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The '''set covering problem''' ('''SCP''') is a classical question in [[combinatorics]], [[computer science]] and [[Computational complexity theory|complexity theory]].
{{Multiple issues
| unreferenced=December 2009
| confusing=December 2006
| rewrite=February 2009
|expert = Mathematics|date = November 2008}}
{{distinguish|Primary constraint}}
In a constrained Hamiltonian system, a dynamical quantity is called a '''first class constraint''' if its Poisson bracket with all the other constraints vanishes on the '''constraint surface''' (the surface implicitly defined by the simultaneous vanishing of all the constraints). A '''second class constraint''' is one that is not first class.


It is a problem "whose study has led to the development of fundamental techniques for the entire field" of [[approximation algorithms]].<ref>{{harvtxt|Vazirani|2001|p=15}}</ref> It was also one of [[Karp's 21 NP-complete problems]] shown to be [[NP-complete]] in 1972.
First and second class constraints were introduced by {{harvs|txt|last=Dirac|authorlink=Paul Dirac|year1=1950|loc=p.136|year2=1964|loc2=p.17}} as a way of quantizing mechanical systems such as gauge theories where the symplectic form is degenerate.


Given a set of elements <math>\{1,2,...,m\}</math> (called the universe) and a set <math>S</math> of <math>n</math> sets whose union equals the universe, the set cover problem is to identify the smallest subset of <math>S</math> whose union equals the universe. For example, consider the universe <math>U = \{1, 2, 3, 4, 5\}</math> and the set of sets <math>S = \{\{1, 2, 3\}, \{2, 4\}, \{3, 4\}, \{4, 5\}\}</math>. Clearly the union of <math>S</math> is <math>U</math>. However, we can cover all of the elements with the following, smaller number of sets: <math>\{\{1, 2, 3\}, \{4, 5\}\}</math>.
The terminology of first and second class constraints is confusingly similar to that of [[primary constraint|primary and secondary constraints]]. These divisions are independent: both first and second class constraints can be either primary or secondary, so this gives altogether four different classes of constraints.


More formally, given a universe <math>\mathcal{U}</math> and a family <math>\mathcal{S}</math> of subsets of <math>\mathcal{U}</math>,
==Poisson brackets==
a ''cover'' is a subfamily <math>\mathcal{C}\subseteq\mathcal{S}</math> of sets whose union is <math>\mathcal{U}</math>. In the set covering [[decision problem]], the input is a pair <math>(\mathcal{U},\mathcal{S})</math> and an integer <math>k</math>; the question is whether
In [[Hamiltonian mechanics]], consider a [[symplectic manifold]] ''M'' with a [[smooth function|smooth]] Hamiltonian over it (for field theories, ''M'' would be infinite-dimensional).
there is a set covering of size <math>k</math> or less. In the set covering [[optimization problem]], the input is a pair <math>(\mathcal{U},\mathcal{S})</math>, and the task is to find a set covering that uses the fewest sets.


The decision version of set covering is [[NP-complete]], and the optimization version of set cover is [[NP-hard]] .{{sfn |Korte|Vygen|2012|p=414}}
Suppose we have some constraints
:<math> f_i(x)=0, </math>
for ''n'' smooth functions


If additionally, you want to minimize the cost of the sets, it becomes Weighted Set Cover Problem. Otherwise, its an Un-weighted Set Cover Problem with all costs equal to one.
:<math>\{ f_i \}_{i= 1}^n</math>


{{Covering-Packing Problem Pairs}}
These will only be defined [[chart (topology)|chartwise]] in general. Suppose that everywhere on the constrained set, the ''n'' derivatives of the ''n'' functions are all [[linearly independent]] and also that the [[Poisson bracket]]s


==Integer linear program formulation==
:{ ''f''<sub>''i''</sub>, ''f''<sub>''j''</sub> }
The minimum set cover problem can be formulated as the following [[integer linear program]] (ILP).<ref>{{harvtxt|Vazirani|2001|p=108}}</ref>
{|
| minimize
| <math>\sum_{S \in \mathcal S} x_S</math>
|
| (minimize the number of sets)
|-
| subject to
| <math>\sum_{S\colon e \in S} x_S \geqslant 1 </math>
| for all <math>e\in \mathcal U</math>
| (cover every element of the universe)
|-
|
| <math>x_S \in \{0,1\}</math>
| for all <math>S\in \mathcal S</math>.
| (every set is either in the set cover or not)
|}
This ILP belongs to the more general class of ILPs for [[covering problem]]s.
The [[Linear programming relaxation#Approximation and integrality gap|integrality gap]] of this ILP is at most <math>\scriptstyle \log n</math>, so its [[Linear programming relaxation|relaxation]] gives a factor-<math>\scriptstyle \log n</math> [[approximation algorithm]] for the minimum set cover problem (where <math>\scriptstyle n</math> is the size of the universe).<ref>{{harvtxt|Vazirani|2001|pp=110–112}}</ref>


== Hitting set formulation ==
and  
Set covering is equivalent to the '''hitting set problem'''. It is easy to see this by observing that an instance of set covering can
be viewed as an arbitrary [[bipartite graph]], with sets represented by vertices on the left, the universe represented by vertices on the
right, and edges representing the inclusion of elements in sets. The task is then to find a minimum cardinality subset of left-vertices which covers all of the right-vertices. In the Hitting set problem, the objective is to cover the left-vertices using a minimum subset of the right vertices. Converting from one problem to the other is therefore achieved by interchanging the two sets of vertices.


== Greedy algorithm ==
:{ ''f''<sub>''i''</sub>, ''H'' }


The [[greedy algorithm]] for set covering chooses sets according to one rule: at each stage, choose the set that contains the largest number of uncovered elements. It can be shown<ref>Chvatal, V. [http://www.jstor.org/stable/3689577 A Greedy Heuristic for the Set-Covering Problem]. Mathematics of Operations Research
all vanish on the constrained subspace. This means we can write
Vol. 4, No. 3 (Aug., 1979), pp. 233-235</ref> that this algorithm achieves an approximation ratio of <math>H(s)</math>, where <math>s</math> is the size of the set to be covered, <math>H(n)</math> is the <math>n</math>-th [[harmonic number]]:


:<math> H(n) = \sum_{k=1}^{n} \frac{1}{k} \le \ln{n} +1</math>
:<math>\{f_i,f_j\}=\sum_k c_{ij}^k f_k</math>


This greedy algorithm actually achieves an approximation ratio of <math>H(s^\prime)</math> where <math>s^\prime</math> is the maximum cardinality set of <math>S</math>.
for some smooth functions


[[Image:SetCoverGreedy.gif|frame|Tight example for the greedy algorithm with k=3]]
:''c''<sub>''ij''</sub><sup>''k''</sup>
There is a standard example on which the greedy algorithm achieves an approximation ratio of <math>\log_2(n)/2</math>.
The universe consists of <math>n=2^{(k+1)}-2</math> elements. The set system consists of <math>k</math> pairwise disjoint sets
<math>S_1,\ldots,S_k</math> with sizes <math>2,4,8,\ldots,2^k</math> respectively, as well as two additional disjoint sets <math>T_0,T_1</math>,
each of which contains half of the elements from each <math>S_i</math>. On this input, the greedy algorithm takes the sets
<math>S_k,\ldots,S_1</math>, in that order, while the optimal solution consists only of <math>T_0</math> and <math>T_1</math>.
An example of such an input for <math>k=3</math> is pictured on the right.


