Podcasts about brownian

If you love playing white noise for sleeping at night, you may really love this brown noise ambience! This brown noise (or Brownian noise!) is super smooth and a lot deeper than our typical white noise to sleep, really helping to cover up outside distractions that keep you awake. It even kind of resembles the noise from fan sounds for sleeping, since the brown noise produces a sleep sound with wind-like qualities. Brown noise can also help you focus better while studying or working, quieting busy thoughts and allowing your mind to concentrate on your tasks. Whether you are struggling to get some sleep at night or need a reliable study aid, brown noise has you covered! Here are some great products to help you sleep! Relaxing White Noise receives a small commission (at no additional cost to you) on purchases made through affiliate links. Thanks for supporting the podcast!⁠⁠Baloo Living Weighted Blankets⁠⁠ (Use code 'relaxingwhitenoise10' for 10% off)At Relaxing White Noise, our goal is to help you sleep well. This episode is eight hours long with no advertisements in the middle, so you can use it as a sleeping sound throughout the night. Listening to our white noise sounds via the podcast gives you the freedom to lock your phone at night, keeping your bedroom dark as you fall asleep.⁠⁠Check out the 10-Hour version on YouTube⁠⁠⁠⁠Contact Us for Partnership Inquiries⁠⁠Relaxing White Noise is the number one online destination for white noise and nature sounds to help you sleep, study or soothe a baby. With more than a billion views across YouTube and other platforms, we are excited to now share our popular ambient tracks on the Relaxing White Noise podcast. People use white noise for sleeping, focus, sound masking or relaxation. We couldn't be happier to help folks live better lives. This podcast has the sound for you whether you use white noise for studying, to soothe a colicky baby, to fall asleep or for simply enjoying a peaceful moment. No need to buy a white noise machine when you can listen to these sounds for free. Cheers to living your best life!DISCLAIMER: Remember that loud sounds can potentially damage your hearing. When playing one of our ambiences, if you cannot have a conversation over the sound without raising your voice, the sound may be too loud for your ears. Please do not place speakers right next to a baby's ears. If you have difficulty hearing or hear ringing in your ears, please immediately discontinue listening to the white noise sounds and consult an audiologist or your physician. The sounds provided by Relaxing White Noise are for entertainment purposes only and are not a treatment for sleep disorders or tinnitus. If you have significant difficulty sleeping on a regular basis, experience fitful/restless sleep, or feel tired during the day, please consult your physician.⁠⁠Relaxing White Noise Privacy Policy⁠⁠© Relaxing White Noise LLC, 2025. All rights reserved. Any reproduction or republication of all or part of this text/visual/audio is prohibited.

Brownian Noise with Rain & Thunder Sounds – Perfect for ADHD & Sleep brownian noise, brown noise ADHD, rain and thunder sounds, brown noise for sleep, ADHD focus sounds, deep sleep sounds, thunderstorm for relaxation, sleep sounds for insomnia, 8 hour brown noise, focus noise for studying, best rain sounds for sleeping, relaxing thunderstorm sounds, sound therapy for ADHD, white noise alternative, calming nature sounds, meditation background noise, peaceful rain sounds, high-quality brown noise, ADHD study sounds, noise for deep concentration, natural sleep aid, thunderstorm white noise, insomnia cure sounds, ambient noise for sleep, best sound for relaxation, study noise with thunder, brown noise for tinnitus, deep relaxation music, nature sounds for mental clarity, stress relief sounds, sleep meditation sounds, focus booster noise, rainstorm with deep thunder, ASMR rain sounds Learn more about your ad choices. Visit megaphone.fm/adchoices

Brownian Noise with Rain & Thunder – Deep Focus & Relaxation for ADHD Learn more about your ad choices. Visit megaphone.fm/adchoices

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Nalini AnantharamanGéométrie spectraleCollège de FranceAnnée 2024-2025Colloque - Géométries aléatoires et applications - Yilin Wang : The Brownian Loop Measure on Riemann Surfaces and Applications to Length SpectraIntervenant :Yilin WangIHESRésuméThe goal of this talk is to showcase how we can use stochastic processes to study the geometry of surfaces. More precisely, we use the Brownian loop measure to express the lengths of closed geodesics on a hyperbolic surface and zeta-regularized determinant of the Laplace-Beltrami operator. This gives a tool to study the length spectra of a hyperbolic surface and we obtain a new identity between the length spectrum of a compact surface and that of the same surface with an arbitrary number of additional cusps. This is a joint work with Yuhao Xue (IHES).

Work habits, FMOD, and brown noise figure prominently in this episode of the GAH, with Alex in particular berating Vince for his poor attempts at work-life balance while Mike maintains order with some helpful tips. Other notable mentions include: Elden Ring (Video Game / FromSoftware)Pacific Drive (Video Game / Ironwood Studios)Solas (Irish-American Musical Band) Featuring: Alex May and Vincent Diamante Recorded April 26, 2024

Stephen Wolfram answers questions from his viewers about the future of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: What scientific breakthroughs would you like to see in 2024? - Whatever happened to graphene? Is it still a viable product of future technologies? - Could we build "bio-vehicles," e.g. instead of batteries, use synthetic adipose tissue, which is ~50–100 times more mass efficient per kWh? (Is there a future in bio-batteries?) - Based on the level of computational advances this last decade, with the trend only showing even more of the same, do you think that traditional engineering disciplines will be relegated to OpenLLM? - Do you think we'll see mass-producible, room-temperature superconductors in the next decade? - ​It has been suggested that AI will displace coders/programmers. Do you think AI might also replace many physical and chemical experiments? - Any thoughts on "zero-knowledge proofs," i.e. the ability to make proofs without revealing details? - Given that some of our greatest accomplishments as a species have happened when we mimic nature, how important do you think biomimetics will be going forward? - Can you see a time when the discovery of new mathematical theorems and axioms will be generated from AIs? - When Betelgeuse explodes, will humans be okay? - Do you think smart textiles/computing fabrics will take off or be viable? Would you wear, say, a sweater to hear instead of a hearing aid? - But things like math, geometry and especially tessellation have patterns that are universally implicit and can be interpreted as interesting by their own existence, and not just by the view of humanity. - Is there a way we can use Brownian motion at a molecular scale as a type of fingerprint for nano-sensors to create things that are piracy-proof? - Why are the axioms of mathematics necessarily the ones that are effective at describing things we see as well? - What do things like dreams and "higher states of consciousness" spoken about in Eastern philosophies tell us about ourselves as observers? - Would it be easy to have an AI remaster old movies, both real ones and cartoons, so we can watch all the old gems in high-end graphics? - "Interesting" is defined by a "coolness" threshold. - Since the scientific paradigm was a major cause for the Enlightenment, can we expect the (multi-)computational paradigm to kick off a socio-philosophical paradigm of comparable importance? - If someone invented calculus in the Stone Age, it would probably have not been used for anything... Do you think there are some ideas that may be "rediscovered" because they have a better use?

I am properly losing track of what I am reading every week in the diary section.Even since we finished Volume II of The Invisible Man (1998-2014) I have been scrabbling around on my hands and knees (figuratively speaking of course) under the lid of my MacBook trying to locate odd bits of stuff to read out.And because I keep stumbling on stuff, we have lost all sense of chronology in terms of what we have included and what can still be used. Which is why I sent Ant an email on Wednesday and asked him to look at a couple of pages to try and ascertain if we had used them already. I couldn't be sure, and as it turned out neither could he, but we both plumped for the 'travelling to Lille' extract as being the safer option - so that is what you are getting.And as far as the rest of the episode is concerned, well it's just the other Mr.H being brilliant. Nuff said.Love'n'railcardshTCD Merch StoreBecome Purple and support the showThe Invisible Man Volume 1: 1991-1997The Invisible Man Volume2: 1998-2014FacebookInstagramWebsite

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Rapid capability gain around supergenius level seems probable even without intelligence needing to improve intelligence, published by Towards Keeperhood on May 6, 2024 on LessWrong. TLDR: 1. Around Einstein-level, relatively small changes in intelligence can lead to large changes in what one is capable to accomplish. 1. E.g. Einstein was a bit better than the other best physi at seeing deep connections and reasoning, but was able to accomplish much more in terms of impressive scientific output. 2. There are architectures where small changes can have significant effects on intelligence. 1. E.g. small changes in human-brain-hyperparameters: Einstein's brain didn't need to be trained on 3x the compute than normal physics professors for him to become much better at forming deep understanding, even without intelligence improving intelligence. Einstein and the heavytail of human intelligence 1905 is often described as the "annus mirabilis" of Albert Einstein. He founded quantum physics by postulating the existence of (light) quanta, explained Brownian motion, introduced the special relativity theory and derived E=mc from it. All of this. In one year. While having a full-time job in the Swiss patent office. With the exception of John von Neumann, we'd say those discoveries alone seem more than any other scientist of the 20th century achieved in their lifetime (though it's debatable). Though perhaps even more impressive is that Einstein was able to derive general relativity. Einstein was often so far ahead of his time that even years after he published his theories the majority of physicists rejected them because they couldn't understand them, sometimes even though there was experimental evidence favoring Einstein's theories. After solving the greatest open physics problems at the time in 1905, he continued working in the patent office until 1908, since the universities were too slow on the uptake to hire him earlier. Example for how far ahead of his time Einstein was: Deriving the theory of light quanta The following section is based on parts of the 8th chapter of "Surfaces and Essences" by Douglas Hofstadter. For an analysis of some of Einstein's discoveries, which show how far ahead of his time he was, I can recommend reading it. At the time, one of the biggest problems in physics was the "Blackbody spectrum", which describes the spectrum of electromagnetic wavelengths emitted by a Blackbody. The problem with it was that the emitted spectrum was not explainable by known physics. Einstein achieved a breakthrough by considering light not just as a wave, but also as light quanta. Although this idea sufficiently explained the Blackbody spectrum, physicists (at least almost) unanimously rejected it. The fight between the "light is corpuscles" and "light is a wave" faction had been decided a century ago, with a clear victory for the "wave" faction. Being aware of these possible doubts, Einstein proposed three experiments to prove his idea, one of which was the photoelectric effect. In the following years, Robert Millikan carried out various experiments on the photoelectric effect, which all confirmed Einstein's predictions. Still, Millikan insisted that the light-quanta theory had no theoretical basis and even falsely claimed that Einstein himself did not believe in his idea anymore. From Surfaces and Essences (p.611): To add insult to injury, although the 1921 Nobel Prize in Physics was awarded to Albert Einstein, it was not for his theory of light quanta but "for his discovery of the law of the photoelectric effect". Weirdly, in the citation there was no mention of the ideas behind that law, since no one on the Nobel Committee (or in all of physics) believed in them! [1][...] And thus Albert Einstein's revolutionary ideas on the nature of light, that most fundamental and all-...

