Abstract
Entropic Dynamics (ED) is a framework that allows one to derive quantum theory as a Hamilton–Killing flow on the cotangent bundle of a statistical manifold. These flows are such that they preserve the symplectic and the metric geometries; they explain the linearity of quantum mechanics and the appearance of complex numbers. In this paper the ED framework is extended to deal with local gauge symmetries. More specifically, on the basis of maximum entropy methods and information geometry, for an appropriate choice of ontic variables and constraints, we derive the quantum dynamics of radiation fields interacting with charged particles.
1. Introduction
With Einstein’s successful introduction of the concept of photons in 1905, the old enigma of the nature of radiation—is it waves or is it particles?—was brought back into physics [1]. It provided the motivation and the context for de Broglie’s matter waves, for Schrödinger’s wave mechanics, and for Bohr’s complementarity [2]. It also marks the beginning of the long history of controversy over conceptual issues concerning the interpretation of quantum mechanics that endure to this day.
Entropic Dynamics (ED) is a framework that was designed to address these conceptual issues. It provides a realist -epistemic interpretation that allows the derivation or reconstruction of the mathematical formalism of quantum theory on the basis of established principles of inference, which include probability theory, entropic methods, and information geometry [3] (for a pedagogical review see [4]). Its signal characteristic is a clear distinction of variables that represent the ontology from variables that represent the epistemology. The ontic variables, those which represent what is real, have definite values at all times; however, they are generally unknown and are, therefore, uncertain. Managing these uncertainties requires the introduction of epistemic variables—the probabilities—and it is the evolution of these probabilities that constitutes the main subject of the theory. Thus, ED is quite conservative in that it achieves an ontic/epistemic clarity that is characteristic of classical theories, but, on the other hand, ED is radically non-classical in that the dynamics is totally relegated to the epistemic sector. ED is a dynamics of probabilities; there is no ontic dynamics.
An important consequence of Entropic Dynamics is that if the dynamical variables—the probabilities—are epistemic, then so must be their canonically conjugate momenta. It may be somewhat surprising, but it is nevertheless true that there are no ontic momenta directly associated with either the particles or the potentials. These quantities are absent from the quantum ontology; they emerge only in the classical limit. Thus, ED paints an ontic picture that is radically different from that proposed by classical physics. Furthermore, being a special instance of the updating of probabilities, the dynamics of probabilities is severely constrained by the requirement that it must be consistent with the rules of entropic and Bayesian inference. It is this restriction that motivates the name ‘entropic’ dynamics. Incidentally, it is the interpretation of probabilities as epistemic variables—that probabilities represent degrees of rational belief—that demands a Bayesian approach.
In this paper the framework of Entropic Dynamics is extended to tackle a local gauge theory. We shall apply it to derive a paradigmatic example of quantum electrodynamics (QED). An obvious question immediately arises: Since QED is one of the most successful and most studied theories in physics, why bother? There are two reasons. The first is that questions of interpretation still plague QED. Here, by reconstructing the formalism of QED, we shall clarify issues such as ‘what is ontic?’ and ‘what is epistemic?’. The second reason for tackling QED is to understand how to handle gauge invariance within the context of Entropic Dynamics. The standard approaches to the quantum theory of gauge fields (see, e.g., [5,6,7]) rely heavily on first formulating a classical gauge theory [8], which is subsequently modified by the imposition of quantization rules. ED follows an altogether different approach. It skips the prior formulation of a classical theory and the application of quantization rules and proceeds directly to formulating the quantum theory. The ED approach to quantum gauge fields is conceptually very different from those advocated in the past.
We shall confine our attention to the QED of non-relativistic point charges. This is clearly an idealization, but it will allow us to focus our attention on a number of foundational issues relevant to local gauge theories while avoiding distracting issues (e.g., particle creation, vacuum polarization, etc.) of relativistic origin. However, not all relativistic considerations are irrelevant distractions; some previous work related to the interplay between gauge and relativity effects can be found in [9,10], and other important applications will be left for future work.
This paper is structured as follows: In Section 2 we introduce the microstates that represent the real things, the particles and the gauge fields, recognizing that the representation of the latter is redundant. The symplectic and information geometry of the epistemic phase space of probabilities and their conjugate momenta are established in Section 3. In Section 4 we study kinematics; namely, we characterize those special congruences of curves—the Hamilton–Killing flows—that are adapted to the geometric structures of the epistemic phase space.
Entropic Dynamics is the subject of Section 5. There, we use the method of maximum entropy to calculate the transition probability for an infinitesimally short step and introduce the notion of entropic time as a device to keep track of the accumulation of many such short steps. Then we derive the Hamiltonian that generates evolution in entropic time. As a first, albeit standard, application, we derive the conservation of charge.
