{"topic":"algorithms-complexity","sort":"top","limit":25,"offset":0,"count":25,"papers":[{"id":"doi:10.1016/j.ces.2012.08.039","kind":"article","title":"Droplet formation and breakup dynamics in microfluidic flow-focusing devices: From dripping to jetting","authors":["Taotao Fu","Yining Wu","Youguang Ma","Huai Li"],"author_count":4,"year":2012,"published":"2012-08-29","venue":"Chemical Engineering Science","cited_by":313,"doi":"10.1016/j.ces.2012.08.039","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.ces.2012.08.039","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.ces.2012.08.039","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2033614532","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Innovative Microfluidic and Catalytic Techniques Innovation"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"doi:10.1104/pp.17.00287","kind":"article","title":"Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models","authors":["Peter J. Franks","Joseph A. Berry","Danica Lombardozzi","Gordon B. Bonan"],"author_count":4,"year":2017,"published":"2017-04-26","venue":"PLANT PHYSIOLOGY","cited_by":159,"doi":"10.1104/pp.17.00287","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1104/pp.17.00287","archive_url":"https://space-kitty.com/papers/doi:10.1104/pp.17.00287","updated":null,"pmid":"28446638","pmcid":null,"openalex_id":"W2608810372","pdf_url":null,"abstract":"The colonization of land by plants and their interaction with biogeochemical and atmospheric processes transformed continental climate and hydrology. Stomata, which evolved to optimize the biological economics of plant carbon uptake in exchange for water loss, play a crucial role in large-scale environmental processes by maintaining a connection between deep soil water reservoirs and the atmosphere, regulating terrestrial carbon sinks and altering surface energy balance as they respond to environmental changes. Stomatal feedback control of leaf gas exchange is observed at multiple temporal and spatial scales, but accurately simulating this dynamic behavior remains challenging, particularly for extreme environmental conditions, including drought. Integration of a more realistic representation of stomatal conductance and its regulation of leaf gas exchange in global models is improving global simulations of carbon, water, and energy fluxes, and these simulations in turn highlight some of the limitations with current leaf-scale models. Our analysis of current leaf-scale models of stomatal conductance representing empirical-based and optimization-based approaches reveals close structural similarities that result in virtually indistinguishable simulations of leaf, canopy, and global fluxes. While acknowledging these similarities, future efforts must focus on more accurate parameterization of stomatal conductance models, informed by studies at multiple temporal and spatial scales, including molecular, fossil, geological, leaf, canopy, and landscape. Stomata first appeared more than 410 million years ago in rudimentary terrestrial plants (Edwards et al., 1998; Raven, 2002; Chater et al., 2016). From then on, they have significantly influenced the fluxes of carbon, water, and energy at the land surface (Berry et al., 2010). After gaining a foothold on land in the late Silurian (Edwards, 1998), the evolution and spread of vascular plants drove one of the most dramatic global climate change events in Earth’s history. The role of plants in changing Earth’s climate was 2-fold: (1) the proliferation of deep-rooting systems and the uptake of nutrients throughout the Devonian enhanced the weathering of Ca-Mg silicate minerals, which facilitated the large-scale transfer of CO2 from the atmosphere to marine carbonates; and (2) unprecedented production of lignin-rich, decay-resistant plant structural material, in conjunction with tectonic basins and wet tropical climates, sequestered massive amounts of carbon in vast coal deposits (Berner, 1997, 2005). The resulting massive drawdown in global atmospheric CO2 concentration from many times that of today, via its reduction of the greenhouse effect, is likely to have contributed significantly to the Permo-Carboniferous glaciation (Royer et al., 2004; Lowry et al., 2014), the most extensive and longest lived glaciation since that time (Crowell, 1978; Scheffler et al., 2003; Montañez and Poulsen, 2013). Ultimately, strong negative feedbacks involving the limitation of terrestrial plant productivity and weathering by low CO2 are likely to have stabilized minimum atmospheric CO2 concentrations above the threshold for severe icehouse conditions (Pagani et al., 2009; Beerling et al., 2012). These megacycles in global vegetation productivity and atmospheric CO2 concentration also are imprinted in the record of plant genome size evolution (Franks et al., 2012a). The colonization of land by plants and extensive greening of the continents marked a dramatic shift in global water and carbon cycles that moderated continental climates and supported a diversity of terrestrial ecosystems (Kleidon et al., 2000; Beerling, 2007; Berry et al., 2010). Stomata played a crucial role in this by maintaining the flow of water from deep soil reservoirs back to the atmosphere, enhancing continental water cycling and cooling of the climate (Berry et al., 2010), a process that continues across terrestrial biomes today (Bonan et al., 1992; Snyder et al., 2004; Feddema et al., 2005; Bala et al., 2007; Arneth et al., 2010). Under current increasing atmospheric CO2 concentration, stomata continue to influence climate as a result of their primary role in optimizing plant water use. Stomatal closure in response to elevated CO2 is a water-conserving mechanism that reduces transpiration but, as a consequence, increases canopy temperature. This physiological forcing adds to the radiative forcing effect of increasing atmospheric CO2 concentration on climate (Sellers et al., 1996a; Betts et al., 1997; Cao et al., 2010). The potential magnitude of physiological climate forcing varies substantially from tropical to temperate to boreal landscapes (Bonan, 2008). However, its mechanism is not fully understood, particularly with regard to the role of vegetation in land-atmosphere coupling (Andrews et al., 2011; Berg et al., 2016; Byrne and O’Gorman, 2016). Owing to the physical and chemical resilience of the guard cell wall and cuticle, stomata are well preserved in fossil plant remains through at least the last 410 million years of the geologic record (Beerling and Woodward, 1997). This resource has proven to be a valuable key to unlocking the history of vegetation-climate coevolution through the Phanerozoic because it has enabled reconstruction of the evolution of plant gas-exchange capacity and productivity (Beerling and Woodward, 1997; Franks and Beerling, 2009a) as well as global atmospheric CO2 concentration (McElwain et al., 1999; Beerling and Royer, 2002; Grein et al., 2011; Franks et al., 2014; Montañez et al., 2016), the latter a critical boundary condition for simulating paleoclimates using global climate models (Kiehl and Shields, 2013; Meissner et al., 2014; Upchurch et al., 2015). Despite these advances, the record of Earth’s vegetation-climate coevolution is incomplete, with significant knowledge gaps remaining at some of the key periods of global transition (Montañez et al., 2016). Next-generation stomatal gas-exchange CO2 proxy models are now helping to reduce uncertainty in reconstructed paleoatmospheric CO2 concentration (Franks et al., 2014). Results from these studies are revising paleo-CO2 estimates that were once widely disparate (e.g. 200–2,800 µmol mol−1 for the Paleocene-Eocene thermal maximum; McInerney and Wing, 2011) to well-constrained values that are more compatible with global paleoclimate simulations (Meissner et al., 2014; Upchurch et al., 2015). However, current paleo-CO2 proxy methods and paleoclimate simulations require refinement and improvement to achieve better agreement across studies and to reduce uncertainty in model outputs. The scales of stomatal influence are illustrated in Figure 1, with examples of some of the quantities involved and some of the tools