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Rapid capability gain around supergenius level seems probable even without intelligence needing to improve intelligence, published by Towards Keeperhood on May 6, 2024 on LessWrong. TLDR: 1. Around Einstein-level, relatively small changes in intelligence can lead to large changes in what one is capable to accomplish. 1. E.g. Einstein was a bit better than the other best physi at seeing deep connections and reasoning, but was able to accomplish much more in terms of impressive scientific output. 2. There are architectures where small changes can have significant effects on intelligence. 1. E.g. small changes in human-brain-hyperparameters: Einstein's brain didn't need to be trained on 3x the compute than normal physics professors for him to become much better at forming deep understanding, even without intelligence improving intelligence. Einstein and the heavytail of human intelligence 1905 is often described as the "annus mirabilis" of Albert Einstein. He founded quantum physics by postulating the existence of (light) quanta, explained Brownian motion, introduced the special relativity theory and derived E=mc from it. All of this. In one year. While having a full-time job in the Swiss patent office. With the exception of John von Neumann, we'd say those discoveries alone seem more than any other scientist of the 20th century achieved in their lifetime (though it's debatable). Though perhaps even more impressive is that Einstein was able to derive general relativity. Einstein was often so far ahead of his time that even years after he published his theories the majority of physicists rejected them because they couldn't understand them, sometimes even though there was experimental evidence favoring Einstein's theories. After solving the greatest open physics problems at the time in 1905, he continued working in the patent office until 1908, since the universities were too slow on the uptake to hire him earlier. Example for how far ahead of his time Einstein was: Deriving the theory of light quanta The following section is based on parts of the 8th chapter of "Surfaces and Essences" by Douglas Hofstadter. For an analysis of some of Einstein's discoveries, which show how far ahead of his time he was, I can recommend reading it. At the time, one of the biggest problems in physics was the "Blackbody spectrum", which describes the spectrum of electromagnetic wavelengths emitted by a Blackbody. The problem with it was that the emitted spectrum was not explainable by known physics. Einstein achieved a breakthrough by considering light not just as a wave, but also as light quanta. Although this idea sufficiently explained the Blackbody spectrum, physicists (at least almost) unanimously rejected it. The fight between the "light is corpuscles" and "light is a wave" faction had been decided a century ago, with a clear victory for the "wave" faction. Being aware of these possible doubts, Einstein proposed three experiments to prove his idea, one of which was the photoelectric effect. In the following years, Robert Millikan carried out various experiments on the photoelectric effect, which all confirmed Einstein's predictions. Still, Millikan insisted that the light-quanta theory had no theoretical basis and even falsely claimed that Einstein himself did not believe in his idea anymore. From Surfaces and Essences (p.611): To add insult to injury, although the 1921 Nobel Prize in Physics was awarded to Albert Einstein, it was not for his theory of light quanta but "for his discovery of the law of the photoelectric effect". Weirdly, in the citation there was no mention of the ideas behind that law, since no one on the Nobel Committee (or in all of physics) believed in them! [1][...] And thus Albert Einstein's revolutionary ideas on the nature of light, that most fundamental and all-...

On May 2, 2024 we spoke with Skirmantas Janusonis on the peculiar morphology and spatial distribution of the serotonin innervation of the brain, and his idea that it can be described using the mathematics of fractional Brownian motion. We consider the kind of developmental mechanisms that could be responsible. Guest: Skirmantas Janusonis, Associate Professor, Department of Psychological and Brain Sciences, University of California, Santa Barbara. Participating: Fidel Santamaria, Department of Neuroscience, Developmental and Regenerative Biology, UTSA Host: Charles Wilson, Department of Neuroscience, Developmental and Regenerative Biology, UTSA Thanks to Jim Tepper for original music

 In this episode, Shekerah and Fatu have a delightful conversation with Jishad Kumar, a theorist and researcher. As a theorist he uses concrete assumptions and models to solve problems which can then be further investigated with in depth experimentation. Jishad's journey into theoretical physics started accidentally when he discovered Brownian motion is related to particle motion and has nothing to do with the color brown. From there, he extensively read books and scientific articles building a very solid knowledge base for his graduate studies. But, Jishad had a difficult start in his research career; he struggled with his first project assignment and did not have good support from this research advisor. During this difficult period, however, he found guidance from another advisor who encouraged him to conquer his fear and gave him the motivation to continue with the assignment and ultimately succeed. Things continued to progress and his confidence grew as he was also able to design a very impressive doctoral research project examining superconductivity. Looking back, Jishad sees this initial research experience as very formative in his research journey, and he is grateful for this. “I cannot stay away from science,” he explains as he also looks back and reflects on all the challenges and triumphs of the journey. Currently Jishad's research focuses on applications of quantum thermo-dynamics, such as quantum heat exchange, and he looks forward to future real-world applications and innovations from this research. His long term goals include setting up his own research lab with students and teaching. To hear more about Jishad's work tune into the latest episode.     Tune into this episode to hear Jishad discuss:His start in theoretical physics in a pre-wikipedia worldKeeping motivation on his journey even with several setbackFuture theoretical research goals and aspirations Reach out to Jishad:LinkedIn - www.linkedin.com/in/drjishadkumarIf you enjoyed this episode, be sure to also check out: From Postdoc to Assistant Professor - The WorkAccidental Discovery of the MicrowaveQuantum Biology with Clarice Aiello - The Work Reach out to Fatu:www.linkedin.com/in/fatubmTwitter: @thee_fatu_band LoveSciencePodcast@gmail.com Reach out to Shekerah:www.linkedin.com/in/shekerah-primus and LoveSciencePodcast@gmail.com Music from Pixabay: Future Artificial Intelligence Technology 130 by TimMoorMusic from https://freemusicarchive.org/music/Scott_Holmes: Hotshot by ScottHolmesMusic

Today, the concept of noise is employed to characterize random fluctuations in general. Before the twentieth century, however, noise only meant disturbing sounds. In the 1900s-50s, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations to be now used as all kinds of signals and information. Transforming Noise examines the historical origin of modern attempts to understand, control, and use noise. Its history sheds light on the interactions between physics, mathematics, mechanical technology, electrical engineering, and information and data sciences in the twentieth century. This book explores the process of engineers and physicists turning noise into an informational concept, starting from the rise of sound reproduction technologies such as the phonograph, telephone, and radio in the 1900s-20s until the theory of Brownian motions for random fluctuations and its application in thermionic tubes of telecommunication systems. These processes produced different theoretical treatments of noise in the 1920s-30s, such as statistical physicists' studies of Brownian fluctuations' temporal evolution, radio engineers' spectral analysis of atmospheric disturbances, and mathematicians' measure-theoretic formulation. Finally, it discusses the period during and after World War II and how researchers have worked on military projects of radar, gunfire control, and secret communications and converted the interwar theoretical studies of noise into tools for statistical detection, estimation, prediction, and information transmission. To physicists, mathematicians, electrical engineers, and computer scientists, this book offers a historical perspective on themes highly relevant in today's science and technology, ranging from Wi-Fi and big data to quantum information and self-organization. This book also appeals to environmental and art historians to modern music scholars as the history of noise constitutes a unique angle to study sound and society. Finally, to researchers in media studies and digital cultures, Transforming Noise demonstrates the deep technoscientific historicity of certain notions - information, channel, noise, equivocation - they have invoked to understand modern media and communication. Interview by Pamela Fuentes historian and editor of New Books Network en español Communications officer- Institute for the History and Philosophy of Science and Technology, University of Toronto Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Today, the concept of noise is employed to characterize random fluctuations in general. Before the twentieth century, however, noise only meant disturbing sounds. In the 1900s-50s, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations to be now used as all kinds of signals and information. Transforming Noise examines the historical origin of modern attempts to understand, control, and use noise. Its history sheds light on the interactions between physics, mathematics, mechanical technology, electrical engineering, and information and data sciences in the twentieth century. This book explores the process of engineers and physicists turning noise into an informational concept, starting from the rise of sound reproduction technologies such as the phonograph, telephone, and radio in the 1900s-20s until the theory of Brownian motions for random fluctuations and its application in thermionic tubes of telecommunication systems. These processes produced different theoretical treatments of noise in the 1920s-30s, such as statistical physicists' studies of Brownian fluctuations' temporal evolution, radio engineers' spectral analysis of atmospheric disturbances, and mathematicians' measure-theoretic formulation. Finally, it discusses the period during and after World War II and how researchers have worked on military projects of radar, gunfire control, and secret communications and converted the interwar theoretical studies of noise into tools for statistical detection, estimation, prediction, and information transmission. To physicists, mathematicians, electrical engineers, and computer scientists, this book offers a historical perspective on themes highly relevant in today's science and technology, ranging from Wi-Fi and big data to quantum information and self-organization. This book also appeals to environmental and art historians to modern music scholars as the history of noise constitutes a unique angle to study sound and society. Finally, to researchers in media studies and digital cultures, Transforming Noise demonstrates the deep technoscientific historicity of certain notions - information, channel, noise, equivocation - they have invoked to understand modern media and communication. Interview by Pamela Fuentes historian and editor of New Books Network en español Communications officer- Institute for the History and Philosophy of Science and Technology, University of Toronto Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/history