Inapproximability results show that the greedy algorithm is essentially the best-possible polynomial time approximation algorithm for set cover
(there is a theorem showing this) and
(see [[Set cover problem#Inapproximability results|Inapproximability results]] below), under plausible complexity assumptions.


== Low-frequency systems ==
:<math>\{f_i,H\}=\sum_j v_i^j f_j</math>


If each element occurs in at most ''f'' sets, then a solution can be found in polynomial time that approximates the optimum to within a factor of ''f'' using [[Linear programming relaxation|LP relaxation]].<ref>{{harvtxt|Vazirani|2001|pp=118–119}}</ref>
for some smooth functions


== Inapproximability results ==
:''v''<sub>''i''</sub><sup>''j''</sup>.


When <math> n</math> refers to the size of the universe, {{harvtxt |Lund|Yannakakis|1994}} showed that set covering cannot be approximated in polynomial time to within a factor of <math>\tfrac{1}{2}\log_2{n} \approx 0.72\ln{n}</math>, unless '''NP''' has [[quasi-polynomial time]] algorithms. Feige (1998) improved this lower bound to <math>\bigl(1-o(1)\bigr)\cdot\ln{n}</math> under the same assumptions, which essentially matches the approximation ratio achieved by the greedy algorithm. {{harvtxt |Raz|Safra|1997}} established a lower bound
This can be done globally, using a [[partition of unity]]. Then, we say we have an irreducible '''first-class constraint''' (''irreducible'' here is in a different sense from that used in [[representation theory]]).
of <math>c\cdot\ln{n}</math>, where <math>c</math> is a constant, under the weaker assumption that '''P'''<math>\not=</math>'''NP'''.
A similar result with a higher value of <math>c</math> was recently proved by {{harvtxt |Alon|Moshkovitz|Safra|2006}}.


== Related problems ==
==Geometric theory==
* Hitting set is an equivalent reformulation of Set Cover.
For a more elegant way, suppose given a [[vector bundle]] over M, with ''n''-dimensional [[fiber]] ''V''. Equip this vector bundle with a [[connection form|connection]]. Suppose too we have a [[smooth section]] ''f'' of this bundle.  
* [[Vertex cover problem|Vertex cover]] is a special case of Hitting Set.
* [[Edge cover problem|Edge cover]] is a special case of Set Cover.
* [[Set packing]] is the dual problem of Set Cover.
* [[Maximum coverage problem]] is to choose at most k sets to cover as many elements as possible.
* [[Dominating set]] is the problem of selecting a set of vertices (the dominating set) in a graph such that all other vertices are adjacent to at least one vertex in the dominating set. The Dominating set problem was shown to be NP complete through a reduction from Set cover.
* [[Exact cover problem]] is to choose a set cover with no element included in more than one covering set.
* [[Closest pair of points problem]]
* [[Nearest neighbor search]]


==See also==
Then the [[covariant derivative]] of ''f'' with respect to the connection is a smooth [[linear map]] Δ''f'' from the [[tangent bundle]] ''TM'' to ''V'', which preserves the [[base point]]. Assume this linear map is right [[invertible]] (i.e. there exists a linear map ''g'' such that (Δ''f'')''g'' is the [[identity function|identity map]]) for all the fibers at the zeros of ''f''. Then, according to the [[implicit function theorem]], the subspace of zeros of ''f'' is a [[submanifold]].
*[[MinHash]]
*[[Sequence assembly]]


==Notes==
The ordinary [[Poisson bracket]] is only defined over <math>C^{\infty}(M)</math>, the space of smooth functions over ''M''. However, using the connection, we can extend it to the space of smooth sections of ''f'' if we work with the [[algebra bundle]] with the [[graded algebra]] of ''V''-tensors as fibers. Assume also that under this Poisson bracket,


{{reflist}}
:{ ''f'', ''f'' } = 0


== References ==
(note that it's not true that


* {{Citation | last1=Alon | first1=Noga | author1-link=Noga Alon | last2=Moshkovitz | first2=Dana | last3=Safra | first3=Shmuel | author3-link=Shmuel Safra | title=Algorithmic construction of sets for k-restrictions | publisher=ACM | year=2006 | journal=ACM Trans. Algorithms | issn=1549-6325 | volume=2 | issue=2 | pages=153–177 | doi=10.1145/1150334.1150336}}.
:{ ''g'', ''g'' } = 0
* {{Citation
| last=Cormen    | first=Thomas H.  | authorlink=Thomas H. Cormen
| last2=Leiserson | first2=Charles E. | authorlink2=Charles E. Leiserson
| last3=Rivest    | first3=Ronald L.  | authorlink3=Ronald L. Rivest
| last4=Stein    | first4=Clifford  | authorlink4=Clifford Stein
| title=Introduction to Algorithms | year=2001 | publisher=MIT Press and McGraw-Hill | location=Cambridge, Mass.
| isbn=0-262-03293-7 | pages=1033–1038}}
* {{Citation | last1=Feige | first1=Uriel | author1-link=Uriel Feige | title=A threshold of ln n for approximating set cover | publisher=ACM | year=1998 | journal=[[Journal of the ACM]] | issn=0004-5411 | volume=45 | issue=4 | pages=634–652 | doi=10.1145/285055.285059}}.
* {{Citation | last1=Lund | first1=Carsten | author1-link=Carsten Lund | last2=Yannakakis | first2=Mihalis | author2-link=Mihalis Yannakakis | title=On the hardness of approximating minimization problems | publisher=ACM | year=1994 | journal=[[Journal of the ACM]] | issn=0004-5411 | volume=41 | issue=5 | pages=960–981 | doi=10.1145/185675.306789}}.
* {{Citation | last1=Raz | first1=Ran | author1-link=Ran Raz | last2=Safra | first2=Shmuel | author2-link=Shmuel Safra | title=STOC '97: Proceedings of the twenty-ninth annual ACM symposium on Theory of computing | publisher=ACM | isbn=978-0-89791-888-6 | year=1997 | chapter=A sub-constant error-probability low-degree test, and a sub-constant error-probability PCP characterization of NP | pages=475–484}}.
* {{cite book
| last = Vazirani | first = Vijay V.
| authorlink = Vijay Vazirani
| title = Approximation Algorithms
| year = 2001
| publisher = Springer-Verlag
| isbn = 3-540-65367-8
| url = http://www.cc.gatech.edu/fac/Vijay.Vazirani/book.pdf
| ref = harv
}}
* {{cite book
| last1 = Korte | first1 = Bernhard
| last2 = Vygen | first2 = Jens
| title = Combinatorial Optimization: Theory and Algorithms
| year = 2012
| isbn = 978-3-642-24487-2
| edition = 5
| publisher = Springer
| ref = harv
}}