In Section 6 we complete the derivation of QED. We discuss the additional requirements that implement gauge invariance and derive the Gauss constraint. Then, we derive the Maxwell equations and verify the emergence of the Coulomb potential. These latter developments yield the already well-known results but with a different interpretation; they serve to reassure us that despite its unorthodox foundations, the ED approach is empirically successful. Section 7 provides a brief summary of the main conclusions, including the fact that in ED, there are no ontic matter waves and there are no ontic photon particles.
2. The Ontic Microstates
In the ED of nonrelativistic matter, the ontic microstates are assigned properties that are clearly recognized as those of particles: they have definite positions and follow continuous trajectories. On the other hand, the ontic microstates of radiation are assigned properties that are clearly recognized as those of fields: to every point x in space one assigns a vector potential degree of freedom .
Our system consists of N particles and a radiation field living in a flat 3-dimensional Euclidean space with metric . The ontic microstates of the particles are represented by the coordinates of their positions , collectively denoted by . (The index n labels the particles and the three spatial coordinates.) The -dimensional ontic configuration space for N particles is denoted by , so that . The ontic microstates of the radiation field are represented by vector potential distributions with . To simplify the notation we shall write . The set of field microstates form the ontic configuration space ; each field configuration is a point . The full ontic configuration space is the Cartesian product .
We have already made two important assumptions about the ontology: the particles’ positions and the radiation field have definite values at all times and they follow continuous trajectories. These two assumptions are in contradiction with the standard Copenhagen interpretation of quantum mechanics.
A third and central assumption is close in spirit to the classical theory of gauge fields: the representation of the radiation field by the field is redundant in that a gauge shift to the new field
where is a scalar function, represents the same ontic microstate. (Notation: . We adopt the usual boundary condition that the fields , including the gauge function , vanish at infinity.) Thus, a given ontic microstate of the radiation field can be represented by any member of a whole family of fields generated by different functions .
The continuity of the paths leads to an important simplification: the dynamics can be studied as a sequence of infinitesimally short steps as the system makes a transition from an initial state to a neighboring state . We seek to develop an Entropic Dynamics that takes into account that the variables and represent the same ontic microstate.
3. The Epistemic Phase Space
The goal of ED is to predict the positions of particles and the values of fields on the basis of information that turns out to be incomplete which forces us to deal with the probability distribution . The notation is meant to show that is a function of t and z and is a functional of A. The epistemic configuration space, or “e-configuration” space, is the statistical manifold of normalized gauge-invariant distributions, .
The restrictions to normalized probabilities and to gauge-invariant distributions are serious technical inconveniences that will be provisionally handled by embedding the space in the larger space
of un-normalized probabilities with no gauge symmetry. The appropriate restrictions will be later reintroduced as normalization and gauge constraints on the “physical” states.
The dynamics of probabilities on is, however, best defined over the corresponding cotangent bundle , which constitutes the epistemic phase space (or “e-phase” space). We are interested in trajectories in e-phase space, and this leads us to consider those special curves that are naturally adapted to the geometry of . In this section we describe the geometry of in terms of its symplectic, metric, and complex structures. This is carried out as a straightforward extension to the infinite dimensional case of quantum fields of the corresponding structures that apply to discrete systems [11] and to finite dimensional systems [4]. For a pedagogical background on symplectic and metric geometry, see [12].
First we shall establish some notation. For simplicity the coordinates of a point on shall be written as , where are coordinates on the base manifold and are coordinates on the cotangent space . The vector tangent to a generic curve parametrized by is written as
where stands for , is an appropriate functional measure of integration, and where we introduced the discrete index to stand for and , respectively.
It is understood that sums and integrations over repeated indices are carried out. The derivative of a functional along is
where is the gradient in ; that is,
and
are the basis covectors. The tilde ‘˜’ is meant to distinguish the gradient on from the gradient ∇ on .
3.1. Symplectic Structure
The coordinates have a clear meaning that is already explicit for ; they represent the probabilities of the ontic variables. The interpretation of will become clear later, in Section 5.3. These privileged coordinates suggest a natural choice for a symplectic 2-form, namely,
where ⊗ is the tensor product. To find the tensor components of we look at the action of on two generic vector fields, and . We find
and the components of , displayed as a matrix, take the familiar form
where
where is a Kronecker symbol, is the Dirac function, and is a Dirac functional.