Today, the concept of noise is employed to characterize random fluctuations in general. Before the twentieth century, however, noise only meant disturbing sounds. In the 1900s-50s, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations to be now used as all kinds of signals and information. Transforming Noise examines the historical origin of modern attempts to understand, control, and use noise. Its history sheds light on the interactions between physics, mathematics, mechanical technology, electrical engineering, and information and data sciences in the twentieth century. This book explores the process of engineers and physicists turning noise into an informational concept, starting from the rise of sound reproduction technologies such as the phonograph, telephone, and radio in the 1900s-20s until the theory of Brownian motions for random fluctuations and its application in thermionic tubes of telecommunication systems. These processes produced different theoretical treatments of noise in the 1920s-30s, such as statistical physicists' studies of Brownian fluctuations' temporal evolution, radio engineers' spectral analysis of atmospheric disturbances, and mathematicians' measure-theoretic formulation. Finally, it discusses the period during and after World War II and how researchers have worked on military projects of radar, gunfire control, and secret communications and converted the interwar theoretical studies of noise into tools for statistical detection, estimation, prediction, and information transmission. To physicists, mathematicians, electrical engineers, and computer scientists, this book offers a historical perspective on themes highly relevant in today's science and technology, ranging from Wi-Fi and big data to quantum information and self-organization. This book also appeals to environmental and art historians to modern music scholars as the history of noise constitutes a unique angle to study sound and society. Finally, to researchers in media studies and digital cultures, Transforming Noise demonstrates the deep technoscientific historicity of certain notions - information, channel, noise, equivocation - they have invoked to understand modern media and communication. Interview by Pamela Fuentes historian and editor of New Books Network en español Communications officer- Institute for the History and Philosophy of Science and Technology, University of Toronto Learn more about your ad choices. Visit megaphone.fm/adchoices

Today, the concept of noise is employed to characterize random fluctuations in general. Before the twentieth century, however, noise only meant disturbing sounds. In the 1900s-50s, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations to be now used as all kinds of signals and information. Transforming Noise examines the historical origin of modern attempts to understand, control, and use noise. Its history sheds light on the interactions between physics, mathematics, mechanical technology, electrical engineering, and information and data sciences in the twentieth century. This book explores the process of engineers and physicists turning noise into an informational concept, starting from the rise of sound reproduction technologies such as the phonograph, telephone, and radio in the 1900s-20s until the theory of Brownian motions for random fluctuations and its application in thermionic tubes of telecommunication systems. These processes produced different theoretical treatments of noise in the 1920s-30s, such as statistical physicists' studies of Brownian fluctuations' temporal evolution, radio engineers' spectral analysis of atmospheric disturbances, and mathematicians' measure-theoretic formulation. Finally, it discusses the period during and after World War II and how researchers have worked on military projects of radar, gunfire control, and secret communications and converted the interwar theoretical studies of noise into tools for statistical detection, estimation, prediction, and information transmission. To physicists, mathematicians, electrical engineers, and computer scientists, this book offers a historical perspective on themes highly relevant in today's science and technology, ranging from Wi-Fi and big data to quantum information and self-organization. This book also appeals to environmental and art historians to modern music scholars as the history of noise constitutes a unique angle to study sound and society. Finally, to researchers in media studies and digital cultures, Transforming Noise demonstrates the deep technoscientific historicity of certain notions - information, channel, noise, equivocation - they have invoked to understand modern media and communication. Interview by Pamela Fuentes historian and editor of New Books Network en español Communications officer- Institute for the History and Philosophy of Science and Technology, University of Toronto Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/science-technology-and-society

Today, the concept of noise is employed to characterize random fluctuations in general. Before the twentieth century, however, noise only meant disturbing sounds. In the 1900s-50s, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations to be now used as all kinds of signals and information. Transforming Noise examines the historical origin of modern attempts to understand, control, and use noise. Its history sheds light on the interactions between physics, mathematics, mechanical technology, electrical engineering, and information and data sciences in the twentieth century. This book explores the process of engineers and physicists turning noise into an informational concept, starting from the rise of sound reproduction technologies such as the phonograph, telephone, and radio in the 1900s-20s until the theory of Brownian motions for random fluctuations and its application in thermionic tubes of telecommunication systems. These processes produced different theoretical treatments of noise in the 1920s-30s, such as statistical physicists' studies of Brownian fluctuations' temporal evolution, radio engineers' spectral analysis of atmospheric disturbances, and mathematicians' measure-theoretic formulation. Finally, it discusses the period during and after World War II and how researchers have worked on military projects of radar, gunfire control, and secret communications and converted the interwar theoretical studies of noise into tools for statistical detection, estimation, prediction, and information transmission. To physicists, mathematicians, electrical engineers, and computer scientists, this book offers a historical perspective on themes highly relevant in today's science and technology, ranging from Wi-Fi and big data to quantum information and self-organization. This book also appeals to environmental and art historians to modern music scholars as the history of noise constitutes a unique angle to study sound and society. Finally, to researchers in media studies and digital cultures, Transforming Noise demonstrates the deep technoscientific historicity of certain notions - information, channel, noise, equivocation - they have invoked to understand modern media and communication. Interview by Pamela Fuentes historian and editor of New Books Network en español Communications officer- Institute for the History and Philosophy of Science and Technology, University of Toronto Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/sound-studies

Today, the concept of noise is employed to characterize random fluctuations in general. Before the twentieth century, however, noise only meant disturbing sounds. In the 1900s-50s, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations to be now used as all kinds of signals and information. Transforming Noise examines the historical origin of modern attempts to understand, control, and use noise. Its history sheds light on the interactions between physics, mathematics, mechanical technology, electrical engineering, and information and data sciences in the twentieth century. This book explores the process of engineers and physicists turning noise into an informational concept, starting from the rise of sound reproduction technologies such as the phonograph, telephone, and radio in the 1900s-20s until the theory of Brownian motions for random fluctuations and its application in thermionic tubes of telecommunication systems. These processes produced different theoretical treatments of noise in the 1920s-30s, such as statistical physicists' studies of Brownian fluctuations' temporal evolution, radio engineers' spectral analysis of atmospheric disturbances, and mathematicians' measure-theoretic formulation. Finally, it discusses the period during and after World War II and how researchers have worked on military projects of radar, gunfire control, and secret communications and converted the interwar theoretical studies of noise into tools for statistical detection, estimation, prediction, and information transmission. To physicists, mathematicians, electrical engineers, and computer scientists, this book offers a historical perspective on themes highly relevant in today's science and technology, ranging from Wi-Fi and big data to quantum information and self-organization. This book also appeals to environmental and art historians to modern music scholars as the history of noise constitutes a unique angle to study sound and society. Finally, to researchers in media studies and digital cultures, Transforming Noise demonstrates the deep technoscientific historicity of certain notions - information, channel, noise, equivocation - they have invoked to understand modern media and communication. Interview by Pamela Fuentes historian and editor of New Books Network en español Communications officer- Institute for the History and Philosophy of Science and Technology, University of Toronto Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/technology

Today, the concept of noise is employed to characterize random fluctuations in general. Before the twentieth century, however, noise only meant disturbing sounds. In the 1900s-50s, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations to be now used as all kinds of signals and information. Transforming Noise examines the historical origin of modern attempts to understand, control, and use noise. Its history sheds light on the interactions between physics, mathematics, mechanical technology, electrical engineering, and information and data sciences in the twentieth century. This book explores the process of engineers and physicists turning noise into an informational concept, starting from the rise of sound reproduction technologies such as the phonograph, telephone, and radio in the 1900s-20s until the theory of Brownian motions for random fluctuations and its application in thermionic tubes of telecommunication systems. These processes produced different theoretical treatments of noise in the 1920s-30s, such as statistical physicists' studies of Brownian fluctuations' temporal evolution, radio engineers' spectral analysis of atmospheric disturbances, and mathematicians' measure-theoretic formulation. Finally, it discusses the period during and after World War II and how researchers have worked on military projects of radar, gunfire control, and secret communications and converted the interwar theoretical studies of noise into tools for statistical detection, estimation, prediction, and information transmission. To physicists, mathematicians, electrical engineers, and computer scientists, this book offers a historical perspective on themes highly relevant in today's science and technology, ranging from Wi-Fi and big data to quantum information and self-organization. This book also appeals to environmental and art historians to modern music scholars as the history of noise constitutes a unique angle to study sound and society. Finally, to researchers in media studies and digital cultures, Transforming Noise demonstrates the deep technoscientific historicity of certain notions - information, channel, noise, equivocation - they have invoked to understand modern media and communication. Interview by Pamela Fuentes historian and editor of New Books Network en español Communications officer- Institute for the History and Philosophy of Science and Technology, University of Toronto

This week, Louie and Sam are joined by Dr Clare Wallace on a quest to understand Brownian motions, the ways we learn maths and how connected the world really is. 

