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Phase space
Phase space
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Diagram showing the periodic orbit of a mass-spring system in simple harmonic motion. (The velocity and position axes have been reversed from the standard convention in order to align the two diagrams)

The phase space of a physical system is the set of all possible physical states of the system when described by a given parameterization. Each possible state corresponds uniquely to a point in the phase space. For mechanical systems, the phase space usually consists of all possible values of the position and momentum parameters. It is the direct product of direct space and reciprocal space.[clarification needed] The concept of phase space was developed in the late 19th century by Ludwig Boltzmann, Henri Poincaré, and Josiah Willard Gibbs.[1]

Principles

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In a phase space, every degree of freedom or parameter of the system is represented as an axis of a multidimensional space; a one-dimensional system is called a phase line, while a two-dimensional system is called a phase plane. For every possible state of the system or allowed combination of values of the system's parameters, a point is included in the multidimensional space. The system's evolving state over time traces a path (a phase-space trajectory for the system) through the high-dimensional space. The phase-space trajectory represents the set of states compatible with starting from one particular initial condition, located in the full phase space that represents the set of states compatible with starting from any initial condition. As a whole, the phase diagram represents all that the system can be, and its shape can easily elucidate qualities of the system that might not be obvious otherwise. A phase space may contain a great number of dimensions. For instance, a gas containing many molecules may require a separate dimension for each particle's x, y and z positions and momenta (6 dimensions for an idealized monatomic gas), and for more complex molecular systems additional dimensions are required to describe vibrational modes of the molecular bonds, as well as spin around 3 axes. Phase spaces are easier to use when analyzing the behavior of mechanical systems restricted to motion around and along various axes of rotation or translation – e.g. in robotics, like analyzing the range of motion of a robotic arm or determining the optimal path to achieve a particular position/momentum result.

Evolution of an ensemble of classical systems in phase space (top). The systems are a massive particle in a one-dimensional potential well (red curve, lower figure). The initially compact ensemble becomes swirled up over time.

Conjugate momenta

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In classical mechanics, any choice of generalized coordinates qi for the position (i.e. coordinates on configuration space) defines conjugate generalized momenta pi, which together define co-ordinates on phase space. More abstractly, in classical mechanics phase space is the cotangent bundle of configuration space, and in this interpretation the procedure above expresses that a choice of local coordinates on configuration space induces a choice of natural local Darboux coordinates for the standard symplectic structure on a cotangent space.

Statistical ensembles in phase space

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The motion of an ensemble of systems in this space is studied by classical statistical mechanics. The local density of points in such systems obeys Liouville's theorem, and so can be taken as constant. Within the context of a model system in classical mechanics, the phase-space coordinates of the system at any given time are composed of all of the system's dynamic variables. Because of this, it is possible to calculate the state of the system at any given time in the future or the past, through integration of Hamilton's or Lagrange's equations of motion.

In low dimensions

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For simple systems, there may be as few as one or two degrees of freedom. One degree of freedom occurs when one has an autonomous ordinary differential equation in a single variable, with the resulting one-dimensional system being called a phase line, and the qualitative behaviour of the system being immediately visible from the phase line. The simplest non-trivial examples are the exponential growth model/decay (one unstable/stable equilibrium) and the logistic growth model (two equilibria, one stable, one unstable).

The phase space of a two-dimensional system is called a phase plane, which occurs in classical mechanics for a single particle moving in one dimension, and where the two variables are position and velocity. In this case, a sketch of the phase portrait may give qualitative information about the dynamics of the system, such as the limit cycle of the Van der Pol oscillator shown in the diagram.

Here the horizontal axis gives the position, and vertical axis the velocity. As the system evolves, its state follows one of the lines (trajectories) on the phase diagram.

Phase portrait of the Van der Pol oscillator
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Phase plot

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A plot of position and momentum variables as a function of time is sometimes called a phase plot or a phase diagram. However the latter expression, "phase diagram", is more usually reserved in the physical sciences for a diagram showing the various regions of stability of the thermodynamic phases of a chemical system, which consists of pressure, temperature, and composition.

Phase portrait

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Potential energy and phase portrait of a simple pendulum. Note that the x-axis, being angular, wraps onto itself after every 2π radians.
Phase portrait of damped oscillator, with increasing damping strength. The equation of motion is

In mathematics, a phase portrait is a geometric representation of the orbits of a dynamical system in the phase plane. Each set of initial conditions is represented by a different point or curve.