== External links ==
in general for this "extended Poisson bracket" anymore) and  
* [http://www.nlsde.buaa.edu.cn/~kexu/benchmarks/set-benchmarks.htm Benchmarks with Hidden Optimum Solutions for Set Covering, Set Packing and Winner Determination]
* [http://www.csc.kth.se/~viggo/wwwcompendium/node146.html A compendium of NP optimization problems - Minimum Set Cover]


{{DEFAULTSORT:Set Cover Problem}}
:{ ''f'', ''H'' } = 0
[[Category:Set families]]
 
[[Category:NP-complete problems]]
on the submanifold of zeros of ''f'' (If these brackets also happen to be zero everywhere, then we say the constraints close [[off shell]]). It turns out the right invertibility condition and the commutativity of flows conditions are ''independent'' of the choice of connection. So, we can drop the connection provided we are working solely with the restricted subspace.
 
==Intuitive meaning==
What does it all mean intuitively? It means the Hamiltonian and constraint flows all commute with each other '''on''' the constrained subspace; or alternatively, that if we start on a point on the constrained subspace, then the Hamiltonian and constraint flows all bring the point to another point on the constrained subspace.
 
Since we wish to restrict ourselves to the constrained subspace only, this suggests that the Hamiltonian, or any other physical [[observable]], should only be defined on that subspace. Equivalently, we can look at the [[equivalence class]] of smooth functions over the symplectic manifold, which agree on the constrained subspace (the [[quotient algebra]] by the [[ideal]] generated by the ''f'''s, in other words).
 
The catch is, the Hamiltonian flows on the constrained subspace depend on the gradient of the Hamiltonian there, not its value. But there's an easy way out of this.
 
Look at the [[orbit (group theory)|orbits]] of the constrained subspace under the action of the [[symplectic flow]]s generated by the ''f'''s. This gives a local [[foliation]] of the subspace because it satisfies [[integrability condition]]s ([[Frobenius theorem (differential topology)|Frobenius theorem]]). It turns out if we start with two different points on a same orbit on the constrained subspace and evolve both of them under two different Hamiltonians, respectively, which agree on the constrained subspace, then the time evolution of both points under their respective Hamiltonian flows will always lie in the same orbit at equal times. It also turns out if we have two smooth functions ''A''<sub>1</sub> and ''B''<sub>1</sub>, which are constant over orbits at least on the constrained subspace (i.e. physical observables) (i.e. {A<sub>1</sub>,f}={B<sub>1</sub>,f}=0 over the constrained subspace)and another two A<sub>2</sub> and B<sub>2</sub>, which are also constant over orbits such that A<sub>1</sub> and B<sub>1</sub> agrees with A<sub>2</sub> and B<sub>2</sub> respectively over the restrained subspace, then their Poisson brackets {A<sub>1</sub>, B<sub>1</sub>} and {A<sub>2</sub>, B<sub>2</sub>} are also constant over orbits and agree over the constrained subspace.
 
In general, we{{Who|date=March 2010}} can't rule out "[[ergodic]]" flows (which basically means that an orbit is dense in some open set), or "subergodic" flows (which an orbit dense in some submanifold of dimension greater than the orbit's dimension). We can't have [[self-intersecting]] orbits.
 
For most "practical" applications of first-class constraints, we do not see such complications: the [[quotient space]] of the restricted subspace by the f-flows (in other words, the orbit space) is well behaved enough to act as a [[differentiable manifold]], which can be turned into a [[symplectic manifold]] by projecting the [[symplectic form]] of M onto it (this can be shown to be [[well defined]]). In light of the observation about physical observables mentioned earlier, we can work with this more "physical" smaller symplectic manifold, but with 2n fewer dimensions.
 
In general, the quotient space is a bit "nasty" to work with when doing concrete calculations (not to mention nonlocal when working with [[diffeomorphism constraint]]s), so what is usually done instead is something similar. Note that the restricted submanifold is a [[bundle]] (but not a [[fiber bundle]] in general) over the quotient manifold. So, instead of working with the quotient manifold, we can work with a [[Section (category theory)|section]] of the bundle instead. This is called [[gauge fixing]].
 
The ''major'' problem is  this bundle might not have a [[global section]] in general. This is where the "problem" of [[global anomaly|global anomalies]] comes in, for example. See [[Gribov ambiguity]]. This is a flaw in quantizing [[gauge theory|gauge theories]] many physicists overlooked.
 
What have been described are irreducible first-class constraints. Another complication is that Δf might not be [[right invertible]] on subspaces of the restricted submanifold of [[codimension]] 1 or greater (which violates the stronger assumption stated earlier in this article). This happens, for example in the [[cotetrad]] formulation of [[general relativity]], at the subspace of configurations where the [[cotetrad field]] and the [[connection form]] happen to be zero over some open subset of space. Here, the constraints are the diffeomorphism constraints.
 
One way to get around this is this: For reducible constraints, we relax the condition on the right invertibility of Δ''f'' into this one: Any smooth function that vanishes at the zeros of ''f'' is the fiberwise contraction of ''f'' with (a non-unique) smooth section of a <math>\bar{V}</math>-vector bundle where <math>\bar{V}</math> is the [[dual vector space]] to the constraint vector space ''V''. This is called the ''regularity condition''.
 
==Constrained Hamiltonian dynamics from a Lagrangian gauge theory==
First of all, we will assume the [[action (physics)|action]] is the integral of a local [[Lagrangian]] that only depends up to the first derivative of the fields. The analysis of more general cases, while possible is more complicated. When going over to the Hamiltonian formalism, we find there are constraints. Recall that in the action formalism, there are [[on shell]] and [[off shell]] configurations. The constraints that hold off shell are called primary constraints while those that only hold on shell are called secondary constraints.
 
==Examples==
Look at the dynamics of a single point particle of mass ''m'' with no internal degrees of freedom moving in a [[pseudo-Riemannian]] spacetime manifold ''S'' with [[metric tensor|metric]] '''g'''. Assume also that the parameter τ describing the trajectory of the particle is arbitrary (i.e. we insist upon [[Parametric_curve#Reparametrization_and_equivalence_relation|reparametrization invariance]]). Then, its [[symplectic space]] is the [[cotangent bundle]] T*S with the canonical symplectic form ω. If we coordinatize ''T'' * ''S'' by its position ''x'' in the base manifold ''S'' and its position within the cotangent space '''p''', then we have a constraint
 
:''f'' = ''m''<sup>2</sup> &minus;'''g'''(''x'')<sup>&minus;1</sup>('''p''','''p''') = 0.
 