This sleep meditation begins with a mindful progressive body scan, making sure your body is fully relaxed, one part at a time, followed by soothing encouragement to  think happy thoughts.... recalling positively wonderful memories of past times, or dreaming of "heart-warming thoughts of fanciful imaginings"... anything to take your mind away from anxious thoughts and worry.  With hair brushing ASMR sound at the end of the recording.   Please Note: This recording might cause ringing in the ears due to low level Brownian noise. If so, do not continue to listen. It's here! https://sleep-like-a-log.com - Grab your FREE 14 NIGHT SLEEP LOG FANCY 4 NEW AD-FREE, ANXIETY REDUCING Episodes per Month?SUBSCRIBE to this show for just £2.99 monthly, at:Apple Podcasts   https://podcasts.apple.com/us/podcast/sleep-like-a-log/id1677920774Please be assured that anything suggested to you, other than what your moral, ethical and legal compass would allow, will not be absorbed successfully and will be rejected by your mind.FeedbackPlease email: support@sleep-like-a-log.comDisclaimer / WarningDO NOT drive, operate heavy machinery, or use this video when it is not safe for you to become drowsy and/or fall asleep. All videos are for entertainment or psycho-educational purposes only. Therefore, no videos on this channel should be used as a substitute for clinical professional advice or support.Please consult your GP before listening to this recording.Written and Spoken by Clare Bailey, Counselling Psychotherapist, Author and Hypnotherapist (BA Hons) MBACP DHP Acc.Hyp

IN THE HALL, I threw myself into the usual chaos of kids hurrying for their lockers before catching their buses for home, bumping against one another, rebounding, bumping into someone else, bouncing with a Brownian shuffle. ... Get full access to The Personal History, Adventures, Experiences & Observations of Peter Leroy at peterleroy.substack.com/subscribe

Experience the comforting blend of Brown Noise's deep tones with the timeless serenity of falling rain. This episode offers a tranquil backdrop designed to envelop listeners in a cocoon of relaxation. Before you drift off, remember to set a sleep timer for a seamless night's rest. Let the profound frequencies of Brown Noise meet the gentle cadence of rain, forming an aural retreat tailor-made for deep relaxation. Brownian noise, often referred to as "Brown Noise," is characterized by a power density that decreases 6 decibels per octave with increasing frequency. This results in a deep, low rumble sound profile, dominated by lower frequencies. Its soothing quality is often likened to the distant roar of a waterfall or the constant hum of a large city, making it a favorite among sound enthusiasts seeking deeper, richer soundscapes for relaxation or sleep Sleep Sounds YouTube: here sleep sounds, natural sleep sounds, sleep soothing sounds, ocean sounds for sleeping, thunderstorm sounds for sleep, rain and thunder sounds for sleeping, free sleep sounds, sounds to sleep by ocean or storm sounds to sleep to, our podcast has you covered. Get bonus content on Patreon Hosted on Acast. See acast.com/privacy for more information.

Support me by becoming wiser and more knowledgeable – check out Albert Einstein's collection of books for sale on Amazon here: https://amzn.to/3Vx9eY1 If you purchase a book through this link, I will earn a 4.5% commission and be extremely delighted. But if you just want to read and aren't ready to add a new book to your collection yet, I'd recommend checking out the ⁠⁠⁠Internet Archive⁠⁠⁠, the largest free digital library in the world. If you're really feeling benevolent you can buy me a coffee or donate over at ⁠https://ko-fi.com/theunadulteratedintellect⁠⁠. I would seriously appreciate it! __________________________________________________ Albert Einstein (14 March 1879 – 18 April 1955) was a German-born theoretical physicist, widely held to be one of the greatest and most influential scientists of all time. Best known for developing the theory of relativity, he also made important contributions to quantum mechanics, and was thus a central figure in the revolutionary reshaping of the scientific understanding of nature that modern physics accomplished in the first decades of the twentieth century. His mass–energy equivalence formula E = mc2, which arises from relativity theory, has been called "the world's most famous equation". He received the 1921 Nobel Prize in Physics "for his services to theoretical physics, and especially for his discovery of the law of the photoelectric effect", a pivotal step in the development of quantum theory. His work is also known for its influence on the philosophy of science. In a 1999 poll of 130 leading physicists worldwide by the British journal Physics World, Einstein was ranked the greatest physicist of all time. His intellectual achievements and originality have made Einstein synonymous with genius. In 1905, a year sometimes described as his annus mirabilis (miracle year), Einstein published four groundbreaking papers. These outlined a theory of the photoelectric effect, explained Brownian motion, introduced his special theory of relativity—a theory which addressed the inability of classical mechanics to account satisfactorily for the behavior of the electromagnetic field—and demonstrated that if the special theory is correct, mass and energy are equivalent to each other. In 1915, he proposed a general theory of relativity that extended his system of mechanics to incorporate gravitation. A cosmological paper that he published the following year laid out the implications of general relativity for the modeling of the structure and evolution of the universe as a whole. The middle part of his career also saw him making important contributions to statistical mechanics and quantum theory. Especially notable was his work on the quantum physics of radiation, in which light consists of particles, subsequently called photons. For much of the last phase of his academic life, Einstein worked on two endeavors that proved ultimately unsuccessful. Firstly, he fought a long rearguard action against quantum theory's introduction of fundamental randomness into science's picture of the world, objecting that "God does not play dice". Secondly, he attempted to devise a unified field theory by generalizing his geometric theory of gravitation to include electromagnetism too. As a result, he became increasingly isolated from the mainstream of modern physics. Born in the German Empire, Einstein moved to Switzerland in 1895, forsaking his German citizenship (as a subject of the Kingdom of Württemberg) the following year. In 1897, at the age of seventeen, he enrolled in the mathematics and physics teaching diploma program at the Swiss Federal polytechnic school in Zürich, graduating in 1900. In 1901, he acquired Swiss citizenship, which he kept for the rest of his life. In 1903, he secured a permanent position at the Swiss Patent Office in Bern. Full essay transcript here Audio source ⁠here⁠⁠ Full Wikipedia entry ⁠here⁠ Albert Einstein's books ⁠here --- Support this podcast: https://podcasters.spotify.com/pod/show/theunadulteratedintellect/support

In this short podcast, Bryan talks about filtration and IAQ, especially as they relate to virus control. He also answers the age-old question: “Can filters capture viruses?” While it may seem like particle size matters when it comes to filter efficacy, filters are not nets that strain air particles and prevent pollutants from passing through. When we talk about particles, we tend to focus on ones that are 0.3 microns in diameter, which tend to be medium-sized particles. Viruses tend to be among the smallest particles that we aim to control when it comes to IAQ. Filter media are crisscrossed fibers that catch particles in different ways. Inertial impaction is one means of stopping particles from passing through; the initial impact stops the particles from passing through. Interception happens when particles graze filter fibers and get stuck. Electrostatic attraction relies on energy to attract and catch particles. Diffusion happens when smaller particles move more erratically due to Brownian motion and get caught in the filter media.  Viruses are among those smaller particles. Smaller particles' erratic motion makes them more likely to collide with the filter media, so they aren't necessarily harder to catch. Higher MERV ratings are associated with higher capture efficiencies. HEPA filters surpass the MERV scale and have also been proven to filter viruses out of the air, but we rarely use true HEPA filtration in residential HVAC because they are too restrictive for total system airflow. We can use bypass HEPA filtration to filter the air without creating a massive restriction at the unit. Large filter-back returns with 2” filters can help catch more particles with a greater surface area without tanking the static pressure.   Learn more about the HVACR Training Symposium or buy a virtual ticket today at https://hvacrschool.com/symposium. If you have an iPhone, subscribe to the podcast HERE, and if you have an Android phone, subscribe HERE. Check out our handy calculators HERE.

