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One of the basic general problems in analytic number theory is to understand as much as possible the fluctuations of the Möbius function , defined as
when
is the product of
distinct primes, and zero otherwise. For instance, as
takes values in
, we have the trivial bound
and the seemingly slight improvement
is equivalent to the notorious Riemann hypothesis.
There is a general Möbius pseudorandomness heuristic that suggests that the sign pattern behaves so randomly (or pseudorandomly) that one should expect a substantial amount of cancellation in sums that involve the sign fluctuation of the Möbius function in a nontrivial fashion, with the amount of cancellation present comparable to the amount that an analogous random sum would provide; cf. the probabilistic heuristic discussed in this recent blog post. There are a number of ways to make this heuristic precise. As already mentioned, the Riemann hypothesis can be considered one such manifestation of the heuristic. Another manifestation is the following old conjecture of Chowla:
Conjecture 1 (Chowla’s conjecture) For any fixed integer
and exponents
, with at least one of the
odd (so as not to completely destroy the sign cancellation), we have
Note that as for any
, we can reduce to the case when the
take values in
here. When only one of the
are odd, this is essentially the prime number theorem in arithmetic progressions (after some elementary sieving), but with two or more of the
are odd, the problem becomes completely open. For instance, the estimate
is morally very close to the conjectured asymptotic
for the von Mangoldt function , where
is the twin prime constant; this asymptotic in turn implies the twin prime conjecture. (To formally deduce estimates for von Mangoldt from estimates for Möbius, though, typically requires some better control on the error terms than
, in particular gains of some power of
are usually needed. See this previous blog post for more discussion.)
Remark 1 The Chowla conjecture resembles an assertion that, for
chosen randomly and uniformly from
to
, the random variables
become asymptotically independent of each other (in the probabilistic sense) as
. However, this is not quite accurate, because some moments (namely those with all exponents
even) have the “wrong” asymptotic value, leading to some unwanted correlation between the two variables. For instance, the events
and
have a strong correlation with each other, basically because they are both strongly correlated with the event of
being divisible by
. A more accurate interpretation of the Chowla conjecture is that the random variables
are asymptotically conditionally independent of each other, after conditioning on the zero pattern
; thus, it is the sign of the Möbius function that fluctuates like random noise, rather than the zero pattern. (The situation is a bit cleaner if one works instead with the Liouville function
instead of the Möbius function
, as this function never vanishes, but we will stick to the traditional Möbius function formalism here.)
A more recent formulation of the Möbius randomness heuristic is the following conjecture of Sarnak. Given a bounded sequence , define the topological entropy of the sequence to be the least exponent
with the property that for any fixed
, and for
going to infinity the set
of
can be covered by
balls of radius
. (If
arises from a minimal topological dynamical system
by
, the above notion is equivalent to the usual notion of the topological entropy of a dynamical system.) For instance, if the sequence is a bit sequence (i.e. it takes values in
), then there are only
-bit patterns that can appear as blocks of
consecutive bits in this sequence. As a special case, a Turing machine with bounded memory that had access to a random number generator at the rate of one random bit produced every
units of time, but otherwise evolved deterministically, would have an output sequence that had a topological entropy of at most
. A bounded sequence is said to be deterministic if its topological entropy is zero. A typical example is a polynomial sequence such as
for some fixed
; the
-blocks of such polynomials sequence have covering numbers that only grow polynomially in
, rather than exponentially, thus yielding the zero entropy. Unipotent flows, such as the horocycle flow on a compact hyperbolic surface, are another good source of deterministic sequences.
Conjecture 2 (Sarnak’s conjecture) Let
be a deterministic bounded sequence. Then
This conjecture in general is still quite far from being solved. However, special cases are known:
- For constant sequences, this is essentially the prime number theorem (1).
- For periodic sequences, this is essentially the prime number theorem in arithmetic progressions.
- For quasiperiodic sequences such as
for some continuous
, this follows from the work of Davenport.
- For nilsequences, this is a result of Ben Green and myself.
- For horocycle flows, this is a result of Bourgain, Sarnak, and Ziegler.
- For the Thue-Morse sequence, this is a result of Dartyge-Tenenbaum (with a stronger error term obtained by Maduit-Rivat). A subsequent result of Bourgain handles all bounded rank one sequences (though the Thue-Morse sequence is actually of rank two), and a related result of Green establishes asymptotic orthogonality of the Möbius function to bounded depth circuits, although such functions are not necessarily deterministic in nature.
- For the Rudin-Shapiro sequence, I sketched out an argument at this MathOverflow post.
- The Möbius function is known to itself be non-deterministic, because its square
(i.e. the indicator of the square-free functions) is known to be non-deterministic (indeed, its topological entropy is
). (The corresponding question for the Liouville function
, however, remains open, as the square
has zero entropy.)
- In the converse direction, it is easy to construct sequences of arbitrarily small positive entropy that correlate with the Möbius function (a rather silly example is
for some fixed large (squarefree)
, which has topological entropy at most
but clearly correlates with
).
See this survey of Sarnak for further discussion of this and related topics.
In this post I wanted to give a very nice argument of Sarnak that links the above two conjectures:
Proposition 3 The Chowla conjecture implies the Sarnak conjecture.
