Pigment

pigment

Three years ago (perhaps more), there was a mini-controversy across LinkedIn and (RIP) Twitter over ‘team of one’ game teams. Teams of one identified as such; others disagreed - an egregious case of political in/correctness. Recently I had a chat with a designer and startup founder. They shared hope around how automating coding via LLMs may enable a one-wo(man) app design team. Responded somewhat bluntly, "Perhaps, but this isn't business". Not the best answer. What about the one team? In games, team of one has always been a thing. I need not quote names since Thomas was alone, and you did spend five nights at Freddie's after Mainichi playing Elite in 1984… Okay… Elite wasn’t (they were two). Undertales of solo developers abound. The barrier to entry has dropped; making compelling games without much technical/artistic skills is easier (and more pointless) than ever before. Throwing assets in the mix made it possible to go and say "Sure, but you didn't make this on your own". Whereas nobody would have gone on to say, "Sure, but your game is running on Windows. Did you author the OS?”. This has happened before. Renaissance geniuses weren't just artists; they were engineers, mixed pigments, designed flying machines. Michelangelo got paint in his eyes - a far cry from Jason Allen’s ethereal technique. In sum: you do not need a large group of people to build a compelling product. Creativity across the board I am attached to the concept of authoring. Authors create personal works; we (consumers) get a personal experience. The genius of (not only) music and writing is in shaping personal experience through consuming personal works. I have never watched Titanic, you have. Purposely: creativity is a bridge no one will cross if we all are on the same shore. Which does not make one the ideal team size. One is a team size. A good size. Two is a good size. Three is a good size... Teams get creative in different ways. In recent years, making apps has become easier. Back in 1998, when I created my first app, I designed a custom window system; in 2008, I wrote a game engine for my first game. Today, we have codeless, in continuity with the team of one ideal. In software, it is not rare for designers to feel disempowered. Whereas engineers can build anything provided they set their mind to it... Concurrently, there is a sense of creativity being vertical, with designers leading the effort while engineers focus on the details. Then you get the idea that designers would be much more productive if they did not have to communicate with engineers. Yet, crossovers between design and engineering are not rare. If you get serious about creativity, you will necessarily encounter Maggie Boden's Creative Mind. Boden's work is equal parts dedicated to creativity in arts, science, and engineering. No code, no life Where no-code is breaking down (it isn't) isn't, okay, can we write apps without code or not? We surely can (did not need LLMs to make this happen). What's more surprising is how engineers ceaselessly toy with the idea of taking themselves out of the loop, whereas artists feel outraged when their work is automated. No, it isn’t surprising. No code, and the 5th wall (1) Wired assumptions about how things (are meant to) work. Trivial example: many teams do not design their own widgets. Meaning that the interaction design effort is now derivative; diegetic interfaces in (mainstream) games are not progressing because we aren’t thinking about interaction beyond the widgets. This isn't only about computing. The printing press, alphabetization, typewriters, Unicode, spellcheckers... have contributed to the sedimentation of a bounded medium; one friend told me (1995), “we are no longer writing to communicate, we are writing to find out whether we have anything to say” - also: we are no longer inventing writing. (2) When discussions between art, science, and engineering are not happening, innovation isn't breaking that fifth wall. Where an engineer would exclaim "I can make this!"? Silence. Where a designer stubbornly asserts, "Make this work"? Silence. In between... obviously! Defeaningly so. In games: before no-code, we got tools like Blueprints, which is designed for… designers to not be talking to coders? Imagine tools for boosting (not negating) cross-disciplinary success. Zero, the forbidden number Around 2010 I came across a forum post where people said okay, apps are now free, at least we can't go lower than this. Others swiftly responded, "Hell no, I'll pay users to install apps". Fast forwarding to the 20s, Hell No has not percolated. Apple does not routinely credit my account for using apps (boo). Still, marketing budgets often exceed 50% to 70% of the total dev cost. Not so relatedly (if you get my drift)… The minimum number of developers needed to build an app isn't one. We do not need developers to make apps. Nor do we need financial advisers to make financial decisions. Do we need to consume goods and services anymore? Am I the product or the user? Top of the food chain? Brainstuff? In a distant future, alien combat units do not go around catching our children with sticky spider webaloo; still, they might break the internet. Playing Kitsune Tails. Keep it together. Photo credit: Chen-Pan Liao via Wikimedia Commons (CC 3.0 Attribution-Share-Alike) Three