Experience a restful and rejuvenating sleep with our 12-hour compilation of soothing brown noise. Brown noise, also known as Brownian noise or red noise, is a type of audio signal that has a gentle and deep sound spectrum. It is characterized by a smooth and consistent frequency range, making it ideal for promoting relaxation and enhancing sleep. Our carefully crafted brown noise track is designed to create a calming and comforting environment that can help you fall asleep faster and achieve a deeper sleep. The gentle and constant sound of brown noise helps mask disruptive background sounds and distractions, allowing your mind and body to unwind and enter a state of tranquility. Whether you struggle with insomnia, have difficulty falling asleep, or simply want to enhance the quality of your sleep, our 12-hour brown noise compilation is here to provide you with a serene auditory experience throughout the night. Lie back, close your eyes, and let the soothing brown noise envelop you in its peaceful embrace. Allow the gentle sound to lull you into a state of deep relaxation and promote a more restful sleep experience. fall asleep faster, deeper sleep, 12 hours, soothing brown noise, restful, rejuvenating sleep, gentle and deep sound, audio signal, smooth frequency range, promote relaxation, enhance sleep, calming, comforting environment, mask disruptive background sounds, distractions, unwind, tranquility, insomnia, difficulty falling asleep, quality of sleep, auditory experience, night, lie back, close your eyes, peaceful embrace, lull, deep relaxation, restful sleep. Support our mission of spreading relaxation and wellness by rating and reviewing our podcast on your preferred platform. Your feedback helps us improve and enables others to discover the benefits of our soothing sounds. Enhance your listening experience by subscribing to our ad-free version, immersing yourself in uninterrupted tranquility.  Clicking Here  Join our community of relaxation seekers and embark on a journey of self-discovery. Subscribe, rate, and review Meditation Sounds today and unlock a world of serenity and rejuvenation.  Email List Support this podcast  https://www.meditationsoundspodcast.com Say goodbye to stubborn belly fat with our revolutionary product! Our formula is designed to target and dissolve unwanted fat, leaving you with a slimmer, more toned midsection. Try it now and experience the results for yourself. #dissolvebellyfat #slimandtoned http://bit.ly/3jV1Ip1 Learn more about your ad choices. Visit megaphone.fm/adchoices

Experience a restful and rejuvenating sleep with our 12-hour compilation of soothing brown noise. Brown noise, also known as Brownian noise or red noise, is a type of audio signal that has a gentle and deep sound spectrum. It is characterized by a smooth and consistent frequency range, making it ideal for promoting relaxation and enhancing sleep. Our carefully crafted brown noise track is designed to create a calming and comforting environment that can help you fall asleep faster and achieve a deeper sleep. The gentle and constant sound of brown noise helps mask disruptive background sounds and distractions, allowing your mind and body to unwind and enter a state of tranquility. Whether you struggle with insomnia, have difficulty falling asleep, or simply want to enhance the quality of your sleep, our 12-hour brown noise compilation is here to provide you with a serene auditory experience throughout the night. Lie back, close your eyes, and let the soothing brown noise envelop you in its peaceful embrace. Allow the gentle sound to lull you into a state of deep relaxation and promote a more restful sleep experience. fall asleep faster, deeper sleep, 12 hours, soothing brown noise, restful, rejuvenating sleep, gentle and deep sound, audio signal, smooth frequency range, promote relaxation, enhance sleep, calming, comforting environment, mask disruptive background sounds, distractions, unwind, tranquility, insomnia, difficulty falling asleep, quality of sleep, auditory experience, night, lie back, close your eyes, peaceful embrace, lull, deep relaxation, restful sleep. Support our mission of spreading relaxation and wellness by rating and reviewing our podcast on your preferred platform. Your feedback helps us improve and enables others to discover the benefits of our soothing sounds. Enhance your listening experience by subscribing to our ad-free version, immersing yourself in uninterrupted tranquility.  Clicking Here  Join our community of relaxation seekers and embark on a journey of self-discovery. Subscribe, rate, and review Meditation Sounds today and unlock a world of serenity and rejuvenation.  Email List Support this podcast  https://www.meditationsoundspodcast.com Say goodbye to stubborn belly fat with our revolutionary product! Our formula is designed to target and dissolve unwanted fat, leaving you with a slimmer, more toned midsection. Try it now and experience the results for yourself. #dissolvebellyfat #slimandtoned http://bit.ly/3jV1Ip1 Learn more about your ad choices. Visit megaphone.fm/adchoices

Discover inner peace and tranquility with the soothing sounds of brown noise. Brown noise, also known as Brownian noise or red noise, is a gentle and consistent sound that can help you relax, focus, and find a sense of calm. Unlike white noise that has an equal distribution of frequencies, brown noise has a deeper and more soothing quality. It resembles the sound of a soft waterfall or the rustling of leaves in a gentle breeze. Its steady and uniform characteristics create a soothing and comforting ambiance that can drown out distractions and promote relaxation. As you listen to the gentle hum of brown noise, allow yourself to let go of stress and tension. Feel the sound enveloping you, creating a cocoon of tranquility. Let it wash away the worries of the day and guide you to a state of inner peace. The soothing nature of brown noise can be particularly helpful during meditation, yoga, or other relaxation practices. It acts as a backdrop, helping to quiet the mind and create a serene atmosphere for deep introspection and reflection. Whether you're seeking a moment of calm amidst a busy day, a way to unwind and de-stress, or a tool to enhance your meditation practice, the soothing brown noise is here to support you. Let it embrace you in its comforting embrace and guide you towards a state of deep relaxation and inner peace. inner peace, tranquility, soothing sounds, brown noise, Brownian noise, red noise, relax, focus, calm, gentle, consistent, soft waterfall, rustling of leaves, steady, uniform, ambiance, distractions, relaxation, stress, tension, wash away, worries, meditation, yoga, relaxation practices, quiet the mind, serene atmosphere, deep introspection, reflection, unwind, de-stress, meditation practice, support, comforting embrace, deep relaxation. Support our mission of spreading relaxation and wellness by rating and reviewing our podcast on your preferred platform. Your feedback helps us improve and enables others to discover the benefits of our soothing sounds. Enhance your listening experience by subscribing to our ad-free version, immersing yourself in uninterrupted tranquility.  Clicking Here  Join our community of relaxation seekers and embark on a journey of self-discovery. Subscribe, rate, and review Meditation Sounds today and unlock a world of serenity and rejuvenation.  Email List Support this podcast  https://www.meditationsoundspodcast.com Say goodbye to stubborn belly fat with our revolutionary product! Our formula is designed to target and dissolve unwanted fat, leaving you with a slimmer, more toned midsection. Try it now and experience the results for yourself. #dissolvebellyfat #slimandtoned http://bit.ly/3jV1Ip1 Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, we present the soft and soothing sound of brown noise. Brown noise, also known as Brownian noise, is a type of random sound that has a relaxing effect on the mind and body. The gentle, constant sound of brown noise provides a comforting background that can help you fall asleep faster and sleep more deeply. The episode features only natural soundscapes with no dialogue or voice, allowing you to fully immerse yourself in the calming sounds of nature and let your worries drift away. Whether you're struggling with insomnia or just need a way to unwind after a stressful day, "Calming Brown Noise" offers the perfect solution to help you relax and achieve a deep, restful sleep.Tags: sleep, relaxation, meditation, natural sounds, brown noise, calming, peaceful, stress relief, anxiety relief, insomnia reliefAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.04.23.537908v1?rss=1 Authors: Dora, M., Obara, C. J., Abel, T., Lippincott-Schwartz, J., Holcman, D. Abstract: The endoplasmic reticulum (ER) is a structurally complex, membrane-enclosed compartment that stretches from the nuclear envelope to the extreme periphery of eukaryotic cells. The organelle is crucial for numerous distinct cellular processes, but how these processes are spatially regulated within the structure is unclear. Traditional imaging-based approaches to understanding protein dynamics within the organelle are limited by the convoluted structure and rapid movement of molecular components. Here, we introduce a combinatorial imaging and machine learning-assisted image analysis approach to track the motion of photoactivated proteins within the ER of live cells. We find that simultaneous knowledge of the underlying ER structure is required to accurately analyze fluorescently-tagged protein redistribution, and after appropriate structural calibration we see all proteins assayed show signatures of Brownian diffusion-dominated motion over micron spatial scales. Remarkably, we find that in some cells the ER structure can be explored in a highly asymmetric manner, likely as a result of uneven connectivity within the organelle. This remains true independently of the size, topology, or folding state of the fluorescently-tagged molecules, suggesting a potential role for ER connectivity in driving spatially regulated biology in eukaryotes. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

In this episode, we explore the benefits of utilizing brown and pink noise at a frequency of 30Hz to enhance focus and concentration during study sessions. Brown noise, also known as Brownian noise or red noise, is a type of random signal that has a deeper and more bass-heavy sound compared to white noise. Pink noise, on the other hand, has a more balanced and soothing sound that resembles the natural frequencies found in our environment. Studies have shown that the combination of brown and pink noise at a frequency of 30Hz can have a positive impact on cognitive performance. The low-frequency sound helps mask distracting noises in the environment, creating a more conducive atmosphere for concentration and productivity. Additionally, the balanced and gentle nature of pink noise promotes a sense of relaxation, reducing stress and anxiety that can hinder focus. By incorporating brown and pink noise at 30Hz into your study routine, you can create a focused and calming auditory backdrop that helps you stay on task and absorb information more effectively. Whether you're preparing for exams, working on a project, or engaging in deep reading, this study boost technique can help optimize your cognitive abilities and improve overall productivity. Brown and pink noise for study, Focus and concentration boost, 30Hz frequency for study, Study with brown and pink noise, Enhance productivity with noise, Improve focus with sound, Concentration aid, Study environment optimization, Study sound therapy, Background noise for studying. Support our mission of spreading relaxation and wellness by rating and reviewing our podcast on your preferred platform. Your feedback helps us improve and enables others to discover the benefits of our soothing sounds. Enhance your listening experience by subscribing to our ad-free version, immersing yourself in uninterrupted tranquility.  Clicking Here  Join our community of relaxation seekers and embark on a journey of self-discovery. Subscribe, rate, and review Meditation Sounds today and unlock a world of serenity and rejuvenation.  Email List Support this podcast  https://www.meditationsoundspodcast.com Say goodbye to stubborn belly fat with our revolutionary product! Our formula is designed to target and dissolve unwanted fat, leaving you with a slimmer, more toned midsection. Try it now and experience the results for yourself. #dissolvebellyfat #slimandtoned http://bit.ly/3jV1Ip1 Learn more about your ad choices. Visit megaphone.fm/adchoices

