Zobrazeno 1 - 10
of 336
pro vyhledávání: '"Bertels, Koen"'
Optimizing the mRNA codon has an essential impact on gene expression for a specific target protein. It is an NP-hard problem; thus, exact solutions to such optimization problems become computationally intractable for realistic problem sizes on both c
Externí odkaz:
http://arxiv.org/abs/2404.14858
The article summarizes the study performed in the context of the Deloitte Quantum Climate Challenge in 2023. We present a hybrid quantum-classical method for calculating Potential Energy Surface scans, which are essential for designing Metal-Organic
Externí odkaz:
http://arxiv.org/abs/2309.05465
In this research, we extend the universal reinforcement learning (URL) agent models of artificial general intelligence to quantum environments. The utility function of a classical exploratory stochastic Knowledge Seeking Agent, KL-KSA, is generalized
Externí odkaz:
http://arxiv.org/abs/2112.03643
Given the impending timeline of developing good-quality quantum processing units, it is time to rethink the approach to advance quantum computing research. Rather than waiting for quantum hardware technologies to mature, we need to start assessing in
Externí odkaz:
http://arxiv.org/abs/2106.11840
Autor:
Sarkar, Aritra, Bertels, Koen
In this research we present a quantum circuit for estimating algorithmic complexity using the coding theorem method. This accelerates inferring algorithmic structure in data for discovering causal generative models. The computation model is restricte
Externí odkaz:
http://arxiv.org/abs/2009.08866
In this research, we present a quantum circuit design and implementation for a parallel universal linear bounded automata. This circuit is able to accelerate the inference of algorithmic structures in data for discovering causal generative models. Th
Externí odkaz:
http://arxiv.org/abs/2006.00987
Publikováno v:
Phys. Rev. A 102, 052608 (2020)
The implementation and practicality of quantum algorithms highly hinge on the quality of operations within a quantum processor. Therefore, including realistic error models in quantum computing simulation platforms is crucial for testing these algorit
Externí odkaz:
http://arxiv.org/abs/2005.06337
In this article, we present QuASeR, a reference-free DNA sequence reconstruction implementation via de novo assembly on both gate-based and quantum annealing platforms. Each one of the four steps of the implementation (TSP, QUBO, Hamiltonians and QAO
Externí odkaz:
http://arxiv.org/abs/2004.05078
An active area of investigation in the search for quantum advantage is Quantum Machine Learning. Quantum Machine Learning, and Parameterized Quantum Circuits in a hybrid quantum-classical setup in particular, could bring advancements in accuracy by u
Externí odkaz:
http://arxiv.org/abs/2003.09887