years ago (perhaps more), there was a mini-controversy across LinkedIn and (RIP) Twitter over ‘team of one’ game teams. Teams of one identified as such; others disagreed - an egregious case of political in/correctness. Three years ago (perhaps more), there was a mini-controversy across LinkedIn and (RIP) Twitter over game teams. Teams of one identified as such; others disagreed - an egregious case of political in/correctness. Recently I had a chat with a designer and startup founder. They shared hope around how automating coding via LLMs may enable a one-wo(man) app design team. Responded somewhat bluntly, "Perhaps, but this isn't business". Recently I had a chat with a designer and startup founder. They shared hope around how automating coding via LLMs may enable a one-wo(man) app design team. Responded somewhat bluntly, "Perhaps, but this isn't business". Not the best answer. Not the best answer. What about the one team? In games, team of one has always been a thing. I need not quote names since Thomas was alone, and you did spend five nights at Freddie's after Mainichi playing Elite in 1984… Okay… Elite wasn’t (they were two). Undertales of solo developers abound. always need not quote names The barrier to entry has dropped; making compelling games without much technical/artistic skills is easier (and more pointless) than ever before. Throwing assets in the mix made it possible to go and say "Sure, but you didn't make this on your own". Whereas nobody would have gone on to say, "Sure, but your game is running on Windows. Did you author the OS?”. This has happened before. Renaissance geniuses weren't just artists; they were engineers, mixed pigments, designed flying machines. Michelangelo got paint in his eyes - a far cry from Jason Allen’s ethereal technique. In sum: you do not need a large group of people to build a compelling product. Creativity across the board I am attached to the concept of authoring. Authors create personal works; we (consumers) get a personal experience. The genius of (not only) music and writing is in shaping personal experience through consuming personal works. I have never watched Titanic, you have. Purposely: creativity is a bridge no one will cross if we all are on the same shore. Which does not make one the ideal team size. One is a team size. A good size. Two is a good size. Three is a good size... Teams get creative in different ways. In recent years, making apps has become easier. Back in 1998, when I created my first app, I designed a custom window system; in 2008, I wrote a game engine for my first game. Today, we have codeless, in continuity with the team of one ideal. In software, it is not rare for designers to feel disempowered. Whereas engineers can build anything provided they set their mind to it... Concurrently, there is a sense of creativity being vertical, with designers leading the effort while engineers focus on the details. Then you get the idea that designers would be much more productive if they did not have to communicate with engineers. Yet, crossovers between design and engineering are not rare. If you get serious about creativity, you will necessarily encounter Maggie Boden's Creative Mind . Boden's work is equal parts dedicated to creativity in arts, science, and engineering. Creative Mind No code, no life Where no-code is breaking down (it isn't) isn't, okay, can we write apps without code or not? We surely can (did not need LLMs to make this happen). What's more surprising is how engineers ceaselessly toy with the idea of taking themselves out of the loop, whereas artists feel outraged when their work is automated. No, it isn’t surprising. No code, and the 5th wall No code, and the 5th wall (1) Wired assumptions about how things (are meant to) work. Trivial example: many teams do not design their own widgets. Meaning that the interaction design effort is now derivative; diegetic interfaces in (mainstream) games are not progressing because we aren’t thinking about interaction beyond the widgets. This isn't only about computing. The printing press, alphabetization, typewriters, Unicode, spellcheckers... have contributed to the sedimentation of a bounded medium; one friend told me (1995), “we are no longer writing to communicate, we are writing to find out whether we have anything to say” - also: we are no longer inventing writing. This isn't only about computing. The printing press, alphabetization, typewriters, Unicode, spellcheckers... have contributed to the sedimentation of a bounded medium; one friend told me (1995), “we are no longer writing to communicate, we are writing to find out whether we have anything to say” - also: we are no longer inventing writing. (2) When discussions between art, science, and engineering are not happening, innovation isn't breaking that fifth wall. Where an engineer would exclaim "I can make this!"