Markus Pflitsch

According to our database, Markus Pflitsch authored at least 11 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Loss Control-Based Key Distribution under Quantum Protection.

Nikita S. Kirsanov, Valeria A. Pastushenko, Aleksei D. Kodukhov, Aziz Aliev, Mikhail Yarovikov, Daniel Strizhak, Ilya Zarubin, Alexander Smirnov, Markus Pflitsch, Valerii M. Vinokur

Entropy, June, 2024

Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes.

Alexandr Sedykh, Maninadh Podapaka, Asel Sagingalieva, Karan Pinto, Markus Pflitsch, Alexey Melnikov

Mach. Learn. Sci. Technol., 2024

Hybrid quantum cycle generative adversarial network for small molecule generation.

Matvei Anoshin, Asel Sagingalieva, Christopher Mansell, Vishal Shete, Markus Pflitsch, Alexey Melnikov

CoRR, 2024

2023

Boosting Quantum Key Distribution via the End-to-End Loss Control.

Aleksei D. Kodukhov, Valeria A. Pastushenko, Nikita S. Kirsanov, Dmitry A. Kronberg, Markus Pflitsch, Valerii M. Vinokur

Cryptogr., July, 2023

Quantum Algorithms Applied to Satellite Mission Planning for Earth Observation.

Serge Rainjonneau, Igor Tokarev, Sergei Iudin, Saaketh Rayaprolu, Karan Pinto, Daria Lemtiuzhnikova, Miras Koblan, Egor Barashov, Mohammad Kordzanganeh, Markus Pflitsch, Alexey Melnikov

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Photovoltaic power forecasting using quantum machine learning.

Asel Sagingalieva, Stefan Komornyik, Arsenii Senokosov, Ayush Joshi, Alexander Sedykh, Christopher Mansell, Olga Tsurkan, Karan Pinto, Markus Pflitsch, Alexey Melnikov

CoRR, 2023

Numerical solution of the incompressible Navier-Stokes equations for chemical mixers via quantum-inspired Tensor Train Finite Element Method.

Egor Kornev, Sergey Dolgov, Karan Pinto, Markus Pflitsch, Michael Perelshtein, Artem Melnikov

CoRR, 2023

Quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes.

Alexander Sedykh, Maninadh Podapaka, Asel Sagingalieva, Nikita Smertyak, Karan Pinto, Markus Pflitsch, Alexey Melnikov

CoRR, 2023

Tetra-AML: Automatic Machine Learning via Tensor Networks.

Aleksei Naumov, Artem Melnikov, Vadim Abronin, F. Oxanichenko, K. Izmailov, Markus Pflitsch, A. Melnikov, Michael Perelshtein

CoRR, 2023

2022

Do we live in a [quantum] simulation? Constraints, observations, and experiments on the simulation hypothesis.

Florian Neukart, Anders Indset, Markus Pflitsch, Michael Perelshtein

CoRR, 2022

Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms.

Mohammad Kordzanganeh, Markus Buchberger, Maxim Povolotskii, Wilhelm Fischer, Andrii Kurkin, Wilfrid Somogyi, Asel Sagingalieva, Markus Pflitsch, Alexey Melnikov

CoRR, 2022