applied to different spatial and temporal scales of study. Together with the diversity of technologies involved in data collection at multiple scales, robust, well-validated physiological models describing the complex behavior of stomata at the leaf level are essential for interpretation and simulation. Understanding and predicting larger scale carbon, water, and energy cycles requires accurate estimates of the leaf diffusive (stomatal) to water and CO2 and for these and are in using stomatal conductance models. Despite in the and of these models, some of the most stomatal to environmental as the response to CO2 and water and 2011; Chater et al., 2011; et al., 2011; 2013; et al., Franks and 2016). The scales of influence of temporal and spatial scales of is a in the tools and technologies illustrated are leaf gas-exchange and the latter a of climate data also are examples of the influence of stomatal feedback to at are change in CO2 change in primary productivity change in global primary productivity and change in global surface The of change is illustrated with and the feedback effect of stomata on across scales of stomatal is their role as feedback in Franks et al., 2013). stomata as negative and feedback on the their primary role of maintaining leaf and optimizing the biological economics of stomata are negative feedback control as the of this negative feedback control at the leaf level are as a feedback forcing of climate processes at the for the of stomatal at larger scales remains a on stomatal and of change across temporal and spatial scales, with on methods to for the role of stomata simulating global carbon, water, and energy fluxes in global models. The temporal scale to of and the spatial scale leaf to The fossil record reveals strong of change in stomatal through periods (Edwards et al., 1998; Franks and Beerling, The from on the coupling between vegetation and climate (Bonan, and the influence of stomatal on leaf gas exchange (Franks and are that these in global vegetation and has to the and these particularly in the of they the current of Earth’s environmental of the from the that stomatal of in leaf preserved the last is with the in atmospheric CO2 concentration that time is now well from studies at elevated and a time as as the and of a leaf, plants in response to a change in This is in the that to the physiological of the change in a (e.g. with a increases stomatal conductance to the in CO2 Franks et al., 2013). remains this is to this for the of the response of to change in a has proven time scales, are strong in including of et al., 2003; et al., 2005; et al., as well as in the response and time scales (Franks et al., 2013). This has in to the change in in leaf as a proxy for change in global a 2014). for the response of to a has that of leaf gas-exchange et al., but this and studies that the of to a was that by to for and change in a from to a of to response in this of From the many of studies that have it that the is than as as to in a on (Franks et al., This of to a be in the interpretation of studies involving the of particularly a is by a of as in many CO2 key to in the of changing a on stomatal is its with stomatal size the diffusive conductance to CO2 and water and in to be to in and it is the of and that and is a negative between and at scales, including a (Franks et al., across in a and Woodward, 2003; et al., 2010), through the fossil record (Franks and Beerling, and across of a is to by et al., et al., 2014; Franks et al., 2015). This negative as a negative the and evolution of stomata forcing by environmental leaf gas achieve a and plants and the of a negative that the of leaf to gas exchange et al., 2016). for stomatal conductance is to and (Franks and Beerling, The by et has its of physical by the and of stomata and the size of the genome that is the of guard be fully stomata to be by at least one the et al., 2000; et al., 2014), and stomatal guard be than their vascular of the than in stomatal size stomatal conductance (Franks and Beerling, is to the evolution of plant genome size et al., and Franks et al., and the This widely observed between stomatal guard cell and plant genome size has the to be that for stomatal conductance for in and genome size (Franks et al., The role of that size and also must be including in the et al., 2013). genome size a on stomatal size and gas-exchange then the of genome size be a significant in the current of across landscapes and of the most of focus has the evolution of the stomatal control in the of of stomatal to CO2 and water as well as by the This is because and models of stomatal control the and of and of studies have that stomatal to CO2 and evolved first in plants and and are in vascular plants of more as and et al., 2009; and 2013; and 2015). These studies the evolution of stomatal particularly in response to water was to as the and 2011; also as the model in and 2012). This has in a of studies a of including and leaf gas-exchange which that stomatal to and CO2 are to land plant et al., 2011; et al., 2011; et al., Franks and 2016; et al., et al., and control are in land plant this that they one stomatal control mechanism (Franks and 2016). This model for stomatal control is illustrated in Figure the model be as a of the model in which of the and with the stomatal response to elevated CO2 and water are from plants now to CO2 in and Franks and 2016; in However, some remains on stomatal is et al., 2016). current models for the evolution of stomatal the and models. models the key of the stomatal control and the evolution of these as plant The plant with are with to their not to The between the models is that the model in some of the of and stomatal control in plant the model that stomatal control including to elevated CO2 and evolved first in in the of and are in involved in of the stomatal control and their feedback control in the regulation of stomatal different resulting from response to response to water response to water potential by and response to elevated model and control in land plants not stomatal the of and feedback control in stomata of as well as of these have to as land plants as a many plant However, the and of stomata in land plant guard that with to for gas a stomatal control model a to the and processes that stomatal and physiological is to fully the and of and stomatal control across the diversity of vascular and plant gas exchange requires a of the of the behavior of stomata for the of plant gas exchange requires some of the stomatal control mechanism and its accurate models of stomatal from of processes the behavior of leaf gas-exchange is the for of guard cell et al., 2012). from of guard cell and has not to the behavior of stomata but to processes the guard cell that were improving the of stomatal et al., et al., 2014). of this more across plant on accurate of the processes stomatal behavior in plant some of these processes are to be in then the and of models have to be Stomatal conductance models applied to larger spatial scales et al., et al., and et al., 2009; et al., The because stomatal conductance models are on physiological and of and models require in of the models one of has but is now a in the of these approaches and with on studies have applied to model plant gas exchange and et al., et al., 2011; et al., 2014), it has not as widely as have from Stomatal control of leaf gas exchange was in of ago and but stomatal control has using approaches et al., 2010). with the of is the of of the of transpiration and CO2 to in stomatal conductance to water as the et al., Stomatal conductance is at some it Stomatal these it to the plant has a of with the least of water in with and on the of this which the of a for to of plant and to the a methods have for for in gas-exchange models stomatal but this requires some the of and in the plant vegetation of as well as a of that be with the et al., This is to a of to atmospheric CO2 for a model the in the model et al., The widely observed of a for a leaf conditions, a by the control of stomatal conductance for some conditions, has applied in the of plant gas including time (Franks et al., 2014). that a some it with water et