4,058 research outputs found
Combining internal and external inputs for sustainable intensification
Farmers and local development organizations around the world use and promote a variety of technologies to increase food production. But the high cost of inorganic fertilizers and other agrochemicals often drives farmers to rely on locally available resources instead of purchased, externally produced inputs. So-called low external input agriculture (LEIA) has spread rapidly to different parts of the globe as a challenging alternative to—or, more frequently, a complement to— Green Revolution technologies...The goal of policy, research, and extension should be to help LEIA farmers achieve "sustainable intensification", which refers to the simultaneous increase in returns to land and labor (in the short run) and the maintenance of soil nutrient balances (in the long run).Soil fertility. ,Food production. ,Technological innovations. ,Fertilizers. ,Agricultural research. ,
Texture control in a pseudospin Bose-Einstein condensate
We describe a wavefunction engineering approach to the formation of textures
in a two-component nonrotated Bose-Einstein condensate. By controlling the
phases of wavepackets that combine in a three-wave interference process, a
ballistically-expanding regular lattice-texture is generated, in which the
phases determine the component textures. A particular example is presented of a
lattice-texture composed of half-quantum vortices and spin-2 textures. We
demonstrate the lattice formation with numerical simulations of a viable
experiment, identifying the textures and relating their locations to a linear
theory of wavepacket interference.Comment: 4 pages, 5 figures, REVTeX4-
Computational Economics: Help for the Underestimated Undergraduate
Our concern in this paper is that the capability of economics undergraduates is substantially underestimated in the design of the present college curriculum and that our students are insufficiently challenged and motivated. Students enter our classrooms with substantial previous knowledge about computers and computation and we are not taking full advantage of this opportunity. We suggest a set of examples from computational economics which are challenging enough to motivate students and simple enough that they can master them within a few hours. By encouraging the students to modify the models in directions of their own interest avenues for creative endeavor are opened which deeply involve the students in their own education.teaching computational economics
Supersymmetry breaking branes on solvmanifolds and de Sitter vacua in string theory
We consider IIA compactifications on solvmanifolds with O6/D6 branes and
study the conditions for obtaining de Sitter vacua in ten dimensions. While
this is a popular set-up for searching de Sitter vacua, we propose a new method
to include supersymmetry breaking sources. For space-time filling branes
preserving bulk supersymmetry, the energy density can easily be extremized with
respect to all fields, thanks to the replacement of the DBI action by a
pullback of a special form given by a pure spinor. For sources breaking bulk
supersymmetry, we propose to replace the DBI action by the pullback of a more
general polyform, which is no longer pure. This generalization provides
corrections to the energy-momentum tensor which give a positive contribution to
the cosmological constant. We find a de Sitter solution to all (bulk and
world-volume) equations derived from this action. We argue it solves the
equations derived from the standard source action. The paper also contains a
review of solvmanifolds.Comment: 57 pages, 3 figures. Important additions (concerning the validity of
our solution in string theory); version to appear in JHE
GPU-based Online Track Reconstruction for the ALICE TPC in Run 3 with Continuous Read-Out
In LHC Run 3, ALICE will increase the data taking rate significantly to 50
kHz continuous read-out of minimum bias Pb-Pb collisions. The reconstruction
strategy of the online-offline computing upgrade foresees a first synchronous
online reconstruction stage during data taking enabling detector calibration
and data compression, and a posterior calibrated asynchronous reconstruction
stage. Many new challenges arise, among them continuous TPC read-out, more
overlapping collisions, no a priori knowledge of the primary vertex and of
location-dependent calibration in the synchronous phase, identification of
low-momentum looping tracks, and sophisticated raw data compression. The
tracking algorithm for the Time Projection Chamber (TPC) will be based on a
Cellular Automaton and the Kalman filter. The reconstruction shall run online,
processing 50 times more collisions per second than today, while yielding
results comparable to current offline reconstruction. Our TPC track finding
leverages the potential of hardware accelerators via the OpenCL and CUDA APIs
in a shared source code for CPUs and GPUs for both reconstruction stages. We
give an overview of the status of Run 3 tracking including performance on
processors and GPUs and achieved compression ratios.Comment: 8 pages, 7 figures, contribution to CHEP 2018 conferenc
Track Reconstruction in the ALICE TPC using GPUs for LHC Run 3
In LHC Run 3, ALICE will increase the data taking rate significantly to
continuous readout of 50 kHz minimum bias Pb-Pb collisions. The reconstruction
strategy of the online offline computing upgrade foresees a first synchronous
online reconstruction stage during data taking enabling detector calibration,
and a posterior calibrated asynchronous reconstruction stage. We present a
tracking algorithm for the Time Projection Chamber (TPC), the main tracking
detector of ALICE. The reconstruction must yield results comparable to current
offline reconstruction and meet the time constraints like in the current High
Level Trigger (HLT), processing 50 times as many collisions per second as
today. It is derived from the current online tracking in the HLT, which is
based on a Cellular automaton and the Kalman filter, and we integrate missing
features from offline tracking for improved resolution. The continuous TPC
readout and overlapping collisions pose new challenges: conversion to spatial
coordinates and the application of time- and location dependent calibration
must happen in between of track seeding and track fitting while the TPC
occupancy increases five-fold. The huge data volume requires a data reduction
factor of 20, which imposes additional requirements: the momentum range must be
extended to identify low-pt looping tracks and a special refit in uncalibrated
coordinates improves the track model entropy encoding. Our TPC track finding
leverages the potential of hardware accelerators via the OpenCL and CUDA APIs
in a shared source code for CPUs, GPUs, and both reconstruction stages. Porting
more reconstruction steps like the remainder of the TPC reconstruction and
tracking for other detectors will shift the computing balance from traditional
processors to GPUs.Comment: 13 pages, 10 figures, proceedings to Connecting The Dots Workshop,
Seattle, 201
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