Papers
Live trends in quantum computing research, updated daily from arXiv.
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28,402
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13,525 papers in 12 months (-19% vs prior quarter)
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Qubit Platforms
Hardware platform mentions in abstracts — Photonic leads
Connecting quantum cities: simulation of a satellite-based quantum network
Raja Yehia, M. Schiavon, Valentina Marulanda Acosta +4 more·Jul 21, 2023
We present and analyze an architecture for a European-scale quantum network using satellite links to connect Quantum Cities, which are metropolitan quantum networks with minimal hardware requirements for the end users. Using NetSquid, a quantum netwo...
Adaptive Trotterization for Time-Dependent Hamiltonian Quantum Dynamics Using Piecewise Conservation Laws.
Hongzheng Zhao, M. Bukov, M. Heyl +1 more·Jul 19, 2023
Digital quantum simulation relies on Trotterization to discretize time evolution into elementary quantum gates. On current quantum processors with notable gate imperfections, there is a critical trade-off between improved accuracy for finer time step...
On quantum annealing without a physical quantum annealer
Ameya Bhave, Ajinkya Borle·Jul 19, 2023
Quantum annealing is an emerging metaheuristic used for solving combinatorial optimisation problems. However, hardware based physical quantum annealers are primarily limited to a single vendor. As an alternative, we can discretise the quantum anneali...
The effect of classical optimizers and Ansatz depth on QAOA performance in noisy devices
Aidan Pellow-Jarman, Shane McFarthing, I. Sinayskiy +3 more·Jul 19, 2023
The Quantum Approximate Optimization Algorithm (QAOA) is a variational quantum algorithm for Near-term Intermediate-Scale Quantum computers (NISQ) providing approximate solutions for combinatorial optimization problems. The QAOA utilizes a quantum-cl...
A Cryogenic Memristive Neural Decoder for Fault-tolerant Quantum Error Correction
Fr'ed'eric Marcotte, Pierre-Antoine Mouny, Victor Yon +6 more·Jul 18, 2023
Neural decoders for quantum error correction (QEC) rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to protect logical information against errors. Its ability to adapt to hard...
Data-driven reactivity prediction of targeted covalent inhibitors using computed quantum features for drug discovery
T. Montgomery, Peter Pog'any, A. Purdy +6 more·Jul 18, 2023
We present an approach to combine novel molecular features with experimental data within a data-driven pipeline. The method is applied to the challenge of predicting the reactivity of a series of sulfonyl fluoride molecular fragments used for drug di...
Quantum Tutte Embeddings
Shion Fukuzawa, M. Goodrich, S. Irani·Jul 17, 2023
Using the framework of Tutte embeddings, we begin an exploration of \emph{quantum graph drawing}, which uses quantum computers to visualize graphs. The main contributions of this paper include formulating a model for quantum graph drawing, describing...
Accelerating variational quantum Monte Carlo using the variational quantum eigensolver
A. Montanaro, Stasja Stanisic·Jul 15, 2023
Variational Monte Carlo (VMC) methods are used to sample classically from distributions corresponding to quantum states which have an efficient classical description. VMC methods are based on performing a number of steps of a Markov chain starting wi...
Comparative Study of Variations in Quantum Approximate Optimization Algorithms for the Traveling Salesman Problem
W. Qian, R. Basili, M. Eshaghian-Wilner +3 more·Jul 14, 2023
The traveling salesman problem (TSP) is one of the most often-used NP-hard problems in computer science to study the effectiveness of computing models and hardware platforms. In this regard, it is also heavily used as a vehicle to study the feasibili...
Impact of Unreliable Devices on Stability of Quantum Computations
S. Dasgupta, T. Humble·Jul 13, 2023
Noisy intermediate-scale quantum (NISQ) devices are valuable platforms for testing the tenets of quantum computing, but these devices are susceptible to errors arising from de-coherence, leakage, cross-talk, and other sources of noise. This raises co...
Spin-Flip Unitary Coupled Cluster Method: Toward Accurate Description of Strong Electron Correlation on Quantum Computers.
Fabijan Pavošević, I. Tavernelli, A. Rubio·Jul 13, 2023
Quantum computers have emerged as a promising platform to simulate strong electron correlation that is crucial to catalysis and photochemistry. However, owing to the choice of a trial wave function employed in the variational quantum eigensolver (VQE...
Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning
Francesco Preti, Michael Schilling, S. Jerbi +4 more·Jul 12, 2023
Shortening quantum circuits is crucial to reducing the destructive effect of environmental decoherence and enabling useful algorithms. Here, we demonstrate an improvement in such compilation tasks via a combination of using hybrid discrete-continuous...
From Vlasov-Poisson to Schrödinger-Poisson: Dark matter simulation with a quantum variational time evolution algorithm
Luca Cappelli, F. Tacchino, G. Murante +2 more·Jul 12, 2023
Cosmological simulations describing the evolution of density perturbations of a self-gravitating collisionless Dark Matter (DM) fluid in an expanding background, provide a powerful tool to follow the formation of cosmic structures over wide dynamic r...
Faster-than-Clifford simulations of entanglement purification circuits and their full-stack optimization
Vaishnavi L. Addala, Shu Ge, Stefan Krastanov·Jul 12, 2023
Generating quantum entanglement is plagued by decoherence. Distillation and error-correction are employed against such noise, but designing a good distillation circuit, especially on today’s imperfect hardware, is challenging. We develop a simulation...
GRAPE optimization for open quantum systems with time-dependent decoherence rates driven by coherent and incoherent controls
V. Petruhanov, A. Pechen·Jul 11, 2023
The GRadient Ascent Pulse Engineering (GRAPE) method is widely used for optimization in quantum control. GRAPE is gradient search method based on exact expressions for gradient of the control objective. It has been applied to various coherently contr...
Towards quantum-enabled cell-centric therapeutics
S. Basu, Jannis Born, Aritra Bose +28 more·Jul 11, 2023
In recent years, there has been tremendous progress in the development of quantum computing hardware, algorithms and services leading to the expectation that in the near future quantum computers will be capable of performing simulations for natural s...
Precise image generation on current noisy quantum computing devices
F. Rehm, S. Vallecorsa, K. Borras +3 more·Jul 11, 2023
The quantum angle generator (QAG) is a new full quantum machine learning model designed to generate accurate images on current noise intermediate scale quantum devices. Variational quantum circuits form the core of the QAG model, and various circuit ...
Reliable Devices Yield Stable Quantum Computations
S. Dasgupta, T. Humble·Jul 10, 2023
Stable quantum computation requires noisy results to remain bounded even in the presence of noise fluctuations. Yet non-stationary noise processes lead to drift in the varying characteristics of a quantum device that can greatly influence the circuit...
Phase transitions in sampling and error correction in local Brownian circuits
S. Sahu, Shao-Kai Jian·Jul 9, 2023
We study the emergence of anticoncentration and approximate unitary design behavior in local Brownian circuits. The dynamics of circuit averaged moments of the probability distribution and entropies of the output state can be represented as imaginary...
Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization
Dheeraj Peddireddy, Utkarsh Priyam, V. Aggarwal·Jul 8, 2023
Variational Quantum algorithms, especially Quantum Approximate Optimization and Variational Quantum Eigensolver (VQE) have established their potential to provide computational advantage in the realm of combinatorial optimization. However, these algor...