Red noise, also known as Brownian noise, is a type of random signal that is similar to white noise but has more energy in the lower frequencies. In this episode, we bring you a calming red noise sound to help you relax and focus. The sound has a low, rumbling quality that can be likened to a soft waterfall or a gentle breeze. It can create a peaceful atmosphere that is perfect for meditation, yoga, or simply unwinding after a long day. The gentle hum of red noise can also help to mask distracting sounds in your environment, allowing you to concentrate on your tasks or studies. So sit back, relax, and let the soothing sound of "Red Noise" carry you away.Tags: sleep, relaxation, meditation, red noise, white noise, calming, focus, concentration, stress relief, anxiety relief, background noiseAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

「量子コンピュータ」シリーズの雑談回です。「あのパラドックスが量子現象名に！？”量子ゼノン効果”」「ギリシア神話からのおしゃれ命名”シジフォスクーリング”」「アリスにちなんで名付けられた”量子チェシャ猫状態”」など、今春から物理学者のLE0さんにオシャレな量子コンピュータ用語について教えてもらっています。 【目次】 0:00 素敵な物理学用語やナイト 2:36 「蛇に睨まれた蛙」 は量子ゼノン効果 10:12 卵パックで原子を絶対零度に！？ 21:16 オシャレ命名するならギリシャ神話は必須 27:57 電子はチェシャネコと同じようにふるまう 36:28 物理学者の苦しみは自分を信じられないこと 58:04 ものを忘れたければ電磁波で 1:07:31 これでマクスウェルの悪魔が分かる 1:13:39 物理学者、悪魔に情報詰めがち 【LE0さんの動画】 ◯ゆる学徒ハウス別館 https://www.youtube.com/@YuruGakutoHouseAnnex ◯ゆる物理学ラジオ 物理学者は量子の夢を見るか。量子コンピューターの現状と未来【量子コンピューター 1/4】 https://youtu.be/j91x9gL6msE 量子論について ・前編：https://youtu.be/COYO69MHV84 ・後編：https://youtu.be/hx7hj5-EUfw ◯カッコいい物理用語シリーズ（今回の台本） https://abounding-utahraptor-77e.notion.site/08445a10ec224ecf9beee895bcb4746f ◯水と学徒の相転移 https://note.com/metoro/n/nb9c6acddb7a7 【参考文献】 ◯Quantum Computation and Quantum Information https://amzn.to/3YnvfqR ◯シジフォスクーリングの画像 ・Cold atom realizations of Brownian motors - Scientific Figure on ResearchGate. Available from: https://www.researchgate.net/figure/Sisyphus-cooling-mechanism_fig6_1849003 [accessed 11 Feb, 2023] ・論文 https://www.tandfonline.com/doi/abs/10.1080/00107510512331337945 ◯不思議の国のアリス https://amzn.to/40RmHKj ◯鏡の国のアリス https://amzn.to/3IiDzCM 【サポーターコミュニティ加入はこちらから】 https://yurugengo.com/support 【親チャンネル：ゆる言語学ラジオ】 https://www.youtube.com/@yurugengo 【フランチャイズプロジェクト：ゆる学徒ハウス】 https://www.youtube.com/@yurugakuto 【おたよりフォーム】 https://forms.gle/BLEZpLcdEPmoZTH4A ※皆様からの楽しいおたよりをお待ちしています！ 【お仕事依頼はこちら！】 info@pedantic.jp 【堀元見プロフィール】 慶應義塾大学理工学部卒。専門は情報工学。WEBにコンテンツを作り散らかすことで生計を立てている。現在の主な収入源は「アカデミックに人の悪口を書くnote有料マガジン」。 Twitter→https://twitter.com/kenhori2 noteマガジン→https://note.com/kenhori2/m/m125fc4524aca 個人YouTube→https://www.youtube.com/@kenHorimoto 【水野太貴プロフィール】 名古屋大学文学部卒。専門は言語学。 某大手出版社で編集者として勤務。言語学の知識が本業に活きてるかと思いきや、そうでもない。 【姉妹チャンネル】 ◯ゆる音楽学ラジオ (https://open.spotify.com/show/7Ba89bnuEW0pyMeUbGR3oT) ◯ゆる民俗学ラジオ (https://open.spotify.com/show/2OPaWdgRVuUv5jLeFBViDU) ◯ゆる天文学ラジオ (https://open.spotify.com/show/6CGctNRBpOJmNPPSbvGV51) ◯ゆる書道学ラジオ (https://open.spotify.com/show/03kMZOoIJS9ybknZGv3zXc) ◯ゆる生態学ラジオ (https://open.spotify.com/show/7tTeHy7MjTGmrFrPGmjwMz) ◯ゆる哲学ラジオ (https://open.spotify.com/show/7t8NNVqRiisEHL4HG9tArT)

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Gradient surfing: the hidden role of regularization, published by Jesse Hoogland on February 6, 2023 on The AI Alignment Forum. Produced as part of the SERI ML Alignment Theory Scholars Program - Winter 2022 Cohort In a previous post, I demonstrated that Brownian motion near singularities defies our expectations from "regular" physics. Singularities trap random motion and take up more of the equilibrium distribution than you'd expect from the Gibbs measure. In the computational probability community, this is a well-known pathology. Sampling techniques like Hamiltonian Monte Carlo get stuck in corners, and this is something to avoid. You typically don't want biased estimates of the distribution you're trying to sample. In deep learning, I argued, this behavior might be less a bug than a feature. The claim of singular learning theory is that models near singularities have lower effective dimensionality. From Occam's razor, we know that simpler models generalize better, so if the dynamics of SGD get stuck at singularities, it would suggest an explanation (at least in part) for why SGD works: the geometry of the loss landscape biases your optimizer towards good solutions. This is not a particularly novel claim. Similar versions of the claim been made before by Mingard et al. and Valle Pérez et al.. But from what I can tell, the proposed mechanism, of singularity "stickiness", is quite different. Moreover, it offers a new possible explanation for the role of regularization. If exploring the set of points with minimum training loss is enough to get to generalization, then perhaps the role of regularizer is not just to privilege "simpler" functions but also to make exploration possible. In the absence of regularization, SGD can't easily move between points of equal loss. When it reaches the bottom of a valley, it's pretty much stuck. Adding a term like weight decay breaks this invariance. It frees the neural network to surf the loss basin, so it can accidentally stumble across better generalizing solutions. So could we improve generalization by exploring the bottom of the loss basin in other ways — without regularization or even without SGD? Could we, for example, get a model to grok through random drift? .No. We can't. That is to say I haven't succeeded yet. Still, in the spirit of "null results are results", let me share the toy model that motivated this hypothesis and the experiments that have (as of yet) failed to confirm it. The inspiration: a toy model First, let's take a look at the model that inspired the hypothesis. Let's begin by modifying the example of the previous post to include an optional regularization term controlled by λ: We deliberately center the regularization away from the origin at c=(−1,−1) so it doesn't already privilege the singularity at the origin. Now, instead of viewing U(x) as a potential and exploring it with Brownian motion, we'll treat it as a loss function and use stochastic gradient descent to optimize for x. We'll start our optimizer at a uniformly sampled random point in this region and take T=100 steps down the gradient (with optional momentum controlled by β). After each gradient step, we'll inject a bit of Gaussian noise to simulate the "stochasticity." Altogether, the update rule for x is as follows: with momentum updated according to: and noise given by, If we sample the final obtained position, x(T) over independent initializations, then, in the absence of regularization and in the presence of a small noise term, we'll get a distribution that looks like the figure on the left. Unlike the case of random motion, the singularity at the origin is now repulsive. Good luck finding those simple solutions now. However, as soon as we turn on the regularization (middle figure) or increase the noise term (figure on the right), the singulari...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Spooky action at a distance in the loss landscape, published by jhoogland on January 28, 2023 on LessWrong. Produced as part of the SERI ML Alignment Theory Scholars Program Winter 2022 Cohort. Not all global minima of the (training) loss landscape are created equal. Even if they achieve equal performance on the training set, different solutions can perform very differently on the test set or out-of-distribution. So why is it that we typically find "simple" solutions that generalize well? In a previous post, I argued that the answer is "singularities" — minimum loss points with ill-defined tangents. It's the "nastiest" singularities that have the most outsized effect on learning and generalization in the limit of large data. These act as implicit regularizers that lower the effective dimensionality of the model. Even after writing this introduction to "singular learning theory", I still find this claim weird and counterintuitive. How is it that the local geometry of a few isolated points determines the global expected behavior over all learning machines on the loss landscape? What explains the "spooky action at a distance" of singularities in the loss landscape? Today, I'd like to share my best efforts at the hand-waving physics-y intuition behind this claim. It boils down to this: singularities translate random motion at the bottom of loss basins into search for generalization. Random walks on the minimum-loss sets Let's first look at the limit in which you've trained so long that we can treat the model as restricted to a set of fixed minimum loss points. Here's the intuition pump: suppose you are a random walker living on some curve that has singularities (self-intersections, cusps, and the like). Every timestep, you take a step of a uniform length in a random available direction. Then, singularities act as a kind of "trap." If you're close to a singularity, you're more likely to take a step towards (and over) the singularity than to take a step away from the singularity. It's not quite an attractor (we're in a stochastic setting, where you can and will still break away every so often), but it's sticky enough that the "biggest" singularity will dominate your stable distribution. In the discrete case, this is just the well-known phenomenon of high-degree nodes dominating most of expected behavior of your graph. In business, it's behind the reason that Google exists. In social networks, it's similar to how your average friend has more friends than you do. To see this, consider a simple toy example: take two polygons and let them intersect at a single point. Next, let a random walker run loose on this setup. How frequently will the random walker cross each point? If you've taken a course in graph theory, you may remember that the equilibrium distribution weights nodes in proportion to their degrees. For two intersecting lines, the intersection is twice as likely as the other points. For three intersecting lines, it's three times as likely, and so on. Now just take the limit of infinitely large polygons/step size to zero, and we'll recover the continuous case we were originally interested in. Brownian motion near the minimum-loss set Well, not quite. You see, restricting ourselves to motion along the minimum-loss points is unrealistic. We're more interested in messy reality, where we're allowed some freedom to bounce around the bottoms of loss basins. This time around, the key intuition-pumping assumption is to view the behavior of stochastic gradient descent late in training as a kind of Brownian motion. When we've reached a low training-loss solution, variability between batches is a source of randomness that no longer substantially improves loss but just jiggles us between solutions that are equivalent from the perspective of the training set. To understand these dy...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Spooky action at a distance in the loss landscape, published by Jesse Hoogland on January 28, 2023 on The AI Alignment Forum. Produced as part of the SERI ML Alignment Theory Scholars Program Winter 2022 Cohort. Not all global minima of the (training) loss landscape are created equal. Even if they achieve equal performance on the training set, different solutions can perform very differently on the test set or out-of-distribution. So why is it that we typically find "simple" solutions that generalize well? In a previous post, I argued that the answer is "singularities" — minimum loss points with ill-defined tangents. It's the "nastiest" singularities that have the most outsized effect on learning and generalization in the limit of large data. These act as implicit regularizers that lower the effective dimensionality of the model. Even after writing this introduction to "singular learning theory", I still find this claim weird and counterintuitive. How is it that the local geometry of a few isolated points determines the global expected behavior over all learning machines on the loss landscape? What explains the "spooky action at a distance" of singularities in the loss landscape? Today, I'd like to share my best efforts at the hand-waving physics-y intuition behind this claim. It boils down to this: singularities translate random motion at the bottom of loss basins into search for generalization. Random walks on the minimum-loss sets Let's first look at the limit in which you've trained so long that we can treat the model as restricted to a set of fixed minimum loss points. Here's the intuition pump: suppose you are a random walker living on some curve that has singularities (self-intersections, cusps, and the like). Every timestep, you take a step of a uniform length in a random available direction. Then, singularities act as a kind of "trap." If you're close to a singularity, you're more likely to take a step towards (and over) the singularity than to take a step away from the singularity. It's not quite an attractor (we're in a stochastic setting, where you can and will still break away every so often), but it's sticky enough that the "biggest" singularity will dominate your stable distribution. In the discrete case, this is just the well-known phenomenon of high-degree nodes dominating most of expected behavior of your graph. In business, it's behind the reason that Google exists. In social networks, it's similar to how your average friend has more friends than you do. To see this, consider a simple toy example: take two polygons and let them intersect at a single point. Next, let a random walker run loose on this setup. How frequently will the random walker cross each point? If you've taken a course in graph theory, you may remember that the equilibrium distribution weights nodes in proportion to their degrees. For two intersecting lines, the intersection is twice as likely as the other points. For three intersecting lines, it's three times as likely, and so on. Now just take the limit of infinitely large polygons/step size to zero, and we'll recover the continuous case we were originally interested in. Brownian motion near the minimum-loss set Well, not quite. You see, restricting ourselves to motion along the minimum-loss points is unrealistic. We're more interested in messy reality, where we're allowed some freedom to bounce around the bottoms of loss basins. This time around, the key intuition-pumping assumption is to view the behavior of stochastic gradient descent late in training as a kind of Brownian motion. When we've reached a low training-loss solution, variability between batches is a source of randomness that no longer substantially improves loss but just jiggles us between solutions that are equivalent from the perspective of the training set. To u...

