Quantum optics in visual sensors and adaptive optics by quantum vacillations of laser beams wave propagation apply in data mining
This article proposes the basic way of behaving of the quantum Sherrington-Kirkpatrick (SK)
model at nothing and limited temperatures is examined. Through the investigation of the …
model at nothing and limited temperatures is examined. Through the investigation of the …
Power of pausing: Advancing understanding of thermalization in experimental quantum annealers
We investigate alternative annealing schedules on the current generation of quantum-
annealing hardware (the D-Wave 2000Q), which includes the use of forward and reverse …
annealing hardware (the D-Wave 2000Q), which includes the use of forward and reverse …
Quantum machine learning and its supremacy in high energy physics
KK Sharma - Modern Physics Letters A, 2021 - World Scientific
This paper reveals the future prospects of quantum algorithms in high energy physics (HEP).
Particle identification, knowing their properties and characteristics is a challenging problem …
Particle identification, knowing their properties and characteristics is a challenging problem …
Guided quantum walk
We utilize the theory of local amplitude transfer (LAT) to gain insights into quantum walks
(QWs) and quantum annealing (QA) beyond the adiabatic theorem. By representing the …
(QWs) and quantum annealing (QA) beyond the adiabatic theorem. By representing the …
Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks
Quantum annealing is a practical approach to approximately implement the adiabatic
quantum computational model in a real-world setting. The goal of an adiabatic algorithm is …
quantum computational model in a real-world setting. The goal of an adiabatic algorithm is …
Finding optimal pathways in chemical reaction networks using ising machines
Y Mizuno, T Komatsuzaki - Physical Review Research, 2024 - APS
Finding optimal pathways in chemical reaction networks is essential for elucidating and
designing chemical processes, with significant applications such as synthesis planning and …
designing chemical processes, with significant applications such as synthesis planning and …
[PDF][PDF] Quantum machine learning in high energy physics: the future prospects
KK Sharma - High Energy Particle Physics, 2018 - researchgate.net
This article reveals the future prospects of quantum machine learning in high energy physics
(HEP). Particle identification, knowing their properties and characteristics is a challenging …
(HEP). Particle identification, knowing their properties and characteristics is a challenging …