Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Decomposition of matrix product states into shallow quantum circuits
Manuel S. Rudolph, Jing Chen, J. Miller +2 more·Sep 1, 2022
Tensor networks (TNs) are a family of computational methods built on graph-structured factorizations of large tensors, which have long represented state-of-the-art methods for the approximate simulation of complex quantum systems on classical compute...
Quantum circuit simulation of linear optics using fermion to qubit encoding
Seungbeom Chin, Jaehee Kim, Joonsuk Huh·Sep 1, 2022
This work proposes a digital quantum simulation protocol for the linear scattering process of bosons, which provides a simple extension to partially distinguishable boson cases. Our protocol is achieved by combining the boson-fermion correspondence r...
Simulation of Entanglement Generation between Absorptive Quantum Memories
A. Zang, Alexander Kolar, Joaquín Chung +3 more·Sep 1, 2022
Quantum entanglement is an essential resource for quantum networks. However, the generation of entanglement between physical devices at remote network nodes is a challenging task towards practical implementation of quantum networks. In this work, we ...
X-parameter based design and simulation of Josephson traveling-wave parametric amplifiers for quantum computing applications
Kaidong Peng, R. Poore, P. Krantz +2 more·Sep 1, 2022
We present an efficient, accurate, and comprehensive analysis framework for generic, multi-port nonlinear parametric circuits, in the presence of dissipation from lossy circuit components, based on "quantum-adapted" X-parameters. We apply this method...
Divide-and-conquer variational quantum algorithms for large-scale electronic structure simulations
Huanhuan Ma, Yi Fan, Jie Liu +3 more·Aug 31, 2022
Exploring the potential application of quantum computers in material design and drug discovery has attracted a lot of interest in the age of quantum computing. However, the quantum resource re-quirement for solving practical electronic structure prob...
Advance quantum image representation and compression using DCTEFRQI approach
Md. Ershadul Haque, Manoranjon Paul, A. Ulhaq +1 more·Aug 30, 2022
In recent year, quantum image processing got a lot of attention in the field of image processing due to opportunity to place huge image data in quantum Hilbert space. Hilbert space or Euclidean space has infinite dimension to locate and process the i...
Measurement optimization of variational quantum simulation by classical shadow and derandomization
Kouhei Nakaji, Suguru Endo, Y. Matsuzaki +1 more·Aug 30, 2022
Simulating large quantum systems is the ultimate goal of quantum computing. Variational quantum simulation (VQS) gives us a tool to achieve the goal in near-term devices by distributing the computation load to both classical and quantum computers. Ho...
Improving the Accuracy of Variational Quantum Eigensolvers with Fewer Qubits Using Orbital Optimization.
Joel Bierman, Yingzhou Li, Jianfeng Lu·Aug 30, 2022
Near-term quantum computers will be limited in the number of qubits on which they can process information as well as the depth of the circuits that they can coherently carry out. To date, experimental demonstrations of algorithms such as the Variatio...
Loading Probability Distributions in a Quantum circuit
K. Dasgupta, Binoy Paine·Aug 29, 2022
Quantum circuits generating probability distributions has applications in several areas. Areas like finance require quantum circuits that can generate distributions that mimic some given data pattern. Hamiltonian simulations require circuits that can ...
Synergistic pretraining of parametrized quantum circuits via tensor networks
Manuel S. Rudolph, J. Miller, Danial Motlagh +3 more·Aug 29, 2022
Parametrized quantum circuits (PQCs) represent a promising framework for using present-day quantum hardware to solve diverse problems in materials science, quantum chemistry, and machine learning. We introduce a “synergistic” approach that addresses ...
Towards Quantum Computing Phase Diagrams of Gauge Theories with Thermal Pure Quantum States.
Z. Davoudi, N. Mueller, Connor Powers·Aug 28, 2022
The phase diagram of strong interactions in nature at finite temperature and chemical potential remains largely theoretically unexplored due to inadequacy of Monte-Carlo-based computational techniques in overcoming a sign problem. Quantum computing o...
Large-scale full-programmable quantum walk and its applications
Yizhi Wang, Yingwen Liu, Junwei Zhan +22 more·Aug 28, 2022
With photonics, the quantum computational advantage has been demonstrated on the task of boson sampling. Next, developing quantum-enhanced approaches for practical problems becomes one of the top priorities for photonic systems. Quantum walks are pow...
Singly-excited resonant open quantum system Tavis-Cummings model with quantum circuit mapping
M. K. Marinković, Marina Radulaski·Aug 25, 2022
Tavis-Cummings (TC) cavity quantum electrodynamical effects, describing the interaction of N atoms with an optical resonator, are at the core of atomic, optical and solid state physics. The full numerical simulation of TC dynamics scales exponentiall...
Noise tailoring for robust amplitude estimation
Archismita Dalal, Amara Katabarwa·Aug 24, 2022
A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the next decade or so, our access is restricted to noisy intermediate-scale quantum (...
Q2Chemistry: A quantum computation platform for quantum chemistry
Yi Fan, Jie Liu, Xiongzhi Zeng +4 more·Aug 23, 2022
Quantum computers provide new opportunities for quantum chemistry. In this article,we present a versatile, extensible, and efficient software package, named Q2Chemistry, for developing quantum algorithms and quantum inspired classical algorithms in t...
Exponential concentration in quantum kernel methods
Supanut Thanasilp, Samson Wang, M. Cerezo +1 more·Aug 23, 2022
Kernel methods in Quantum Machine Learning (QML) have recently gained significant attention as a potential candidate for achieving a quantum advantage in data analysis. Among other attractive properties, when training a kernel-based model one is guar...
Solvable model of deep thermalization with distinct design times
Matteo Ippoliti, W. Ho·Aug 22, 2022
We study the emergence over time of a universal, uniform distribution of quantum states supported on a finite subsystem, induced by projectively measuring the rest of the system. Dubbed deep thermalization, this phenomenon represents a form of equili...
Hamiltonian simulation of quantum beats in radical pairs undergoing thermal relaxation on near-term quantum computers.
Meltem Tolunay, I. Liepuoniute, M. Vyushkova +1 more·Aug 22, 2022
Quantum dynamics of the radical pair mechanism is a major driving force in quantum biology, materials science, and spin chemistry. The rich quantum physical underpinnings of the mechanism are determined by a coherent oscillation (quantum beats) betwe...
Revisiting semiconductor bulk hamiltonians using quantum computers
Raphael César de Souza Pimenta, A. T. Bezerra·Aug 22, 2022
With the advent of near-term quantum computers, it is now possible to simulate solid-state properties using quantum algorithms. By an adequate description of the system's Hamiltonian, variational methods enable to fetch of the band structure and othe...
Quantum Multi-Agent Meta Reinforcement Learning
Won Joon Yun, Jihong Park, Joongheon Kim·Aug 22, 2022
Although quantum supremacy is yet to come, there has recently been an increasing interest in identifying the potential of quantum machine learning (QML) in the looming era of practical quantum computing. Motivated by this, in this article we re-desig...