TY - JOUR
AB - In this paper we experimentally study the transitional range of Reynolds numbers in
plane Couette–Poiseuille flow, focusing our attention on the localized turbulent structures
triggered by a strong impulsive jet and the large-scale flow generated around these
structures. We present a detailed investigation of the large-scale flow and show how
its amplitude depends on Reynolds number and amplitude perturbation. In addition,
we characterize the initial dynamics of the localized turbulent spot, which includes the
coupling between the small and large scales, as well as the dependence of the advection
speed on the large-scale flow generated around the spot. Finally, we provide the first
experimental measurements of the large-scale flow around an oblique turbulent band.
AU - Klotz, Lukasz
AU - Pavlenko, A. M.
AU - Wesfreid, J. E.
ID - 9207
JF - Journal of Fluid Mechanics
SN - 0022-1120
TI - Experimental measurements in plane Couette-Poiseuille flow: Dynamics of the large- and small-scale flow
VL - 912
ER -
TY - CONF
AB - Modern neural networks can easily fit their training set perfectly. Surprisingly, despite being “overfit” in this way, they tend to generalize well to future data, thereby defying the classic bias–variance trade-off of machine learning theory. Of the many possible explanations, a prevalent one is that training by stochastic gradient descent (SGD) imposes an implicit bias that leads it to learn simple functions, and these simple functions generalize well. However, the specifics of this implicit bias are not well understood.
In this work, we explore the smoothness conjecture which states that SGD is implicitly biased towards learning functions that are smooth. We propose several measures to formalize the intuitive notion of smoothness, and we conduct experiments to determine whether SGD indeed implicitly optimizes for these measures. Our findings rule out the possibility that smoothness measures based on first-order derivatives are being implicitly enforced. They are supportive, though, of the smoothness conjecture for measures based on second-order derivatives.
AU - Volhejn, Vaclav
AU - Lampert, Christoph
ID - 9210
SN - 03029743
T2 - 42nd German Conference on Pattern Recognition
TI - Does SGD implicitly optimize for smoothness?
VL - 12544 LNCS
ER -
TY - JOUR
AB - Plant fitness is largely dependent on the root, the underground organ, which, besides its anchoring function, supplies the plant body with water and all nutrients necessary for growth and development. To exploit the soil effectively, roots must constantly integrate environmental signals and react through adjustment of growth and development. Important components of the root management strategy involve a rapid modulation of the root growth kinetics and growth direction, as well as an increase of the root system radius through formation of lateral roots (LRs). At the molecular level, such a fascinating growth and developmental flexibility of root organ requires regulatory networks that guarantee stability of the developmental program but also allows integration of various environmental inputs. The plant hormone auxin is one of the principal endogenous regulators of root system architecture by controlling primary root growth and formation of LR. In this review, we discuss recent progress in understanding molecular networks where auxin is one of the main players shaping the root system and acting as mediator between endogenous cues and environmental factors.
AU - Cavallari, Nicola
AU - Artner, Christina
AU - Benková, Eva
ID - 9212
IS - 7
JF - Cold Spring Harbor Perspectives in Biology
SN - 1943-0264
TI - Auxin-regulated lateral root organogenesis
VL - 13
ER -
TY - JOUR
AB - We re-examine attempts to study the many-body localization transition using measures that are physically natural on the ergodic/quantum chaotic regime of the phase diagram. Using simple scaling arguments and an analysis of various models for which rigorous results are available, we find that these measures can be particularly adversely affected by the strong finite-size effects observed in nearly all numerical studies of many-body localization. This severely impacts their utility in probing the transition and the localized phase. In light of this analysis, we discuss a recent study (Šuntajs et al., 2020) of the behaviour of the Thouless energy and level repulsion in disordered spin chains, and its implications for the question of whether MBL is a true phase of matter.
AU - Abanin, D. A.
AU - Bardarson, J. H.
AU - De Tomasi, G.
AU - Gopalakrishnan, S.
AU - Khemani, V.
AU - Parameswaran, S. A.
AU - Pollmann, F.
AU - Potter, A. C.
AU - Serbyn, Maksym
AU - Vasseur, R.
ID - 9224
IS - 4
JF - Annals of Physics
SN - 00034916
TI - Distinguishing localization from chaos: Challenges in finite-size systems
VL - 427
ER -
TY - JOUR
AB - The Landau–Pekar equations describe the dynamics of a strongly coupled polaron.
Here, we provide a class of initial data for which the associated effective Hamiltonian
has a uniform spectral gap for all times. For such initial data, this allows us to extend the
results on the adiabatic theorem for the Landau–Pekar equations and their derivation
from the Fröhlich model obtained in previous works to larger times.
