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Gravity makes things orbit...but what happens when the mass distribution itself is rotating and dragging phase space into resonances and chaos? In this scene we follow tens of thousands of stars in a toy barred galaxy: a flat disc with a central mass and a rotating bar of extra...

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Mathelirium

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152,143 просмотров • 7 месяцев назад •via X (Twitter)

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When gravitational potential rotates, it can lock onto an orbit’s phase and start rearranging motion. Order can turn into visible structure, and structure can slide into chaos, without any collisions or extra bodies. This is a toy barred galaxy...a softened central potential plus a rotating bar-shaped overdensity. The bar's angle sways and wobbles, and its strength breathes over time, so the force field keeps changing.
1:00

When gravitational potential rotates, it can lock onto an orbit’s phase and start rearranging motion. Order can turn into visible structure, and structure can slide into chaos, without any collisions or extra bodies. This is a toy barred galaxy...a softened central potential plus a rotating bar-shaped overdensity. The bar's angle sways and wobbles, and its strength breathes over time, so the force field keeps changing.

Mathelirium

10,118 просмотров • 4 месяцев назад

We know gravity pulls things together in space...but have you ever seen what it does in phase space? In this scene we're not watching a blob of matter in x–space. We're watching a thin probability sheet in (x, v).... position–velocity space... being pulled by its own gravity. In the collisionless limit, Liouville’s theorem says this sheet can stretch, fold, and swirl, but never tear or change area. Collapse in x is "paid for" by stretching in v. Numerically, this is a 1D cold-dark-matter toy universe: a sheet of particles evolved under the Vlasov-Poisson system. We solve Poisson on a periodic line, get the self-consistent gravitational field, then integrate Hamilton’s equations so the sheet folds into a multi-layer spiral. The glowing filaments are where the sheet keeps revisiting, carving out dense caustics in phase space. It's gravity not as "stuff falling down," but as area-preserving origami in phase space. #Mathelirium #VlasovPoisson #PhaseSpace #Liouville #DarkMatter #HamiltonianFlow #ProbabilityFlow
0:40

We know gravity pulls things together in space...but have you ever seen what it does in phase space? In this scene we're not watching a blob of matter in x–space. We're watching a thin probability sheet in (x, v).... position–velocity space... being pulled by its own gravity. In the collisionless limit, Liouville’s theorem says this sheet can stretch, fold, and swirl, but never tear or change area. Collapse in x is "paid for" by stretching in v. Numerically, this is a 1D cold-dark-matter toy universe: a sheet of particles evolved under the Vlasov-Poisson system. We solve Poisson on a periodic line, get the self-consistent gravitational field, then integrate Hamilton’s equations so the sheet folds into a multi-layer spiral. The glowing filaments are where the sheet keeps revisiting, carving out dense caustics in phase space. It's gravity not as "stuff falling down," but as area-preserving origami in phase space. #Mathelirium #VlasovPoisson #PhaseSpace #Liouville #DarkMatter #HamiltonianFlow #ProbabilityFlow

Mathelirium

47,586 просмотров • 7 месяцев назад

You're watching spacetime in motion...two spinning black holes orbit, twist, and merge, dragging the very geometry of the universe into a luminous storm. Their union births a single remnant that fires smoke-wreathed jet as gravitational waves ring the cosmic fabric itself. 🤩😍 #Math #Physics #Astrophysics #SciArt #MathArt
1:00

You're watching spacetime in motion...two spinning black holes orbit, twist, and merge, dragging the very geometry of the universe into a luminous storm. Their union births a single remnant that fires smoke-wreathed jet as gravitational waves ring the cosmic fabric itself. 🤩😍 #Math #Physics #Astrophysics #SciArt #MathArt

