Randomness from Determinism. Complexity Explorers Krakow.

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Is randomness actually lack of knowledge? Is everything already determined but often impossible to predict? Let’s hear it from Stephen Wolfram's point of view and see the evolution of a one-dimensional cellular automaton. Randomness from Determinism - presentation from Complexity Explorers Krakow group that is set up for learning and discussing anything related to an intersection of Philosophy and Computer Science.

Sciences

Randomness from
Determinism
Complexity Explorers Kraków
Marcin Stępień @marcinstepien Kraków 2018-09-26

src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg

src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg
www.wolframscience.com/nk
s

More at http://www.conwaylife.com/wiki/
2D Cellular Automaton

Source: Wolfram, Steven. "New Kind of Science." https://www.wolframscience.com/nks/pages/p53--more-cellular-automata/image-xlarge.png
1D Cellular Automaton

1D Cellular Automata (90th)
Weisstein, Eric W. "Elementary Cellular Automaton." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/ElementaryCellularAutomaton.html

The complete set of 256 (rules 0-255) elementary cellular automata:
http://mathworld.wolfram.com/ElementaryCellularAutomaton.html
Elementary Cellular Automaton

Patterns from All Possible Elementary Cellular Automata
Demo
PatternsFromAllPossibleElementaryCellularAutomata/

Weisstein, Eric W. "Rule 30." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/Rule30.html

Rule 30
Weisstein, Eric W. "Rule 30." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/Rule30.html

Randomness
2 approaches
By (lack) of
structure
By provienience
<<Classic>> <<AIT Complexity>>

Is Information Fundamental
src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg
https://youtu.be/aQ9Ukrt6Wc4

What Is Complexity in the Cosmos
src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg
https://youtu.be/xrXEQlvUpYI

Source: Wolfram, Steven. "New Kind of Science"

Could it be that some place out there in the
computational universe, we might find our
physical universe?
S. Wolfram
src: https://en.wikiquote.org/wiki/Stephen_Wolfram

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Context. WASP-76 b has been a recurrent subject of study since the detection of a signature in high-resolution transit spectroscopy data indicating an asymmetry between the two limbs of the planet. The existence of this asymmetric signature has been confirmed by multiple studies, but its physical origin is still under debate. In addition, it contrasts with the absence of asymmetry reported in the infrared (IR) phase curve. Aims. We provide a more comprehensive dataset of WASP-76 b with the goal of drawing a complete view of the physical processes at work in this atmosphere. In particular, we attempt to reconcile visible high-resolution transit spectroscopy data and IR broadband phase curves. Methods. We gathered 3 phase curves, 20 occultations, and 6 transits for WASP-76 b in the visible with the CHEOPS space telescope. We also report the analysis of three unpublished sectors observed by the TESS space telescope (also in the visible), which represents 34 phase curves. Results. WASP-76 b displays an occultation of 260±11 and 152±10 ppm in TESS and CHEOPS bandpasses respectively. Depending on the composition assumed for the atmosphere and the data reduction used for the IR data, we derived geometric albedo estimates that range from 0.05 ± 0.023 to 0.146 ± 0.013 and from <0.13 to 0.189 ± 0.017 in the CHEOPS and TESS bandpasses, respectively. As expected from the IR phase curves, a low-order model of the phase curves does not yield any detectable asymmetry in the visible either. However, an empirical model allowing for sharper phase curve variations offers a hint of a flux excess before the occultation, with an amplitude of ∼40 ppm, an orbital offset of ∼−30◦ , and a width of ∼20◦ . We also constrained the orbital eccentricity of WASP-76 b to a value lower than 0.0067, with a 99.7% confidence level. This result contradicts earlier proposed scenarios aimed at explaining the asymmetry observed in high-resolution transit spectroscopy. Conclusions. In light of these findings, we hypothesise that WASP-76 b could have night-side clouds that extend predominantly towards its eastern limb. At this limb, the clouds would be associated with spherical droplets or spherically shaped aerosols of an unknown species, which would be responsible for a glory effect in the visible phase curves.

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Mustard, as a crop, is susceptible to a variety of pests that can affect its growth and yield. Here’s a rundown of some common pests that target mustard plants: Aphids: These small, sap-sucking insects can cause significant damage by feeding on the leaves and stems. Aphids also excrete a sticky substance known as honeydew, which can lead to the growth of sooty mold on the plants. Flea Beetles: These tiny beetles jump like fleas when disturbed and chew small holes in the leaves. They are particularly damaging in the early growth stages of the plant. Cabbage Loopers: The larvae of a type of moth, these caterpillars are known for their distinctive looping movement. They chew large holes in the leaves and can defoliate plants if present in large numbers. Diamondback Moth Larvae: Another caterpillar pest, these larvae chew small holes in the leaves and can cause extensive damage, especially when infestations are heavy. Whiteflies: These are tiny, winged insects that feed on plant sap and can quickly become a problem in greenhouse or close planting conditions. Like aphids, they also secrete honeydew. Cutworms: These are the larvae of certain types of moths and are known for cutting young plants at the stem base at ground level. They are most destructive during the night. Root Maggots: The larvae of root maggot flies, these pests attack the roots of mustard plants, causing wilting and potentially killing young plants. Harlequin Bugs: These are colorful stink bugs that suck the sap from mustard plant stems and leaves, causing the leaves to become stippled, wilt, and eventually die if the infestation is severe. Mustard Sawfly: The larvae of the mustard sawfly can cause considerable defoliation, as they feed voraciously on the leaves. Clubroot: Caused by a fungus-like organism, clubroot affects the roots, causing them to swell and distort. While technically a disease, it is often associated with pest management because controlling it involves similar preventative strategies. Control Measures: Managing pests in mustard involves a combination of cultural, biological, and chemical methods. Crop rotation, resistant varieties, timely sowing, maintaining plant health, and using natural predators like ladybugs and parasitic wasps can help keep pest populations under control. Chemical pesticides should be used as a last resort due to their potential impact on the environment and non-target species.

