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Hybrid Quantum algorithm to classify Hermitian matrix definiteness

We present a hybrid algorithm that accomplishes the classification of a
Hermitian matrix according to its signature into three classes (positive
semi-definite, negative or indefinite). The algorithm i

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Quantum-Classical Hybrid Algorithm for the Simulation of All-Electron Correlation

While the treatment of chemically relevant systems containing hundreds or
even thousands of electrons remains beyond the reach of quantum devices, the
development of quantum-classical hybrid algorithm

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Optimising Stochastic Routing for Taxi Fleets with Model Enhanced Reinforcement Learning

The future of mobility-as-a-Service (Maas)should embrace an integrated system
of ride-hailing, street-hailing and ride-sharing with optimised intelligent
vehicle routing in response to a real-time, st

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Deep Learning-based Hybrid Graph-Coloring Algorithm for Register Allocation

Register allocation, which is a crucial phase of a good optimizing compiler,
relies on graph coloring. Hence, an efficient graph coloring algorithm is of
paramount importance. In this work we try to l

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Dynamical Self-energy Mapping (DSEM) for quantum computing

For noisy intermediate-scale quantum (NISQ) devices only a moderate number of
qubits with a limited coherence is available thus enabling only shallow
circuits and a few time evolution steps in the cur

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Improving probability selecting based weights for Satisfiability Problem

The Boolean Satisfiability problem (SAT) is important on artificial intelligence community and the impact of its solving on complex problems. Recently, great breakthroughs have been made respectively

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Hybrid Gradient Descent and Linear Programming for Deep Neural Networks

A Solver + Gradient Descent Training Algorithm for Deep Neural Networks

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A Machine Learning Approach to Boosting Computational Efficiency in Quantum Control Algorithms

Recommender System Expedited Quantum Control Optimization

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NeuroHSMD: Neuromorphic Hybrid Spiking Motion Detector

Vertebrate retinas are highly-efficient in processing trivial visual tasks
such as detecting moving objects, yet a complex task for modern computers. The
detection of object motion is done by speciali

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HybridSVD: When Collaborative Information is Not Enough

We propose a new hybrid algorithm that allows incorporating both user and
item side information within the standard collaborative filtering technique.
One of its key features is that it naturally exte

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Quadratic and Higher-Order Unconstrained Binary Optimization of Railway Dispatching Problem for Quantum Computing

The consequences of disruptions in railway traffic are the primary cause of
passengers' dissatisfaction. Hence, appropriate dispatching decisions are
necessary (e.g., by assigning the order of trains)

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The Algorithm of Shor for Prime Factorization

Continued Fractions and Probability Estimations in the Shor Algorithm -- A Detailed and Self-Contained Treatise

We present the relevant results and proofs from the theory of continued fractions in detail (even in more detail than in text books) filling the gap to allow a complete comprehension of the algorithm of shor for prime factorization.

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Hybrid quantum--classical algorithm for computing imaginary-time correlation functions

Quantitative descriptions of strongly correlated materials pose a
considerable challenge in condensed matter physics and chemistry. A promising
approach to address this problem is quantum embedding me

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Towards an Optimal Hybrid Algorithm for EV Charging Stations Placement using Quantum Annealing and Genetic Algorithms

Quantum Annealing is a heuristic for solving optimization problems that have
seen a recent surge in usage owing to the success of D-Wave Systems. This paper
aims to find a good heuristic for solving t

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Disordered Systems and Neural Networks

Statistical Mechanics

Quantum Physics

Computational Physics

Quantum Annealers for Low-Temperature Boltzmann Monte Carlo Simulations

Accelerating equilibrium spin-glass simulations using quantum annealers via generative deep learning

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Multi-car paint shop optimization with quantum annealing

We present a generalization of the binary paint shop problem (BPSP) to tackle
an automotive industry application, the multi-car paint shop (MCPS) problem.
The objective of the optimization is to minim

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Unsupervised Machine Learning on a Hybrid Quantum Computer

Machine learning techniques have led to broad adoption of a statistical model
of computing. The statistical distributions natively available on quantum
processors are a superset of those available cla

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A Hybrid Quantum-Classical Algorithm for Loan Collection

Hybrid Quantum-Classical Algorithms for Loan Collection Optimization with Loan Loss Provisions

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Measurement-Based Time Evolution for Quantum Simulation of Fermionic Systems

Quantum simulation using time evolution in phase estimation-based quantum
algorithms can yield unbiased solutions of classically intractable models. But
long runtimes open such algorithms to decoheren

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Quantum Circuit Learning

We propose a classical-quantum hybrid algorithm for machine learning on
near-term quantum processors, which we call quantum circuit learning. A quantum
circuit driven by our framework learns a given t

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