Mathelirium

42,531 просмотров • 7 месяцев назад

A Hamiltonian system is a way of describing motion where position and momentum evolve together as one coupled system. The plot shows an energy landscape in phase space, with the motion of the system traced directly on top of it and projected onto the underlying phase portrait. #HamiltonianSystems #PhaseSpace #PhysicsSimulation #DynamicalSystems #MathematicalPhysics
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A Hamiltonian system is a way of describing motion where position and momentum evolve together as one coupled system. The plot shows an energy landscape in phase space, with the motion of the system traced directly on top of it and projected onto the underlying phase portrait. #HamiltonianSystems #PhaseSpace #PhysicsSimulation #DynamicalSystems #MathematicalPhysics

Mathelirium

35,744 просмотров • 1 месяц назад

We know gravity pulls things together in space… but have you ever watched it work in phase space? In this scene we’re looking at a thin probability sheet in (x, v) position-velocity space evolving under its own self-gravity. In the collisionless limit, Liouville’s theorem says the sheet can stretch, fold, and swirl, but it can’t tear and it can’t change area. Any collapse in x is paid for by stretching in v. Numerically this is a 1D cold-dark-matter toy universe: a sheet of particles evolved under the Vlasov-Poisson system. We solve Poisson on a periodic line to get the self-consistent gravitational field, then integrate Hamilton’s equations so the sheet folds into a multi-layer spiral. The glowing filaments are the places the sheet keeps revisiting dense, sharp caustics carved into phase space. Gravity here isn’t stuff falling down. It’s area-preserving origami in (x, v). #Physics #VlasovPoisson #PhaseSpace #Liouville #DarkMatter #HamiltonianFlow #ProbabilityFlow #Mathematics
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We know gravity pulls things together in space… but have you ever watched it work in phase space? In this scene we’re looking at a thin probability sheet in (x, v) position-velocity space evolving under its own self-gravity. In the collisionless limit, Liouville’s theorem says the sheet can stretch, fold, and swirl, but it can’t tear and it can’t change area. Any collapse in x is paid for by stretching in v. Numerically this is a 1D cold-dark-matter toy universe: a sheet of particles evolved under the Vlasov-Poisson system. We solve Poisson on a periodic line to get the self-consistent gravitational field, then integrate Hamilton’s equations so the sheet folds into a multi-layer spiral. The glowing filaments are the places the sheet keeps revisiting dense, sharp caustics carved into phase space. Gravity here isn’t stuff falling down. It’s area-preserving origami in (x, v). #Physics #VlasovPoisson #PhaseSpace #Liouville #DarkMatter #HamiltonianFlow #ProbabilityFlow #Mathematics

Mathelirium

16,437 просмотров • 5 месяцев назад

What happens when you take a polynomial and keep changing its coefficients every frame? You get a resonant root field in the complex plane where clusters, arcs and outer flares form, dissolve, and reappear as the system evolves in time.
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What happens when you take a polynomial and keep changing its coefficients every frame? You get a resonant root field in the complex plane where clusters, arcs and outer flares form, dissolve, and reappear as the system evolves in time.

Mathelirium

17,344 просмотров • 1 месяц назад

Erwin Schrödinger’s 1926 equation changed the game by turning Quantum Mechanics into wave dynamics. That move gave Physics a new way to think. Instead of forcing a particle onto one sharp path, it lets a complex wavefunction evolve in time, with its shape and phase holding the structure of the phenomenon. What makes this so striking is that Schrödinger’s equation does not start from vague mystery. It starts from a precise and daring idea The state of a particle is a complex field ψ(x,t), and the dynamics must push ψ forward in a way that preserves total probability.
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Erwin Schrödinger’s 1926 equation changed the game by turning Quantum Mechanics into wave dynamics. That move gave Physics a new way to think. Instead of forcing a particle onto one sharp path, it lets a complex wavefunction evolve in time, with its shape and phase holding the structure of the phenomenon. What makes this so striking is that Schrödinger’s equation does not start from vague mystery. It starts from a precise and daring idea The state of a particle is a complex field ψ(x,t), and the dynamics must push ψ forward in a way that preserves total probability.