al., and across it to be in plants with capacity (Franks and a is and as with it is not for of the of and on plant and for the of must be and for the plant vegetation of in the of these in different plant the capacity of stomatal models to plant gas must be the of approaches with surface models the fluxes of and CO2 between the land and These models, with models of atmospheric and the terrestrial of models. to models is the regulation of transpiration and by The of is in to the model as However, it is from that is of the the of et al., also is to it be that plants with 1, and this has observed et al., 2015). The 1, the physiological that plant The of the model is that it is by the leaf with for leaf CO2 concentration, in of the et al., to well as which is This connection is because 1, are of plant more its as However, with the the model a for tools and plant and its the and models the physiological The primary for this is illustrated in Figure which the global between and for plants at current current atmospheric CO2 1, a require a of but for plants the with increasing The is not as for because of their than for the plants with capacity for to and 1, and is in Figure of with across in leaf gas-exchange capacity and data is from data by et between CO2 and stomatal conductance to water for with from that are for atmospheric CO2 concentration and a of leaf The is a a in representing with increasing for in using above than The is values by the model 1, and as in et al., to of the data from et representing plants in and plants from a temperate are for the to are as values as in for of the different are as temperate boreal the model is applied to the data for plants from by of and a of the gas-exchange behavior of global vegetation well is for this that of for applied a for in global for plants and for plants (Bonan et al., 2011; et al., et has with in which a of is applied et al., et al., 2015). also has with for and values to the plant in et is to this also to potential values of to global biomes are illustrated in Figure temperate and boreal and it is to values of 1, and a for values of as in These different of potential for as in global models. for are for different plant as the et stomatal model in et al., et al., and in the simulations in and These values are on by et but in some values are from for 1, and a using and the model as was the for et from gas-exchange with values for 1, a have simulations the similarities and the stomatal models. Figure simulations of for the model as in using the global of for plants (Bonan et al., is the of the model et al., with for and a model (Bonan et al., 2014), with water which was by et for with regard to these simulations is the for in the model was for the condition of CO2 in land surface models, is as in the minimum of and of leaf stomatal in response to CO2 concentration at the leaf at the leaf surface at atmospheric and leaf are for the model et al., with and the model et al., with and and the model (Bonan et al., 2014), with water simulations the et model as in (Bonan et al., 2011) with values for the plant The of potential to is conditions for the simulations were as µmol µmol µmol for and leaf were the was that on the these boundary conductance was is to models of stomatal conductance to and and in this has stomatal conductance with the models. models, stomatal conductance with atmospheric CO2 concentrations than as has by et al., The model in this in their response to The has a in stomatal conductance with increasing and have stomatal conductance at low but this as The in with the and models in Figure result from the values for and and is to in and is at in the of to and are between the models and that a of is to a of using with these the stomatal to are the to However, a larger stomatal conductance at low with and stomatal conductance at larger has a larger to than is with the from water CO2 in the to water CO2 the model with the and models for and the model with the model for The CO2 response of the model and model simulations at CO2 concentrations than but from models at et also that the and model to the model be to The and simulations in Figure are at a leaf leaf the response of in the model and but with to the of and values in for the and models. were as in Figure but with for and water CO2 for the and stomatal to CO2 are the model estimates stomatal conductance with CO2 concentrations than The in and are with a of potential to of the to and increasing to water CO2 at agreement the models for the response of to CO2 maintaining the close agreement the models for response to and and with and The effect on the and model but in with the it the model CO2 to the and This is because the in the of at a CO2 concentration et al., which better with models that in of with highlight this in models, the CO2 response for to the of and increasing were as in Figure but was to and was to water CO2 at of on stomatal to were as in Figure but with for the and models. The simulations in Figure that stomatal to in atmospheric CO2 concentration from to with by to and This is with reduction in CO2 studies as CO2 increases from to and the in stomatal conductance increases to to the in stomatal conductance is to the of atmospheric CO2 concentration but at CO2 concentration, the is These for models, the observed in with elevated CO2 is significantly influenced by the also highlight the potential influence of and its in plants different atmospheric CO2 concentrations on the of to in stomatal conductance with in atmospheric CO2 concentration from to is for simulations using different stomatal conductance models and as for to in the simulations from the model in to is as the and The effect of this is to the transition between the and is a transition in stomatal conductance a of atmospheric CO2 concentration, in et a and that it was in the resulting from the of the et model that at the scale of the The CO2 response for with the of is more of leaf and larger scales the behavior of many of in different is simulations with the and models for a highlight the similarities the models. et a canopy parameterization for with and the model at the stomatal models and in this in with at in et al., 2014). The model with with the than the model and better the and the model the water also the data between the and models. This result is with the leaf simulations in Figure but model simulations with the data are the uncertainty in of simulations of using the and models, data above the the as by et model with model with the model with the water model with from to model with from to model with from to water The is the for the the is the for the and the is the from the in the model to with in the model to with and in the model to water CO2 with a more realistic between the models. a that with the in the the of the model to the data and was to the model and and values to with the of for the from the the and model simulations were to with and it is that parameterization of 1, and in the and models, and in the and models, the land surface model to data from simulations with the and models in the potential influence that in the parameterization of and have on estimates of water and carbon fluxes. simulations using and atmospheric forcing data for to from the and for data et al., 2016). is agreement between simulations using the stomatal conductance model in and but some simulations using with the values for different plant to simulations using with a global of for plants and for result in primary productivity in the and and surface is in the and and with this increases transpiration to in the that were with of the model for in et al., et al., 2015). simulations with also but the model reduces in model et al., 2015). these are substantially plant in simulations using the stomatal conductance model are different values that with the values for plant than a of for plants and with and and and with and The are transpiration increases that has surface with the simulations using values in and with for the leaf and canopy scales these global simulations that vegetation models the model for stomatal conductance the are values for plant the of empirical-based and optimization-based