invariance of error locations. A sequential convex approximation approach is introduced to solve the nonlinear sparse optimization problem with a convergence guarantee. An identifiability-aware version of the proposed algorithm is presented to improve the accuracy of gross error localization using a necessary rank condition for identifiable gross error matrix. The efficacy of the approach is demonstrated through application to power system nonlinear state estimation in IEEE 14-bus and 118-bus networks.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Computer Science, Information Systems
Xiaodong Feng, Sen Wu
Summary: The study introduces the Self-Paced Sparse Coding (SPSC) framework, which enhances learning robustness by gradually incorporating data from easy to complex into the learning process of SC. The framework implements soft instance selection and generalizes the self-paced learning schema to different levels of dynamic selection. An optimization algorithm and theoretical explanation are provided to analyze the effectiveness of the method.
INFORMATION SCIENCES
(2021)
Article
Quantum Science & Technology
Akshay Gaikwad, Arvind, Kavita Dorai
Summary: In this study, a constrained convex optimization (CCO) method is used to experimentally characterize arbitrary quantum states and unknown quantum processes on a two-qubit NMR quantum information processor. The CCO method provides physically valid density matrices and process matrices with significantly improved fidelity compared to standard methods, even in the presence of errors due to decoherence. Additionally, the study assumes Markovian system dynamics and uses a Lindblad master equation in conjunction with the CCO method to completely characterize noise processes present in the NMR system.
QUANTUM INFORMATION PROCESSING
(2021)
Article
Computer Science, Information Systems
Diogo Cruz, Francisco A. Monteiro, Bruno C. Coutinho
Summary: This paper investigates the construction and decoding methods for quantum error correction codes (QECCs) that can achieve the maximum performance in the finite blocklength regime. By extending the classical decoding strategy called GRAND to quantum systems, efficient decoding of QECCs is achieved. Furthermore, a quantum-GRAND algorithm is proposed that utilizes quantum noise statistics to enable adaptive code membership testing and efficient syndrome decoding.
Article
Quantum Science & Technology
Tyson Jones, Simon C. Benjamin
Summary: This study explores a method for automatically recompiling a quantum circuit A into a target circuit /3, with the goal of achieving the same behavior on a specific input. This method can be crucial for hybrid, NISQ-era algorithms for dynamical simulation or eigensolving.
Article
Mathematics, Applied
Mei Wang, Xiao-Bing Li, Bin Yao, Yeong-Cheng Liou
Summary: This paper addresses the global error bound for the robust counterpart of uncertain inequality systems, characterizing necessary and sufficient conditions for the existence of global error bounds using right derivative, projection operator, normal cone, and basic condition qualification. The study also demonstrates that the dual characterization of error bounds for convex inequality systems under interval uncertainty is necessary but not sufficient.
JOURNAL OF NONLINEAR AND CONVEX ANALYSIS
(2021)
Article
Multidisciplinary Sciences
Jeffrey M. Gertler, Brian Baker, Juliang Li, Shruti Shirol, Jens Koch, Chen Wang
Summary: In this study, a logical qubit encoded in multi-photon states of a superconducting cavity is protected with autonomous correction of certain quantum errors by tailoring the dissipation it is exposed to. The passive protocol implemented with continuous-wave control fields autonomously corrects single-photon-loss errors and increases the coherence time of the bosonic qubit by over a factor of two. This approach offers a resource-efficient alternative or supplement to active QEC in future quantum computing architectures.
Article
Engineering, Electrical & Electronic
Mengbo You, Aihong Yuan, Min Zou, Kouichi Konno
Summary: Unsupervised band selection is important for reducing the dimensionality of hyperspectral imagery. However, improving classification performance with a small set of selected bands is still challenging due to the lack of discriminative information. This article proposes a method called GAMR, which formulates a convex optimization problem to refine pseudolabels and estimates similarity between band pairs by reconstructing a global affinity matrix. Experimental results demonstrate the effectiveness and superiority of GAMR over seven state-of-the-art methods.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Physics, Applied
Huo Chen, Daniel A. Lidar
PHYSICAL REVIEW APPLIED
(2020)
Correction
Quantum Science & Technology
Adam Pearson, Anurag Mishra, Itay Hen, Daniel A. Lidar
NPJ QUANTUM INFORMATION
(2020)
Article
Quantum Science & Technology
Richard Y. Li, Tameem Albash, Daniel A. Lidar
QUANTUM SCIENCE AND TECHNOLOGY
(2020)
Article
Quantum Science & Technology
Mostafa Khezri, Jeffrey A. Grover, James I. Basham, Steven M. Disseler, Huo Chen, Sergey Novikov, Kenneth M. Zick, Daniel A. Lidar
Summary: The study focused on a high coherence four-junction capacitively shunted flux qubit (CSFQ) and implemented a nonlinear annealing path to correct Josephson junction asymmetry, leading to an increased probability of the qubit being in the correct state. By annealing through small spectral gaps, the multi-level structure of the CSFQ circuit model was confirmed.