Mathelirium

54,730 просмотров • 3 месяцев назад

The Elusive Concept of Time - Part II Pulsar Timing The first scene showed you Time as a local rate...clocks nearer the hole run slower, light gets redshifted, and spin drags the geometry around. This follow-up keeps the same idea, but turns it into a timing experiment. Instead of watching a clock face, we watch a receiver compare what arrives versus what flat space would predict. In the animation, the three small orange dots are the pulsars...orbiting emitters that flash regularly (in their own proper time). The larger white dot is the receiver sitting off to the side, and the little dark nub next to it is a tiny craft/antenna marker to make it feel like an instrument, not a star. When a pulsar lines up behind the hole relative to the receiver, the arrival times jump, because curved spacetime added extra delay and bent the path. #Physics #GeneralRelativity #PulsarTiming #BlackHoles #FrameDragging #Spacetime #Astrophysics #Time
1:00

The Elusive Concept of Time - Part II Pulsar Timing The first scene showed you Time as a local rate...clocks nearer the hole run slower, light gets redshifted, and spin drags the geometry around. This follow-up keeps the same idea, but turns it into a timing experiment. Instead of watching a clock face, we watch a receiver compare what arrives versus what flat space would predict. In the animation, the three small orange dots are the pulsars...orbiting emitters that flash regularly (in their own proper time). The larger white dot is the receiver sitting off to the side, and the little dark nub next to it is a tiny craft/antenna marker to make it feel like an instrument, not a star. When a pulsar lines up behind the hole relative to the receiver, the arrival times jump, because curved spacetime added extra delay and bent the path. #Physics #GeneralRelativity #PulsarTiming #BlackHoles #FrameDragging #Spacetime #Astrophysics #Time

Mathelirium

55,826 просмотров • 5 месяцев назад

Earth orbits the Sun, and the Sun orbits the center of the galaxy... but what is the Milky Way itself orbiting? The Milky Way is not orbiting a single object. Instead, it is moving around a shared center of mass alongside the Andromeda galaxy. While most of the universe is being pushed apart by dark energy, the gravity within our "Local Group" is strong enough to pull these two galaxies toward each other in a slow "cosmic dance." This movement isn't a clean, circular orbit; it is a direct path toward a massive collision and merger that will occur in about 4 to 5 billion years.
1:21

Earth orbits the Sun, and the Sun orbits the center of the galaxy... but what is the Milky Way itself orbiting? The Milky Way is not orbiting a single object. Instead, it is moving around a shared center of mass alongside the Andromeda galaxy. While most of the universe is being pushed apart by dark energy, the gravity within our "Local Group" is strong enough to pull these two galaxies toward each other in a slow "cosmic dance." This movement isn't a clean, circular orbit; it is a direct path toward a massive collision and merger that will occur in about 4 to 5 billion years.

Cosmos Archive

47,427 просмотров • 4 месяцев назад

Phase Space Is the Real Stage of Dynamics. So, Stop Watching the Object and Watch the State. Ordinary Space tells you where something is. Phase Space tells you what state it is in. Position alone is not enough because you also need the variable that tells you where the system is trying to go. In the animation, the left panel shows the particle moving in Ordinary Space, while the right panel shows the same system as a moving point in Phase Space. For one degree of freedom, the state is (x, p) and as time evolves, that state traces a trajectory t ↦ (x(t), p(t)) Instead of thinking of a differential equation as just a formula, Phase Space lets you see it as a flow on the space of states. For this lecture we use ẋ = p ṗ = x − x³ with Hamiltonian H(x,p) = 0.5 p² + 0.25 x⁴ − 0.5 x² #PhaseSpace #DynamicalSystems #NonlinearDynamics #HamiltonianMechanics #Mathematics
0:30