models of in global land surface models in to methods are of stomatal model parameterization on global were in the global model the et stomatal conductance model with values in simulations using the stomatal conductance model with a global of for plants and for The is as were by using and and for atmospheric forcing data for to and primary productivity and surface for of the and in and but for the are parameterization of stomatal conductance models in global The of global simulations was as in Figure that of using a of for simulations with the stomatal conductance different plant were values for 1, from the values for plant using This the between simulations using the stomatal conductance The and of stomatal conductance models is for in the of soil is to stomatal closure in models diffusive limitations in response to soil by 1, with a shift to at a more physiological stomatal conductance drought. models limitations and reduce stomatal conductance by as soil increases models scale with than with limitation on et al., et al., 2011; et al., and diffusive and limitations must be et al., 2013). is also uncertainty the of the soil and 2014). a is model to in land surface models the process of plant water uptake and the of plant on stomata (Bonan et al., 2014; et al., 2016; et al., 2016). The role of stomata in processes and the coevolution of this have with knowledge and better of geological, and global and at scale of but is a role for studies at one scale to at the level are the in some the of of the stomatal conductance control mechanism and its behavior multiple and environmental The of more realistic representation of stomatal conductance and its regulation of leaf gas exchange in global models is improving global simulations of carbon, water, and energy fluxes, and these simulations with in turn highlight some of the limitations with current leaf-scale models. Our analysis of current leaf-scale models of stomatal conductance representing empirical-based optimization-based approaches reveals close structural similarities that virtually and indistinguishable in simulations of leaf, canopy, and global fluxes. for land model","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"peer_reviewed":null,"categories":["Plant Water Relations and Carbon Dynamics"],"details":null,"provenance":"openalex","attribution":"Abstract of \"Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models\" by Peter J. Franks, Joseph A. Berry, Danica Lombardozzi et al., https://doi.org/10.1104/pp.17.00287, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.5194/hess-17-4297-2013","kind":"article","title":"A thermodynamic approach to link self-organization, preferential flow and rainfall–runoff behaviour","authors":["Erwin Zehe","Uwe Ehret","Theresa Blume","Axel Kleidon","Ulrike Scherer","Martijn C. Westhoff"],"author_count":6,"year":2013,"published":"2013-11-01","venue":"Hydrology and earth system sciences","cited_by":80,"doi":"10.5194/hess-17-4297-2013","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.5194/hess-17-4297-2013","archive_url":"https://space-kitty.com/papers/doi:10.5194/hess-17-4297-2013","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2119987059","pdf_url":"https://hess.copernicus.org/articles/17/4297/2013/hess-17-4297-2013.pdf","abstract":"Abstract. This study investigates whether a thermodynamically optimal hillslope structure can, if existent, serve as a first guess for uncalibrated predictions of rainfall–runoff. To this end we propose a thermodynamic framework to link rainfall–runoff processes and dynamics of potential energy, kinetic energy and capillary binding energy in catchments and hillslopes. The starting point is that hydraulic equilibrium in soil corresponds to local thermodynamic equilibrium (LTE), characterized by a local maximum entropy/minimum of free energy of soil water. Deviations from LTE occur either due to evaporative losses, which increase absolute values of negative capillary binding energy of soil water and reduce its potential energy, or due to infiltration of rainfall, which increases potential energy of soil water and reduces the strength of capillary binding energy. The amplitude and relaxation time of these deviations depend on climate, vegetation, soil hydraulic functions, topography and density of macropores. Based on this framework we analysed the free energy balance of hillslopes within numerical experiments that perturbed model structures with respect to the surface density of macropores. These model structures have been previously shown to allow successful long-term simulations of the water balances of the Weiherbach and the Malalcahuello catchments, which are located in distinctly different pedological and climatic settings. Our findings offer a new perspective on different functions of preferential flow paths depending on the pedological setting. Free energy dynamics of soil water in the cohesive soils of the Weiherbach is dominated by dynamics of capillary binding energy. Macropores act as dissipative wetting structures by enlarging water flows against steep gradients in soil water potential after long dry spells. This implies accelerated depletion of these gradients and faster relaxation back towards LTE. We found two local optima in macropore density that maximize reduction rates of free energy of soil water during rainfall-driven conditions. These two optima exist because reduction rates of free energy are, in this case, a second-order polynomial of the wetting rate, which implicitly depends on macroporosity. An uncalibrated long-term simulation of the water balance of the Weiherbach catchment based on the first optimum macroporosity performed almost as well as the best fit when macroporosity was calibrated to match rainfall–runoff. In the Malalcahuello catchment we did not find an apparent optimum density of macropores, because free energy dynamics of soil water during rainfall-driven conditions is dominated by increases of potential energy. Macropores act as dissipative drainage structures by enhancing export of potential energy. No optimum macropore density exists in this case because potential energy change rates scale linearly with the wetting rate. We found, however, a distinguished macroporosity that assures steady-state conditions of the potential energy balance of the soil, in the sense that average storage of potential energy is compensated by average potential energy export. This distinguished macroporosity was close to the value that yielded the best fit of rainfall–runoff behaviour during a calibration exercise and allowed a robust estimate of the annual runoff coefficient. Our findings are promising for predictions in ungauged catchments (PUB) as the optimal/distinguished model structures can serve as a first guess for uncalibrated predictions of rainfall–runoff. They also offer an alternative for classifying catchments according to their similarity of the free energy balance components.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"peer_reviewed":null,"categories":["Soil and Unsaturated Flow"],"details":null,"provenance":"openalex","attribution":"Abstract of \"A thermodynamic approach to link self-organization, preferential flow and rainfall–runoff behaviour\" by Erwin Zehe, Uwe Ehret, Theresa Blume et al., https://doi.org/10.5194/hess-17-4297-2013, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"doi:10.1016/j.ijpe.2016.02.004","kind":"article","title":"Closed loop supply chain networks: Designs for energy and time value efficiency","authors":["Dinesh K. Kadambala","Nachiappan Subramanian","Manoj Kumar Tiwari","Muhammad Dan-Asabe Abdulrahman","Chang Liu"],"author_count":5,"year":2016,"published":"2016-02-16","venue":"International Journal of Production Economics","cited_by":79,"doi":"10.1016/j.ijpe.2016.02.004","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.ijpe.2016.02.004","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.ijpe.2016.02.004","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2283878895","pdf_url":null,"abstract":null,"abstract_license":null,"license":"cc-by","is_open_access":true,"peer_reviewed":null,"categories":["Sustainable Supply Chain