3.2. Information Geometry
The simplex of normalized probability distributions is a statistical manifold. Its metric geometry, which turns out to be spherically symmetric, is uniquely determined by information geometry up to a multiplicative overall constant that fixes the units of length (see [4]). The information geometry of the embedding e-configuration space of un-normalized probabilities, Equation (2), is also spherically symmetric but it is not uniquely determined. It turns out that without loss of generality (see [4]) the geometries of and of the e-phase space can be assigned the simplest of the spherically symmetric geometries consistent with information geometry, namely, we can choose them to be flat. With this choice the length element on is
Displaying the components of the metric tensor G in matrix form, we find
where ℏ is a constant (eventually identified with Planck’s constant) that can be given a geometric interpretation: it controls the relative contributions of and to the length of the infinitesimal vector .
3.3. Complex Structure
The inverse of the metric tensor allows us to raise an index of the symplectic form and define a new tensor J with components
The negative sign is purely conventional. Written as a matrix J takes the form
It is easy to check that
which means that has a complex structure and suggests that it might be useful to perform a canonical transformation from the coordinates to complex coordinates where
is the wave functional (or, for simplicity, just the wave “function”). This is the geometrical reason for complex numbers in quantum mechanics: the joint presence of a symplectic and a metric structure implies a complex structure. Such manifolds are usually called Kähler manifolds; the e-phase space is a very special Kähler manifold in that its metric structure is derived from information geometry. For details of the subtleties of the transformation from to see [4,11].
In wave function coordinates, Equations (12) and (13) become
The transformation (17) is canonical in the sense that the components of the symplectic tensor , Equation (10), remain unchanged. Notice also that, unlike the components of the metric tensor G in coordinates (Equation (13)), in wave function coordinates the components of G (Equation (18)) are constants, which makes explicit both the flatness of the e-phase space and the convenience of introducing wave functions.
4. Kinematics
4.1. Hamilton Flows
Given the symplectic form , there are families of vector fields that are special in the sense that the Lie derivative of along vanishes.
that is, the symplectic form is preserved along the integral curves generated by . These curves, which are naturally adapted to the symplectic structure of , are such that associated with the vector field there exists a scalar function such that the components of are given by Hamilton’s equations [12]. In wave function coordinates we have
where is the parameter along the curves. This justifies calling the Hamiltonian vector field associated with the Hamiltonian function , and the congruence of these curves is called a Hamilton flow. Eventually we shall choose to be the actual Hamiltonian that generates a flow in time. At this point, however, is some generic Hamiltonian function, and there is no implication that the parameter represents time; for example, could be the generator of rotations and the corresponding rotation angle.
The action of on two Hamiltonian vector fields, and , generated, respectively, by and , is
which, using (20), gives
which is recognized as the Poisson bracket.
4.2. Normalization
We shall eventually require that probabilities be normalized. This is expressed as a constraint,
on the physically relevant states. Since the constraint must be preserved by time evolution we shall require Hamiltonian functions such that
Conversely, if is conserved along the flow generated by , then is conserved along the Hamilton flow generated by and parametrized by ,
which means that generates symmetry. The flow generated by is given by Hamilton’s equation,
which is easily integrated to give
The interpretation is as follows. The symmetry generated by is the consequence of embedding the e-phase space of normalized probabilities into the larger embedding space of un-normalized probabilities. One consequence of introducing one superfluous coordinate is also introducing a superfluous momentum . The extra coordinate is eliminated by imposing the constraint . The extra momentum is eliminated by declaring it unphysical. This is achieved by declaring that states along the flow are equivalent, that is, states with different lie on the same “ray”.
4.3. Hamilton–Killing Flows
We can further restrict the choice of the Hamiltonian function by requiring that, in addition to preserving the symplectic structure , it must also preserve the metric structure G. Thus we seek a Hamiltonian that satisfies
and generates flows that are simultaneously Hamilton flows and Killing flows. As shown in [11] (see also [4]), the Hamilton–Killing flows (or HK flows) are generated by Hamiltonians of the form
where the kernels , , and are independent of and . Requiring that the flow also preserve normalization implies that must be invariant under the global phase shift (27). Therefore, and , and must be bilinear in and ; that is,
The kernel can be conveniently interpreted as the matrix element,
of a self-adjoint operator . (For a pedagogical presentation of the Schrödinger representation in quantum field theory, see [13].) Such bilinear Hamiltonians lead to equations of motion,
that are recognized as Schrödinger equations. Thus, the requirement of HK flows that also preserve normalization provides an explanation for the linearity of quantum mechanics and its attendant superposition principle.
The main result of this section is that the special curves that are adapted to the symplectic and the information metric structures of the e-phase are HK flows generated by bilinear Hamiltonians. This concludes our discussion of kinematics.