Phase Space Is the Real Stage of Dynamics. So, Stop Watching the Object and Watch the State. Ordinary Space tells you where something is. Phase Space tells you what state it is in. Position alone is not enough because you also need the variable that tells you where the system is trying to go. In the animation, the left panel shows the particle moving in Ordinary Space, while the right panel shows the same system as a moving point in Phase Space. For one degree of freedom, the state is (x, p) and as time evolves, that state traces a trajectory t ↦ (x(t), p(t)) Instead of thinking of a differential equation as just a formula, Phase Space lets you see it as a flow on the space of states. For this lecture we use ẋ = p ṗ = x − x³ with Hamiltonian H(x,p) = 0.5 p² + 0.25 x⁴ − 0.5 x² #PhaseSpace #DynamicalSystems #NonlinearDynamics #HamiltonianMechanics #Mathematics

Mathelirium

30,340 просмотров • 3 месяцев назад

Boost A Mass To Light Speed, And Gravity Becomes A Shockwave. The Aichelburg-Sexl Ultraboost is an exact solution of General Relativity obtained by boosting the Schwarzschild gravitational field toward light speed while keeping the energy finite.
0:30

Boost A Mass To Light Speed, And Gravity Becomes A Shockwave. The Aichelburg-Sexl Ultraboost is an exact solution of General Relativity obtained by boosting the Schwarzschild gravitational field toward light speed while keeping the energy finite.

Mathelirium

12,414 просмотров • 2 месяцев назад

You're watching a Quadratic-Differential Teichmüller flow unfold. We drive the scene with a time-varying quadratic differential built from moving zeros and poles. Its log-magnitude sets the color, and its phase defines the horizontal foliation (the direction is half the phase). Then a Teichmüller stretch biases things along vs. against that foliation...so the surface deforms in a geodesic-like way. 🤩🤗🫠
1:26

You're watching a Quadratic-Differential Teichmüller flow unfold. We drive the scene with a time-varying quadratic differential built from moving zeros and poles. Its log-magnitude sets the color, and its phase defines the horizontal foliation (the direction is half the phase). Then a Teichmüller stretch biases things along vs. against that foliation...so the surface deforms in a geodesic-like way. 🤩🤗🫠

Mathelirium

11,938 просмотров • 8 месяцев назад

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML
0:59

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

Mathelirium

139,588 просмотров • 7 месяцев назад

Black Hole Can Ring Like a Bell A Black Hole can vibrate after it is disturbed. Instead of settling instantly, its horizon releases gravitational waves in fading tones called quasinormal modes. This is commonly known as Ringdown. Each tone carries information about the black hole’s final mass and spin, which is why physicists call this Black-Hole Spectroscopy. In a way, when Spacetime strikes a Black Hole, the Black Hole answers with its own gravitational sound. #BlackHole #GeneralRelativity #GravitationalWaves #Spacetime #Einstein #Astrophysics #Physics #Mathematics #Cosmology
0:50

Black Hole Can Ring Like a Bell A Black Hole can vibrate after it is disturbed. Instead of settling instantly, its horizon releases gravitational waves in fading tones called quasinormal modes. This is commonly known as Ringdown. Each tone carries information about the black hole’s final mass and spin, which is why physicists call this Black-Hole Spectroscopy. In a way, when Spacetime strikes a Black Hole, the Black Hole answers with its own gravitational sound. #BlackHole #GeneralRelativity #GravitationalWaves #Spacetime #Einstein #Astrophysics #Physics #Mathematics #Cosmology