? Silence. Where a designer stubbornly asserts, "Make this work"? Silence. In between... obviously! Defeaningly so. In games: before no-code, we got tools like Blueprints, which is designed for… designers to not be talking to coders? Imagine tools for boosting (not negating) cross-disciplinary success. Zero, the forbidden number Around 2010 I came across a forum post where people said okay, apps are now free, at least we can't go lower than this. Others swiftly responded, "Hell no, I'll pay users to install apps". Fast forwarding to the 20s, Hell No has not percolated. Apple does not routinely credit my account for using apps (boo). Still, marketing budgets often exceed 50% to 70% of the total dev cost. Not so relatedly (if you get my drift)… The minimum number of developers needed to build an app isn't one. We do not need developers to make apps. Nor do we need financial advisers to make financial decisions. Do we need to consume goods and services anymore? Am I the product or the user? Top of the food chain? Brainstuff? In a distant future, alien combat units do not go around catching our children with sticky spider webaloo; still, they might break the internet. Playing Kitsune Tails. In a distant future, alien combat units do not go around catching our children with sticky spider webaloo; still, they might break the internet. Playing Kitsune Tails . Kitsune Tails Keep it together. Photo credit: Chen-Pan Liao via Wikimedia Commons (CC 3.0 Attribution-Share-Alike) Chen-Pan Liao

No-code, No life

(1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK;
(2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK;
(3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK;
(4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK;
(5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). Table of Links Abstract and Introduction
2 Methodology
2.1 Local spectral irradiance as a function of stellar temperature
2.2 Thermodynamic model of an oxygenic light-harvesting system
2.3 Lattice model of an oxygenic light-harvesting system
3 Results
3.1 Orbital distances and incident spectral fluxes
3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR
3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR
3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’
4 Discussion
Acknowledgements, Author Contribution Statement, Authors disclosure statement and References 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature As in previous work [Duffy et al., 2023], we use stellar spectral models for stars of different effective temperatures, Ts, generated by the phoenix code [Husser, T.-O. et al., 2013]. To reduce expense of subsequent numerical integration calculations, we smooth and re-sample the spectrum down to 4000 points, which still captures the large scale features. The absorption profiles of typical light-harvesting pigments are quite broad, with a Full Width at Half Maximum (FWHM) > 10 nm. Photon absorption by these pigments therefore integrates over this wavelength range (see next subsection), meaning that the photosynthetic pigments can only resolve spectral details on scales comparable to or larger than their own absorption line-width. Even with this smoothing, spectral resolution is well below this limit. This paper is available on arxiv under CC 4.0 license. (1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK; (2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK; (5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). (1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK; (2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK; (5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). Table of Links Abstract and Introduction 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 3 Results 3.1 Orbital distances and incident spectral fluxes 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 4 Discussion Acknowledgements, Author Contribution Statement, Authors disclosure statement and References Abstract and Introduction Abstract and Introduction 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature 2.1 Local spectral irradiance as a function of stellar temperature 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 3 Results 3.1 Orbital distances and incident spectral fluxes 3.1 Orbital distances and incident spectral fluxes 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 4 Discussion 4 Discussion Acknowledgements, Author Contribution Statement, Authors disclosure statement and References Acknowledgements, Author Contribution Statement, Authors disclosure statement and References 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature As in previous work [Duffy et al., 2023], we use stellar spectral models for stars of different effective temperatures, Ts, generated by the phoenix code [Husser, T.-O. et al., 2013]. To reduce expense of subsequent numerical integration calculations, we smooth and re-sample the spectrum down to 4000 points, which still captures the large scale features. The absorption profiles of typical light-harvesting pigments are quite broad, with a Full Width at Half Maximum (FWHM) > 10 nm. Photon absorption by these pigments therefore integrates over this wavelength range (see next subsection), meaning that the photosynthetic pigments can only resolve spectral details on scales comparable to or larger than their own absorption line-width. Even with this smoothing, spectral resolution is well below this limit. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Thermodynamic Limits Around M-dwarf Stars: Local Spectral Irradiance

Thermodynamic Limits Around M-dwarf Stars: Acknowledgements

(1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK;
(2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK;
(3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK;