The Hamiltonian ''H'' is, surprisingly enough, ''H'' = 0. In light of the observation that the Hamiltonian is only defined up to the equivalence class of smooth functions agreeing on the constrained subspace, we can use a new Hamiltonian H'=f instead. Then, we have the interesting case where the Hamiltonian is the same as a constraint! See [[Hamiltonian constraint]] for more details.
 
Consider now the case of a [[Yang-Mills theory]] for a real [[simple Lie algebra]] ''L'' (with a [[negative definite]] [[Killing form]] η) [[minimally coupled]] to a real scalar field σ, which transforms as an [[orthogonal representation]] ρ with the underlying vector space ''V'' under ''L'' in (''d'' &minus; 1) + 1 [[Minkowski spacetime]]. For l in ''L'', we write
 
:&rho;(l)[&sigma;]
 
as
 
:l[&sigma;]
 
for simplicity. Let '''A''' be the ''L''-valued [[connection form]] of the theory. Note that the '''A''' here differs from the '''A''' used by physicists by a factor of ''i'' and "g". This agrees with the mathematician's convention. The action ''S'' is given by
 
:<math>S[\bold{A},\sigma]=\int d^dx \frac{1}{4g^2}\eta((\bold{g}^{-1}\otimes \bold{g}^{-1})(\bold{F},\bold{F}))+\frac{1}{2}\alpha(\bold{g}^{-1}(D\sigma,D\sigma))</math>
 
where '''g''' is the Minkowski metric, '''F''' is the [[curvature form]]
:<math>d\bold{A}+\bold{A}\wedge\bold{A}</math> (
 
no ''i''s or ''g''s!) where the second term is a formal shorthand for pretending the Lie bracket is a commutator, ''D'' is the covariant derivative
 
:D&sigma; = d&sigma; &minus; '''A'''[&sigma;]
 
and α is the orthogonal form for ρ.
 
''I hope I have all the signs and factors right. I can't guarantee it.''
 
What is the Hamiltonian version of this model? Well, first, we have to split '''A''' noncovariantly into a time component φ and a spatial part <math>\vec{A}</math>. Then, the resulting symplectic space has the conjugate variables σ, π<sub>σ</sub> (taking values in the underlying vector space of <math>\bar{\rho}</math>, the dual rep of ρ), <math>\vec{A}</math>, <math>\vec{\pi}_A</math>, φ and π<sub>φ</sub>. for each spatial point, we have the constraints, π<sub>φ</sub>=0 and the [[Gaussian constraint]]
 
:<math>\vec{D}\cdot\vec{\pi}_A-\rho'(\pi_\sigma,\sigma)=0</math>
 
where since ρ is an [[intertwiner]]
 
:<math>\rho:L\otimes V\rightarrow V</math>,
 
ρ' is the dualized intertwiner
 
:<math>\rho':\bar{V}\otimes V\rightarrow L</math>
 
(L is self-dual via η). The Hamiltonian,
 
:<math>H_f=\int d^{d-1}x \frac{1}{2}\alpha^{-1}(\pi_\sigma,\pi_\sigma)+\frac{1}{2}\alpha(\vec{D}\sigma\cdot\vec{D}\sigma)-\frac{g^2}{2}\eta(\vec{\pi}_A,\vec{\pi}_A)-\frac{1}{2g^2}\eta(\bold{B}\cdot \bold{B})-\eta(\pi_\phi,f)-<\pi_\sigma,\phi[\sigma]>-\eta(\phi,\vec{D}\cdot\vec{\pi}_A).</math>
 
The last two terms are a linear combination of the Gaussian constraints and we have a whole family of (gauge equivalent)Hamiltonians parametrized by ''f''. In fact, since the last three terms vanish for the constrained states, we can drop them.
 
==Second class constraints==
 
In a constrained Hamiltonian system, a dynamical quantity is '''second class''' if its Poisson bracket with at least one constraint is nonvanishing. A constraint that has a nonzero Poisson bracket with at least one other constraint, then, is a '''second class constraint'''.
 
See [[first class constraints]]  or [[Dirac bracket]] for the preliminaries.
 
===An example: a particle confined to a sphere===
{{Disputeabout|"The second class constraints and Hamiltonian given in this example"|date=March 2009}}
 
Before going on to the general theory, let's look at a specific example step by step to motivate the general analysis.
 
Let's start with the [[action (physics)|action]] describing a [[Newtonian dynamics|Newtonian]] particle of [[mass]] m constrained to a surface of radius R within a uniform [[gravitational field]] ''g''. When one works in Lagrangian mechanics, there are several ways to implement a constraint: one can switch to generalized coordinates that manifestly solve the constraint or one can use a Lagrange multiplier.
 
In this case, the particle is constrained to a sphere, therefore the natural solution would be to use angular coordinates to describe the position of the particle instead of Cartesian and solve the constraint in that way (the first choice). For didactic reasons, instead, consider the problem in Cartesian coordinates with a Lagrange multiplier term.
 
The action is given by
 
<math>S=\int dt L=\int dt \left[\frac{m}{2}(\dot{x}^2+\dot{y}^2+\dot{z}^2)-mgz+\frac{\lambda}{2}(x^2+y^2+z^2-R^2)\right]</math>
 
where the last term is the [[Lagrange multiplier]] term enforcing the constraint.
 
Of course, we could have just used different [[coordinates]] and written it as
 
<math>S=\int dt \left[\frac{mR^2}{2}(\dot{\theta}^2+\sin^2(\theta)\dot{\phi}^2)+mgR\cos(\theta)\right]</math>
 
instead, but let's look at the former coordinatization.
 
The [[conjugate momentum|conjugate momenta]] are given by
 
<math>p_x=m\dot{x}</math>, <math>p_y=m\dot{y}</math>, <math>p_z=m\dot{z}</math>, <math>p_\lambda=0</math>.
 
Note that we can't determine <math>\dot{\lambda}</math> from the momenta.
 
The [[Hamiltonian mechanics|Hamiltonian]] is given by
 
<math>H=\vec{p}\cdot\dot{\vec{r}}+p_\lambda \dot{\lambda}-L=\frac{p^2}{2m}+p_\lambda \dot{\lambda}+mgz-\frac{\lambda}{2}(r^2-R^2)</math>.
 
