Papers
Live trends in quantum computing research, updated daily from arXiv.
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Optimal two-qubit gates in recurrence protocols of entanglement purification
Francesco Preti, T. Calarco, J. M. Torres +1 more·May 24, 2022
We propose and investigate a method to optimize recurrence entanglement purification protocols. The approach is based on a numerical search in the whole set of SU(4) matrices with the aid of a quasi-Newton algorithm. Our method evaluates average conc...
Proposal for low-power atom trapping on a GaN-on-sapphire chip
Aiping Liu, Lei Xu, Xin-Biao Xu +6 more·May 24, 2022
The hybrid photon-atom integrated circuits, which include photonic microcavities and trapped single neutral atom in their evanescent field, are of great potential for quantum information processing. In this platform, the atoms provide the single-photo...
Scalable semi-classical implementation of Shor factoring using time-multiplexed degenerate optical parametric oscillators
Ming-hai Li, Wei Wang, Zikang Tang +1 more·May 24, 2022
A scheme to encode arbitrarily long integer pairs on degenerate optical parametric oscilla-tions multiplexed in time is proposed. The classical entanglement between the polarization directions and the phases of the oscillating pulses, regarded as two...
Is quantum computing green? An estimate for an energy-efficiency quantum advantage
Daniel Jaschke, S. Montangero·May 24, 2022
The quantum advantage threshold determines when a quantum processing unit (QPU) is more efficient with respect to classical computing hardware in terms of algorithmic complexity. The ‘green’ quantum advantage threshold—based on a comparison of energe...
QCSH: A full quantum computer nuclear shell-model package
Peng-Li Lv, Shijie Wei, Hao-Nan Xie +1 more·May 24, 2022
The nuclear system is a promising area for demonstrating practical quantum advantage. A comprehensive computation of a nuclear system in a classical computer is beyond the capacity of current classical computers. With the rapid development of hardwar...
How Much Entanglement Do Quantum Optimization Algorithms Require?
Yanzhu Chen, Linghua Zhu, Chenxu Liu +3 more·May 24, 2022
ADAPT-QAOA, a novel problem-tailored version of quantum approximate optimization algorithm, speeds up convergence using entangling operators while reducing the total number of CNOTs. We explore how much entanglement is required to speed up optimizati...
QPack Scores: Quantitative performance metrics for application-oriented quantum computer benchmarking
Huub Donkers, Koen J. Mesman, Z. Al-Ars +1 more·May 24, 2022
This paper presents the benchmark score definitions of QPack, an application-oriented cross-platform benchmarking suite for quantum computers and simulators, which makes use of scalable Quantum Approximate Optimization Algorithm and Variational Quant...
Watermarking PRFs against Quantum Adversaries
Fuyuki Kitagawa, R. Nishimaki·May 23, 2022
We initiate the study of software watermarking against quantum adversaries. A quantum adversary generates a quantum state as a pirate software that potentially removes an embedded message from a classical marked software. Extracting an embedded messa...
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...
Overfitting in quantum machine learning and entangling dropout
Masahiro Kobayashi, Kouhei Nakaji, N. Yamamoto·May 23, 2022
The ultimate goal in machine learning is to construct a model function that has a generalization capability for unseen dataset, based on given training dataset. If the model function has too much expressibility power, then it may overfit to the train...
Classification of four-qubit entangled states via machine learning
S. Vintskevich, N. Bao, A. Nomerotski +2 more·May 21, 2022
We apply the support vector machine (SVM) algorithm to derive a set of entanglement witnesses (EW) to identify entanglement patterns in families of four-qubit states. The effectiveness of SVM for practical EW implementations stems from the coarse-gra...
Cryptanalysis of three quantum money schemes
Andriyan Bilyk, Javad Doliskani, Zhiyong Gong·May 21, 2022
We investigate the security assumptions behind three public-key quantum money schemes. Aaronson and Christiano proposed a scheme based on hidden subspaces of the vector space $$\mathbb {F}_2^n$$ F 2 n in 2012. It was conjectured by Pena et al. (IACR ...
A Quantum-compute Algorithm for Exact Laser-driven Electron Dynamics in Molecules
Fabian Langkabel, A. Bande·May 21, 2022
In this work, we investigate the capability of known quantum-computing algorithms for fault-tolerant quantum computing to simulate the laser-driven electron dynamics in small molecules such as lithium hydride. These computations are executed on a qua...
Squeezing and quantum approximate optimization
Gopal Chandra Santra, F. Jendrzejewski, P. Hauke +1 more·May 20, 2022
Variational quantum algorithms offer fascinating prospects for the solution of combinatorial optimization problems using digital quantum computers. However, the achievable performance in such algorithms and the role of quantum correlations therein re...
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...
Degeneracy engineering for classical and quantum annealing: A case study of sparse linear regression in collider physics
E. Anschuetz, Lena Funcke, Patrick T. Komiske +2 more·May 20, 2022
Classical and quantum annealing are computing paradigms that have been proposed to solve a wide range of optimization problems. In this paper, we aim to enhance the performance of annealing algorithms by introducing the technique of degeneracy engine...
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...
Tower: data structures in Quantum superposition
Charles Yuan, Michael Carbin·May 20, 2022
Emerging quantum algorithms for problems such as element distinctness, subset sum, and closest pair demonstrate computational advantages by relying on abstract data structures. Practically realizing such an algorithm as a program for a quantum comput...
Optimal quantum reservoir computing for the NISQ era
L. Domingo, G. Carlo, F. Borondo·May 20, 2022
Universal fault-tolerant quantum computers require millions of qubits with low error rates. Since this technology is years ahead, noisy intermediate-scale quantum (NISQ) computation is receiving tremendous interest. In this setup, quantum reservoir c...