Gordon Brown's New Britain Report promised a radical examination of the state of the UK. We see if it lives up to Labour's hype. Trust us, it doesn't.The opinion polls and the recent Chester by election result suggest that Labour, either as a minority or majority, will form the Westminster government post the 2024 General Election. Where does this leave the SNP de facto referendum strategy, would this be enough to tempt the Scottish left back into the Labour fold, and would Labour call a snap indyref2?Meanwhile Ian Blackford has resigned as SNP leader at Westminster. Stephen Flynn and Alison Thewliss are the two candidates vying to take over. What difference, if any, will victory for either candidate mean?Away from the world of party politics Lesley wonders if the Yes movement can learn from, and be inspired by, the successful Eigg buy out campaign. ★ Support this podcast ★

Black-Scholes is a beautiful model driven by Brownian motion, but Brownian motion is too restrictive to accurately describe the asset prices. One way to generalize Brownian motion which is widely used in science is to allow discontinuous jumps. This lies underneath some very fancy models that financial institutions employ. Building on last week, Jacob joins Tom and Tony to go over how these jump diffusion models look under the hood.

Black-Scholes is a beautiful model driven by Brownian motion, but Brownian motion is too restrictive to accurately describe the asset prices. One way to generalize Brownian motion which is widely used in science is to allow discontinuous jumps. This lies underneath some very fancy models that financial institutions employ. Building on last week, Jacob joins Tom and Tony to go over how these jump diffusion models look under the hood.

Try our Sleep App, Slow for iPhone. https://slow-app.com/ The sleep app that lets you create your own sleep soundscapes, add-free. Get the sleep you need, download the app: https://slow-app.com/ Become a paid podcast subscriber, and unlock all add-free premium episodes: https://anchor.fm/sleeppodcast/subscribe Give feedback: Send us your sound request in a podcast review, and we will try to make it for you. Our premium sleep app: https://slow-app.com/ Get Spotify sleep playlists here: https://podlink.to/long-sleep-playlist Today's episode is devoted to Brown Noise. In science, Brownian noise, also known as Brown noise or red noise, is the type of signal noise produced by Brownian motion, hence its alternative name of random walk noise. The term "Brown noise" does not come from the color, but after Robert Brown, who documented the erratic motion for multiple types of inanimate particles in water. On this sleep podcast you will find: Relaxing nature sounds, sleep soundscapes, binaural beats, deep sleep sounds, rain sounds, ocean sounds, ocean waves, white noise machines, thunderstorms, waterfall sounds, baby sleep sounds, tinnitus masker sounds, jungle, forest sounds, relaxing music, and guided sleep meditations. We hope this channel will help you with your sleepless nights, insomnia, sleep apnea, sleep paralysis. Use this podcast as your daily sleep podcast and experience the benefits of good quality sleep. We recommend that you talk with a doctor if your sleep doesn't improve. There are many people who find it difficult to sleep at night. Can you relate? 2 AM in bed, but you just can't relax, your head is spinning… Nature sounds are one of the best ways to relax and sleep and de-stress. Use nature sounds as a way to fall asleep. Play this sleep podcast with relaxing sounds for sleep when you go to bed or just when you need some calmness in your life. Some of these relaxing sounds include rain, ocean waves, crickets, and the sound of a fireplace. Sounds have a powerful effect on our mood and emotions. They can calm us down, help us focus, and even lull us to sleep. The sounds that you listen to can have a significant impact on your sleep quality. This is because the brain associates the sound with a certain feeling or mood. So if you listen to calming sounds like rain or ocean waves, it will help you relax and fall asleep faster than if you were listening to traffic noise. Some people use white noise machines or thunderstorms as a way of blocking out distracting noises in their environment, such as tinnitus or snoring partners. Nature sounds are a great way to help you sleep better. You can use them as background noise for meditation or for sleep. The most popular type of nature sounds is rain and ocean waves. Many other types of sounds can also be used, such as thunderstorms, waterfall, and baby sleep sounds. These natural noises have been shown to help people fall asleep faster and stay asleep longer than using white noise machines or tinnitus maskers. Have a relaxing day and sleep well :) You spend 1/3 of your life sleeping so do it well. Sleep is your superpower.

Last week, we discussed a very big bacterium, one you can see with your naked eye! But back in high school we all learned that bacteria and prokaryotes in general were pretty simple cells and were definitely smaller than our cells. While we've found a lot of examples that push back against this idea, there is a fundamental truth behind it -- a simple cell has definite physical constraints on how big it can grow. What are those constraints? And how do these giant bacteria (and our own cells) get around these problems? References: https://royalsocietypublishing.org/doi/10.1098/rsif.2008.0014 http://www.math.uchicago.edu/~lawler/reu.pdf https://www.science.org/content/article/largest-bacterium-ever-discovered-has-unexpectedly-complex-cells