We can't eliminate <math>\dot{\lambda}</math> at this stage yet. We are here treating <math>\dot{\lambda}</math> as a shorthand for a function of the [[symplectic space]] which we have yet to determine and ''not'' an independent variable. For notational consistency, define <math>u_1=\dot{\lambda}</math> from now on. The above Hamiltonian with the <math>p_\lambda</math> term is the "naive Hamiltonian". Note that since, on-shell, the constraint must be satisfied, one cannot distinguish between the naive Hamiltonian and the above Hamiltonian with the undetermined coefficient, <math>\dot{\lambda}=u_1</math>, on-shell.
 
We have the [[primary constraint]] p<sub>λ</sub>=0.
 
We require, on the grounds of consistency, that the [[Poisson bracket]] of all the constraints with the Hamiltonian vanish at the constrained subspace. In other words, the constraints must not evolve in time if they are going to be identically zero along the equations of motion.
 
From this consistency condition, we immediately get the [[First_class_constraints#Constrained_Hamiltonian_dynamics_from_a_Lagrangian_gauge_theory|secondary constraint]]
 
r<sup>2</sup>-R<sup>2</sup>=0.
 
By the same reasoning, this constraint should be added into the Hamiltonian with an undetermined (not necessarily constant) coefficient <math>u_2</math>. At this point, the Hamiltonian is
:<math>
H = \frac{p^2}{2m} + mgz - \frac{\lambda}{2}(r^2-R^2) + u_1 p_\lambda + u_2 (r^2-R^2)
</math>
 
And from the secondary constraint, we get the tertiary constraint
 
<math>\vec{p}\cdot\vec{r}=0</math>,
 
by demanding on the grounds of consistency that <math>\{r^2-R^2,\, H\}_{PB} = 0</math> on-shell. Again, one should add this constraint into the Hamiltonian since on-shell no one can tell the difference. Therefore, so far, the Hamiltonian looks like
:<math>
H = \frac{p^2}{2m} + mgz - \frac{\lambda}{2}(r^2-R^2) + u_1 p_\lambda + u_2 (r^2-R^2) + u_3 \vec{p}\cdot\vec{r},
</math>
where <math>u_1</math>, <math>u_2</math>, and <math>u_3</math> are still completely undetermined. Note that frequently all constraints that are found from consistency conditions are referred to as "secondary constraints" and secondary, tertiary, quaternary, etc. constraints are not distinguished.
 
The tertiary constraint's consistency condition yields
:<math>
\{\vec{p}\cdot\vec{r},\, H\}_{PB} = \frac{p^2}{m} - mgz+ \lambda r^2 -2 u_2 r^2 = 0.
</math>
This is ''not'' a quaternary constraint, but a condition which fixes one of the undetermined coefficients. In particular, it fixes
:<math>
u_2 = \frac{\lambda}{2} + \frac{1}{r^2}\left(\frac{p^2}{2m}-\frac{1}{2}mgz \right).
</math>
 
Now that there are new terms in the Hamiltonian, one should go back and check the consistency conditions for the primary and secondary constraints. The secondary constraint's consistency condition gives
:<math>
\frac{2}{m}\vec{r}\cdot\vec{p} + 2 u_3 r^2 = 0.
</math>
Again, this is ''not'' a new constraint; it only determines that
:<math>
u_3 = -\frac{\vec{r}\cdot\vec{p}}{m r^2}.
</math>
 
At this point there are no more constraints or consistency conditions to check.
 
Putting it all together,
:<math>H=\left(2-\frac{R^2}{r^2}\right)\frac{p^2}{2m} + \frac{1}{2}\left(1+\frac{R^2}{r^2}\right)mgz - \frac{(\vec{r}\cdot\vec{p})^2}{mr^2} + u_1 p_\lambda</math>.
When finding the equations of motion, one should use the above Hamiltonian, and as long as one is careful to never use constraints before taking derivatives in the Poisson bracket then one gets the correct equations of motion. That is, the equations of motion are given by
:<math>
\dot{\vec{r}} = \{\vec{r}, \, H\}_{PB}, \quad \dot{\vec{p}} = \{ \vec{p},\, H\}_{PB}, \quad \dot{\lambda} = \{ \lambda,\, H\}_{PB},
\quad \dot{p}_\lambda = \{ p_\lambda, H\}_{PB}.
</math>
 
Before analyzing the Hamiltonian, consider the three constraints:
:<math>
\phi_1 = p_\lambda, \quad \phi_2 = r^2-R^2, \quad \phi_3 = \vec{p}\cdot\vec{r}.
</math>
Notice the nontrivial [[Poisson bracket]] structure of the constraints. In particular,
:<math>
\{\phi_2, \phi_3\} = 2 r^2 \neq 0.
</math>
The above Poisson bracket does not just fail to vanish off-shell, which might be anticipated, but even on-shell it is nonzero. Therefore, <math>\phi_2</math> and <math>\phi_3</math> are '''second class constraints''' while <math>\phi_1</math> is a [[first class constraint]]. Note that these constraints satisfy the regularity condition.
 
Here, we have a symplectic space where the Poisson bracket does not have "nice properties" on the constrained subspace. But [[Paul Dirac|Dirac]] noticed that we can turn the underlying [[differential manifold]] of the [[symplectic space]] into a [[Poisson manifold]] using a different bracket, called the [[Dirac bracket]], such that the Dirac bracket of any (smooth) function with any of the second class constraints always vanishes and a couple of other nice properties.
 
If one wanted to canonically quantize this system, then, one needs to promote the canonical Dirac brackets not the canonical Poisson brackets to commutation relations.
 
Examination of the above Hamiltonian shows a number of interesting things happening. One thing to note is that on-shell when the constraints are satisfied the extended Hamiltonian is identical to the naive Hamiltonian, as required. Also, note that <math>\lambda</math> dropped out of the extended Hamiltonian. Since <math>\phi_1</math> is a first class primary constraint it should be interpreted as a generator of a gauge transformation. The gauge freedom is the freedom to choose <math>\lambda</math> which has ceased to have any effect on the particle's dynamics. Therefore, that <math>\lambda</math> dropped out of the Hamiltonian, that <math>u_1</math> is undetermined, and that <math>\phi_1 = p_\lambda</math> is first class, are all closely interrelated.
 
Note that it would be more natural not to start with a Lagrangian with a Lagrange multiplier, but instead take <math>r^2-R^2</math> as a primary constraint and proceed through the formalism. The result would the elimination of the extraneous <math>\lambda</math> dynamical quantity. Perhaps, the example is more edifying in its current form.
 