Mathelirium

30,136 просмотров • 6 дней назад

A common misconception in physics is that gravity must be negligible at the quantum scale because its measured strength appears weak compared to electromagnetism and the strong nuclear force. However, this perception arises from considering gravity only in its weak field limit. Obviously, it will appear weak under such conditions, but the situation changes when we consider regions of high mass-energy density. For example, when examining strong gravitational fields near black holes, the force becomes immensely powerful. With this in mind, lets re-examine unification and gravity at the quantum scale: Following our holographic mass solution, elementary particles like protons are found to be microscopic Schwarzschild black holes and their mass-energy density is sufficient to create a gravitational curvature equivalent to the strong nuclear force. The vacuum energy density of space provides enough energy to maintain these structures through Planck-scale dynamics, preventing their rapid evaporation via Hawking radiation, so they are ultra-stable. These discoveries, expounded in our studies like The Origin of Mass and the Nature of Gravity, available to download for free on CERN's Zenodo preprint server-🔗 -demonstrate that what we observe as distinct fundamental forces are in fact manifestations of a unified force operating at different scales, where quantum vacuum fluctuations significantly curve spacetime (the curvature being gravity) with the resulting encapsulation generating screening effects that modulate the apparent strength of gravity from its fundamental high-energy state, which results in nuclear confinement forces, to its familiar weak-field behavior that appears as regular Newtonian gravity.
0:30

A common misconception in physics is that gravity must be negligible at the quantum scale because its measured strength appears weak compared to electromagnetism and the strong nuclear force. However, this perception arises from considering gravity only in its weak field limit. Obviously, it will appear weak under such conditions, but the situation changes when we consider regions of high mass-energy density. For example, when examining strong gravitational fields near black holes, the force becomes immensely powerful. With this in mind, lets re-examine unification and gravity at the quantum scale: Following our holographic mass solution, elementary particles like protons are found to be microscopic Schwarzschild black holes and their mass-energy density is sufficient to create a gravitational curvature equivalent to the strong nuclear force. The vacuum energy density of space provides enough energy to maintain these structures through Planck-scale dynamics, preventing their rapid evaporation via Hawking radiation, so they are ultra-stable. These discoveries, expounded in our studies like The Origin of Mass and the Nature of Gravity, available to download for free on CERN's Zenodo preprint server-🔗 -demonstrate that what we observe as distinct fundamental forces are in fact manifestations of a unified force operating at different scales, where quantum vacuum fluctuations significantly curve spacetime (the curvature being gravity) with the resulting encapsulation generating screening effects that modulate the apparent strength of gravity from its fundamental high-energy state, which results in nuclear confinement forces, to its familiar weak-field behavior that appears as regular Newtonian gravity.

Nassim Haramein

19,882 просмотров • 1 год назад

When the Lorenz Attractor Becomes a Cosmos Many of us have seen plots of the famous Lorenz system that famous butterfly-shaped chaos: ẋ = σ(y - x) ẏ = x(ρ - z) - y ż = xy - βz But here, we went one layer deeper. At every point (x, y, z), we computed the local Jacobian matrix, J(x, y, z) = [ -σ σ 0 ] [ ρ - z -1 - x ] [ y x - β ] Then we found its eigenvalues λ and plotted them in the complex plane. Re(λ) tells us whether nearby motion is locally growing or decaying. Im(λ) tells us whether that local motion is rotating. That gives us the spectral flow of the Lorenz system and not the attractor itself, but the hidden local linear geometry driving its instability. When I saw that flow, it looked strangely cosmic with two mirrored swarms curling like particles trapped in a mathematical whirlpool. So I mapped that spectral flow onto our living fabric, not as Einstein Spacetime this time, but as a creative geometric stage for chaos itself. #LorenzSystem #ChaosTheory #DynamicalSystems #Eigenvalues #SpectralFlow #ComplexPlane #NonlinearDynamics #Mathematics #Physics
0:40