Did Wassily Kandinsky really invent abstract art? Randall takes Chris on a journey with many twists and turns.  *** Download slides: https://mega.nz/file/J9tGTQAC#5Oa99t7-pxmdxowHcq0pe5i5nSpKYg-Gns1MXlJtovc *** Topics discussed include:  the first abstract painting Wassily Kandinsky Hilma af Klint Helena Blavatsky automatic drawing Rudolf Steiner The Ten Largest Theosophy Sigmund Freud Adolf Hitler and the Nazis Bauhaus school Georgiana Houghton Albert Einstein the birth of the modern world *** Timeline: 1859 -- Georgiana Houghton starts making "spirit" drawings at seances 1862 -- Hilma af Klint born 1863 -- Salon des Refusés  1871 -- Houghton pays for a show in London 1874 -- Impression, Sunrise by Monet 1875 -- Helena Blavatsky cofounds the Theosophical Society, as "the synthesis of science, religion and philosophy", proclaiming that it was reviving an "Ancient Wisdom" which underlay all the world's religions.  1880 -- Hilma's 10-year-old sister dies, spurring her interest in the occult 1882 -- Hilma af Klint enrolled in Sweden' s Royal Academy of Fine Arts.  1884 -- Georgiana Houghton dies 1887 -- Hilma af Klint graduates with honors, awarded use of shared studio until 1909. Here she paints first 100 or so Paintings For the Temple.  1888 -- The Five is founded 1895 -- X-rays discovered 1895 -- Sigmund Freud publishes one of his first books, Studies on Hysteria 1896 -- Radio waves discovered, first radios 1900 1896 -- radioactivity discovered 1896 -- Hilma experiments with automatic drawing. was participating in weekly seances with The Five. * Through her work with The Five, Hilma af Klint created experimental automatic drawing as early as 1896, leading her toward an inventive geometric visual language capable of conceptualizing invisible forces both of the inner and outer worlds.[citation needed] She explored world religions, atoms, and the plant world and wrote extensively about her discoveries.[5] As she became more familiar with this form of expression, Hilma af Klint was assigned by the High Masters to create the paintings for the "Temple" – however she never understood what this "Temple" referred to.  Hilma af Klint felt she was being directed by a force that would literally guide her hand. She wrote in her notebook:  The pictures were painted directly through me, without any preliminary drawings, and with great force. I had no idea what the paintings were supposed to depict; nevertheless I worked swiftly and surely, without changing a single brush stroke.[14] * 1903 -- Kandinsky paints the Blue Rider 1904 -- Hilma af Klint joins Theosophical society 1904 -- Hilma af Klint was informed by spirit guides a great temple should be built and filled with paintings.  1905 -- Albert Einstein publishes his 4 seminal papers: photoelectric effect, Brownian motion, special relativity, and the equivalence of mass and energy. 1906 -- Klint begins automatic painting https://www.nytimes.com/2019/10/21/travel/stockholm-hilma-af-klint.html * led by a spiritual guide named Amaliel who contacted af Klint during séances and not only “commissioned” the paintings but, at least at the outset, had, she claimed, directed her hand as she painted. “The pictures were painted directly through me, without any preliminary drawings and with great force,” af Klint wrote in one of her journals of the 193 mostly abstract works known as “The Paintings for the Temple,” meditations on human life and relationships in the most elemental terms. “I had no idea what the paintings were supposed to depict, nevertheless I worked swiftly and surely without changing a single brush stroke.”  * https://www.bbc.com/culture/article/20181012-hilma-af-klint-the-enigmatic-vision-of-a-mystic Absorbing a wide array of cultural influences old and new – from Goethe's colour theories to Darwin's discoveries concerning evolution, from Car Linnaeus's botanical taxonomies to cutting-edge ideas about atomic matter and radioactivity – Af Klint set about composing for posterity an alluring eye-music that echoed back the complex psyche of her age.  * 1907 -- De Fem finishes The Ten Largest 1908 -- Hilma meets Rudolf Steiner * In 1908 af Klint met Rudolf Steiner for the first time. In one of the few remaining letters, she was asking Steiner to visit her in Stockholm and see the finished part of the Paintings for the Temple series, 111 paintings in total. Steiner did see the paintings but mostly left unimpressed, stating that her way of working was inappropriate for a theosophist. According to H.P. Blavatsky, mediumship was a faulty practice, leading its adepts on the wrong path of occultism and black magic.[18] However, during their meeting, Steiner stated that af Klint's contemporaries would not be able to accept and understand their paintings, and it would take another 50 years to decipher them. Of all the paintings shown to him, Steiner paid special attention only to the Primordial Chaos Group, noting them as "the best symbolically".[19] After meeting Steiner, af Klint was devastated by his response and, apparently, stopped painting for 4 years. Interestingly enough, Steiner kept photographs of some of af Klint's artworks, some of them even hand-coloured. Later the same year he met Wassily Kandinsky, who had not yet come to abstract painting. Some art historians assume that Kandinsky could have seen the photographs and perhaps was influenced by them while developing his own abstract path.[20] Later in her life, she made a decision to destroy all her correspondence. She left a collection of more than 1200 paintings and 125 diaries to her nephew, Erik af Klint. Among her last paintings made in 1930s, there are two watercolours predicting the events of World War II, titled The Blitz and The Fight in the Mediterranean.[21]  * https://www.theguardian.com/artanddesign/2016/feb/21/hilma-af-klint-occult-spiritualism-abstract-serpentine-gallery In 1908, after making 111 paintings, she collapsed: “She had completed a painting every third day – including the 10 huge ones. She was exhausted.” And there was further reason for despond. That same year, Steiner was lecturing in Stockholm. She invited this charismatic man to see her paintings (Mondrian petitioned Steiner too, but always in vain). She had hoped he would interpret the work. Instead he advised: “No one must see this for 50 years.” For four years after this verdict she gave up painting and looked after her sightless mother. Johan shows me a photograph of Hilma at Hanmora, looking down with tenderness, a hand on her mother's shoulder – the more sympathetic of clues to her character.  * 1910 -- first abstract by Kandinsky 1919 -- Bauhaus school founded 1923 -- Hilma writes Steiner asking him what she should do, "burn them?" She never hears back. 1925 -- Rudolf Steiner dies 1928 -- Theosophy reaches peak membership 1930s -- While studies, sketches, and improvisations exist (particularly of Composition II), a Nazi raid on the Bauhaus in the 1930s resulted in the confiscation of Kandinsky's first three Compositions. They were displayed in the State-sponsored exhibit "Degenerate Art", and then destroyed (along with works by Paul Klee, Franz Marc and other modern artists)  1932 -- Hilma af Klint's last will. In  will, Hilma keaves 1200 paintings, 26,000 pages of notes (125 notebooks), not to be shown until 20 years after her death. 1933 -- Hitler appointed chancellor of Germany 1944 -- Hilma dies of car accident. She was 82. Also Kandinsky (77), Mondrian (pneumonia, 71) 1970s -- Johan af Kilnt offers works to the Moderna Museet, they refuse. The then-director turned them down. “When he heard that she was a medium, there was no discussion. He didn't even look at the pictures.” Only in 2013 did the museum redeem itself with a retrospective. https://www.theguardian.com/artanddesign/2020/oct/06/hilma-af-klint-abstract-art-beyond-the-visible-film-documentary 1985 -- Hilma's work discovered. Distant relative of Klint finds paintings just hanging on walls of theosophical society.  1986 -- Hilma af Klint show: The Spiritual in Art, Abstract Painting 1890-1985  2013 -- Hilma af Klint Moderna Museet Stockholm show: perhaps their most popular in history 2019 -- Hilma af Klint Guggenheim show: may have been it's most popular 2020 -- Beyond the Visible: Hilma af Klint documentary *** recorded April 21, 2022 *** Visit us at https://chrisandrandall.com/

Brownian motion provides financial theorists with the basic building block for understanding prices evolving under market forces.  Today, Jacob join Tom and Tony to discuss some of the finer points of Brownian paths. We will use their symmetries to discuss the frequency of maxima and minima along the path, even if they are not identifiable at the time.

Brownian motion provides financial theorists with the basic building block for understanding prices evolving under market forces.  Today, Jacob join Tom and Tony to discuss some of the finer points of Brownian paths. We will use their symmetries to discuss the frequency of maxima and minima along the path, even if they are not identifiable at the time.

Hello beautiful lights! Welcome to the Mystery Box on this channel, Lex spun the wheel and it landed on, Robert Brown! Brown Noise is low key slept on, literally and figuratively! Named after brilliant botanist Robert Brown, who discovered Brownian Motion (random particle motion) in the early 1800s. Most people use this sound to help relax their mind. It is often used while sleeping. Even if it is used just for 10 mins a day, the benefits are wonderful. Think of the sound like tiny gold/brown particles moving through your body, cleansing you of negative energy and helping you ground. This sound makes me think of Mother Earth and her gift of healing. Grab headphones, go outside barefoot and ground with Brownian Noise! --- Support this podcast: https://anchor.fm/saint-finnikin/support

What happens when you disrupt the healthcare workforce industry while it is being disrupted by a global pandemic? Dr. Alexi Nazem, the CEO of Nomad Health, discusses his role leading Nomad to modernize the travel nursing industry right at a time of unprecedented need, extraordinary uncertainty and recurrent staffing crises. From death-defying moments to leading through breakneck growth, Nazem describes his journey doing to the travel nursing industry what Travelocity did to travel agencies. Join also for a conversation around the strengths and weaknesses of medicine's leadership training, pursuing both clinical practice and entrepreneurship, and the "Brownian motion" at the heart of company creation. --- Send in a voice message: https://anchor.fm/tdio/message

On the Money Vikings Podcast #39 - Brian Reeves from Gator Traders and The Money Vikings get together for the first time, talking about Gann Fans, Chaos Theory, Brownian movements, Andrew's Pitchfork and a few stocks we're watching like MVIS, BNGO, CWSFF/CMC, UAVS. Subscribe to Gator Traders and use code TMV20 for 20% off from 6/6 - 6/19. Where to Find us:

We're back with a quick run down of the win against Sheffield Wednesday before diving into a  preview of what (we decide) is our biggest game of the year against Leicester. We then meander through Newcastle, January transfers and Frank Lampard via Eistein's Nobel prize for Brownian motion and the war in Iraq. Not even joking.If you don't have enough nonsense in your life, subscribe wherever you get your podcasts and follow us at @BluesBrosEFC on Twitter.