Phase portraits are an invaluable tool in studying dynamical systems. They consist of a plot of typical trajectories in the phase space. This reveals information such as whether an attractor, a repellor or limit cycle is present for the chosen parameter value. The concept of topological equivalence is important in classifying the behaviour of systems by specifying when two different phase portraits represent the same qualitative dynamic behavior. An attractor is a stable point which is also called a "sink". The repeller is considered as an unstable point, which is also known as a "source".

A phase portrait graph of a dynamical system depicts the system's trajectories (with arrows) and stable steady states (with dots) and unstable steady states (with circles) in a phase space. The axes are of state variables.

Phase integral

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In classical statistical mechanics (continuous energies) the concept of phase space provides a classical analog to the partition function (sum over states) known as the phase integral.[2] Instead of summing the Boltzmann factor over discretely spaced energy states (defined by appropriate integer quantum numbers for each degree of freedom), one may integrate over continuous phase space. Such integration essentially consists of two parts: integration of the momentum component of all degrees of freedom (momentum space) and integration of the position component of all degrees of freedom (configuration space). Once the phase integral is known, it may be related to the classical partition function by multiplication of a normalization constant representing the number of quantum energy states per unit phase space. This normalization constant is simply the inverse of the Planck constant raised to a power equal to the number of degrees of freedom for the system.[3]

Applications

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Illustration of how a phase portrait would be constructed for the motion of a simple pendulum
Time-series flow in phase space specified by the differential equation of a pendulum. The X axis corresponds to the pendulum's position, and the Y axis its speed.

Chaos theory

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Classic examples of phase diagrams from chaos theory are:

Quantum mechanics

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In quantum mechanics, the coordinates p and q of phase space normally become Hermitian operators in a Hilbert space.

But they may alternatively retain their classical interpretation, provided functions of them compose in novel algebraic ways (through Groenewold's 1946 star product). This is consistent with the uncertainty principle of quantum mechanics. Every quantum mechanical observable corresponds to a unique function or distribution on phase space, and conversely, as specified by Hermann Weyl (1927) and supplemented by John von Neumann (1931); Eugene Wigner (1932); and, in a grand synthesis, by H. J. Groenewold (1946). With J. E. Moyal (1949), these completed the foundations of the phase-space formulation of quantum mechanics, a complete and logically autonomous reformulation of quantum mechanics.[4] (Its modern abstractions include deformation quantization and geometric quantization.)

Expectation values in phase-space quantization are obtained isomorphically to tracing operator observables with the density matrix in Hilbert space: they are obtained by phase-space integrals of observables, with the Wigner quasi-probability distribution effectively serving as a measure.

Thus, by expressing quantum mechanics in phase space (the same ambit as for classical mechanics), the Weyl map facilitates recognition of quantum mechanics as a deformation (generalization) of classical mechanics, with deformation parameter ħ/S, where S is the action of the relevant process. (Other familiar deformations in physics involve the deformation of classical Newtonian into relativistic mechanics, with deformation parameter v/c;[citation needed] or the deformation of Newtonian gravity into general relativity, with deformation parameter Schwarzschild radius/characteristic dimension.)[citation needed]

Classical expressions, observables, and operations (such as Poisson brackets) are modified by ħ-dependent quantum corrections, as the conventional commutative multiplication applying in classical mechanics is generalized to the noncommutative star-multiplication characterizing quantum mechanics and underlying its uncertainty principle.

Thermodynamics and statistical mechanics

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In thermodynamics and statistical mechanics contexts, the term "phase space" has two meanings: for one, it is used in the same sense as in classical mechanics. If a thermodynamic system consists of N particles, then a point in the 6N-dimensional phase space describes the dynamic state of every particle in that system, as each particle is associated with 3 position variables and 3 momentum variables. In this sense, as long as the particles are distinguishable, a point in phase space is said to be a microstate of the system. (For indistinguishable particles a microstate consists of a set of N! points, corresponding to all possible exchanges of the N particles.) N is typically on the order of the Avogadro number, thus describing the system at a microscopic level is often impractical. This leads to the use of phase space in a different sense.

The phase space can also refer to the space that is parameterized by the macroscopic states of the system, such as pressure, temperature, etc. For instance, one may view the pressure–volume diagram or temperature–entropy diagram as describing part of this phase space. A point in this phase space is correspondingly called a macrostate. There may easily be more than one microstate with the same macrostate. For example, for a fixed temperature, the system could have many dynamic configurations at the microscopic level. When used in this sense, a phase is a region of phase space where the system in question is in, for example, the liquid phase, or solid phase, etc.

Since there are many more microstates than macrostates, the phase space in the first sense is usually a manifold of much larger dimensions than in the second sense. Clearly, many more parameters are required to register every detail of the system down to the molecular or atomic scale than to simply specify, say, the temperature or the pressure of the system.