AU - Feliciangeli, Dario
AU - Rademacher, Simone Anna Elvira
AU - Seiringer, Robert
ID - 9225
JF - Letters in Mathematical Physics
SN - 03779017
TI - Persistence of the spectral gap for the Landau–Pekar equations
VL - 111
ER -
TY - JOUR
AB - Half a century after Lewis Wolpert's seminal conceptual advance on how cellular fates distribute in space, we provide a brief historical perspective on how the concept of positional information emerged and influenced the field of developmental biology and beyond. We focus on a modern interpretation of this concept in terms of information theory, largely centered on its application to cell specification in the early Drosophila embryo. We argue that a true physical variable (position) is encoded in local concentrations of patterning molecules, that this mapping is stochastic, and that the processes by which positions and corresponding cell fates are determined based on these concentrations need to take such stochasticity into account. With this approach, we shift the focus from biological mechanisms, molecules, genes and pathways to quantitative systems-level questions: where does positional information reside, how it is transformed and accessed during development, and what fundamental limits it is subject to?
AU - Tkačik, Gašper
AU - Gregor, Thomas
ID - 9226
IS - 2
JF - Development
TI - The many bits of positional information
VL - 148
ER -
TY - CONF
AB - In the multiway cut problem we are given a weighted undirected graph G=(V,E) and a set T⊆V of k terminals. The goal is to find a minimum weight set of edges E′⊆E with the property that by removing E′ from G all the terminals become disconnected. In this paper we present a simple local search approximation algorithm for the multiway cut problem with approximation ratio 2−2k . We present an experimental evaluation of the performance of our local search algorithm and show that it greatly outperforms the isolation heuristic of Dalhaus et al. and it has similar performance as the much more complex algorithms of Calinescu et al., Sharma and Vondrak, and Buchbinder et al. which have the currently best known approximation ratios for this problem.
AU - Bloch-Hansen, Andrew
AU - Samei, Nasim
AU - Solis-Oba, Roberto
ID - 9227
SN - 0302-9743
T2 - Conference on Algorithms and Discrete Applied Mathematics
TI - Experimental evaluation of a local search approximation algorithm for the multiway cut problem
VL - 12601
ER -
TY - JOUR
AB - Legacy conferences are costly and time consuming, and exclude scientists lacking various resources or abilities. During the 2020 pandemic, we created an online conference platform, Neuromatch Conferences (NMC), aimed at developing technological and cultural changes to make conferences more democratic, scalable, and accessible. We discuss the lessons we learned.
AU - Achakulvisut, Titipat
AU - Ruangrong, Tulakan
AU - Mineault, Patrick
AU - Vogels, Tim P
AU - Peters, Megan A.K.
AU - Poirazi, Panayiota
AU - Rozell, Christopher
AU - Wyble, Brad
AU - Goodman, Dan F.M.
AU - Kording, Konrad Paul
ID - 9228
IS - 4
JF - Trends in Cognitive Sciences
SN - 1364-6613
TI - Towards democratizing and automating online conferences: Lessons from the Neuromatch Conferences
VL - 25
ER -
TY - GEN
AB - We consider a model of the Riemann zeta function on the critical axis and study its maximum over intervals of length (log T)θ, where θ is either fixed or tends to zero at a suitable rate.
It is shown that the deterministic level of the maximum interpolates smoothly between the ones
of log-correlated variables and of i.i.d. random variables, exhibiting a smooth transition ‘from
3/4 to 1/4’ in the second order. This provides a natural context where extreme value statistics of
log-correlated variables with time-dependent variance and rate occur. A key ingredient of the
proof is a precise upper tail tightness estimate for the maximum of the model on intervals of
size one, that includes a Gaussian correction. This correction is expected to be present for the
Riemann zeta function and pertains to the question of the correct order of the maximum of
the zeta function in large intervals.
AU - Arguin, Louis-Pierre
AU - Dubach, Guillaume
AU - Hartung, Lisa
ID - 9230
T2 - arXiv
TI - Maxima of a random model of the Riemann zeta function over intervals of varying length
ER -
TY - JOUR
AB - In this paper, we present two new inertial projection-type methods for solving multivalued variational inequality problems in finite-dimensional spaces. We establish the convergence of the sequence generated by these methods when the multivalued mapping associated with the problem is only required to be locally bounded without any monotonicity assumption. Furthermore, the inertial techniques that we employ in this paper are quite different from the ones used in most papers. Moreover, based on the weaker assumptions on the inertial factor in our methods, we derive several special cases of our methods. Finally, we present some experimental results to illustrate the profits that we gain by introducing the inertial extrapolation steps.
AU - Izuchukwu, Chinedu
AU - Shehu, Yekini
ID - 9234
IS - 2
JF - Networks and Spatial Economics
KW - Computer Networks and Communications
KW - Software
KW - Artificial Intelligence
SN - 1566-113X
TI - New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity
VL - 21
ER -