5. Entropic Dynamics
Having figured that HK flows yield specially privileged families of curves, our next goal is to figure out which of these curves are good candidates to be actual trajectories. We want to derive the dynamics of probabilities. First, we use the method of maximum entropy to calculate the transition probability of a short step; this is the central idea behind any entropic dynamics. Then, since the rules of inference are atemporal, the assumptions behind the construction of the concept of time must be explicitly stated. An entropic notion of time is introduced as a book-keeping device to keep track of the accumulation of a succession of short steps. The final step yields a Hamiltonian that generates an HK flow in entropic time and allows us to write the Schrödinger functional equation. Similar ideas have been previously developed in [4,11]. Here the ED framework will be further extended to the case of a field with local gauge symmetry.
5.1. The Transition Probability for a Short Step
The continuity of trajectories in the ontic configuration space allows us to analyze the evolution as a sequence of short steps, which leads us to calculate the transition probability from z to and from A to . To guarantee that the dynamics is consistent with the rules for updating probabilities the transition probability is found by maximizing the entropy
relative to the prior Q and subject to the appropriate constraints. The relevant physical information is introduced in two different ways. The information that is common to all short steps is codified into the prior while the information that is specific to each individual short step is introduced as a constraint on the transition probability .
The prior Q codifies the information that the particles and the field evolve by taking infinitesimally short steps, but Q is otherwise maximally uninformative in the sense that it must reflect the translational and rotational invariance of the space and it must express total ignorance about any correlations. The desired prior is Gaussian,
where the constants and are Lagrange multipliers to be specified later. (The Gaussian prior Q can itself be derived using the method of maximum entropy.) The multipliers and will eventually be made arbitrarily large to ensure that Q leads to intrinsic changes that are infinitesimally small. The index n in indicates that the particles need not be identical.
The physical information about directionality and correlations is specific to each short step. It is introduced via a constraint that involves a functional called the “drift potential.” The constraint consists of imposing that the expected change of over a short step is some small amount ,
More explicitly, we can Taylor-expand and write
As in other forms of ED, the drift potential is of central importance. It plays three separate roles: (1) it serves to express a constraint that codifies physical information about short steps; (2) it turns out to be a momentum that is canonically conjugate to the probability ; and (3) it will be closely related to the phase of the wave functional in Equation (17).
Finally, we require one last set of constraints that describes how each particle interacts with the gauge field A. We impose that the expected displacement for each particle satisfies
The coupling is local: the particle at z couples to the field at z. The numerical values of the quantities and could be specified directly, but it is more convenient to specify them indirectly in terms of the corresponding Lagrange multipliers.
We are now ready to assign the transition probability . Maximize the entropy (33) relative to the prior (34) and subject to the constraints (36) and (37), and normalization. The result is a Gaussian distribution,
where , , , and are Lagrange multipliers, and . Later we will write the parameters as , where will be identified with the electric charges in Heaviside–Lorentz units (i.e., rationalized Gaussian units), and c is the speed of light. Completing the square in the exponent, P can be rewritten as
where and are the expected steps,
Let a generic step be described as
Then the fluctuations and satisfy
while the correlations vanish:
5.2. Entropic Time
An Entropic Dynamics of probabilities requires an entropic notion of time. This involves introducing the concept of instants that are suitably ordered and adopting a convenient measure of the interval between instants. In ED an instant is specified by the information—codified into the functions and —that is sufficient for generating the next instant. Indeed, if the distribution and the drift potential refer to the instant t, then the distribution
generated from by serves both to define the dynamics of and to construct what we mean by the “next” instant . Later we shall complete the construction by specifying the evolution of .
Before proceeding further, a couple of remarks are in order. In Equation (46) we see that given the information codified into a present instant t, the future instant turns out to be independent of any past instant . Thus, formally, ED is a Markovian process. However, it is important to emphasize that there is an important difference. Markovian processes are assumed to develop in an already existing time determined by external clocks. In ED there is no such pre-existing time; information about the system at one instant is used to generate or construct the next instant. Thus, ED is fully relational with respect to time [14].
The second remark is that the evolution equation involves a transition probability that was derived by maximizing an entropy which implies that there is a clear evolution from a past instant towards a future instant. Therefore, in ED the instants are ordered and there is a natural arrow of time.
We shall now address the unfinished task of specifying the Lagrange multipliers that appear in the transition probability, Equation (38). As discussed in [4] the last step in the construction of time is specifying the measure of duration— the interval between successive instants—in terms of the multipliers , , and . Thus, the transition probability provides us with a clock. As a matter of convenience we choose multipliers adapted to the translational symmetries of Newtonian space and, accordingly, we shall choose them to be constants independent of x and .