===Example: Proca action===
Another example we will use is the [[Proca action]]. The fields are <math>A^\mu = (\vec{A},\phi)</math> and the action is
:<math>S = \int d^dx dt \left[ \frac{1}{2}E^2 - \frac{1}{4}B_{ij}B_{ij} - \frac{m^2}{2}A^2 + \frac{m^2}{2}\phi^2\right]</math>
where
:<math>\vec{E} \equiv -\nabla\phi - \dot{\vec{A}}</math>
and
:<math>B_{ij} \equiv \frac{\partial A_j}{\partial x_i} - \frac{\partial A_i}{\partial x_j}</math>.
<math>(\vec{A},-\vec{E})</math> and <math>(\phi,\pi)</math> are [[canonical variables]]. The second class constraints are
:<math>\pi \approx 0</math>
and
:<math>\nabla\cdot\vec{E} + m^2 \phi \approx 0</math>.
The Hamiltonian is given by
:<math>H = \int d^dx \left[ \frac{1}{2}E^2 + \frac{1}{4}B_{ij}B_{ij} - \pi\nabla\cdot\vec{A} + \vec{E}\cdot\nabla\phi + \frac{m^2}{2}A^2 - \frac{m^2}{2}\phi^2\right]</math>.
 
1, N. K. Falck and A. C. Hirshfeld, 1983, "Dirac-bracket quantisation of a constrained nonlinear system: the rigid rotator", Eur. J. Phys. 4 p.&nbsp;5. {{doi|10.1088/0143-0807/4/1/003}}  (Note that the form of the quantum momentum in this paper is dubious.)
 
2, T. Homma, T. Inamoto, and T. Miyazaki, 1990, "Schrödinger equation for the nonrelativistic particle constrained on a hypersurface in a curved space ", Phys. Rev. D 42, p.&nbsp;2049. http://prd.aps.org/abstract/PRD/v42/i6/p2049_1. (Tote that the Hamiltonian suggested by the authors from second form of the constraint, (i.e., the time derivative of the <math> f(x)=0 </math> ), is not completely compatible with the formalism of Hamiltonian mechanics.)
 
==See also==
 
*[[Dirac bracket]],
*[[holonomic constraint]],
*[[analysis of flows]]
 
==References==
 
*{{Citation | last1=Dirac | first1=P. A. M. | author1-link=Paul Dirac | title=Generalized Hamiltonian dynamics | doi=10.4153/CJM-1950-012-1  | id={{MR|0043724}} | year=1950 | journal=[[Canadian Journal of Mathematics]] | issn=0008-414X | volume=2 | pages=129–148}}
*{{Citation | last1=Dirac | first1=Paul A. M. | title=Lectures on quantum mechanics | url=http://books.google.com/books?id=GVwzb1rZW9kC | publisher=Belfer Graduate School of Science, New York | series=Belfer Graduate School of Science Monographs Series | id={{MR|2220894}} Reprinted by Dover in 2001. | year=1964 | volume=2}}
 
{{DEFAULTSORT:First Class Constraint}}
[[Category:Classical mechanics]]
[[Category:Theoretical physics]]

Revision as of 22:17, 12 August 2014

Template:Multiple issues Template:Distinguish In a constrained Hamiltonian system, a dynamical quantity is called a first class constraint if its Poisson bracket with all the other constraints vanishes on the constraint surface (the surface implicitly defined by the simultaneous vanishing of all the constraints). A second class constraint is one that is not first class.

First and second class constraints were introduced by Template:Harvs as a way of quantizing mechanical systems such as gauge theories where the symplectic form is degenerate.

The terminology of first and second class constraints is confusingly similar to that of primary and secondary constraints. These divisions are independent: both first and second class constraints can be either primary or secondary, so this gives altogether four different classes of constraints.

Poisson brackets

In Hamiltonian mechanics, consider a symplectic manifold M with a smooth Hamiltonian over it (for field theories, M would be infinite-dimensional).

Suppose we have some constraints

fi(x)=0,

for n smooth functions

{fi}i=1n

These will only be defined chartwise in general. Suppose that everywhere on the constrained set, the n derivatives of the n functions are all linearly independent and also that the Poisson brackets

{ fi, fj }

and

{ fi, H }

all vanish on the constrained subspace. This means we can write

{fi,fj}=kcijkfk

for some smooth functions

cijk

(there is a theorem showing this) and

{fi,H}=jvijfj

for some smooth functions

vij.

This can be done globally, using a partition of unity. Then, we say we have an irreducible first-class constraint (irreducible here is in a different sense from that used in representation theory).

Geometric theory

For a more elegant way, suppose given a vector bundle over M, with n-dimensional fiber V. Equip this vector bundle with a connection. Suppose too we have a smooth section f of this bundle.

Then the covariant derivative of f with respect to the connection is a smooth linear map Δf from the tangent bundle TM to V, which preserves the base point. Assume this linear map is right invertible (i.e. there exists a linear map g such that (Δf)g is the identity map) for all the fibers at the zeros of f. Then, according to the implicit function theorem, the subspace of zeros of f is a submanifold.

The ordinary Poisson bracket is only defined over C(M), the space of smooth functions over M. However, using the connection, we can extend it to the space of smooth sections of f if we work with the algebra bundle with the graded algebra of V-tensors as fibers. Assume also that under this Poisson bracket,

{ f, f } = 0

(note that it's not true that

{ g, g } = 0

in general for this "extended Poisson bracket" anymore) and

{ f, H } = 0

on the submanifold of zeros of f (If these brackets also happen to be zero everywhere, then we say the constraints close off shell). It turns out the right invertibility condition and the commutativity of flows conditions are independent of the choice of connection. So, we can drop the connection provided we are working solely with the restricted subspace.

Intuitive meaning

What does it all mean intuitively? It means the Hamiltonian and constraint flows all commute with each other on the constrained subspace; or alternatively, that if we start on a point on the constrained subspace, then the Hamiltonian and constraint flows all bring the point to another point on the constrained subspace.

Since we wish to restrict ourselves to the constrained subspace only, this suggests that the Hamiltonian, or any other physical observable, should only be defined on that subspace. Equivalently, we can look at the equivalence class of smooth functions over the symplectic manifold, which agree on the constrained subspace (the quotient algebra by the ideal generated by the f's, in other words).

The catch is, the Hamiltonian flows on the constrained subspace depend on the gradient of the Hamiltonian there, not its value. But there's an easy way out of this.

Look at the orbits of the constrained subspace under the action of the symplectic flows generated by the f's. This gives a local foliation of the subspace because it satisfies integrability conditions (Frobenius theorem). It turns out if we start with two different points on a same orbit on the constrained subspace and evolve both of them under two different Hamiltonians, respectively, which agree on the constrained subspace, then the time evolution of both points under their respective Hamiltonian flows will always lie in the same orbit at equal times. It also turns out if we have two smooth functions A1 and B1, which are constant over orbits at least on the constrained subspace (i.e. physical observables) (i.e. {A1,f}={B1,f}=0 over the constrained subspace)and another two A2 and B2, which are also constant over orbits such that A1 and B1 agrees with A2 and B2 respectively over the restrained subspace, then their Poisson brackets {A1, B1} and {A2, B2} are also constant over orbits and agree over the constrained subspace.