Optics

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Phase space is extensively used in nonimaging optics,[5] the branch of optics devoted to illumination. It is also an important concept in Hamiltonian optics.

Medicine

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In medicine and bioengineering, the phase space method is used to visualize multidimensional physiological responses.[6][7]

See also

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Applications
Mathematics
Physics

References

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Further reading

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In physics, phase space is a multidimensional space that represents all possible states of a , with each axis corresponding to a coordinate such as position or , allowing a complete description of the 's configuration at any instant. For a classical of N particles in , the phase space is typically 6N-dimensional, comprising 3N position coordinates and 3N coordinates, forming a comprehensive framework for analyzing trajectories and evolutions under . The concept originated in the late 19th century amid efforts to formalize , with early contributions from , who introduced the concept of "phase" in 1872 to describe the distribution of molecular states, and the term "phase space" coined by J. Willard Gibbs in 1902, with refinements by emphasizing its role in ensemble theory and ergodic behavior. In classical , phase space underpins key principles such as , which states that the phase space volume occupied by an ensemble of systems remains constant over time due to the incompressible flow of trajectories, enabling predictions of thermodynamic properties from microscopic dynamics. This conservation property highlights phase space's utility in bridging deterministic mechanics with probabilistic descriptions of large systems. In , phase space adapts to the through quasi-probability distributions, such as the Wigner function, which provides a phase-space representation of the density operator while revealing interference effects and the . These formulations, developed prominently by in 1932, allow quantum states to be visualized in a continuous phase space despite the discrete nature of observables, facilitating comparisons between classical and quantum behaviors in areas like and many-body physics. Beyond fundamental theory, phase space concepts extend to applications in , where Poincaré sections map complex trajectories to lower dimensions, and in fields like control systems, aiding the analysis of stability and attractors.

Fundamental Principles

Definition and Coordinates

In and , the concept of phase space, developed in the late 19th century including contributions from , was advanced by in his 1902 book Elementary Principles in Statistical Mechanics, where he explicitly termed it "phase space" while representing the states of a mechanical system in a multidimensional space. This framework was further formalized within , building on William Rowan Hamilton's 1834 reformulation of dynamics, where phase space provides a complete description of a system's evolution. Phase space is mathematically defined as the TQT^*Q of the configuration space QQ, which parameterizes all possible positions of the ; for a with nn , the phase space has 2n2n, and each point (q,p)(q, p) uniquely specifies the state of the at a given time, encompassing both positional and . In this construction, the configuration space QQ is typically a manifold of nn, such as Rn\mathbb{R}^n for unconstrained particles, and the equips it with fiber coordinates representing momenta, enabling a symplectic structure that preserves the geometry under dynamics. The standard coordinates of phase space consist of generalized position coordinates qiq_i (for i=1,,ni = 1, \dots, n) and their conjugate momenta pip_i, defined via the Lagrangian as pi=Lq˙ip_i = \frac{\partial L}{\partial \dot{q}_i}, where LL is the system's Lagrangian. For a single particle in one dimension, phase space is two-dimensional with coordinates (q,p)(q, p), where qq is position and p=mq˙p = m \dot{q} is ; for NN non-interacting particles in three dimensions, it extends to 6N6N-dimensional with coordinates (q1,p1,,qN,pN)( \mathbf{q}_1, \mathbf{p}_1, \dots, \mathbf{q}_N, \mathbf{p}_N ). The dynamics on this space are governed by the Hamiltonian H(q,p,t)H(q, p, t), the total energy expressed in terms of these coordinates, through Hamilton's equations: dqidt=Hpi,dpidt=Hqi.\frac{dq_i}{dt} = \frac{\partial H}{\partial p_i}, \quad \frac{dp_i}{dt} = -\frac{\partial H}{\partial q_i}. These equations describe trajectories in phase space as integral curves of the Hamiltonian vector field. Canonical transformations are coordinate changes (q,p)(Q,P)(q, p) \to (Q, P) that preserve the form of Hamilton's equations and the symplectic structure of phase space, ensuring that the new coordinates Qi,PiQ_i, P_i also satisfy the conjugate pairing and the fundamental Poisson brackets {qi,pj}=δij\{q_i, p_j\} = \delta_{ij}. Such transformations maintain the geometric integrity of phase space, allowing equivalent descriptions of the same dynamics.