Management"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"arxiv:1903.05956","kind":"article","title":"Fast Approximate Shortest Paths in the Congested Clique","authors":["Keren Censor-Hillel","Michal Dory","Janne H. Korhonen","Dean Leitersdorf"],"author_count":4,"year":2019,"published":"2019-03-14","venue":"Distributed Computing","cited_by":43,"doi":"10.1007/s00446-020-00380-5","arxiv_id":"1903.05956","nct_id":null,"source_url":"https://arxiv.org/abs/1903.05956","archive_url":"https://space-kitty.com/papers/arxiv:1903.05956","updated":"2019-10-31","pmid":null,"pmcid":null,"openalex_id":"W2921999720","pdf_url":"https://arxiv.org/pdf/1903.05956","abstract":"We design fast deterministic algorithms for distance computation in the congested clique model. Our key contributions include: -- A $(2+ε)$-approximation for all-pairs shortest paths in $O(\\log^2{n} / ε)$ rounds on unweighted undirected graphs. With a small additional additive factor, this also applies for weighted graphs. This is the first sub-polynomial constant-factor approximation for APSP in this model. -- A $(1+ε)$-approximation for multi-source shortest paths from $O(\\sqrt{n})$ sources in $O(\\log^2{n} / ε)$ rounds on weighted undirected graphs. This is the first sub-polynomial algorithm obtaining this approximation for a set of sources of polynomial size. Our main techniques are new distance tools that are obtained via improved algorithms for sparse matrix multiplication, which we leverage to construct efficient hopsets and shortest paths. Furthermore, our techniques extend to additional distance problems for which we improve upon the state-of-the-art, including diameter approximation, and an exact single-source shortest paths algorithm for weighted undirected graphs in $\\tilde{O}(n^{1/6})$ rounds.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":null,"categories":["cs.DC","cs.DS"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"arxiv:1601.04640","kind":"article","title":"CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap","authors":["Vladimir Lončar","Antun Balaž","Aleksandar Bogojević","Srdjan Škrbić","Paulsamy Muruganandam","Sadhan K. Adhikari"],"author_count":6,"year":2015,"published":"2015-12-18","venue":"Computer Physics Communications","cited_by":62,"doi":"10.1016/j.cpc.2015.11.014","arxiv_id":"1601.04640","nct_id":null,"source_url":"https://doi.org/10.1016/j.cpc.2015.11.014","archive_url":"https://space-kitty.com/papers/arxiv:1601.04640","updated":"2022-08-01","pmid":null,"pmcid":null,"openalex_id":"W2208560416","pdf_url":"https://ars.els-cdn.com/content/image/1-s2.0-S0010465515004361-gr1_lrg.jpg","abstract":"In this paper we present new versions of previously published numerical programs for solving the dipolar Gross-Pitaevskii (GP) equation including the contact interaction in two and three spatial dimensions in imaginary and in real time, yielding both stationary and non-stationary solutions. New versions of programs were developed using CUDA toolkit and can make use of Nvidia GPU devices. The algorithm used is the same split-step semi-implicit Crank-Nicolson method as in the previous version (R. Kishor Kumar et al., Comput. Phys. Commun. 195, 117 (2015)), which is here implemented as a series of CUDA kernels that compute the solution on the GPU. In addition, the Fast Fourier Transform (FFT) library used in the previous version is replaced by cuFFT library, which works on CUDA-enabled GPUs. We present speedup test results obtained using new versions of programs and demonstrate an average speedup of 12 to 25, depending on the program and input size.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":true,"peer_reviewed":null,"categories":["Cold Atom Physics and Bose-Einstein Condensates"],"details":null,"provenance":"openalex+arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"doi:10.1016/j.jnnfm.2019.04.003","kind":"article","title":"A new finite element formulation for viscoelastic flows: Circumventing simultaneously the LBB condition and the high-Weissenberg number problem","authors":["Stylianos Varchanis","Alexandros Syrakos","Yannis Dimakopoulos","JOHN A. TSAMOPOULOS"],"author_count":4,"year":2019,"published":"2019-04-13","venue":"Journal of Non-Newtonian Fluid Mechanics","cited_by":59,"doi":"10.1016/j.jnnfm.2019.04.003","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.jnnfm.2019.04.003","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.jnnfm.2019.04.003","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2937757426","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Advanced Numerical Methods in Computational Mathematics"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"arxiv:1610.05329","kind":"article","title":"OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross–Pitaevskii equation","authors":["Vladimir Lončar","Luis E. Young-S.","Srdjan Škrbić","Paulsamy Muruganandam","Sadhan K. Adhikari","Antun Balaž"],"author_count":6,"year":2016,"published":"2016-09-09","venue":"Computer Physics Communications","cited_by":59,"doi":"10.1016/j.cpc.2016.07.029","arxiv_id":"1610.05329","nct_id":null,"source_url":"https://doi.org/10.1016/j.cpc.2016.07.029","archive_url":"https://space-kitty.com/papers/arxiv:1610.05329","updated":"2022-08-01","pmid":null,"pmcid":null,"openalex_id":"W2514049505","pdf_url":"https://ars.els-cdn.com/content/image/1-s2.0-S0010465516302272-gr1_lrg.jpg","abstract":"We present new versions of the previously published C and CUDA programs for solving the dipolar Gross-Pitaevskii equation in one, two, and three spatial dimensions, which calculate stationary and non-stationary solutions by propagation in imaginary or real time. Presented programs are improved and parallelized versions of previous programs, divided into three packages according to the type of parallelization. First package contains improved and threaded version of sequential C programs using OpenMP. Second package additionally parallelizes three-dimensional variants of the OpenMP programs using MPI, allowing them to be run on distributed-memory systems. Finally, previous three-dimensional CUDA-parallelized programs are further parallelized using MPI, similarly as the OpenMP programs. We also present speedup test results obtained using new versions of programs in comparison with the previous sequential C and parallel CUDA programs. The improvements to the sequential version yield a speedup of 1.1 to 1.9, depending on the program. OpenMP parallelization yields further speedup of 2 to 12 on a 16-core workstation, while OpenMP/MPI version demonstrates a speedup of 11.5 to 16.5 on a computer cluster with 32 nodes used. CUDA/MPI version shows a speedup of 9 to 10 on a computer cluster with 32 nodes.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":true,"peer_reviewed":null,"categories":["Parallel Computing and Optimization Techniques"],"details":null,"provenance":"openalex+arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"doi:10.1016/j.fuel.2019.116486","kind":"article","title":"Modelling of fully-coupled CO2 diffusion and adsorption-induced coal matrix swelling","authors":["K.H.S.M. Sampath","M.S.A. Perera","Stephan Konrad Matthai","Pathegama Gamage Ranjith","Dongyin Li"],"author_count":5,"year":2019,"published":"2019-11-06","venue":"Fuel","cited_by":57,"doi":"10.1016/j.fuel.2019.116486","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.fuel.2019.116486","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.fuel.2019.116486","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2988003731","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Coal Properties and Utilization"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"arxiv:1705.02044","kind":"preprint","title":"A Survey of Shortest-Path Algorithms","authors":["Amgad Madkour","Walid G. Aref","Faizan Ur Rehman","Mohamed Abdur Rahman","Saleh Basalamah"],"author_count":5,"year":2017,"published":"2017-05-04","venue":null,"cited_by":58,"doi":null,"arxiv_id":"1705.02044","nct_id":null,"source_url":"https://arxiv.org/abs/1705.02044","archive_url":"https://space-kitty.com/papers/arxiv:1705.02044","updated":"2017-05-04","pmid":null,"pmcid":null,"openalex_id":"W2612665926","pdf_url":"https://arxiv.org/pdf/1705.02044","abstract":"A shortest-path algorithm finds a path containing the minimal cost between two vertices in a graph. A plethora of shortest-path algorithms is studied in the literature that span across multiple disciplines. This paper presents a survey of shortest-path algorithms based on a taxonomy that is introduced in the paper. One dimension of this taxonomy is the various flavors of the shortest-path problem. There is no one general algorithm that is capable of solving all variants of the shortest-path problem due to the space and time complexities associated with each algorithm. Other important dimensions of the taxonomy include whether the shortest-path algorithm operates over a static or a dynamic graph, whether the shortest-path algorithm produces exact or approximate answers, and whether the objective of the shortest-path algorithm is to achieve time-dependence or is to only be goal directed. This survey studies and classifies shortest-path algorithms according to the proposed taxonomy. The survey also presents the challenges and proposed solutions associated with each category in the taxonomy.