(4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK;
(5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). Table of Links Abstract and Introduction
2 Methodology
2.1 Local spectral irradiance as a function of stellar temperature
2.2 Thermodynamic model of an oxygenic light-harvesting system
2.3 Lattice model of an oxygenic light-harvesting system
3 Results
3.1 Orbital distances and incident spectral fluxes
3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR
3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR
3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’
4 Discussion
Acknowledgements, Author Contribution Statement, Authors disclosure statement and References 2.3 Lattice model of an oxygenic light-harvesting system While the previous model explicitly relates νe and ϕe to the thermodynamic properties of the antenna, it neglects the influence of antenna topology. The assumption that the excitation samples the entirety of the antenna super-structure is unrealistic, as is the assumption of a single rate constant for N2 → NRC (see Fig. 1 d). Therefore, we construct a complimentary lattice diffusion model in which localized, non-interacting, excitations “hop” between clusters of pigments. Specific antenna topologies are discussed in the Results section but in essence a set of discrete antenna “sites” are arranged around a central RC, either in linear branches (see Fig. 3 a) or a hexagonal lattice (see Fig. 3 b). The sites can be pigment clusters within LHCs, entire LHCs, or even blocks of multiple LHCs, but the assumption is always that excitation equilibration within a site is much faster than inter-site hopping. For Ns antenna sites we define the population vector as, where the second case arises from the fact that trapping is irreversible. The diagonal elements are, as before but now only encodes the thermodynamics of a single hopping event. The overall thermodynamics of energy capture, migration to the RC and trapping are strictly implicit. As with the thermodynamic model the dynamics are solved in the steady state to obtain νe and ϕe. We start with a model that aims to replicate plant PSII for fp (λ; Ts = 5800 K). The sites are composed of NLHC discrete LHCII trimers, each containing coupled Chl b and Chl a domains (see Fig. 3 a and b.). We then subject this optimised antenna to spectral fluxes from lower mass stars and then attempt to recover photosynthetic performance by, as before, adding additional LHCII trimers. Finally, we apply the same approach to a modified antenna model which attempts to compensate for entropic barriers with an energetic ’funnel’ structure. This is achieved by introducing a progressive blueshift in λ p m as more and more LHCII are added to the system. This paper is available on arxiv under CC 4.0 license. (1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK; (2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK; (5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). (1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK; (2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK; (5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). Table of Links Abstract and Introduction 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 3 Results 3.1 Orbital distances and incident spectral fluxes 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 4 Discussion Acknowledgements, Author Contribution Statement, Authors disclosure statement and References Abstract and Introduction Abstract and Introduction 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature 2.1 Local spectral irradiance as a function of stellar temperature 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 3 Results 3.1 Orbital distances and incident spectral fluxes 3.1 Orbital distances and incident spectral fluxes 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 4 Discussion 4 Discussion Acknowledgements, Author Contribution Statement, Authors disclosure statement and References Acknowledgements, Author Contribution Statement, Authors disclosure statement and References 2.3 Lattice model of an oxygenic light-harvesting system While the previous model explicitly relates νe and ϕe to the thermodynamic properties of the antenna, it neglects the influence of antenna topology. The assumption that the excitation samples the entirety of the antenna super-structure is unrealistic, as is the assumption of a single rate constant for N2 → NRC (see Fig. 1 d). Therefore, we construct a complimentary lattice diffusion model in which localized, non-interacting, excitations “hop” between clusters of pigments. Specific antenna topologies are discussed in the Results section but in essence a set of discrete antenna “sites” are arranged around a central RC, either in linear branches (see Fig. 3 a) or a hexagonal lattice (see Fig. 3 b). The sites can be pigment clusters within LHCs, entire LHCs, or even blocks of multiple LHCs, but the assumption is always that excitation equilibration within a site is much faster than inter-site hopping. For Ns antenna sites we define the population vector as, where the second case arises from the fact that trapping is irreversible. The diagonal elements are, as before but now only encodes the thermodynamics of a single hopping event. The overall thermodynamics of energy capture, migration to the RC and trapping are strictly implicit. As with the thermodynamic model the dynamics are solved in the steady state to obtain νe and ϕe. We start with a model that aims to replicate plant PSII for fp (λ; Ts = 5800 K). The sites are composed of NLHC discrete LHCII trimers, each containing coupled Chl b and Chl a domains (see Fig. 3 a and b.). We then subject this optimised antenna to spectral fluxes from lower mass stars and then attempt to recover photosynthetic performance by, as before, adding additional LHCII trimers. Finally, we apply the same approach to a modified antenna model which attempts to compensate for entropic barriers with an energetic ’funnel’ structure. This is achieved by introducing a progressive blueshift in λ p m as more and more LHCII are added to the system. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Thermodynamic Limits Around M-dwarf Stars: Lattice Model of an Oxygenic Light-harvesting System

Thermodynamic Limits on Oxygenic Photosynthesis Around M-dwarf Stars: Abstract and Introduction

(1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK;
(2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK;
(3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK;
(4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK;
(5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). Table of Links Abstract and Introduction
2 Methodology
2.1 Local spectral irradiance as a function of stellar temperature
2.2 Thermodynamic model of an oxygenic light-harvesting system
2.3 Lattice model of an oxygenic light-harvesting system
3 Results
3.1 Orbital distances and incident spectral fluxes
3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR
3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR
3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’
4 Discussion
Acknowledgements, Author Contribution Statement, Authors disclosure statement and References 4 Discussion The results of our generalized antenna models suggest that the oxygenic photosynthesis is likely feasible on exo-planets orbiting low mass M-dwarf stars, though there are some restrictions. A light-harvesting system similar to PSII of vascular plants (but with a larger antenna) would be severely entropy-limited even before we factor in local limitations like water scarcity, atmospheric attenuation of light, etc. However, this reflects the fact that plants are evolved to deal with highly variable irradiance [Vialet-Chabrand et al., 2017, Li et al., 2021] rather than constant low light. One of the major risks to plants is actually excessive illumination which can cause oxidative damage to PSII, a metabolically costly phenomenon known as photoinhibition, and one that should be familiar to anyone who has suddenly moved a houseplant into full sun. To mitigate photoinhibition [Aro et al., 1993], plants possess regulatory mechanisms that suppress photon absorption and down-regulate the antenna [Ruban, 2016, Ruban and Wilson, 2021]. Therefore it is unsurprising that such a system does not perform well in severely PAR-depleted light. However, by introducing an energetic gradient to the antenna (the energy funnel) we were able to significantly improve antenna efficiency and electron output. Of the branched and hexagonal antenna topologies the former performs better, able to match the performance of the latter but with fewer LHC subunits and a shallower energetic gradient. Fewer LHC subunits is perhaps the most important factor as it is directly related to the metabolic “cost” of the antenna. Of course, there are countless other modifications that could be made to the antenna. For example, one could increase pigment density which would increase the overall cross-section of each LHC and enhance inter-pigment energy transfer. The pigment concentration in LHCII is already very high, approximately 1 mol dm−3 , and the protein scaffold enforces highly specific inter-pigment distances and relative orientations to avoid dissipative processes such as concentration quenching [Liu et al., 2004]. However, one could imagine an adaptation similar to the chlorosome antenna of green sulphur bacteria [Oostergetel et al., 2010]. This structure is a solid aggregate of ∼ 300, 000 BChls encapsulated in a membrane sheath, effectively the densest pigment packing possible, and it facilitates (anoxygenic) photosynthesis in extremely low illumination. It should be noted however that such as structure is is a significant metabolic investment and one that is not seen in any large multi-cellular organism. Alternatively, one could replace Chl a and b with pigments with larger intrinsic cross-sections and/or absorption widths, which would increase the rate of photon absorption, γi . Since intermolecular energy transfer depends on the oscillator strengths and spectral overlap of the pigments involved, this may also enhance the intrinsic transfer rates, (Ki,j ) −1 . Still, the branched, funnel antenna strategy is a plausible one because it explicitly addresses the fundamental thermodynamic limits inherent in light-harvesting. More importantly, such an antenna actually exists on in Earth in the form of the phycobilisome of oxygenic cyanobacteria [Saer and Blankenship, 2017]. Like our model, the phycobilisome is modular and can adapt to changes in irradiance. Kolodny et al. [2022] recently showed that cyanobacteria in