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Bollworms are among the most damaging pests in cotton cultivation, affecting the bolls where the cotton fibers are formed. There are several species of bollworms, each capable of causing significant yield loss and quality degradation if not effectively managed. Here’s a detailed look at the primary bollworm species affecting cotton: Cotton Bollworm (Helicoverpa armigera): Also known as the corn earworm or the Old World bollworm, this pest is found in many regions around the world. It is highly polyphagous (feeds on many different plants) and poses a threat not only to cotton but also to maize, tomatoes, and legumes. The larvae bore into the cotton bolls, feeding on the developing seeds and fibers, which can lead to boll rot. Pink Bollworm (Pectinophora gossypiella): A significant pest of cotton, the pink bollworm larvae infest the cotton bolls, feeding on the seeds and lint. This can severely damage or destroy the bolls. In regions where pink bollworms are prevalent, they have been a major driver for the adoption of genetically engineered Bt cotton, which expresses a bacterium gene toxic to certain insects. Tobacco Budworm (Heliothis virescens): Closely related to the cotton bollworm, the tobacco budworm primarily attacks tobacco but is also a common pest in cotton. It primarily damages the flowers and bolls of the cotton plant. Differentiating between the tobacco budworm and the cotton bollworm based on appearance can be challenging, but it is crucial for effective management. American Bollworm (Helicoverpa zea): Known in some regions as the corn earworm, it is similar in behavior to Helicoverpa armigera and poses a threat to a variety of crops, including cotton. The larvae attack the cotton bolls, leading to direct damage to the cotton lint and seeds. Management Strategies: Cultural Controls: Crop rotation, destruction of crop residues, and deep plowing can help break the pest’s life cycle. Timing of planting can also be adjusted to avoid peak pest infestation. Biological Controls: Natural enemies like Trichogramma wasps, which parasitize bollworm eggs, and predators such as lacewings and ladybugs can be encouraged. Bacillus thuringiensis (Bt) products can also be sprayed, which are particularly effective against young larvae. Chemical Controls: Insecticides may be required when infestation levels exceed economic thresholds. However, resistance management must be considered, alternating modes of action to avoid developing resistance. Genetic Approaches: Bt cotton, genetically modified to express Bacillus thuringiensis toxin, has been highly effective in controlling bollworms and has dramatically reduced the reliance on chemical insecticides. Monitoring and Scouting: Regular field scouting and using pheromone traps to monitor adult populations can help in timely and targeted application of control measures. The effective management of bollworms often requires an integrated approach

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Randomness from Determinism. Complexity Explorers Krakow.

1. Randomness from Determinism Complexity Explorers Kraków Marcin Stępień @marcinstepien Kraków 2018-09-26

2. src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg

3. src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg www.wolframscience.com/nk s

4. More at http://www.conwaylife.com/wiki/ 2D Cellular Automaton

5. Source: Wolfram, Steven. "New Kind of Science." https://www.wolframscience.com/nks/pages/p53--more-cellular-automata/image-xlarge.png 1D Cellular Automaton

6. 1D Cellular Automata (90th) Weisstein, Eric W. "Elementary Cellular Automaton." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/ElementaryCellularAutomaton.html

7. The complete set of 256 (rules 0-255) elementary cellular automata: http://mathworld.wolfram.com/ElementaryCellularAutomaton.html Elementary Cellular Automaton

8. Patterns from All Possible Elementary Cellular Automata Demo PatternsFromAllPossibleElementaryCellularAutomata/

9. Weisstein, Eric W. "Rule 30." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/Rule30.html

10. Rule 30 Weisstein, Eric W. "Rule 30." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/Rule30.html

11. Randomness 2 approaches By (lack) of structure By provienience <<Classic>> <<AIT Complexity>>

12. Is Information Fundamental src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg https://youtu.be/aQ9Ukrt6Wc4

13. What Is Complexity in the Cosmos src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg https://youtu.be/xrXEQlvUpYI

14. Source: Wolfram, Steven. "New Kind of Science"

15. Could it be that some place out there in the computational universe, we might find our physical universe? S. Wolfram src: https://en.wikiquote.org/wiki/Stephen_Wolfram

Randomness from Determinism. Complexity Explorers Krakow.

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