Furthermore, we want the transition probability to lead to infinitesimally short steps and particles with well-defined expected velocities. Equation (40) shows that this is achieved choosing the ratio proportional to ,
where we introduced proportionality constants that will eventually be identified with the particle masses. As in previous work we shall also take to be constant and set such that if has units of time, then has units of mass. Then,
The expected drift for particles, Equation (40), and their fluctuations, Equation (43), become
As far as the radiation goes, its multiplier is also chosen to lead to a well-defined expected rate of change,
The proportionality constant is such that the field A is measured in Heaviside–Lorentz units. Then,
5.3. The Hamiltonian
Our next goal is to identify a Hamiltonian that generates evolution in entropic time. The traditional approach in mechanics makes use of a Lagrangian to identify the momentum that is conjugate to the coordinate q. In ED no Lagrangians are available, and an alternative method is required. We propose that a momentum conjugate to can be identified from Equation (46), which is the evolution equation for written in integral form. The process takes a few steps. The first step consists of rewriting Equation (46) in differential form:
This is a continuity equation where the velocity of the probability flow—the current velocity—has components along and along given by
where
The derivation leading from (46) to (52) is given in Appendix A. The second step is to show that (52) can be written in Hamiltonian form,
which suggests that is a convenient canonical momentum. Equation (54) shows that and differ by a function of the generalized coordinate . This is just a canonical transformation and the choice of either or as the conjugate momentum is just a matter of convenience. To show that (52) can be written in the form (55) we must find the Hamiltonian . This is straightforward: equating (52) to (55) yields a linear functional differential equation that can be easily integrated for . The result is
where the unspecified functional is an integration constant. We write to emphasize that is independent of , but in principle we could have . It is straightforward to check that (56) is a solution to (55): just take a variation and integrate by parts.
Yet another piece of information that guides our choice of Hamiltonian is that in order to generate HK flows must take the bilinear form, Equation (30). Transforming to wave function coordinates, Equation (56) becomes
where, setting , is the covariant derivative,
and the new functional differs from the old by a functional of ,
In order to generate an HK flow the functional must itself be bilinear,
for some Hermitian kernel , while still remaining independent of ,
Substituting (60) into (61) leads to
which must be satisfied for all choices of and . Therefore the kernel must be local in the ontic configuration space ,
where is a real functional that plays the role of a potential. This is how potentials are introduced in the ED framework. Substituting (63) into (57), we obtain the Hamiltonian
where the kernel is the operator
For brevity we will refer to both and as “the Hamiltonian”. The Schrödinger equation is the Hamilton equation of motion, Equation (32):
A familiar example is the potential for the pure electrodynamics of radiation and particles in a vacuum,
Additional terms may be included to describe direct particle–particle interactions and the index of refraction or other effects of the dielectric polarization of a material medium.
5.4. Charge Conservation
At this point in the argument, we do not yet have a locally gauge invariant dynamics; this will depend on appropriate choices of the potential and of the initial wave function . However, irrespective of the choice of and , there is a symmetry under the global phase transformation
where is a constant. One expects that there is a conservation law associated with this symmetry and, indeed, there is. The derivation can be carried out following any of several standard methods. We shall make use Hamilton’s Equation (55), which is the continuity Equation (52).
The operators that represent the densities of electric charge and electric current are
The corresponding Hamiltonian functionals are
and
Using Equation (52) we find
The integral over of the last term is a vanishing surface term,
Therefore
Integrating by parts and using
we find
which, using (71), yields the desired result,
We have derived a mathematically legitimate conservation law with a perhaps unfamiliar interpretation and this warrants some comments. First, as is evident from (70) and (71), and are expected values. We claim that we have a charge conservation law because the identity (74) holds for any arbitrary choice of the probability , but the electric charges are not some ontic substance that is physically attached to point particles. They are parameters that operate at the epistemic level of probabilities; they are Lagrange multipliers that regulate the probabilistic correlations between particles and fields. Indeed, as befits an Entropic Dynamics of probabilities, the velocity that defines the electric current is not the velocity of the particles but the velocity of the probability flow.
The fact that charges (and also masses) are introduced via Lagrange multipliers leads us to a second comment motivated by a potential analogy with the statistical mechanics of thermal equilibrium. The point is that quantities such as temperatures and chemical potentials are also introduced via Lagrange multipliers and they are subject to fluctuations, which raises the question of whether charges and masses might also fluctuate. In principle the answer is yes, but it is not clear how to bring about such an effect, and perhaps the analogy, like all analogies, should not be pushed too far.