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":false,"categories":["cs.DS"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"arxiv:1712.09121","kind":"article","title":"Improved Distributed Algorithms for Exact Shortest Paths","authors":["Mohsen Ghaffari","Jason Li"],"author_count":2,"year":2017,"published":"2017-12-25","venue":"ACM Symposium on Theory of Computing (STOC)","cited_by":54,"doi":"10.1145/3188745.3188948","arxiv_id":"1712.09121","nct_id":null,"source_url":"https://arxiv.org/abs/1712.09121","archive_url":"https://space-kitty.com/papers/arxiv:1712.09121","updated":"2018-04-11","pmid":null,"pmcid":null,"openalex_id":"W2963948050","pdf_url":"https://arxiv.org/pdf/1712.09121","abstract":"Computing shortest paths is one of the central problems in the theory of distributed computing. For the last few years, substantial progress has been made on the approximate single source shortest paths problem, culminating in an algorithm of Becker et al. [DISC'17] which deterministically computes $(1+o(1))$-approximate shortest paths in $\\tilde O(D+\\sqrt n)$ time, where $D$ is the hop-diameter of the graph. Up to logarithmic factors, this time complexity is optimal, matching the lower bound of Elkin [STOC'04]. The question of exact shortest paths however saw no algorithmic progress for decades, until the recent breakthrough of Elkin [STOC'17], which established a sublinear-time algorithm for exact single source shortest paths on undirected graphs. Shortly after, Huang et al. [FOCS'17] provided improved algorithms for exact all pairs shortest paths problem on directed graphs. In this paper, we present a new single-source shortest path algorithm with complexity $\\tilde O(n^{3/4}D^{1/4})$. For polylogarithmic $D$, this improves on Elkin's $\\tilde{O}(n^{5/6})$ bound and gets closer to the $\\tildeΩ(n^{1/2})$ lower bound of Elkin [STOC'04]. For larger values of $D$, we present an improved variant of our algorithm which achieves complexity $\\tilde{O}\\left( n^{3/4+o(1)}+ \\min\\{ n^{3/4}D^{1/6},n^{6/7}\\}+D\\right)$, and thus compares favorably with Elkin's bound of $\\tilde{O}(n^{5/6} + n^{2/3}D^{1/3} + D ) $ in essentially the entire range of parameters. This algorithm provides also a qualitative improvement, because it works for the more challenging case of directed graphs (i.e., graphs where the two directions of an edge can have different weights), constituting the first sublinear-time algorithm for directed graphs. Our algorithm also extends to the case of exact $κ$-source shortest paths...","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":null,"categories":["cs.DC","cs.DS"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"arxiv:2311.18295","kind":"article","title":"Almost-Linear Time Algorithms for Incremental Graphs: Cycle Detection, SCCs, $s$-$t$ Shortest Path, and Minimum-Cost Flow","authors":["Li Chen","Rasmus Kyng","Yang P. Liu","Simon Meierhans","Maximilian Probst Gutenberg"],"author_count":5,"year":2023,"published":"2023-11-30","venue":"ACM Symposium on Theory of Computing (STOC)","cited_by":12,"doi":"10.1145/3618260.3649745","arxiv_id":"2311.18295","nct_id":null,"source_url":"https://arxiv.org/abs/2311.18295","archive_url":"https://space-kitty.com/papers/arxiv:2311.18295","updated":"2023-11-30","pmid":null,"pmcid":null,"openalex_id":"W4399522860","pdf_url":"https://arxiv.org/pdf/2311.18295","abstract":"We give the first almost-linear time algorithms for several problems in incremental graphs including cycle detection, strongly connected component maintenance, $s$-$t$ shortest path, maximum flow, and minimum-cost flow. To solve these problems, we give a deterministic data structure that returns a $m^{o(1)}$-approximate minimum-ratio cycle in fully dynamic graphs in amortized $m^{o(1)}$ time per update. Combining this with the interior point method framework of Brand-Liu-Sidford (STOC 2023) gives the first almost-linear time algorithm for deciding the first update in an incremental graph after which the cost of the minimum-cost flow attains value at most some given threshold $F$. By rather direct reductions to minimum-cost flow, we are then able to solve the problems in incremental graphs mentioned above. At a high level, our algorithm dynamizes the $\\ell_1$ oblivious routing of Rozhoň-Grunau-Haeupler-Zuzic-Li (STOC 2022), and develops a method to extract an approximate minimum ratio cycle from the structure of the oblivious routing. To maintain the oblivious routing, we use tools from concurrent work of Kyng-Meierhans-Probst Gutenberg which designed vertex sparsifiers for shortest paths, in order to maintain a sparse neighborhood cover in fully dynamic graphs. To find a cycle, we first show that an approximate minimum ratio cycle can be represented as a fundamental cycle on a small set of trees resulting from the oblivious routing. Then, we find a cycle whose quality is comparable to the best tree cycle. This final cycle query step involves vertex and edge sparsification procedures reminiscent of previous works, but crucially requires a more powerful dynamic spanner which can handle far more edge insertions. We build such a spanner via a construction that hearkens back to the classic greedy spanner algorithm.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":null,"categories":["cs.DS"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"doi:10.1002/hyp.13780","kind":"article","title":"Non‐linear quickflow response as indicators of runoff generation mechanisms","authors":["Charles I. Scaife","Nitin K. Singh","R. E. Emanuel","Chelcy Ford Miniat","Lawrence E. Band"],"author_count":5,"year":2020,"published":"2020-04-15","venue":"Hydrological Processes","cited_by":48,"doi":"10.1002/hyp.13780","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1002/hyp.13780","archive_url":"https://space-kitty.com/papers/doi:10.1002/hyp.13780","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W3017298719","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Hydrology and Watershed Management Studies"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"doi:10.1016/j.apenergy.2010.11.006","kind":"article","title":"Experimental investigation of frost formation on a parallel flow evaporator","authors":["Jianghong Wu","Guang Ouyang","Puxiu Hou","Haobin Xiao"],"author_count":4,"year":2010,"published":"2010-12-10","venue":"Applied Energy","cited_by":53,"doi":"10.1016/j.apenergy.2010.11.006","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.apenergy.2010.11.006","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.apenergy.2010.11.006","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2121043278","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Refrigeration and Air Conditioning Technologies"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"arxiv:2203.00671","kind":"preprint","title":"Maximum Flow and Minimum-Cost Flow in Almost-Linear Time","authors":["Li Chen","Rasmus Kyng","Yang P. Liu","Richard Peng","Maximilian Probst Gutenberg","Sushant Sachdeva"],"author_count":6,"year":2022,"published":"2022-03-01","venue":null,"cited_by":12,"doi":null,"arxiv_id":"2203.00671","nct_id":null,"source_url":"https://arxiv.org/abs/2203.00671","archive_url":"https://space-kitty.com/papers/arxiv:2203.00671","updated":"2022-04-22","pmid":null,"pmcid":null,"openalex_id":"W4224930729","pdf_url":"https://arxiv.org/pdf/2203.00671","abstract":"We give an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with $m$ edges and polynomially bounded integral demands, costs, and capacities in $m^{1+o(1)}$ time. Our algorithm builds the flow through a sequence of $m^{1+o(1)}$ approximate undirected minimum-ratio cycles, each of which is computed and processed in amortized $m^{o(1)}$ time using a new dynamic graph data structure. Our framework extends to algorithms running in $m^{1+o(1)}$ time for computing flows that minimize general edge-separable convex functions to high accuracy. This gives almost-linear time algorithms for several problems including entropy-regularized optimal transport, matrix scaling, $p$-norm flows, and $p$-norm isotonic regression on arbitrary directed acyclic graphs.