NPJ QUANTUM INFORMATION
(2021)
Article
Physics, Applied
Lorenzo Campos Venuti, Domenico D'Alessandro, Daniel A. Lidar
Summary: The text discusses the application of quantum computing in optimization, focusing on finding the optimal control schedule for quantum annealing (QA) and the quantum approximate optimization algorithm (QAOA). By rigorously analyzing the quantum optimal control problem within Pontryagin's maximum principle framework, the study extends previous findings to open systems and suggests that continuous schedules may be more suitable for practical quantum optimization in noisy experimental environments.
PHYSICAL REVIEW APPLIED
(2021)
Article
Quantum Science & Technology
Matthew Kowalsky, Tameem Albash, Itay Hen, Daniel A. Lidar
Summary: With the saturation of current semiconductor technology, special-purpose hardware has become an alternative solution for specific computation-intensive challenges. This research attempts to assess and compare the performance of different dedicated optimization hardware approaches using a mapping of linear equations, providing insights into their promise and limitations for a particular class of optimization problems.
QUANTUM SCIENCE AND TECHNOLOGY
(2022)
Article
Physics, Applied
Mostafa Khezri, Xi Dai, Rui Yang, Tameem Albash, Adrian Lupascu, Daniel A. Lidar
Summary: This article introduces how to use superconducting circuits to construct quantum annealing systems, and control the annealing schedule during the annealing process to improve the success probability of the annealing protocol.
PHYSICAL REVIEW APPLIED
(2022)
Article
Physics, Applied
Yuki Bando, Ka-Wa Yip, Huo Chen, Daniel A. Lidar, Hidetoshi Nishimori
Summary: This paper reports the results of reverse annealing experiments using the D-Wave 2000Q device. The study focuses on the p = 2 p-spin problem and observes a strong asymmetry in the partial success probabilities. By performing open-system simulations, it is found that the adiabatic master equation fails to agree with the experiment, while the polaron transformed Redfield equation is in close agreement.
PHYSICAL REVIEW APPLIED
(2022)
Article
Physics, Applied
Haimeng Zhang, Bibek Pokharel, E. M. Levenson-Falk, Daniel Lidar
Summary: This study utilizes a simple model called the post-Markovian master equation to accurately capture and predict non-Markovian noise in a superconducting qubit system. The model also allows for the extraction of information about crosstalk and measures of non-Markovianity.
PHYSICAL REVIEW APPLIED
(2022)
Article
Physics, Multidisciplinary
Huo Chen, Daniel A. Lidar
Summary: This article introduces an open-source software package called Hamiltonian Open Quantum System Toolkit (HOQST) for simulating the dynamics of open quantum systems in Hamiltonian quantum computing. It features key master equations suitable for describing the dynamics of a reduced system coupled to a quantum bath with an arbitrary time-dependent Hamiltonian.
COMMUNICATIONS PHYSICS
(2022)
Article
Physics, Applied
Vinay Tripathi, Huo Chen, Mostafa Khezri, Ka-Wa Yip, E. M. Levenson-Falk, Daniel A. Lidar
Summary: The current available superconducting quantum processors are noisy and prone to errors, which can be suppressed by using dynamical decoupling to suppress crosstalk. We demonstrated the success of this scheme through experiments on several IBM quantum cloud processors and achieved improvements in quantum memory and gate operations. Our work paves the way for higher-fidelity logic gates in transmon-based quantum computers.
PHYSICAL REVIEW APPLIED
(2022)
Article
Multidisciplinary Sciences
Evgeny Mozgunov, Daniel A. Lidar
Summary: We propose a new quantum adiabatic theorem to bound the adiabatic timescale for various systems, including those with originally unbounded Hamiltonian. Our bound is specifically effective for qubits in superconducting circuits and does not contain a factor of 2n in the timescale, unlike previous results. We also demonstrate the dependence of the timescale on circuit parameters and discuss a method for obtaining an effective Hamiltonian approximating the true dynamics induced by slowly changing control parameters.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2023)
Article
Physics, Multidisciplinary
Brian Barch, Razieh Mohseninia, Daniel Lidar
Summary: The VZ model of quantum computation employs controllable Z-diagonal Hamiltonians in the presence of an external X field, achieving universality in one dimension with a gate set of O(1) depth overhead; its output distribution cannot be classically simulated, offering a low-resource method of demonstrating quantum supremacy.
PHYSICAL REVIEW RESEARCH
(2021)
Review
Physics, Applied
E. J. Crosson, D. A. Lidar
Summary: Optimization, sampling, and machine learning are key topics in quantum computing. Quantum annealing (QA) is a widely used heuristic algorithm for optimization and sampling. Continued exploration and development of algorithms within the QA framework show promising routes to achieve quantum enhancement.
NATURE REVIEWS PHYSICS
(2021)
Article
Physics, Multidisciplinary
Yuki Bando, Yuki Susa, Hiroki Oshiyama, Naokazu Shibata, Masayuki Ohzeki, Fernando Javier Gomez-Ruiz, Daniel A. Lidar, Sei Suzuki, Adolfo del Campo, Hidetoshi Nishimori
PHYSICAL REVIEW RESEARCH
(2020)