deep water, where light is very blue-shifted, will lenghten their phycobilisome rods by adding more terminal PE subunits and will increase overall antenna efficiency, ϕF , by tuning pigment content (and possibly density). The most important result, however, is the recent work of Battistuzzi et al. [2023] who showed that cyanobacteria could comfortably adapt to the the light typical of M-dwarf stars. Moreover, they used a sophisticated starlight simulator setup which models atmospheric attenuation of light, meaning their cyanobacteria were likely subject to ever scanter illumination than we consider here. Interestingly, they also considered pure “far red” (700−800 nm) illumination and found that this retarded growth rate relative to the M-dwarf light, implying that, as in our model, the organism was adapting its antenna to intercept more photons in the depleted PAR region.It should be noted that they also considered on the red-adapted strains described in the introduction that fared equally well in M-dwarf and far red light. Strictly, both our modelling and the experimental work of Kolodny et al. [2022]. concerns the acclimation of an existing antenna to an unusual lightenvironment rather than the ground-up evolution of an antenna structure specifically optimized to it. Nevertheless, Kolodny’s work demonstrates that oxygenic photosynthesis is, in principle, possible around very low mass stars and our findings indicate that the key consideration is overcoming a fundamental entropic barrier to light-harvesting. This paper is available on arxiv under CC 4.0 license. (1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK; (2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK; (5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). (1) Samir Chitnavis, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK; (2) Thomas J. Haworth, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (3) Edward Gillen, Astronomy Unit, Queen Mary University of London, Mile End Road, London E1 4NS, UK; (4) Conrad W. Mullineaux, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK; (5) Christopher D. P. Duffy, School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End, London E1 4NS, UK & Digital Environment Research Institute, Queen Mary University of London, Empire House, Whitechapel E1 1HH, UK (Email: c.duffy@qmul.ac.uk). Table of Links Abstract and Introduction 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 3 Results 3.1 Orbital distances and incident spectral fluxes 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 4 Discussion Acknowledgements, Author Contribution Statement, Authors disclosure statement and References Abstract and Introduction Abstract and Introduction 2 Methodology 2.1 Local spectral irradiance as a function of stellar temperature 2.1 Local spectral irradiance as a function of stellar temperature 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.2 Thermodynamic model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 2.3 Lattice model of an oxygenic light-harvesting system 3 Results 3.1 Orbital distances and incident spectral fluxes 3.1 Orbital distances and incident spectral fluxes 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.2 Thermodynamic antenna model: Increasing antenna size in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.3 Lattice antenna model: Increasing the size of a “flat” antenna in limited PAR 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 3.4 Lattice antenna model: Improving antenna efficiency with an energetic ’funnel’ 4 Discussion 4 Discussion Acknowledgements, Author Contribution Statement, Authors disclosure statement and References Acknowledgements, Author Contribution Statement, Authors disclosure statement and References 4 Discussion The results of our generalized antenna models suggest that the oxygenic photosynthesis is likely feasible on exo-planets orbiting low mass M-dwarf stars, though there are some restrictions. A light-harvesting system similar to PSII of vascular plants (but with a larger antenna) would be severely entropy-limited even before we factor in local limitations like water scarcity, atmospheric attenuation of light, etc. However, this reflects the fact that plants are evolved to deal with highly variable irradiance [Vialet-Chabrand et al., 2017, Li et al., 2021] rather than constant low light. One of the major risks to plants is actually excessive illumination which can cause oxidative damage to PSII, a metabolically costly phenomenon known as photoinhibition, and one that should be familiar to anyone who has suddenly moved a houseplant into full sun. To mitigate photoinhibition [Aro et al., 1993], plants possess regulatory mechanisms that suppress photon absorption and down-regulate the antenna [Ruban, 2016, Ruban and Wilson, 2021]. Therefore it is unsurprising that such a system does not perform well in severely PAR-depleted light. However, by introducing an energetic gradient to the antenna (the energy funnel) we were able to significantly improve antenna efficiency and electron output. Of the branched and hexagonal antenna topologies the former performs better, able to match the performance of the latter but with fewer LHC subunits and a shallower energetic gradient. Fewer LHC subunits is perhaps the most important factor as it is directly related to the metabolic “cost” of the antenna. Of course, there are countless other modifications that could be made to the antenna. For example, one could increase pigment density which would increase the overall cross-section of each LHC and enhance inter-pigment energy transfer. The pigment concentration in LHCII is already very high, approximately 1 mol dm−3 , and the protein scaffold enforces highly specific inter-pigment distances and relative orientations to avoid dissipative processes such as concentration quenching [Liu et al., 2004]. However, one could imagine an adaptation similar to the chlorosome antenna of green sulphur bacteria [Oostergetel et al., 2010]. This structure is a solid aggregate of ∼ 300, 000 BChls encapsulated in a membrane sheath, effectively the densest pigment packing possible, and it facilitates (anoxygenic) photosynthesis in extremely low illumination. It should be noted however that such as structure is is a significant metabolic investment and one that is not seen in any large multi-cellular organism. Alternatively, one could replace Chl a and b with pigments with larger intrinsic cross-sections and/or absorption widths, which would increase the rate of photon absorption, γi . Since intermolecular energy transfer depends on the oscillator strengths and spectral overlap of the pigments involved, this may also enhance the intrinsic transfer rates, (Ki,j ) −1 . Still, the branched, funnel antenna strategy is a plausible one because it explicitly addresses the fundamental thermodynamic limits inherent in light-harvesting. More importantly, such an antenna actually exists on in Earth in the form of the phycobilisome of oxygenic cyanobacteria [Saer and Blankenship, 2017]. Like our model, the phycobilisome is modular and can adapt to changes in irradiance. Kolodny et al. [2022] recently showed that cyanobacteria in deep water, where light is very blue-shifted, will lenghten their phycobilisome rods by adding more terminal PE subunits and will increase overall antenna efficiency, ϕF , by tuning pigment content (and possibly density). The most important result, however, is the recent work of Battistuzzi et al. [2023] who showed that cyanobacteria could comfortably adapt to the the light typical of M-dwarf stars. Moreover, they used a sophisticated starlight simulator setup which models atmospheric attenuation of light, meaning their cyanobacteria were likely subject to ever scanter illumination than we consider here. Interestingly, they also considered pure “far red” (700−800 nm) illumination and found that this retarded growth rate relative to the M-dwarf light, implying that, as in our model, the organism was adapting its antenna to intercept more photons in the depleted PAR region.It should be noted that they also considered on the red-adapted strains described in the introduction that fared equally well in M-dwarf and far red light. Strictly, both our modelling and the experimental work of Kolodny et al. [2022]. concerns the acclimation of an existing antenna to an unusual lightenvironment rather than the ground-up evolution of an antenna structure specifically optimized to it. Nevertheless, Kolodny’s work demonstrates that oxygenic photosynthesis is, in principle, possible around very low mass stars and our findings indicate that the key consideration is overcoming a fundamental entropic barrier to light-harvesting. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Thermodynamic Limits Around M-dwarf Stars: Discussion 

Solve for the Edges and Get The Middle for Free: Innovating for Inclusivity 

WildlifeDatasets: an Open-source Toolkit for Animal Re-identification: Conclusion and References

Dear reader, Welcome to the latest edition of the “One More Thing in AI newsletter." For Startup founders and Business Leaders like you who want to get smarter on AI in less than 5 minutes. In this focused edition, we are going to present a few AI startups that caught my eye. Why? It will give you an idea of the art of the possible in the field of AI, especially in your organizations. It might also inspire you to start something on your own! I hope you enjoy this edition. I'd love to hear your feedback (positive or negative). Best regards, Renjit Philip Notable AI Startups Changing the World AI technology is getting super advanced, and startups are using it to shake up different industries in cool ways. Let's check out some of these brilliant companies: Pay Automatically With JustPaid Businesses can find dealing with invoices and payments a hassle. But JustPaid has created an awesome AI system that does it all automatically. Their AI tracks usage makes invoices, sets up customer accounts, and handles payments—all within a company's normal systems. JustPaid started in the US but plans to offer its payment AI everywhere. Robot Farmers Detecting Crop Diseases In places like the UAE, where growing food is tough, Egrobots uses robots and AI to spot crop diseases before they spread. Their robot scouts roam farms collecting data that their AI analyzes. They also have an app that can instantly identify diseases on plants and give farmers advice. This tech could boost food supplies. AI Making Amazing Videos ZhipuAI is working on incredible AI that turns words into videos! This Chinese startup got investments from Alibaba and the government to take on OpenAI's