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":true,"peer_reviewed":false,"categories":["cs.DS"],"details":null,"provenance":"arxiv+openalex","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"doi:10.1007/s11207-018-1365-7","kind":"article","title":"Subsurface Zonal and Meridional Flow During Cycles 23 and 24","authors":["Rudolf W. Komm","R. Howe","F. Hill"],"author_count":3,"year":2018,"published":"2018-10-01","venue":"Solar Physics","cited_by":44,"doi":"10.1007/s11207-018-1365-7","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1007/s11207-018-1365-7","archive_url":"https://space-kitty.com/papers/doi:10.1007/s11207-018-1365-7","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2896287720","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Solar and Space Plasma Dynamics"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"doi:10.1109/tnet.2017.2786268","kind":"article","title":"Minimizing Controller Response Time Through Flow Redirecting in SDNs","authors":["Pengzhan Wang","Hongli Xu","Liusheng Huang","Chen Qian","Shaowei Wang","Yanjing Sun"],"author_count":6,"year":2018,"published":"2018-01-08","venue":"IEEE/ACM Transactions on Networking","cited_by":34,"doi":"10.1109/tnet.2017.2786268","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1109/tnet.2017.2786268","archive_url":"https://space-kitty.com/papers/doi:10.1109/tnet.2017.2786268","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2783147117","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Software-Defined Networks and 5G"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"arxiv:math/0603207","kind":"article","title":"Fast matrix multiplication is stable","authors":["James Demmel","Ioana Dumitriu","Olga Holtz","Robert Kleinberg"],"author_count":4,"year":2006,"published":"2006-03-09","venue":"Numer. Math. 106 (2007), no. 2, 199-224","cited_by":77,"doi":"10.1007/s00211-007-0061-6","arxiv_id":"math/0603207","nct_id":null,"source_url":"https://arxiv.org/abs/math/0603207","archive_url":"https://space-kitty.com/papers/arxiv:math/0603207","updated":"2006-12-07","pmid":null,"pmcid":null,"openalex_id":"W2147348850","pdf_url":"https://arxiv.org/pdf/math/0603207","abstract":"We perform forward error analysis for a large class of recursive matrix multiplication algorithms in the spirit of [D. Bini and G. Lotti, Stability of fast algorithms for matrix multiplication, Numer. Math. 36 (1980), 63--72]. As a consequence of our analysis, we show that the exponent of matrix multiplication (the optimal running time) can be achieved by numerically stable algorithms. We also show that new group-theoretic algorithms proposed in [H. Cohn, and C. Umans, A group-theoretic approach to fast matrix multiplication, FOCS 2003, 438--449] and [H. Cohn, R. Kleinberg, B. Szegedy and C. Umans, Group-theoretic algorithms for matrix multiplication, FOCS 2005, 379--388] are all included in the class of algorithms to which our analysis applies, and are therefore numerically stable. We perform detailed error analysis for three specific fast group-theoretic algorithms.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":null,"categories":["math.NA","cs.CC","cs.DS","math.GR"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"doi:10.1007/s00348-019-2849-4","kind":"article","title":"Magnetic resonance velocimetry in high-speed turbulent flows: sources of measurement errors and a new approach for higher accuracy","authors":["Kristine John","Saad Jahangir","Udhav Ulhas Gawandalkar","Willian Hogendoorn","Christian Poelma","Sven Grundmann","Martin Bruschewski"],"author_count":7,"year":2020,"published":"2020-01-14","venue":"Experiments in Fluids","cited_by":32,"doi":"10.1007/s00348-019-2849-4","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1007/s00348-019-2849-4","archive_url":"https://space-kitty.com/papers/doi:10.1007/s00348-019-2849-4","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W3000392428","pdf_url":"http://resolver.tudelft.nl/uuid:6072d654-f7c5-46a6-b75b-620a05088cc0","abstract":null,"abstract_license":null,"license":"other-oa","is_open_access":true,"peer_reviewed":null,"categories":["Advanced MRI Techniques and Applications"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."},{"id":"arxiv:1708.05622","kind":"article","title":"Improved Rectangular Matrix Multiplication using Powers of the Coppersmith-Winograd Tensor","authors":["François Le Gall","Florent Urrutia"],"author_count":2,"year":2017,"published":"2017-08-18","venue":"Proceedings of the 29th ACM-SIAM Symposium on Discrete Algorithms (SODA 2018), pp. 1029-1046, 2018","cited_by":21,"doi":"10.1137/1.9781611975031.67","arxiv_id":"1708.05622","nct_id":null,"source_url":"https://arxiv.org/abs/1708.05622","archive_url":"https://space-kitty.com/papers/arxiv:1708.05622","updated":"2017-11-06","pmid":null,"pmcid":null,"openalex_id":"W2750276603","pdf_url":"https://arxiv.org/pdf/1708.05622","abstract":"In the past few years, successive improvements of the asymptotic complexity of square matrix multiplication have been obtained by developing novel methods to analyze the powers of the Coppersmith-Winograd tensor, a basic construction introduced thirty years ago. In this paper we show how to generalize this approach to make progress on the complexity of rectangular matrix multiplication as well, by developing a framework to analyze powers of tensors in an asymmetric way. By applying this methodology to the fourth power of the Coppersmith-Winograd tensor, we succeed in improving the complexity of rectangular matrix multiplication. Let $α$ denote the maximum value such that the product of an $n\\times n^α$ matrix by an $n^α\\times n$ matrix can be computed with $O(n^{2+ε})$ arithmetic operations for any $ε>0$. By analyzing the fourth power of the Coppersmith-Winograd tensor using our methods, we obtain the new lower bound $α>0.31389$, which improves the previous lower bound $α>0.30298$ obtained five years ago by Le Gall (FOCS'12) from the analysis of the second power of the Coppersmith-Winograd tensor. More generally, we give faster algorithms computing the product of an $n\\times n^k$ matrix by an $n^k\\times n$ matrix for any value $k\\neq 1$. (In the case $k=1$, we recover the bounds recently obtained for square matrix multiplication). These improvements immediately lead to improvements in the complexity of a multitude of fundamental problems for which the bottleneck is rectangular matrix multiplication, such as computing the all-pair shortest paths in directed graphs with bounded weights.