In general, weTemplate:Who can't rule out "ergodic" flows (which basically means that an orbit is dense in some open set), or "subergodic" flows (which an orbit dense in some submanifold of dimension greater than the orbit's dimension). We can't have self-intersecting orbits.

For most "practical" applications of first-class constraints, we do not see such complications: the quotient space of the restricted subspace by the f-flows (in other words, the orbit space) is well behaved enough to act as a differentiable manifold, which can be turned into a symplectic manifold by projecting the symplectic form of M onto it (this can be shown to be well defined). In light of the observation about physical observables mentioned earlier, we can work with this more "physical" smaller symplectic manifold, but with 2n fewer dimensions.

In general, the quotient space is a bit "nasty" to work with when doing concrete calculations (not to mention nonlocal when working with diffeomorphism constraints), so what is usually done instead is something similar. Note that the restricted submanifold is a bundle (but not a fiber bundle in general) over the quotient manifold. So, instead of working with the quotient manifold, we can work with a section of the bundle instead. This is called gauge fixing.

The major problem is this bundle might not have a global section in general. This is where the "problem" of global anomalies comes in, for example. See Gribov ambiguity. This is a flaw in quantizing gauge theories many physicists overlooked.

What have been described are irreducible first-class constraints. Another complication is that Δf might not be right invertible on subspaces of the restricted submanifold of codimension 1 or greater (which violates the stronger assumption stated earlier in this article). This happens, for example in the cotetrad formulation of general relativity, at the subspace of configurations where the cotetrad field and the connection form happen to be zero over some open subset of space. Here, the constraints are the diffeomorphism constraints.

One way to get around this is this: For reducible constraints, we relax the condition on the right invertibility of Δf into this one: Any smooth function that vanishes at the zeros of f is the fiberwise contraction of f with (a non-unique) smooth section of a V¯-vector bundle where V¯ is the dual vector space to the constraint vector space V. This is called the regularity condition.

Constrained Hamiltonian dynamics from a Lagrangian gauge theory

First of all, we will assume the action is the integral of a local Lagrangian that only depends up to the first derivative of the fields. The analysis of more general cases, while possible is more complicated. When going over to the Hamiltonian formalism, we find there are constraints. Recall that in the action formalism, there are on shell and off shell configurations. The constraints that hold off shell are called primary constraints while those that only hold on shell are called secondary constraints.

Examples

Look at the dynamics of a single point particle of mass m with no internal degrees of freedom moving in a pseudo-Riemannian spacetime manifold S with metric g. Assume also that the parameter τ describing the trajectory of the particle is arbitrary (i.e. we insist upon reparametrization invariance). Then, its symplectic space is the cotangent bundle T*S with the canonical symplectic form ω. If we coordinatize T * S by its position x in the base manifold S and its position within the cotangent space p, then we have a constraint

f = m2g(x)−1(p,p) = 0.

The Hamiltonian H is, surprisingly enough, H = 0. In light of the observation that the Hamiltonian is only defined up to the equivalence class of smooth functions agreeing on the constrained subspace, we can use a new Hamiltonian H'=f instead. Then, we have the interesting case where the Hamiltonian is the same as a constraint! See Hamiltonian constraint for more details.

Consider now the case of a Yang-Mills theory for a real simple Lie algebra L (with a negative definite Killing form η) minimally coupled to a real scalar field σ, which transforms as an orthogonal representation ρ with the underlying vector space V under L in (d − 1) + 1 Minkowski spacetime. For l in L, we write

ρ(l)[σ]

as

l[σ]

for simplicity. Let A be the L-valued connection form of the theory. Note that the A here differs from the A used by physicists by a factor of i and "g". This agrees with the mathematician's convention. The action S is given by

S[A,σ]=ddx14g2η((g1g1)(F,F))+12α(g1(Dσ,Dσ))

where g is the Minkowski metric, F is the curvature form

dA+AA (

no is or gs!) where the second term is a formal shorthand for pretending the Lie bracket is a commutator, D is the covariant derivative

Dσ = dσ − A[σ]

and α is the orthogonal form for ρ.

I hope I have all the signs and factors right. I can't guarantee it.

What is the Hamiltonian version of this model? Well, first, we have to split A noncovariantly into a time component φ and a spatial part A. Then, the resulting symplectic space has the conjugate variables σ, πσ (taking values in the underlying vector space of ρ¯, the dual rep of ρ), A, πA, φ and πφ. for each spatial point, we have the constraints, πφ=0 and the Gaussian constraint

DπAρ(πσ,σ)=0

where since ρ is an intertwiner

ρ:LVV,

ρ' is the dualized intertwiner

ρ:V¯VL

(L is self-dual via η). The Hamiltonian,

Hf=dd1x12α1(πσ,πσ)+12α(DσDσ)g22η(πA,πA)12g2η(BB)η(πϕ,f)<πσ,ϕ[σ]>η(ϕ,DπA).

The last two terms are a linear combination of the Gaussian constraints and we have a whole family of (gauge equivalent)Hamiltonians parametrized by f. In fact, since the last three terms vanish for the constrained states, we can drop them.

Second class constraints

In a constrained Hamiltonian system, a dynamical quantity is second class if its Poisson bracket with at least one constraint is nonvanishing. A constraint that has a nonzero Poisson bracket with at least one other constraint, then, is a second class constraint.

See first class constraints or Dirac bracket for the preliminaries.

An example: a particle confined to a sphere

Template:Disputeabout

Before going on to the general theory, let's look at a specific example step by step to motivate the general analysis.

Let's start with the action describing a Newtonian particle of mass m constrained to a surface of radius R within a uniform gravitational field g. When one works in Lagrangian mechanics, there are several ways to implement a constraint: one can switch to generalized coordinates that manifestly solve the constraint or one can use a Lagrange multiplier.

In this case, the particle is constrained to a sphere, therefore the natural solution would be to use angular coordinates to describe the position of the particle instead of Cartesian and solve the constraint in that way (the first choice). For didactic reasons, instead, consider the problem in Cartesian coordinates with a Lagrange multiplier term.

The action is given by

S=dtL=dt[m2(x˙2+y˙2+z˙2)mgz+λ2(x2+y2+z2R2)]

where the last term is the Lagrange multiplier term enforcing the constraint.

Of course, we could have just used different coordinates and written it as

S=dt[mR22(θ˙2+sin2(θ)ϕ˙2)+mgRcos(θ)]

instead, but let's look at the former coordinatization.

The conjugate momenta are given by

px=mx˙, py=my˙, pz=mz˙, pλ=0.

Note that we can't determine λ˙ from the momenta.

The Hamiltonian is given by

H=pr˙+pλλ˙L=p22m+pλλ˙+mgzλ2(r2R2).

