In mathematical analysis, Lorentz spaces, introduced by George G. Lorentz in the 1950s,[1][2] are generalisations of the more familiar 
 spaces.
The Lorentz spaces are denoted by 
.  Like the 
 spaces, they are characterized by a norm (technically a quasinorm) that encodes information about the "size" of a function, just as the 
 norm does.  The two basic qualitative notions of "size" of a function are: how tall is the graph of the function, and how spread out is it.  The Lorentz norms provide tighter control over both qualities than the 
 norms, by exponentially rescaling the measure in both the range (
) and the domain (
). The Lorentz norms, like the 
 norms, are invariant under arbitrary rearrangements of the values of a function.
Definition
The Lorentz space on a measure space 
 is the space of complex-valued measurable functions 
 on X such that the following quasinorm is finite

where 
 and 
.  Thus, when 
,

and, when 
,

It is also conventional to set 
.
Decreasing rearrangements
The quasinorm is invariant under rearranging the values of the function 
, essentially by definition.  In particular, given a complex-valued measurable function 
 defined on a measure space, 
, its decreasing rearrangement function, 
 can be defined as

where 
 is the so-called distribution function of 
, given by

Here, for notational convenience, 
 is defined to be 
.
The two functions 
 and 
 are equimeasurable, meaning that

where 
 is the Lebesgue measure on the real line. The related symmetric decreasing rearrangement function, which is also equimeasurable with 
, would be defined on the real line by

Given these definitions, for 
 and 
, the Lorentz quasinorms are given by

Lorentz sequence spaces
When 
 (the counting measure on 
), the resulting Lorentz space is a sequence space.  However, in this case it is convenient to use different notation.
Definition.
For 
 (or 
 in the complex case), let 
 denote the p-norm for 
 and 
 the ∞-norm. Denote by 
 the Banach space of all sequences with finite p-norm. Let 
 the Banach space of all sequences satisfying 
, endowed with the ∞-norm. Denote by 
 the normed space of all sequences with only finitely many nonzero entries. These spaces all play a role in the definition of the Lorentz sequence spaces 
 below.
Let 
 be a sequence of positive real numbers satisfying 
, and define the norm 
. The Lorentz sequence space 
 is defined as the Banach space of all sequences where this norm is finite. Equivalently, we can define 
 as the completion of 
 under 
.
Properties
The Lorentz spaces are genuinely generalisations of the 
 spaces in the sense that, for any 
, 
, which follows from Cavalieri's principle. Further, 
 coincides with weak 
. They are quasi-Banach spaces (that is, quasi-normed spaces which are also complete) and are normable for 
 and 
. When 
, 
 is equipped with a norm, but it is not possible to define a norm equivalent to the quasinorm of 
, the weak 
 space.  As a concrete example that the triangle inequality fails in 
, consider

whose 
 quasi-norm equals one, whereas the quasi-norm of their sum 
 equals four.
The space 
 is contained in 
 whenever 
.  The Lorentz spaces are real interpolation spaces between 
 and 
.
Hölder's inequality
 where 
, 
, 
, and 
.
Dual space
If 
 is a nonatomic σ-finite measure space, then 
(i) 
 for 
, or 
; 
(ii) 
 for 
, or 
; 
(iii) 
 for 
. 
Here 
 for 
, 
 for 
, and 
.
Atomic decomposition
The following are equivalent for 
. 
(i) 
. 
(ii) 
 where 
 has disjoint support, with measure 
, on which 
 almost everywhere, and 
. 
(iii) 
 almost everywhere, where 
 and 
.
(iv) 
 where 
 has disjoint support 
, with nonzero measure, on which 
 almost everywhere, 
 are positive constants, and 
.
(v) 
 almost everywhere, where 
.
See also
References
Notes
- ^ G. Lorentz, "Some new function spaces", Annals of Mathematics 51 (1950), pp. 37-55.
 
- ^ G. Lorentz, "On the theory of spaces Λ", Pacific Journal of Mathematics 1 (1951), pp. 411-429.
 
 
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