In the case of thermal equilibrium, the precise specification of the expected energy implies a precise value of temperature. To induce temperature fluctuations one requires an uncertainty in the energy constraint which is brought about by spontaneous energy exchanges with an environment. Similarly, in ED the precise specification of expected value constraints also leads to precise values for the corresponding multipliers which is the situation discussed in this paper. To induce fluctuations in charge and mass, one must require that the corresponding constraints be imprecisely specified. The discussion of the physical conditions that might possibly bring about such interesting effects lies beyond the scope of the present study.
So far we have discussed ED on the larger unconstrained e-phase space . Next we discuss the additional requirements that implement gauge invariance and yield proper entropic electrodynamics.
6. Quantum Electrodynamics
6.1. Gauge Invariance and the Gauss Constraint
We require that probabilities, phases, and wave functions reflect the consequences of invariance under the local gauge transformation.
The main constraint follows from the observation that A and represent the same ontic microstate, and therefore, the corresponding probabilities must be equal.
(We adopt Dirac’s weak equality ≈ notation that holds once the constraints are implemented.) This can be expressed in differential form: Taylor-expanding for small , we obtain the identity
which must hold for arbitrary choices of . Therefore, the allowed s are constrained to satisfy
Analogous conditions apply to any gauge-invariant functional.
The invariance of must be preserved by time evolution, and this determines the gauge transformation of the drift potential and the phase . From Equations (52)–(54) we see that remains invariant under provided and transform according to the local gauge transformations,
where is a function on the -space . The dynamical preservation of the gauge symmetry follows from the fact that the original constraints (36) and (37) are not independent of each other—both are linear in the same displacements —which leads to the invariant combination in (53). Thus, our particular choice of entropic prior and constraints has led to an ED that allows a gauge-covariant HK flow.
We require that transforms according to (80), but being a functional of A, we can also calculate directly:
Therefore, equating (81) to (80), the change in is
which, after integrating by parts and rearranging, gives
Since this identity must hold for arbitrary choices of , the allowed phases are constrained to satisfy the infinite set of constraints (one at every point ),
Having established the constraints on s and s, we can find the constraints on wave functions . Using (76) and (80) and Taylor-expanding gives
But we can also calculate directly:
Therefore,
which, after some algebra, leads to
Once again, since is an arbitrary function, we conclude that the requirement of gauge invariance restricts the allowed quantum states to those that satisfy the infinite set of constraints (one at every point )
which is recognized as the quantum version of Gauss’ law,
provided one identifies
as the representation of the electric field operator acting on functionals of and is the electric charge density, Equation (69). In classical electrodynamics Equation (91) corresponds to the assertion that the electric field (times ) is the momentum that is canonically conjugate to the potential .
Incidentally, the derivative operator is how electric fields are introduced in the ED approach. ED is founded on the recognition that the ontic degrees of freedom are the radiation field, which is redundantly represented by the vector potential . And that is all there is; there is no such thing as an ontic electric field!
6.2. Time Evolution
From now on we adopt the Hamiltonian given by Equation (65) and, to be specific, the potential is given in Equation (67):
where
The mere existence of the Gauss constraint, Equation (90), induces an additional change. As pointed out by Dirac [8], it leads us to consider the modified Hamiltonian,
where is some well-behaved but otherwise arbitrary function of x, t, and of the ontic variables and .
Remark 1.
In the Dirac approach to the classical dynamics of constrained Hamiltonian systems [8], there is one quantity Φ for each constraint, which accounts for being a function of x, and at each x the quantity is an arbitrary functional of the canonical variables and and their respective momenta. In the ED approach to quantum dynamics there is an important difference: the canonical variables are ψ and , not , , and their momenta. The HK flows require that the Hamiltonians and be bilinear in ψ and , Equation (64), which in turn implies that the kernels and must be independent of the canonical variables ψ and . Thus can depend on and but not on ψ and .
The new Schrödinger equation is
Imposing shows that the arbitrary function has no effect on the evolution of , but it does introduce indeterminism in the evolution of gauge-dependent fields such as (see Equation (136)).
The consistency of the whole scheme requires that the Gauss constraint be preserved by time evolution, that is,
More explicitly,
so that
which requires that we evaluate the commutator.
First we consider the commutators and . The former vanishes trivially. For the latter we need , which is
and implies that
and
Therefore,
Next we deal with and . For the former, we use
and
which, substituting from (93), implies that
Next consider . We use (69) and (58), so that
and
Therefore, substituting from (93),
Combining (104) and (108) leads to
which, together with (101), implies that
and proves (97). Note that (110) is not a weak equality; it holds strongly.