We can't eliminate λ˙ at this stage yet. We are here treating λ˙ as a shorthand for a function of the symplectic space which we have yet to determine and not an independent variable. For notational consistency, define u1=λ˙ from now on. The above Hamiltonian with the pλ term is the "naive Hamiltonian". Note that since, on-shell, the constraint must be satisfied, one cannot distinguish between the naive Hamiltonian and the above Hamiltonian with the undetermined coefficient, λ˙=u1, on-shell.

We have the primary constraint pλ=0.

We require, on the grounds of consistency, that the Poisson bracket of all the constraints with the Hamiltonian vanish at the constrained subspace. In other words, the constraints must not evolve in time if they are going to be identically zero along the equations of motion.

From this consistency condition, we immediately get the secondary constraint

r2-R2=0.

By the same reasoning, this constraint should be added into the Hamiltonian with an undetermined (not necessarily constant) coefficient u2. At this point, the Hamiltonian is

H=p22m+mgzλ2(r2R2)+u1pλ+u2(r2R2)

And from the secondary constraint, we get the tertiary constraint

pr=0,

by demanding on the grounds of consistency that {r2R2,H}PB=0 on-shell. Again, one should add this constraint into the Hamiltonian since on-shell no one can tell the difference. Therefore, so far, the Hamiltonian looks like

H=p22m+mgzλ2(r2R2)+u1pλ+u2(r2R2)+u3pr,

where u1, u2, and u3 are still completely undetermined. Note that frequently all constraints that are found from consistency conditions are referred to as "secondary constraints" and secondary, tertiary, quaternary, etc. constraints are not distinguished.

The tertiary constraint's consistency condition yields

{pr,H}PB=p2mmgz+λr22u2r2=0.

This is not a quaternary constraint, but a condition which fixes one of the undetermined coefficients. In particular, it fixes

u2=λ2+1r2(p22m12mgz).

Now that there are new terms in the Hamiltonian, one should go back and check the consistency conditions for the primary and secondary constraints. The secondary constraint's consistency condition gives

2mrp+2u3r2=0.

Again, this is not a new constraint; it only determines that

u3=rpmr2.

At this point there are no more constraints or consistency conditions to check.

Putting it all together,

H=(2R2r2)p22m+12(1+R2r2)mgz(rp)2mr2+u1pλ.

When finding the equations of motion, one should use the above Hamiltonian, and as long as one is careful to never use constraints before taking derivatives in the Poisson bracket then one gets the correct equations of motion. That is, the equations of motion are given by

r˙={r,H}PB,p˙={p,H}PB,λ˙={λ,H}PB,p˙λ={pλ,H}PB.

Before analyzing the Hamiltonian, consider the three constraints:

ϕ1=pλ,ϕ2=r2R2,ϕ3=pr.

Notice the nontrivial Poisson bracket structure of the constraints. In particular,

{ϕ2,ϕ3}=2r20.

The above Poisson bracket does not just fail to vanish off-shell, which might be anticipated, but even on-shell it is nonzero. Therefore, ϕ2 and ϕ3 are second class constraints while ϕ1 is a first class constraint. Note that these constraints satisfy the regularity condition.

Here, we have a symplectic space where the Poisson bracket does not have "nice properties" on the constrained subspace. But Dirac noticed that we can turn the underlying differential manifold of the symplectic space into a Poisson manifold using a different bracket, called the Dirac bracket, such that the Dirac bracket of any (smooth) function with any of the second class constraints always vanishes and a couple of other nice properties.

If one wanted to canonically quantize this system, then, one needs to promote the canonical Dirac brackets not the canonical Poisson brackets to commutation relations.

Examination of the above Hamiltonian shows a number of interesting things happening. One thing to note is that on-shell when the constraints are satisfied the extended Hamiltonian is identical to the naive Hamiltonian, as required. Also, note that λ dropped out of the extended Hamiltonian. Since ϕ1 is a first class primary constraint it should be interpreted as a generator of a gauge transformation. The gauge freedom is the freedom to choose λ which has ceased to have any effect on the particle's dynamics. Therefore, that λ dropped out of the Hamiltonian, that u1 is undetermined, and that ϕ1=pλ is first class, are all closely interrelated.

Note that it would be more natural not to start with a Lagrangian with a Lagrange multiplier, but instead take r2R2 as a primary constraint and proceed through the formalism. The result would the elimination of the extraneous λ dynamical quantity. Perhaps, the example is more edifying in its current form.

Example: Proca action

Another example we will use is the Proca action. The fields are Aμ=(A,ϕ) and the action is

S=ddxdt[12E214BijBijm22A2+m22ϕ2]

where

EϕA˙

and

BijAjxiAixj.

(A,E) and (ϕ,π) are canonical variables. The second class constraints are

π0

and

E+m2ϕ0.

The Hamiltonian is given by

H=ddx[12E2+14BijBijπA+Eϕ+m22A2m22ϕ2].

1, N. K. Falck and A. C. Hirshfeld, 1983, "Dirac-bracket quantisation of a constrained nonlinear system: the rigid rotator", Eur. J. Phys. 4 p. 5. 21 year-old Glazier James Grippo from Edam, enjoys hang gliding, industrial property developers in singapore developers in singapore and camping. Finds the entire world an motivating place we have spent 4 months at Alejandro de Humboldt National Park. (Note that the form of the quantum momentum in this paper is dubious.)

2, T. Homma, T. Inamoto, and T. Miyazaki, 1990, "Schrödinger equation for the nonrelativistic particle constrained on a hypersurface in a curved space ", Phys. Rev. D 42, p. 2049. http://prd.aps.org/abstract/PRD/v42/i6/p2049_1. (Tote that the Hamiltonian suggested by the authors from second form of the constraint, (i.e., the time derivative of the f(x)=0 ), is not completely compatible with the formalism of Hamiltonian mechanics.)

See also

References

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    15.6.1 As the agent is an intermediary, generally, as soon as the principal and third party are introduced right into a contractual relationship, the agent drops out of the image, subject to any problems with remuneration or indemnification that he could have against the principal, and extra exceptionally, against the third occasion. Generally, agents are entitled to be indemnified for all liabilities reasonably incurred within the execution of the brokers´ authority.

    To achieve the very best outcomes, you must be always updated on market situations, including past transaction information and reliable projections. You could review and examine comparable homes that are currently available in the market, especially these which have been sold or not bought up to now six months. You'll be able to see a pattern of such report by clicking here It's essential to defend yourself in opposition to unscrupulous patrons. They are often very skilled in using highly unethical and manipulative techniques to try and lure you into a lure. That you must also protect your self, your loved ones, and personal belongings as you'll be serving many strangers in your home. Sign a listing itemizing of all of the objects provided by the proprietor, together with their situation. HSR Prime Recruiter 2010