• Coxeter Arrangements and Solomon's Descent Algebra 

      [OWP-2011-03] Douglass, J. Matthew; Pfeiffer, Götz; Röhrle, Gerhard (Mathematisches Forschungsinstitut Oberwolfach, 2011-05-6)
    • Criteria for Algebraicity of Analytic Functions 

      [OWP-2018-25] Bochnak, Jacek; Gwoździewicz, Janusz; Kucharz, Wojciech (Mathematisches Forschungsinstitut Oberwolfach, 2018-11-12)
      We consider functions defined on an open subset of a nonsingular, either real or complex, algebraic set. We give criteria for an analytic function to be a Nash (resp. regular, resp. polynomial) function. Our criteria depend ...
    • Cryptanalysis of Public-key Cryptosystems Based on Algebraic Geometry Codes 

      [OWP-2012-01] Márquez-Corbella, Irene; Martínez-Moro, Edgar; Pellikaan, Ruud (Mathematisches Forschungsinstitut Oberwolfach, 2012-03-20)
      This paper addresses the question of retrieving the triple $(\mathcal{X},\mathcal{P},\mathcal{E})$ from the algebraic geometry code $\mathcal{C}_L(\mathcal{X},\mathcal{P},\mathcal{E})$, where $\mathcal{X}$ is an algebraic ...
    • 1431 - Cryptography 

      [OWR-2014-35] (2014) - (27 Jul - 02 Aug 2014)
      The Oberwolfach workshop Cryptography brought together scientists from cryptography with mathematicians specializing in the algorithmic problems underlying cryptographic security. The goal of the workshop was to stimulate ...
    • 1703 - Cryptography 

      [OWR-2017-5] (2017) - (15 Jan - 21 Jan 2017)
      The Oberwolfach workshop Cryptography brought together scientists from cryptography with mathematicians specializing in the algorithmic problems underlying cryptographic security. The goal of the workshop was to stimulate ...
    • Crystal energy functions via the charge in types A and C 

      [OWP-2011-25] Lenart, Cristian; Schilling, Anne (Mathematisches Forschungsinstitut Oberwolfach, 2011-05-23)
      The Ram-Yip formula for Macdonald polynomials (at $t=0$) provides a statistic which we call charge. In types $A$ and $C$ it can be defined on tensor products of Kashiwara-Nakashima single column crystals. In this ...
    • Curriculum development in university mathematics: where mathematicians and education collide 

      [SNAP-2015-011-EN] Sangwin, Christopher J. (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      This snapshot looks at educational aspects of the design of curricula in mathematics. In particular, we examine choices textbook authors have made when introducing the concept of the completness of the real numbers. Can ...
    • Curvatura escalar positiva y aplicaciones 

      [SNAP-2019-004-ES] Rosenberg, Jonathan; Wraith, David (Mathematisches Forschungsinstitut Oberwolfach, 2021)
      Introducimos la idea de curvatura, incluyendo su desarrollo histórico, y nos enfocamos en la curvatura escalar de una variedad. Uno de los temas principales de investigación actual es entender la curvatura escalar positiva. ...
    • Cutoff Phenomenon: Surprising Behaviour in Card Shuffling and other Markov Chains 

      [SNAP-2023-005-EN] Baraquin, Isabelle; Lafrenière, Nadia; Schuh, Katharina (Mathematisches Forschungsinstitut Oberwolfach, 2023-12-21)
      This snapshot compares two techniques of shuffling a deck of cards, asking how long it will take to shuffle the cards until a “well-mixed deck” is obtained. Surprisingly, the number of shuffles can be very different for ...
    • Cutoff-Phänomen: überraschendes Verhalten beim Kartenmischen und bei weiteren Markovketten 

      [SNAP-2023-005-DE] Baraquin, Isabelle; Lafrenière, Nadia; Schuh, Katharina (Mathematisches Forschungsinstitut Oberwolfach, 2024-10-22)
      Dieser Schnappschuss vergleicht zwei Arten des Kartenmischens und untersucht, wie lange es dauert einen "gut gemischten" Kartenstapel zu erhalten. Überraschenderweise kann das Mischverhalten auch für sehr ähnlich ausschauende ...
    • Darcy's law and groundwater flow modelling 

      [SNAP-2015-007-EN] Schweizer, Ben (Mathematisches Forschungsinstitut Oberwolfach, 2015)
      Formulations of natural phenomena are derived, sometimes, from experimentation and observation. Mathematical methods can be applied to expand on these formulations, and develop them into better models. In the year 1856, ...
    • 0313 - Darstellungen endlicher Gruppen 

      [TB-2003-14] (2003) - (23 Mar - 29 Mar 2003)
    • 0008 - Darstellungstheorie endlich-dimensionaler Algebren 

      [TB-2000-8] (2000) - (20 Feb - 26 Feb 2000)
    • 9925 - Darstellungstheorie endlicher Gruppen 

      [TB-1999-25] (1999) - (20 Jun - 26 Jun 1999)
    • 2208 - Data Assimilation - Mathematical Foundation and Applications 

      [OWR-2022-10] (2022) - (20 Feb - 26 Feb 2022)
      The field of "Data Assimilation'' has been driven by applications from the geosciences where complex mathematical models are interfaced with observational data in order to improve model forecasts. Mathematically, data ...
    • Data assimilation: mathematics for merging models and data 

      [SNAP-2018-011-EN] Morzfeld, Matthias; Reich, Sebastian (Mathematisches Forschungsinstitut Oberwolfach, 2018-07-10)
      When you describe a physical process, for example, the weather on Earth, or an engineered system, such as a self-driving car, you typically have two sources of information. The first is a mathematical model, and the ...
    • Deciding Non-Freeness of Rational Möbius Groups 

      [OWP-2022-07] Detinko, Alla; Flannery, Dane; Hulpke, Alexander (Mathematisches Forschungsinstitut Oberwolfach, 2022-03-22)
      We explore a new computational approach to a classical problem: certifying non-freeness of (2-generator, parabolic) Möbius subgroups of SL(2, $\mathbb{Q}$). The main tools used are algorithms for Zariski dense groups and ...
    • Deep Learning and Inverse Problems 

      [SNAP-2019-015-EN] Arridge, Simon; de Hoop, Maarten; Maass, Peter; Öktem, Ozan; Schönlieb, Carola; Unser, Michael (Mathematisches Forschungsinstitut Oberwolfach, 2019-11-21)
      Big data and deep learning are modern buzz words which presently infiltrate all fields of science and technology. These new concepts are impressive in terms of the stunning results they achieve for a large variety of ...
    • 2110b - Deep Learning for Inverse Problems (hybrid meeting) 

      [OWR-2021-13] (2021) - (07 Mar - 13 Mar 2021)
      Machine learning and in particular deep learning offer several data-driven methods to amend the typical shortcomings of purely analytical approaches. The mathematical research on these combined models is presently exploding ...