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":null,"categories":["cs.DS","cs.CC"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"arxiv:1602.07013","kind":"article","title":"Improved Bounds for Shortest Paths in Dense Distance Graphs","authors":["Paweł Gawrychowski","Adam Karczmarz"],"author_count":2,"year":2016,"published":"2016-02-23","venue":null,"cited_by":13,"doi":"10.4230/lipics.icalp.2018.61","arxiv_id":"1602.07013","nct_id":null,"source_url":"https://arxiv.org/abs/1602.07013","archive_url":"https://space-kitty.com/papers/arxiv:1602.07013","updated":"2016-07-15","pmid":null,"pmcid":null,"openalex_id":"W2278003675","pdf_url":"https://arxiv.org/pdf/1602.07013","abstract":"We study the problem of computing shortest paths in so-called dense distance graphs. Every planar graph $G$ on $n$ vertices can be partitioned into a set of $O(n/r)$ edge-disjoint regions (called an $r$-division) with $O(r)$ vertices each, such that each region has $O(\\sqrt{r})$ vertices (called boundary vertices) in common with other regions. A dense distance graph of a region is a complete graph containing all-pairs distances between its boundary nodes. A dense distance graph of an $r$-division is the union of the $O(n/r)$ dense distance graphs of the individual pieces. Since the introduction of dense distance graphs by Fakcharoenphol and Rao, computing single-source shortest paths in dense distance graphs has found numerous applications in fundamental planar graph algorithms. Fakcharoenphol and Rao proposed an algorithm (later called FR-Dijkstra) for computing single-source shortest paths in a dense distance graph in $O\\left(\\frac{n}{\\sqrt{r}}\\log{n}\\log{r}\\right)$ time. We show an $O\\left(\\frac{n}{\\sqrt{r}}\\left(\\frac{\\log^2{r}}{\\log^2\\log{r}}+\\log{n}\\log^ε{r}\\right)\\right)$ time algorithm for this problem, which is the first improvement to date over FR-Dijkstra for the important case when $r$ is polynomial in $n$. In this case, our algorithm is faster by a factor of $O(\\log^2{\\log{n}})$ and implies improved upper bounds for such planar graph problems as multiple-source multiple-sink maximum flow, single-source all-sinks maximum flow, and (dynamic) exact distance oracles.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":null,"categories":["cs.DS"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"doi:10.1145/3728631","kind":"article","title":"Maximum Flow and Minimum-Cost Flow in Almost-Linear Time","authors":["Li Chen","Rasmus Kyng","Yang P. Liu","Richard Peng","Maximilian Probst Gutenberg","Sushant Sachdeva"],"author_count":6,"year":2025,"published":"2025-04-09","venue":"Journal of the ACM","cited_by":22,"doi":"10.1145/3728631","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1145/3728631","archive_url":"https://space-kitty.com/papers/doi:10.1145/3728631","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W4409280356","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728631","abstract":"We present an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with m edges and polynomially bounded integral demands, costs, and capacities in \\(m^{1+o(1)}\\) time. Our algorithm builds the flow through a sequence of \\(m^{1+o(1)}\\) approximate undirected minimum-ratio cycles, each of which is computed and processed in amortized \\(m^{o(1)}\\) time using a new dynamic graph data structure. Our framework extends to algorithms running in \\(m^{1+o(1)}\\) time for computing flows that minimize general edge-separable convex functions to high accuracy. This gives almost-linear time algorithms for several problems including entropy-regularized optimal transport, matrix scaling, p -norm flows, and p -norm isotonic regression on arbitrary directed acyclic graphs.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"peer_reviewed":null,"categories":["Complexity and Algorithms in Graphs"],"details":null,"provenance":"openalex","attribution":"Abstract of \"Maximum Flow and Minimum-Cost Flow in Almost-Linear Time\" by Li Chen, Rasmus Kyng, Yang P. Liu et al., https://doi.org/10.1145/3728631, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified."},{"id":"arxiv:cs/0008011","kind":"preprint","title":"All Pairs Shortest Paths using Bridging Sets and Rectangular Matrix Multiplication","authors":["Uri Zwick"],"author_count":1,"year":2000,"published":"2000-08-16","venue":null,"cited_by":7,"doi":null,"arxiv_id":"cs/0008011","nct_id":null,"source_url":"https://arxiv.org/abs/cs/0008011","archive_url":"https://space-kitty.com/papers/arxiv:cs/0008011","updated":"2000-08-16","pmid":null,"pmcid":null,"openalex_id":"W1552892715","pdf_url":"https://arxiv.org/pdf/cs/0008011","abstract":"We present two new algorithms for solving the {\\em All Pairs Shortest Paths} (APSP) problem for weighted directed graphs. Both algorithms use fast matrix multiplication algorithms. The first algorithm solves the APSP problem for weighted directed graphs in which the edge weights are integers of small absolute value in $\\Ot(n^{2+μ})$ time, where $μ$ satisfies the equation $ω(1,μ,1)=1+2μ$ and $ω(1,μ,1)$ is the exponent of the multiplication of an $n\\times n^μ$ matrix by an $n^μ\\times n$ matrix. Currently, the best available bounds on $ω(1,μ,1)$, obtained by Coppersmith, imply that $μ<0.575$. The running time of our algorithm is therefore $O(n^{2.575})$. Our algorithm improves on the $\\Ot(n^{(3+ω)/2})$ time algorithm, where $ω=ω(1,1,1)<2.376$ is the usual exponent of matrix multiplication, obtained by Alon, Galil and Margalit, whose running time is only known to be $O(n^{2.688})$. The second algorithm solves the APSP problem {\\em almost} exactly for directed graphs with {\\em arbitrary} non-negative real weights. The algorithm runs in $\\Ot((n^ω/\\eps)\\log (W/\\eps))$ time, where $\\eps>0$ is an error parameter and W is the largest edge weight in the graph, after the edge weights are scaled so that the smallest non-zero edge weight in the graph is 1. It returns estimates of all the distances in the graph with a stretch of at most $1+\\eps$. Corresponding paths can also be found efficiently.","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":false,"categories":["cs.DS"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"arxiv:1008.4563","kind":"article","title":"Shortest paths between shortest paths and independent sets","authors":["Marcin Kaminski","Paul Medvedev","Martin Milanic"],"author_count":3,"year":2010,"published":"2010-08-26","venue":"Lecture notes in computer science","cited_by":12,"doi":"10.1007/978-3-642-19222-7_7","arxiv_id":"1008.4563","nct_id":null,"source_url":"https://arxiv.org/abs/1008.4563","archive_url":"https://space-kitty.com/papers/arxiv:1008.4563","updated":"2011-02-07","pmid":null,"pmcid":null,"openalex_id":"W1542990689","pdf_url":"https://arxiv.org/pdf/1008.4563","abstract":"We study problems of reconfiguration of shortest paths in graphs. We prove that the shortest reconfiguration sequence can be exponential in the size of the graph and that it is NP-hard to compute the shortest reconfiguration sequence even when we know that the sequence has polynomial length. Moreover, we also study reconfiguration of independent sets in three different models and analyze relationships between these models, observing that shortest path reconfiguration is a special case of independent set reconfiguration in perfect graphs, under any of the three models. Finally, we give polynomial results for restricted classes of graphs (even-hole-free and $P_4$-free graphs).","abstract_license":"CC0-1.0 (arXiv descriptive metadata)","license":null,"is_open_access":false,"peer_reviewed":null,"categories":["cs.CC","cs.DM"],"details":null,"provenance":"arxiv","attribution":"Abstract: arXiv descriptive metadata (CC0). Thank you to arXiv for use of its open access interoperability. This service was not reviewed or approved by, nor does it necessarily express or reflect the policies or opinions of, arXiv."},{"id":"doi:10.1016/j.ijepes.2017.11.022","kind":"article","title":"Current-based Newton-Raphson power flow calculation for AT-fed railway power supply systems","authors":["Kritsada Mongkoldee","Thanatchai Kulworawanichpong"],"author_count":2,"year":2017,"published":"2017-11-29","venue":"International Journal of Electrical Power & Energy Systems","cited_by":28,"doi":"10.1016/j.ijepes.2017.11.022","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.ijepes.2017.11.022","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.ijepes.2017.11.022","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2768413823","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"peer_reviewed":null,"categories":["Optimal Power Flow Distribution"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0)."}],"next":"https://space-kitty.com/api/v1/topics/algorithms-complexity/papers?sort=top&limit=25&offset=25"}