Conjugate Variables

In , form pairs consisting of qiq_i and their corresponding momenta pip_i, where the momenta are defined through the of the Lagrangian L(q,q˙,t)L(q, \dot{q}, t) to the Hamiltonian H(q,p,t)H(q, p, t), specifically pi=Lq˙ip_i = \frac{\partial L}{\partial \dot{q}_i}. This pairing elevates the velocities q˙i\dot{q}_i to independent dynamical variables pip_i, enabling a symmetric formulation of the in phase space. The symplectic structure of phase space arises from these conjugate pairs, endowing the space with a that encodes the fundamental algebraic relations: {qi,pj}=δij\{q_i, p_j\} = \delta_{ij}, {qi,qj}=0\{q_i, q_j\} = 0, and {pi,pj}=0\{p_i, p_j\} = 0, where δij\delta_{ij} is the . More generally, for smooth functions ff and gg on the phase space, the is defined as {f,g}=i(fqigpifpigqi),\{f, g\} = \sum_i \left( \frac{\partial f}{\partial q_i} \frac{\partial g}{\partial p_i} - \frac{\partial f}{\partial p_i} \frac{\partial g}{\partial q_i} \right), which satisfies bilinearity, antisymmetry, and the , thereby defining a on the manifold. This bracket governs the of any function ff via dfdt={f,H}+ft\frac{df}{dt} = \{f, H\} + \frac{\partial f}{\partial t}, where HH is the Hamiltonian, yielding Hamilton's equations as a special case for f=qif = q_i or pip_i. Canonical coordinates refer to any set of variables (Qk,Pk)(Q_k, P_k) obtained from the original (qi,pi)(q_i, p_i) via point transformations that preserve the fundamental Poisson brackets, ensuring the symplectic structure remains invariant. Such transformations maintain the form of Hamilton's equations and are essential for simplifying problems in . Darboux's theorem guarantees that any admits a local where the symplectic form takes the canonical Darboux form idqidpi\sum_i dq_i \wedge dp_i, affirming the local existence of conjugate coordinates around any point. This result underscores the uniformity of , implying no local invariants beyond the dimension in such spaces.

Liouville's Theorem

Liouville's theorem states that in Hamiltonian systems, the volume of any region in phase space remains invariant under , implying an where phase space volumes neither expand nor contract despite the deformation of their shapes. This invariance underscores the deterministic and reversible nature of classical Hamiltonian dynamics, ensuring that the measure of accessible states is preserved along trajectories. The theorem was originally proved by in 1838 in the context of differential equations, without explicit reference to phase space or . An independent proof was provided by around 1842, later published in 1866, where he applied it to mechanical systems using Hamilton's equations. To sketch the proof, consider the velocity field in phase space derived from Hamilton's equations for qiq_i and pip_i: q˙i=Hpi\dot{q}_i = \frac{\partial H}{\partial p_i} and p˙i=Hqi\dot{p}_i = -\frac{\partial H}{\partial q_i}, so the field is v=(Hp1,,Hq1,)\mathbf{v} = \left( \frac{\partial H}{\partial p_1}, \dots, -\frac{\partial H}{\partial q_1}, \dots \right). The is v=i(qiHpi+pi(Hqi))=0,\nabla \cdot \mathbf{v} = \sum_i \left( \frac{\partial}{\partial q_i} \frac{\partial H}{\partial p_i} + \frac{\partial}{\partial p_i} \left( -\frac{\partial H}{\partial q_i} \right) \right) = 0, since the mixed partial derivatives commute. By the , the rate of change of a phase space volume VV is dVdt=V(v)dV=0.\frac{dV}{dt} = \int_V (\nabla \cdot \mathbf{v}) \, dV = 0. Geometrically, the time evolution corresponds to a that preserves the symplectic 2-form ω=idqidpi\omega = \sum_i dq_i \wedge dp_i, ensuring the flow maintains the volume element dV=ωn/n!dV = \omega^n / n! for an nn-degree-of-freedom system. This preservation highlights how Hamiltonian flows act like shear deformations in phase space, distorting shapes without altering volumes.

Low-Dimensional Representations

One-Dimensional Systems

In one-dimensional systems, the phase space is a two-dimensional plane parameterized by the position coordinate qq and its conjugate pp, representing the state of a with a single degree of freedom. Trajectories in this space trace the evolution of the system under the governing dynamics, with the Hamiltonian H(q,p)H(q, p) determining the flow. A canonical example is the simple harmonic oscillator, governed by the Hamiltonian H=p22m+12kq2H = \frac{p^2}{2m} + \frac{1}{2} k q^2, where mm is the and kk is the spring constant. The constant-energy contours form closed elliptical trajectories in the (q,p)(q, p) plane, as the total energy E=HE = H remains fixed, yielding p=±2m(E12kq2)p = \pm \sqrt{2m \left( E - \frac{1}{2} k q^2 \right)}
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