We can also check the mutual consistency of time evolution and time-dependent gauge transformations. Write Equation (85) as , where is the unitary operator
Then, the consistency of (95) with the transformed Schrödinger equation,
requires that
or
Substituting (111), we find
Thus, we discover the familiar fact that the Hamiltonian is not invariant under time-dependent gauge transformations and that the effect of the latter is to cause a shift in the background scalar potential.
6.3. Gauge Transformations as HK Flows
Consider the Hamiltonian functional that describes the expected electric charge density smeared by an arbitrary function ,
It generates an HK flow parametrized by and defined by the Hamilton/Schrödinger equation,
The corresponding integral curve is
Compared with (85), this is recognized as the gauge orbit generated by gauge transformations with function . In other words, the smeared expected charge density is the generator of gauge transformations.
We can also consider the Hamiltonian function that describes the smeared Gauss constraint, Equation (94),
The corresponding HK flow is given by
and its integral curves are
We see that if , then too, that is, generate curves along which the Gauss constraint is obeyed.
Remark 2.
According to Dirac’s hypothesis, constraints that commute with all other constraints (called first-class constraints) are the generators of gauge transformations [8]. Even though Dirac’s hypothesis holds true for those cases he tested, in the context of ED the Dirac hypothesis fails. Indeed, we can easily check that the commutators
vanish strongly so that the constraints are first class, but Equation (122) clearly shows that does not generate gauge transformations.
6.4. Maxwell Equations
We have just concluded our formulation of the ED approach to non-relativistic quantum electrodynamics. In the next two sections we shall offer some further evidence that despite ED’s unorthodox foundations, which include clarity about which variables play an ontic and which an epistemic role and the absence of ontic dynamics, the ED model developed here is empirically equivalent to the standard versions of QED.
We saw, in Equations (67) and (91), that the electric and the magnetic fields are not fundamental; they are derivative, auxiliary concepts related to the concept that is actually fundamental, which is the vector potential . Let
Two of the Maxwell equations we have already discussed. The absence of magnetic monopoles follows from the definition of the field, Equation (67):
Gauss’ law is the Gauss constraint (Equation (90)), to be imposed on wave functions:
The other two Maxwell equations are equations of time evolution for , , and ,
We use (93) and (94) to write the modified Hamiltonian as
where
where the last term has been integrated by parts. Calculating the PBs leads to
The A-commutators give
The first equation is trivial; the second only slightly less so. We use
and (134) follows.
Substituting this into (132), the time evolution of is
This shows that the longitudinal component of is quite arbitrary, which is the defining characteristic of gauge fields. We can make this explicit by decomposing into its longitudinal and transverse parts,
with
so that is the gauge-dependent component and is gauge-invariant. We can also write (136) as
which, if we interpret the function as a scalar potential, recovers the familiar expression for the electric field in terms of the potentials and . At this point we can extend the gauge transformations to the scalar potential , and write
which makes the electric field (139) gauge invariant. This is a shift in perspective that warrants emphasis: In standard approaches to electrodynamics, whether classical or quantum, an identity such as (139) is taken as part of the definition of the potentials from the already given, presumably fundamental, classical field strengths. In the ED approach, (139) is a derived result. The fundamental equation is (136); it describes the time evolution of the field in terms of the quantities and introduced by the Gauss constraint, Equations (90)–(94).
The third Maxwell equation follows immediately; we just take the curl of (139) to find Faraday’s law,
Next we deal with (133). Since
we can replace with in the commutators. The commutator is given in (99). The commutator requires more algebra; we use (103) and substitute it into
This can be simplified considerably. From , we obtain the identity
which, when combined with Equations (53) and (71), leads to
Finally, substitute (99) and (145) into (133) to find the fourth Maxwell equation, the Ampère-Maxwell law,
This derivation of the Maxwell equations has taken full account of the redundancy of the representation of the field, but it has been carried out without having specified a gauge condition. In other words, the derivation holds for all gauges. However, in applications, there is no reason not take advantage of the freedom to choose a convenient gauge; this we do next.
6.5. The Coulomb Potential
The Gauss constraint is a restriction on the longitudinal component of the electric field operator. This suggests decomposing the vector operator into its longitudinal and transverse parts,
where, using (139), we obtain
We can take advantage of (140) to impose the Coulomb gauge,
Then can be written as the gradient of a scalar potential operator ,
and the Gauss constraint reads
which is the quantum version of the Poisson equation. The solution to (151) is the Coulomb potential,
where we used (69). This reproduces a well-known result in QED, namely, that the scalar potential is not an independent dynamical variable but a function of the particle positions. (Note that is not a function of the canonical variables and .)
