Zobrazeno 1 - 10
of 1 976
pro vyhledávání: '"Białas, P."'
Autor:
Caune, Laura, Skoric, Luka, Blunt, Nick S., Ruban, Archibald, McDaniel, Jimmy, Valery, Joseph A., Patterson, Andrew D., Gramolin, Alexander V., Majaniemi, Joonas, Barnes, Kenton M., Bialas, Tomasz, Buğdaycı, Okan, Crawford, Ophelia, Gehér, György P., Krovi, Hari, Matekole, Elisha, Topal, Canberk, Poletto, Stefano, Bryant, Michael, Snyder, Kalan, Gillespie, Neil I., Jones, Glenn, Johar, Kauser, Campbell, Earl T., Hill, Alexander D.
Quantum error correction (QEC) will be essential to achieve the accuracy needed for quantum computers to realise their full potential. The field has seen promising progress with demonstrations of early QEC and real-time decoded experiments. As quantu
Externí odkaz:
http://arxiv.org/abs/2410.05202
We describe a method to estimate R\'enyi entanglement entropy of a spin system, which is based on the replica trick and generative neural networks with explicit probability estimation. It can be extended to any spin system or lattice field theory. We
Externí odkaz:
http://arxiv.org/abs/2406.06193
Publikováno v:
Condensed Matter Physics, 2024, Vol. 27, No. 3, 33601
We discuss the distribution of partition function zeros for the grand-canonical ensemble of the zeta-urn model, where tuning a single parameter can give a first or any higher order condensation transition. We compute the locus of zeros for finite-siz
Externí odkaz:
http://arxiv.org/abs/2312.01806
We construct admissible polynomial meshes on piecewise polynomial or trigonometric curves of the complex plane, by mapping univariate Chebyshev points. Such meshes can be used for polynomial least-squares, for the extraction of Fekete-like and Leja-l
Externí odkaz:
http://arxiv.org/abs/2311.06511
Autor:
Bartoš, František, Sarafoglou, Alexandra, Godmann, Henrik R., Sahrani, Amir, Leunk, David Klein, Gui, Pierre Y., Voss, David, Ullah, Kaleem, Zoubek, Malte J., Nippold, Franziska, Aust, Frederik, Vieira, Felipe F., Islam, Chris-Gabriel, Zoubek, Anton J., Shabani, Sara, Petter, Jonas, Roos, Ingeborg B., Finnemann, Adam, Lob, Aaron B., Hoffstadt, Madlen F., Nak, Jason, de Ron, Jill, Derks, Koen, Huth, Karoline, Terpstra, Sjoerd, Bastelica, Thomas, Matetovici, Magda, Ott, Vincent L., Zetea, Andreea S., Karnbach, Katharina, Donzallaz, Michelle C., John, Arne, Moore, Roy M., Assion, Franziska, van Bork, Riet, Leidinger, Theresa E., Zhao, Xiaochang, Motaghi, Adrian Karami, Pan, Ting, Armstrong, Hannah, Peng, Tianqi, Bialas, Mara, Pang, Joyce Y. -C., Fu, Bohan, Yang, Shujun, Lin, Xiaoyi, Sleiffer, Dana, Bognar, Miklos, Aczel, Balazs, Wagenmakers, Eric-Jan
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected $350{,}757$ coin flips to test the counterintuitive prediction from a physics model of human
Externí odkaz:
http://arxiv.org/abs/2310.04153
We extend our previous studies on a counter-intuitive effect in which a directed transport of a free Brownian particle induced by active fluctuations can be significantly enhanced when the particle is placed in a periodic potential. It is in clear co
Externí odkaz:
http://arxiv.org/abs/2310.02419
Autor:
Barber, Ben, Barnes, Kenton M., Bialas, Tomasz, Buğdaycı, Okan, Campbell, Earl T., Gillespie, Neil I., Johar, Kauser, Rajan, Ram, Richardson, Adam W., Skoric, Luka, Topal, Canberk, Turner, Mark L., Ziad, Abbas B.
To unleash the potential of quantum computers, noise effects on qubits' performance must be carefully managed. The decoders responsible for diagnosing noise-induced computational errors must use resources efficiently to enable scaling to large qubit
Externí odkaz:
http://arxiv.org/abs/2309.05558
Transformer based large language models with emergent capabilities are becoming increasingly ubiquitous in society. However, the task of understanding and interpreting their internal workings, in the context of adversarial attacks, remains largely un
Externí odkaz:
http://arxiv.org/abs/2309.00254
Publikováno v:
BMC Medical Education, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Objective Manual therapy is a crucial component in rehabilitation education, yet there is a lack of models for evaluating learning in this area. This study aims to develop a foundational evaluation model for manual therapy learning among reh
Externí odkaz:
https://doaj.org/article/efa31a8c70c04a52b6778f4465c9e509
Publikováno v:
Computer Physics Communications 2024 109094
Machine learning techniques, in particular the so-called normalizing flows, are becoming increasingly popular in the context of Monte Carlo simulations as they can effectively approximate target probability distributions. In the case of lattice field
Externí odkaz:
http://arxiv.org/abs/2308.13294