Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Minssen P"'
Autor:
Acharya, Atithi, Yalovetzky, Romina, Minssen, Pierre, Chakrabarti, Shouvanik, Shaydulin, Ruslan, Raymond, Rudy, Sun, Yue, Herman, Dylan, Andrist, Ruben S., Salton, Grant, Schuetz, Martin J. A., Katzgraber, Helmut G., Pistoia, Marco
Industrially relevant constrained optimization problems, such as portfolio optimization and portfolio rebalancing, are often intractable or difficult to solve exactly. In this work, we propose and benchmark a decomposition pipeline targeting portfoli
Externí odkaz:
http://arxiv.org/abs/2409.10301
Autor:
Perlin, Michael A., Shaydulin, Ruslan, Hall, Benjamin P., Minssen, Pierre, Li, Changhao, Dubey, Kabir, Rines, Rich, Anschuetz, Eric R., Pistoia, Marco, Gokhale, Pranav
Combinatorial optimization problems that arise in science and industry typically have constraints. Yet the presence of constraints makes them challenging to tackle using both classical and quantum optimization algorithms. We propose a new quantum alg
Externí odkaz:
http://arxiv.org/abs/2403.05653
Decision trees are widely adopted machine learning models due to their simplicity and explainability. However, as training data size grows, standard methods become increasingly slow, scaling polynomially with the number of training examples. In this
Externí odkaz:
http://arxiv.org/abs/2309.09976
Autor:
Shaydulin, Ruslan, Li, Changhao, Chakrabarti, Shouvanik, DeCross, Matthew, Herman, Dylan, Kumar, Niraj, Larson, Jeffrey, Lykov, Danylo, Minssen, Pierre, Sun, Yue, Alexeev, Yuri, Dreiling, Joan M., Gaebler, John P., Gatterman, Thomas M., Gerber, Justin A., Gilmore, Kevin, Gresh, Dan, Hewitt, Nathan, Horst, Chandler V., Hu, Shaohan, Johansen, Jacob, Matheny, Mitchell, Mengle, Tanner, Mills, Michael, Moses, Steven A., Neyenhuis, Brian, Siegfried, Peter, Yalovetzky, Romina, Pistoia, Marco
Publikováno v:
Sci. Adv. 10 (22), eadm6761 (2024)
The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm for solving optimization problems on quantum computers. However, the potential of QAOA to tackle classically intractable problems remains unclear. Here, we perform
Externí odkaz:
http://arxiv.org/abs/2308.02342
Autor:
Andrist, Ruben S., Schuetz, Martin J. A., Minssen, Pierre, Yalovetzky, Romina, Chakrabarti, Shouvanik, Herman, Dylan, Kumar, Niraj, Salton, Grant, Shaydulin, Ruslan, Sun, Yue, Pistoia, Marco, Katzgraber, Helmut G.
Publikováno v:
Phys. Rev. Research 5, 043277 (2023)
Rydberg atom arrays are among the leading contenders for the demonstration of quantum speedups. Motivated by recent experiments with up to 289 qubits [Ebadi et al., Science 376, 1209 (2022)] we study the maximum independent set problem on unit-disk g
Externí odkaz:
http://arxiv.org/abs/2307.09442
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The limited capabilities of current quantum hardware significantly constrain the scale of experimental demonstrations of most quantum algorithmic primitives. This makes it challenging to perform benchmarking of the current hardware using use
Externí odkaz:
https://doaj.org/article/86e9cdf8f55d4c50bf81a1950b2d4fdf
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-6 (2024)
The newly adopted EU AI Act represents a pivotal milestone that heralds a new era of AI regulation across industries. With its broad territorial scope and applicability, this comprehensive legislation establishes stringent requirements for AI systems
Externí odkaz:
https://doaj.org/article/99d01209336c421a881af3f6ca613efe
Autor:
Kop, Mauritz, Aboy, Mateo, De Jong, Eline, Gasser, Urs, Minssen, Timo, Cohen, I. Glenn, Brongersma, Mark, Quintel, Teresa, Floridi, Luciano, Laflamme, Raymond
The expected societal impact of quantum technologies (QT) urges us to proceed and innovate responsibly. This article proposes a conceptual framework for Responsible QT that seeks to integrate considerations about ethical, legal, social, and policy im
Externí odkaz:
http://arxiv.org/abs/2303.16671
Autor:
Cherrat, El Amine, Raj, Snehal, Kerenidis, Iordanis, Shekhar, Abhishek, Wood, Ben, Dee, Jon, Chakrabarti, Shouvanik, Chen, Richard, Herman, Dylan, Hu, Shaohan, Minssen, Pierre, Shaydulin, Ruslan, Sun, Yue, Yalovetzky, Romina, Pistoia, Marco
Publikováno v:
Quantum 7, 1191 (2023)
Quantum machine learning has the potential for a transformative impact across industry sectors and in particular in finance. In our work we look at the problem of hedging where deep reinforcement learning offers a powerful framework for real markets.
Externí odkaz:
http://arxiv.org/abs/2303.16585
Mixed Integer Programs (MIPs) model many optimization problems of interest in Computer Science, Operations Research, and Financial Engineering. Solving MIPs is NP-Hard in general, but several solvers have found success in obtaining near-optimal solut
Externí odkaz:
http://arxiv.org/abs/2210.03210