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Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Storage properties of a quantum perceptron.
Katerina Gratsea, V. Kasper, M. Lewenstein·Nov 16, 2021
Driven by growing computational power and algorithmic developments, machine learning methods have become valuable tools for analyzing vast amounts of data. Simultaneously, the fast technological progress of quantum information processing suggests emp...
Dissipative entanglement generation between two driven qubits in circuit quantum electrodynamics
Sebasti'an Luciano Gallardo, D. Domínguez, M. J. S'anchez·Nov 16, 2021
An entangled state generation protocol for a system of two qubits driven with an ac signal and coupled through a resonator is introduced. We explain the mechanism of entanglement generation in terms of an interplay between unitary Landau-Zener-Stücke...
Crystalline Formations of NbN/4H-SiC Heterostructure Interfaces
M. Katz, Chieh-I. Liu, A. Rigosi +4 more·Nov 16, 2021
Given the importance of incorporating various superconducting materials to device fabrication or substrate development, studying the interface for possible interactions is warranted. In this work, NbN films sputter-deposited on 4H-SiC were heat-treat...
A Projection Operator-based Newton Method for the Trajectory Optimization of Closed Quantum Systems
Jieqiu Shao, J. Combes, J. Hauser +1 more·Nov 16, 2021
Quantum optimal control is an important technology that enables fast state preparation and gate design. In the absence of an analytic solution, most quantum optimal control methods rely on an iterative scheme to update the solution estimate. At prese...
Circular Rosenzweig-Porter random matrix ensemble
Wouter Buijsman, Yevgeny Bar Lev·Nov 15, 2021
The Rosenzweig-Porter random matrix ensemble serves as a qualitative phenomenological model for the level statistics and fractality of eigenstates across the many-body localization transition in static systems. We propose a unitary (circular) analogu...
Stochastic gradient line Bayesian optimization for efficient noise-robust optimization of parameterized quantum circuits
Shiro Tamiya, H. Yamasaki·Nov 15, 2021
Optimizing parameterized quantum circuits is a key routine in using near-term quantum devices. However, the existing algorithms for such optimization require an excessive number of quantum-measurement shots for estimating expectation values of observ...
Quantum approximation algorithms for many-body and electronic structure problems
Karen J. Morenz Korol, Kenny Choo, Antonio Mezzacapo·Nov 15, 2021
Computing many-body ground state energies and resolving electronic structure calculations are fundamental problems for fields such as quantum chemistry or condensed matter. Several quantum computing algorithms that address these problems exist, althou...
Fidelity-Guaranteed Entanglement Routing in Quantum Networks
Jian Li, Ming-jian Wang, Kaiping Xue +4 more·Nov 15, 2021
Entanglement routing establishes remote entanglement connection between two arbitrary nodes, which is one of the most important functions in quantum networks. The existing routing mechanisms mainly improve the robustness and throughput facing the fai...
Measurement-induced entanglement phase transitions in variational quantum circuits
R. Wiersema, Cunlu Zhou, J. Carrasquilla +1 more·Nov 15, 2021
Variational quantum algorithms (VQAs), which classically optimize a parametrized quantum circuit to solve a computational task, promise to advance our understanding of quantum many-body systems and improve machine learning algorithms using near-term ...
Experimental self-testing for photonic graph states.
Jia-Min Xu, Qing Zhou, Yuxiang Yang +5 more·Nov 15, 2021
Graph states-one of the most representative families of multipartite entangled states-are important resources for multiparty quantum communication, quantum error correction, and quantum computation. Device-independent certification of highly entangle...
Quantum algorithms for approximate function loading
Gabriel Marin-Sanchez, Javier Gonzalez-Conde, M. Sanz·Nov 15, 2021
Loading classical data into quantum computers represents an essential stage in many relevant quantum algorithms, especially in the field of quantum machine learning. Therefore, the inefficiency of this loading process means a major bottleneck for the...
Robust Preparation of Wigner-Negative States with Optimized SNAP-Displacement Sequences
M. Kudra, Mikael Kervinen, Ingrid Strandberg +10 more·Nov 15, 2021
Hosting non-classical states of light in three-dimensional microwave cavities has emerged as a promising paradigm for continuous-variable quantum information processing. Here we experimentally demonstrate high-fidelity generation of a range of Wigner...
Scalable Variational Quantum Circuits for Autoencoder-based Drug Discovery
Junde Li, Swaroop Ghosh·Nov 15, 2021
The de novo design of drug molecules is recognized as a time-consuming and costly process, and computational approaches have been applied in each stage of the drug discovery pipeline. Variational autoencoder is one of the computer-aided design method...
Simulation of Quantum Many-Body Dynamics with Tensor Processing Units: Floquet Prethermalization
A. Morningstar, M. Hauru, J. Beall +4 more·Nov 15, 2021
Tensor Processing Units (TPUs) are specialized hardware accelerators developed by Google to support large-scale machine-learning tasks, but they can also be leveraged to accelerate and scale other linear-algebra-intensive computations. In this paper ...
Quantum homotopy perturbation method for nonlinear dissipative ordinary differential equations
Cheng Xue, Yuchun Wu, G. Guo·Nov 15, 2021
While quantum computing provides an exponential advantage in solving linear differential equations, there are relatively few quantum algorithms for solving nonlinear differential equations. In our work, based on the homotopy perturbation method, we p...
Leveraging Quantum Annealer to identify an Event-topology at High Energy Colliders
Minho Kim, P. Ko, Jae-hyeon Park +1 more·Nov 15, 2021
With increasing energy and luminosity available at the Large Hadron collider (LHC), we get a chance to take a pure bottom-up approach solely based on data. This will extend the scope of our understanding about Nature without relying on theoretical pr...
Quantum Phase Recognition via Quantum Kernel Methods
Yusen Wu, Bujiao Wu, Jingbo B. Wang +1 more·Nov 15, 2021
The application of quantum computation to accelerate machine learning algorithms is one of the most promising areas of research in quantum algorithms. In this paper, we explore the power of quantum learning algorithms in solving an important class of...
Muzzle the Shuttle: Efficient Compilation for Multi-Trap Trapped-Ion Quantum Computers
Abdullah Ash-Saki, R. Topaloglu, Swaroop Ghosh·Nov 15, 2021
Trapped-ion systems can have a limited number of ions (qubits) in a single trap. Increasing the qubit count to run meaningful quantum algorithms would require multiple traps where ions need to shuttle between traps to communicate. The existing compil...
Formal Quantum Software Engineering. Introducing the Formal Methods of Software Engineering to Quantum Computing
Carmelo R. Cartiere·Nov 14, 2021
Quantum computing (QC) represents the future of computing systems, but the tools for reasoning about the quantum model of computation, in which the laws obeyed are those on the quantum mechanical scale, are still a mix of linear algebra and Dirac not...
Collectively pair-driven-dissipative bosonic arrays: exotic and self-oscillatory condensates
Yinan Chen, C. Navarrete-Benlloch·Nov 14, 2021
Modern quantum platforms such as superconducting circuits provide exciting opportunities for the experimental exploration of driven-dissipative many-body systems in unconventional regimes. One of such regimes occurs in bosonic systems, where nowadays...