similar Sora tech. While it is excellent for movies and shows, there are worries about using it for fake videos, too. AI Coding Buddies Coding is hard, but Replit made an AI assistant called Teams that helps while you program! It suggests fixes and better ways to write code in real-time on their browser IDE. It's like having an intelligent coding partner, making you a better, faster coder. AI Salesperson's Assistant For salespeople, the SiftHub AI acts like a virtual briefcase loaded with all the latest info on products and companies. With $5.5 million in funding, the company's AI preps sales teams so they can focus on building relationships during client meetings. Better Business Planning with AI Pigment scored a massive $145 million investment in its AI business planning software. The tool combines a company's data to precisely forecast finances and collaborate across departments on strategy. Fun AI Videos for Social Media Higgsfield created an app called Diffuse that uses AI to make animated videos on your phone. This app is perfect for posting engaging videos on TikTok, YouTube Shorts, and more. With $8 million invested, this startup is unleashing AI's video creation magic. These AI startups are completely changing how we work, farm, make videos, and more. The AI revolution has barely started! That is it for this edition of the newsletter. If you subscribe to our email edition, you get our newsletter first, and it stays in your mailbox as a future reference. Until next time, keep learning, applying, and experimenting with AI! Also published here. Dear reader, Dear reader, Welcome to the latest edition of the “ One More Thing in AI newsletter." For Startup founders and Business Leaders like you who want to get smarter on AI in less than 5 minutes . One More Thing in AI newsletter." For Startup founders and Business Leaders like you who want to get smarter on AI in less than 5 minutes In this focused edition, we are going to present a few AI startups that caught my eye. Why? It will give you an idea of the art of the possible in the field of AI, especially in your organizations. It might also inspire you to start something on your own! I hope you enjoy this edition. I'd love to hear your feedback (positive or negative). Best regards, Renjit Philip Renjit Philip Notable AI Startups Changing the World AI technology is getting super advanced, and startups are using it to shake up different industries in cool ways. Let's check out some of these brilliant companies: Pay Automatically With JustPaid Businesses can find dealing with invoices and payments a hassle. But JustPaid has created an awesome AI system that does it all automatically. Their AI tracks usage makes invoices, sets up customer accounts, and handles payments—all within a company's normal systems. JustPaid started in the US but plans to offer its payment AI everywhere. Robot Farmers Detecting Crop Diseases In places like the UAE, where growing food is tough, Egrobots uses robots and AI to spot crop diseases before they spread. Their robot scouts roam farms collecting data that their AI analyzes. They also have an app that can instantly identify diseases on plants and give farmers advice. This tech could boost food supplies. AI Making Amazing Videos ZhipuAI is working on incredible AI that turns words into videos! This Chinese startup got investments from Alibaba and the government to take on OpenAI's similar Sora tech. While it is excellent for movies and shows, there are worries about using it for fake videos, too. AI Coding Buddies Coding is hard, but Replit made an AI assistant called Teams that helps while you program! It suggests fixes and better ways to write code in real-time on their browser IDE. It's like having an intelligent coding partner, making you a better, faster coder. AI Salesperson's Assistant For salespeople, the SiftHub AI acts like a virtual briefcase loaded with all the latest info on products and companies. With $5.5 million in funding, the company's AI preps sales teams so they can focus on building relationships during client meetings. Better Business Planning with AI Pigment scored a massive $145 million investment in its AI business planning software. The tool combines a company's data to precisely forecast finances and collaborate across departments on strategy. Fun AI Videos for Social Media Higgsfield created an app called Diffuse that uses AI to make animated videos on your phone. This app is perfect for posting engaging videos on TikTok, YouTube Shorts, and more. With $8 million invested, this startup is unleashing AI's video creation magic. These AI startups are completely changing how we work, farm, make videos, and more. The AI revolution has barely started! That is it for this edition of the newsletter. If you subscribe to our email edition, you get our newsletter first, and it stays in your mailbox as a future reference. Until next time, keep learning, applying, and experimenting with AI! That is it for this edition of the newsletter. If you subscribe to our email edition , you get our newsletter first, and it stays in your mailbox as a future reference. Until next time, keep learning, applying, and experimenting with AI! subscribe to our email edition Also published here. Also published here . here

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