Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Digital quantum simulation of an extended Agassi model: Using machine learning to disentangle its phase-diagram
Álvaro Sáiz, J. García-Ramos, J. M. Arias +2 more·May 30, 2022
A digital quantum simulation for the extended Agassi model is proposed using a quantum platform with eight trapped ions. The extended Agassi model is an analytically solvable model including both short range pairing and long range monopole-monopole i...
Running the Dual-PQC GAN on noisy simulators and real quantum hardware
Su Yeon Chang, Edwin Agnew, E. Combarro +3 more·May 30, 2022
In an earlier work [1], we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of quantum GAN. We applied the model on a realistic High-Energy Physics (HEP) use case: the exact theoretical ...
Mid-Circuit Cavity Measurement in a Neutral Atom Array.
Emma Deist, Yue-Hui Lu, Jacquelyn Ho +4 more·May 27, 2022
Subsystem readout during a quantum process, or mid-circuit measurement, is crucial for error correction in quantum computation, simulation, and metrology. Ideal mid-circuit measurement should be faster than the decoherence of the system, high-fidelit...
Quantum error mitigation via quantum-noise-effect circuit groups
Y. Hama, Hirofumi Nishi·May 27, 2022
Near-term quantum computers have been built as intermediate-scale quantum devices and are fragile against quantum noise effects, namely, NISQ devices. Traditional quantum-error-correcting codes are not implemented on such devices and to perform quant...
Simulating groundstate and dynamical quantum phase transitions on a superconducting quantum computer
J. Dborin, V. Wimalaweera, F. Barratt +3 more·May 25, 2022
The phenomena of quantum criticality underlie many novel collective phenomena found in condensed matter systems. They present a challenge for classical and quantum simulation, in part because of diverging correlation lengths and consequently strong f...
Simulation Complexity of Many-Body Localized Systems
Adam Ehrenberg, A. Deshpande, C. Baldwin +2 more·May 25, 2022
We use complexity theory to rigorously investigate the difficulty of classically simulating evolution under many-body localized (MBL) Hamiltonians. Using the defining feature that MBL systems have a complete set of quasilocal integrals of motion (LIO...
Classically optimized Hamiltonian simulation
Conor Mc Keever, M. Lubasch·May 23, 2022
Hamiltonian simulation is a promising application for quantum computers to achieve a quantum advantage. We present classical algorithms based on tensor network methods to optimize quantum circuits for this task. We show that, compared to Trotter prod...
Quantum variational learning for entanglement witnessing
Francesco Scala, Stefano Mangini, C. Macchiavello +2 more·May 20, 2022
Several proposals have been recently introduced to implement Quantum Machine Learning (QML) algorithms for the analysis of classical data sets employing variational learning means. There has been, however, a limited amount of work on the characteriza...
NISQ algorithm for the matrix elements of a generic observable
Rebecca Erbanni, Kishor Bharti, L. Kwek +1 more·May 20, 2022
The calculation of off-diagonal matrix elements has various applications in fields such as nuclear physics and quantum chemistry. In this paper, we present a noisy intermediate scale quantum algorithm for estimating the diagonal and off-diagonal matr...
TensorCircuit: a Quantum Software Framework for the NISQ Era
Shi-Xin Zhang, J. Allcock, Z. Wan +13 more·May 20, 2022
TensorCircuit is an open source quantum circuit simulator based on tensor network contraction, designed for speed, flexibility and code efficiency. Written purely in Python, and built on top of industry-standard machine learning frameworks, TensorCir...
Nonadiabatic Holonomic Quantum Computation via Path Optimization
Lingtong Ji, Yan Liang, P. Shen +1 more·May 19, 2022
Nonadiabatic holonomic quantum computation (NHQC) is implemented by fast evolution processes in a geometric way to withstand local noises. However, recent works of implementing NHQC are sensitive to the systematic noise and error. Here, we present a ...
Low-rank tensor decompositions of quantum circuits
Patrick Gelß, Stefan Klus, Sebastian Knebel +2 more·May 19, 2022
Quantum computing is arguably one of the most revolutionary and disrup-tive technologies of this century. Due to the ever-increasing number of potential applications as well as the continuing rise in complexity, the development, simulation, optimizat...
Estimating the randomness of quantum circuit ensembles up to 50 qubits
Minzhao Liu, Junyu Liu, Y. Alexeev +1 more·May 19, 2022
Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information. The ability of random circuits to approximate any random uni...
Exponential challenges in unbiasing quantum Monte Carlo algorithms with quantum computers
G. Mazzola, Giuseppe Carleo·May 18, 2022
Recently, Huggins et. al. [Nature, 603, 416-420 (2022)] devised a general projective Quantum Monte Carlo method suitable for implementation on quantum computers. This hybrid approach, however, relies on a subroutine -the computation of the local ener...
Quantum neural networks
Kerstin Beer·May 17, 2022
This PhD thesis combines two of the most exciting research areas of the last decades: quantum computing and machine learning. We introduce dissipative quantum neural networks (DQNNs), which are designed for fully quantum learning tasks, are capable o...
Evolution strategies: application in hybrid quantum-classical neural networks
Lucas Friedrich, J. Maziero·May 17, 2022
With the rapid development of quantum computers, several applications are being proposed for them. Quantum simulations, simulation of chemical reactions, solution of optimization problems and quantum neural networks (QNNs) are some examples. However,...
Conditional Born machine for Monte Carlo events generation
Oriel Kiss, M. Grossi, E. Kajomovitz +1 more·May 16, 2022
Generative modeling is a promising task for near-term quantum devices, which can use the stochastic nature of quantum measurements as a random source. So called Born machines are purely quantum models and promise to generate probability distributions...
Multi-state Swap Test Algorithm
Wen Liu, Han-Wen Yin, Zhirao Wang +1 more·May 15, 2022
. Estimating the overlap between two states is an important task with several applications in quantum information. However, the typical swap test circuit can only measure a sole pair of quantum states at a time. In this study we designed a recursive ...
Efficient Hierarchical State Vector Simulation of Quantum Circuits via Acyclic Graph Partitioning
B. Fang, M. Özkaya, A. Li +2 more·May 14, 2022
Early but promising results in quantum computing have been enabled by the concurrent development of quan-tum algorithms, devices, and materials. Classical simulation of quantum programs has enabled the design and analysis of algorithms and implementa...
Forward-backward stochastic simulations: Q-based model for measurement and Bell-nonlocality consistent with weak local realistic premises
M D Reid, P D Drummond·May 12, 2022
We show how measurement and nonlocality can be explained consistently with macroscopic realism and no-signaling, and causal relations for macroscopic quantities. Considering measurement of a field amplitude $\hat{x}$, we derive theorems that lead to ...