In terms of and , and imposing the Gauss constraint, the Hamiltonian (130) now reads
Integrating the Coulomb term by parts and using the Poisson equation yields the familiar result
where we have invoked the usual “argument” that the infinite constant contributed by the self-energy terms can be dropped because it has no effect on energy differences and transition rates. (Clearly the present non-relativistic formulation is not adequate to deal with the self-energy terms.) We can shift the Coulomb term from to and write in the standard form,
with
We have reached familiar QED territory. Even though the ED ontic/epistemic interpretation differs from the standard textbook presentations, the ED equations reproduce the standard formalism of QED in the Coulomb gauge.
6.6. The Action
In the ED framework the introduction of an action principle is not fundamental; it is a convenient way to summarize the content of an already established formalism. The idea is to construct an action that reproduces the equations of motion and the constraints.
Consider a region R of the e-phase space and a time interval T that extends from to , and define the action functional
where is given in (65). The equations of motion and the Gauss constraint are obtained by requiring that the action be stationary under variations and that vanish at the boundary of the region . The functional is a Lagrange multiplier that enforces the Gauss constraint. Then
The variation leads to the constraint
while and lead to
and its complex conjugate.
7. Final Remarks
With the derivation of the QED Hamiltonian, whether in an unspecified gauge, Equation (130), or in the Coulomb gauge, Equation (155), the ED formulation of QED reaches a certain level of completion. On the basis of entropic inference we have not just derived electrodynamics; we have derived quantum electrodynamics. We have derived the linear Schrödinger equation with its attendant superposition principle. Along the way we have justified the need for complex numbers and the arrow of time. These are general consequences of the ED framework. Here we have expanded the framework to include invariance under local gauge transformations. This has allowed us to rederive charge conservation, the Maxwell equations, the Coulomb potential, and the familiar QED equations that have historically received so much empirical support. And, of course, the understanding of local gauge invariance within the ED setting is a necessary stepping stone towards relativistic quantum field theories such as Yang–Mills theories and gravity.
Much, however, remains to be done. Most glaring is the absence of any mention of the concept of photons. We have two reasons not to pursue those applications where the concept of photons becomes an indispensable tool. One reason is to avoid this paper becoming too long. Another reason is that the actual study of the quantum correlations between particles and fields, the transition rates of photon emission and absorption, and so much more can now be pursued by standard techniques. But there is one important remark concerning photons that must be included here.
Photons are the names we give to those special quantum states—the wave functions of certain excited states of the radiation field–that provide the indispensable vocabulary to analyze exchanges of energy and momentum. Therefore, even before one addresses the details of the construction of Fock spaces for the radiation field, the ED framework allows us to arrive at the following possibly unsettling conclusion: photons are not particles and, even worse, they are not real. The point being made is simple. The ED philosophy insists on a clear ontological commitment: particles and radiation fields are real, and they belong to the ontic sector. Probabilities and wave functions are not real, and they belong to the epistemic sector. They are tools we have developed to figure out what the real things might be doing—what the ontic microstates might be and how they might be changing. Perhaps surprisingly, quantities such as energies, linear and angular momenta, electric currents and even photons all belong to the epistemic sector. They are not properties of ontic particles or ontic fields but concepts that are useful in the analysis of the dynamics of probabilities.
Funding
This research received no external funding.
Data Availability Statement
Data is contained within the article.
Acknowledgments
I would like to acknowledge Connor Dolan for engaging in insightful discussions in the early stages of this project.
Conflicts of Interest
The author declares no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
| ED | Entropic Dynamics |
| QM | Quantum Mechanics |
| QED | Quantum Electrodynamics |
Appendix A. The Continuity Equation
The goal is to rewrite the integral equation for the evolution of probability, Equation (46), in differential form as a continuity equation. We proceed by adapting a technique [4] borrowed from diffusion theory [15]. Multiply Equation (46) by a smooth test functional and integrate over with measure ,
The test functional is assumed to be sufficiently smooth precisely so that orders of integration can be swapped and we can Taylor-expand about . Since and are of , keeping terms up to , then as , the integral in the brackets is
Rearrange this using Equations (49) and (51):
Substitute this into the RHS of (A1):
Next use
integrate (A4) by parts, and divide by to get
This must hold for arbitrary test functionals . Therefore we get a differential equation,
which is a continuity equation for the probability flow in the ontic configuration space
with a current velocity that has components along ,
and along ,
where
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