Papers
Live trends in quantum computing research, updated daily from arXiv.
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Hardware platform mentions in abstracts — Photonic leads
Bright semiconductor single-photon sources pumped by heterogeneously integrated micropillar lasers with electrical injections
Xueshi Li, Shunfa Liu, Yuming Wei +11 more·Feb 3, 2023
The emerging hybrid integrated quantum photonics combines the advantages of different functional components into a single chip to meet the stringent requirements for quantum information processing. Despite the tremendous progress in hybrid integratio...
Designing a Hybrid Digital / Analog Quantum Physics Emulator as Open Hardware
Marcus Edwards·Feb 2, 2023
One of the most exciting quantum emulation [1] breakthroughs was the first analog signal-based emulation of a universal quantum computer [2]. This yielded a very interesting paper, but no practical use - even for theorists. The reason for this was th...
Studying phonon coherence with a quantum sensor
A. Cleland, E. Alex Wollack, A. Safavi-Naeini·Feb 1, 2023
Nanomechanical oscillators offer numerous advantages for quantum technologies. Their integration with superconducting qubits shows promise for hardware-efficient quantum error-correction protocols involving superpositions of mechanical coherent state...
Variational Amplitude Amplification for Solving QUBO Problems
Daniel Koch, Massimiliano Cutugno, Saahil Patel +2 more·Jan 31, 2023
We investigate the use of amplitude amplification on the gate-based model of quantum computing as a means for solving combinatorial optimization problems. This study focuses primarily on quadratic unconstrained binary optimization (QUBO) problems, wh...
Implementing a Hybrid Quantum-Classical Neural Network by Utilizing a Variational Quantum Circuit for Detection of Dementia
R. Kim·Jan 29, 2023
Magnetic resonance imaging (MRI) is a common technique to scan brains for strokes, tumors, and other abnormalities that cause forms of dementia. However, correctly diagnosing forms of dementia from MRIs is difficult, as nearly 1 in 3 patients with Al...
Digitized-counterdiabatic quantum factorization
N. N. Hegade, E. Solano·Jan 26, 2023
We factorize a 48-bit integer using 10 trapped-ion qubits on a Quantinuum’s quantum computer. This result outperforms the recent achievement by B. Yan et al., arXiv:2212.12372 (2022), increasing the success probability by a factor of 6 with a non-hyb...
Overlap-ADAPT-VQE: practical quantum chemistry on quantum computers via overlap-guided compact Ansätze
C'esar Feniou, M. Hassan, Diata Traor'e +3 more·Jan 24, 2023
ADAPT-VQE is a robust algorithm for hybrid quantum-classical simulations of quantum chemical systems on near-term quantum computers. While its iterative process systematically reaches the ground state energy, practical implementations of ADAPT-VQE ar...
Scalable Quantum Error Correction for Surface Codes Using FPGA
Namitha Liyanage, Yue Wu, Alexander Dennisovich Deters +1 more·Jan 20, 2023
A fault-tolerant quantum computer must decode and correct errors faster than they appear. The faster errors can be corrected, the more time the computer can do useful work. The Union-Find (UF) decoder is promising with an average time complexity slig...
Solving various NP-hard problems using exponentially fewer qubits on a quantum computer
Yagnik Chatterjee, E. Bourreau, Marko J. Ranvci'c·Jan 17, 2023
NP-hard problems are not believed to be exactly solvable through general polynomial time algorithms. Hybrid quantum-classical algorithms to address such combinatorial problems have been of great interest in the past few years. Such algorithms are heu...
Hybrid quantum-classical convolutional neural networks to improve molecular protein binding affinity predictions
L. Domingo, M. Djukic, C. Johnson +1 more·Jan 16, 2023
One of the main challenges in drug discovery is to find molecules that bind specifically and strongly to their target protein while having minimal binding to other proteins. By predicting binding affinity, it is possible to identify the most promisin...
Quantum simulations in effective model spaces: Hamiltonian-learning variational quantum eigensolver using digital quantum computers and application to the Lipkin-Meshkov-Glick model
C. Robin, M. Savage·Jan 14, 2023
The utility of effective model spaces in quantum simulations of non-relativistic quantum many-body systems is explored in the context of the Lipkin-Meshkov-Glick model of interacting fermions. We introduce an iterative hybrid-classical-quantum algori...
TeD-Q: a tensor network enhanced distributed hybrid quantum machine learning framework
Yaocheng Chen, C. Kuo, Yuxuan Du +2 more·Jan 13, 2023
TeD-Q is an open-source software framework for quantum machine learning, variational quantum algorithm (VQA), and simulation of quantum computing. It seamlessly integrates classical machine learning libraries with quantum simulators, giving users the...
SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced Training
Philipp Altmann, Leo Sünkel, Jonas Stein +3 more·Jan 6, 2023
Applying new computing paradigms like quantum computing to the field of machine learning has recently gained attention. However, as high-dimensional real-world applications are not yet feasible to be solved using purely quantum hardware, hybrid metho...
Quantum Machine Learning Applied to the Classification of Diabetes
Juan Kenyhy Hancco-Quispe, Jordan Piero Borda-Colque, Fred Torres-Cruz·Dec 31, 2022
Quantum Machine Learning (QML) shows how it maintains certain significant advantages over machine learning methods. It now shows that hybrid quantum methods have great scope for deployment and optimisation, and hold promise for future industries. As ...
FIPS Compliant Quantum Secure Communication Using Quantum Permutation Pad
Alex He, Dafu Lou, Eric She +5 more·Dec 30, 2022
Quantum computing has entered a fast development track since Shor's algorithm was proposed in 1994. Multi-cloud services of quantum computing farms are currently available. One of which, IBM quantum computing, presented a road map showing their Kooka...
Reduced basis emulation of pairing in finite systems
V. Baran, D. Nichita·Dec 29, 2022
In recent years, reduced basis methods (RBMs) have been adapted to the many-body eigenvalue problem and they have been used, largely in nuclear physics, as fast emulators able to bypass expensive direct computations while still providing highly accur...
Hybrid quantum-gap-estimation algorithm using a filtered time series
Woojun Lee, Ryan Scott, V. Scarola·Dec 28, 2022
Quantum simulation advantage over classical memory limitations would allow compact quantum circuits to yield insight into intractable quantum many-body problems, but the interrelated obstacles of large circuit depth in quantum time evolution and nois...
Digitized Counterdiabatic Quantum Algorithm for Protein Folding
P. Chandarana, N. N. Hegade, I. Montalban +2 more·Dec 27, 2022
We propose a hybrid classical-quantum digitized-counterdiabatic algorithm to tackle the protein folding problem on a tetrahedral lattice. Digitized-counterdiabatic quantum computing is a paradigm developed to compress quantum algorithms via the digit...
An introduction to variational quantum algorithms for combinatorial optimization problems
Camille Grange, M. Poss, E. Bourreau·Dec 22, 2022
Noisy intermediate-scale quantum computers (NISQ computers) are now readily available, motivating many researchers to experiment with Variational Quantum Algorithms (VQAs). Among them, the Quantum Approximate Optimization Algorithm (QAOA) is one of t...
Recommending Solution Paths for Solving Optimization Problems with Quantum Computing
Benedikt Poggel, Nils Quetschlich, Lukas Burgholzer +2 more·Dec 21, 2022
Solving real-world optimization problems with quantum computing requires choosing between a large number of options concerning formulation, encoding, algorithm and hardware. Finding good solution paths is challenging for end users and researchers ali...