When the Lorenz Attractor Becomes a Cosmos Many of us have seen plots of the famous Lorenz system that famous butterfly-shaped chaos: ẋ = σ(y - x) ẏ = x(ρ - z) - y ż = xy - βz But here, we went one layer deeper. At every point (x, y, z), we computed the local Jacobian matrix, J(x, y, z) = [ -σ σ 0 ] [ ρ - z -1 - x ] [ y x - β ] Then we found its eigenvalues λ and plotted them in the complex plane. Re(λ) tells us whether nearby motion is locally growing or decaying. Im(λ) tells us whether that local motion is rotating. That gives us the spectral flow of the Lorenz system and not the attractor itself, but the hidden local linear geometry driving its instability. When I saw that flow, it looked strangely cosmic with two mirrored swarms curling like particles trapped in a mathematical whirlpool. So I mapped that spectral flow onto our living fabric, not as Einstein Spacetime this time, but as a creative geometric stage for chaos itself. #LorenzSystem #ChaosTheory #DynamicalSystems #Eigenvalues #SpectralFlow #ComplexPlane #NonlinearDynamics #Mathematics #Physics

Mathelirium

22,342 просмотров • 13 дней назад

We often hear that Machine Learning models learn patterns in data. But what does that look like in geometry? Picture dropping an elastic mesh into a cloud of points and letting it adapt. How would it bend, stretch, and settle so it matches the shape hiding in the data? In this scene we watch a self-organizing map(SOM)...a classic unsupervised neural model...learn a 2D dataset arranged like a spiral arm. Over the points we place a square grid of neurons whose weights live in the same plane. At the start it’s just a flat net drifting across the cloud. No clue what the structure is. Fir the SOM, learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, then nudge that neuron and its neighbours toward the point. Repeat, repeat, repeat...while gradually shrinking how wide the neighbourhood influence spreads. The result is satisfying...the grid stops being a grid and turns into a coordinate sheet wrapped onto the spiral. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML #SelfOrganizingMap #Topology
0:59

We often hear that Machine Learning models learn patterns in data. But what does that look like in geometry? Picture dropping an elastic mesh into a cloud of points and letting it adapt. How would it bend, stretch, and settle so it matches the shape hiding in the data? In this scene we watch a self-organizing map(SOM)...a classic unsupervised neural model...learn a 2D dataset arranged like a spiral arm. Over the points we place a square grid of neurons whose weights live in the same plane. At the start it’s just a flat net drifting across the cloud. No clue what the structure is. Fir the SOM, learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, then nudge that neuron and its neighbours toward the point. Repeat, repeat, repeat...while gradually shrinking how wide the neighbourhood influence spreads. The result is satisfying...the grid stops being a grid and turns into a coordinate sheet wrapped onto the spiral. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML #SelfOrganizingMap #Topology

Mathelirium

23,021 просмотров • 5 месяцев назад

Speech Carries Its Own Hidden Geometry in Phase Space Speech is usually shown as a waveform of amplitude changing in time. Phase-space reconstruction gives a different view by pairing the signal with a delayed version of itself, so the voice is seen as a path rather than just a trace. On the left is the raw sound signal. On the right is the geometric structure formed by rhythm, syllables, and emphasis as the voice unfolds. * Real human speech data from the public GitHub repository voxserv/audio_quality_testing_samples, using the 16 kHz file test01_20s.wav.
0:30

Speech Carries Its Own Hidden Geometry in Phase Space Speech is usually shown as a waveform of amplitude changing in time. Phase-space reconstruction gives a different view by pairing the signal with a delayed version of itself, so the voice is seen as a path rather than just a trace. On the left is the raw sound signal. On the right is the geometric structure formed by rhythm, syllables, and emphasis as the voice unfolds. * Real human speech data from the public GitHub repository voxserv/audio_quality_testing_samples, using the 16 kHz file test01_20s.wav.

Mathelirium

18,725 просмотров • 3 месяцев назад

This video has been a work in progress for a few weeks, but with the precarious situation we find ourselves in, we feel that now is the time to show the strength of Ospreys support. Here’s how far and wide we reach outside of Ospreylia with more to follow!
0:46

This video has been a work in progress for a few weeks, but with the precarious situation we find ourselves in, we feel that now is the time to show the strength of Ospreys support. Here’s how far and wide we reach outside of Ospreylia with more to follow!

Ospreys Supporters

28,196 просмотров • 5 месяцев назад