The argument does not use any number-theoretic properties of the Möbius function; one could replace in both conjectures by any other function from the natural numbers to
and obtain the same implication. The argument consists of the following ingredients:
- To show that
, it suffices to show that the expectation of the random variable
, where
is drawn uniformly at random from
to
, can be made arbitrary small by making
large (and
even larger).
- By the union bound and the zero topological entropy of
, it suffices to show that for any bounded deterministic coefficients
, the random variable
concentrates with exponentially high probability.
- Finally, this exponentially high concentration can be achieved by the moment method, using a slight variant of the moment method proof of the large deviation estimates such as the Chernoff inequality or Hoeffding inequality (as discussed in this blog post).
As is often the case, though, while the “top-down” order of steps presented above is perhaps the clearest way to think conceptually about the argument, in order to present the argument formally it is more convenient to present the arguments in the reverse (or “bottom-up”) order. This is the approach taken below the fold.
One of the basic problems in analytic number theory is to estimate sums of the form
as , where
ranges over primes and
is some explicit function of interest (e.g. a linear phase function
for some real number
). This is essentially the same task as obtaining estimates on the sum
where is the von Mangoldt function. If
is bounded,
, then from the prime number theorem one has the trivial bound
but often (when is somehow “oscillatory” in nature) one is seeking the refinement
Thanks to identities such as
is the Möbius function, refinements such as (1) are similar in spirit to estimates of the form
before one can use identities such as (3) to recover (1). Still, one generally thinks of (1) and (4) as being “morally” equivalent, even if they are not formally equivalent.
When is oscillating in a sufficiently “irrational” way, then one standard way to proceed is the method of Type I and Type II sums, which uses truncated versions of divisor identities such as (3) to expand out either (1) or (4) into linear (Type I) or bilinear sums (Type II) with which one can exploit the oscillation of
. For instance, Vaughan’s identity lets one rewrite the sum in (1) as the sum of the Type I sum
the Type I sum
the Type II sum
and the error term , whenever
are parameters, and
are the sequences
and
Similarly one can express (4) as the Type I sum
the Type II sum
and the error term , whenever
with
, and
is the sequence
After eliminating troublesome sequences such as via Cauchy-Schwarz or the triangle inequality, one is then faced with the task of estimating Type I sums such as
or Type II sums such as
for various . Here, the trivial bound is
, but due to a number of logarithmic inefficiencies in the above method, one has to obtain bounds that are more like
for some constant
(e.g.
) in order to end up with an asymptotic such as (1) or (4).
However, in a recent paper of Bourgain, Sarnak, and Ziegler, it was observed that as long as one is only seeking the Mobius orthogonality (4) rather than the von Mangoldt orthogonality (1), one can avoid losing any logarithmic factors, and rely purely on qualitative equidistribution properties of . A special case of their orthogonality criterion (which actually dates back to an earlier paper of Katai, as was pointed out to me by Nikos Frantzikinakis) is as follows:
Proposition 1 (Orthogonality criterion) Let
be a bounded function such that
for any distinct primes
(where the decay rate of the error term
may depend on
and
). Then
Actually, the Bourgain-Sarnak-Ziegler paper establishes a more quantitative version of this proposition, in which can be replaced by an arbitrary bounded multiplicative function, but we will content ourselves with the above weaker special case. (See also these notes of Harper, which uses the Katai argument to give a slightly weaker quantitative bound in the same spirit.) This criterion can be viewed as a multiplicative variant of the classical van der Corput lemma, which in our notation asserts that
if one has
for each fixed non-zero
.
As a sample application, Proposition 1 easily gives a proof of the asymptotic
for any irrational . (For rational
, this is a little trickier, as it is basically equivalent to the prime number theorem in arithmetic progressions.) The paper of Bourgain, Sarnak, and Ziegler also apply this criterion to nilsequences (obtaining a quick proof of a qualitative version of a result of Ben Green and myself, see these notes of Ziegler for details) and to horocycle flows (for which no Möbius orthogonality result was previously known).
Informally, the connection between (5) and (6) comes from the multiplicative nature of the Möbius function. If (6) failed, then exhibits strong correlation with
; by change of variables, we then expect
to correlate with
and
to correlate with
, for “typical”
at least. On the other hand, since
is multiplicative,
exhibits strong correlation with
. Putting all this together (and pretending correlation is transitive), this would give the claim (in the contrapositive). Of course, correlation is not quite transitive, but it turns out that one can use the Cauchy-Schwarz inequality as a substitute for transitivity of correlation in this case.
I will give a proof of Proposition 1 below the fold (which is not quite based on the argument in the above mentioned paper, but on a variant of that argument communicated to me by Tamar Ziegler, and also independently discovered by Adam Harper). The main idea is to exploit the following observation: if is a “large” but finite set of primes (in the sense that the sum
is large), then for a typical large number
(much larger than the elements of
), the number of primes in
that divide
is pretty close to
:
In particular, one can sum (7) against and obtain an approximation
that approximates a sum of by a bunch of sparser sums of
. Since
we see (heuristically, at least) that in order to establish (4), it would suffice to establish the sparser estimates
for all (or at least for “most”
).
Now we make the change of variables . As the Möbius function is multiplicative, we usually have
. (There is an exception when
is divisible by
, but this will be a rare event and we will be able to ignore it.) So it should suffice to show that
for most . However, by the hypothesis (5), the sequences
are asymptotically orthogonal as
varies, and this claim will then follow from a Cauchy-Schwarz argument.

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