Utilizing Smoothing Techniques to Bound
Abstract.
We demonstrate an improved explicit upper bound of for using smoothing techniques. Our method sharpens previous bounds relying on the Riemann–Siegel formula and the triangle inequality. In particular, we prove that for ,
and for ,
Key words and phrases:
Riemann zeta function, upper bound, 1-line, numerical integration, smoothing2020 Mathematics Subject Classification
11M06, 11Y351. Introduction
Studying the behavior of the Riemann zeta function on the one-line has been of particular interest for a number of years, largely due to its utility in expanding the zero-free regions of [3]. It is often useful to have quality explicit upper bounds on , particularly when probing zero-free regions of the zeta function by computational means. Several such bounds have been proved, including in [9] and [6]. A vast majority of these bounds rely heavily on the Riemann–Siegel formula or similar approximate functional equations of the zeta function where the value of is approximated by
for some .
For large , previous researchers have applied exponential sum techniques to the Riemann–Siegel formula to achieve quality explicit upper bounds of . In [9], Patel proved
| (1.1) |
for . The bounds and are essentially trivial bounds arising from applying the triangle inequality to the Riemann–Siegel formula. The bound arises via exponential sum estimates and is better than the previous bounds only when is sufficiently large.
Hiary, Leong, and Yang [6] refined the work of Patel and showed
| (1.2) |
for . Hiary, Leong, and Yang use further exponential sum arguments to improve (1.1) for large , but for they use Patel’s bound .
Working with smoothed sums can sometimes yield improved quantitative or qualitative results. One noteworthy example of this philosophy is Helfgott’s proof of the ternary Goldbach conjecture (see [4]), in which smoothed sums appear throughout the argument. We show that utilizing smoothing techniques can improve the “trivial” bounds of for small . In particular, we obtain improved upper bounds for . We essentially work with a smooth representation
| (1.3) |
for suitable . The following is our main result.
Theorem 1.1.
If , then
| (1.4) |
Furthermore, if , then
| (1.5) |
Theorem 1.1 improves upon (1.1) and (1.2) for . While both bounds rely heavily on smoothing, the bound
also depends in part on exponential sum techniques. However, the bound
relies only on a trivial bound for . This bound, without using exponential sums, is an improvement of (1.1) and (1.2) for .
In this paper, we focus on smoothings of the form seen in (1.3), but it would be interesting to consider the effects of different smoothing functions. It is possible that using exponential sums and smoothing techniques in tandem yields even better results. It would also be worthwhile to see if using smoothings could sharpen bounds on or in ranges of interest.
In Section 2 we prove a smoothed representation of of the form seen in (1.3) and show that that smoothed sum can be bounded by plus some small error. In Section 3, we twice bound our main error term, once optimizing for smaller and once for larger . Finally, in Section 4 we prove Theorem 1.1.
Some of our work relies on computer calculation. All the code used in this paper is available at our “Utilizing Smoothing Techniques to Bound ” GitHub repository [1].
2. A Smoothed Representation of
We begin by proving a smoothed approximation of of the form given in (1.3).
Lemma 2.1.
For all and ,
| (2.1) | ||||
Proof.
Since the inverse Mellin transform of for is [8, 2.5.1], we can write
Taking and summing over , we can write
where interchanging the order of summation and integration is justified by absolute convergence.
We shift the line of integration to , picking up contributions from poles at and . Hence
and rearranging gives
Applying the triangle inequality yields
We perform a change of variables in the integral to obtain
which gives the desired bound. ∎
We now proceed by bounding the terms on the right-hand side of Lemma 2.1 individually. We begin with the summation.
Lemma 2.2.
If , , and
then
| (2.2) |
Proof.
Since , it follows that . Therefore,
| (2.3) |
We write as a Taylor series to obtain
For ease of notation, we define
so that
Furthermore, note that we can write
Expanding as a Taylor series gives
We can bound by
Applying this bound, we find
Using this, (2.3) becomes
3. Bounding the Integral
To aid in bounding the integral in (2.1), we make use of two previously proven bounds on the Riemann zeta function.
Lemma 3.1.
If , then
| (3.1) |
Furthermore, for , we have
| (3.2) |
Proof.
While (3.1) is essentially a trivial bound, the bound (3.2) relies on exponential sums. The trivial bound is better for while (3.2) is better for larger .
As (3.1) and (3.2) are both of the form , we bound the integral in (2.1) using an arbitrary bound on of this form.
For the duration of this paper, we fix .
Lemma 3.2.
If there exist with such that
| (3.3) |
for all , then for all we have
| (3.4) |
where
Remark 3.3.
Since our choice of is sufficiently large, the variable in the integrals and is far enough from the origin that the exponential decay of the gamma function causes their value to be small. As such, the effect of these integrals on our error is minimal. Most of our error will arise from , which is large since its range contains the origin. In an attempt to maximize our savings we bound twice, using both bounds of found in Lemma 3.1. The bound in (3.2) will give better error for large , while (3.1) will be more effective for small values of .
Proof of Lemma 3.2.
Due to the conjugate symmetry of the zeta function, it follows that the bound holds for all . As such, we define
and split the integral
| (3.5) |
We bound and separately.
First, consider . Using our bound (3.3), we have
where
Consider . Then , so we can bound
Furthermore, since , we have . Thus we have
To eliminate the -dependence in the bounds of integration, we can bound and write
However, due to the conjugate symmetry of the gamma function, these integrals are exactly and , so we have
For , since its integrand and are nonnegative, we can simply bound . Thus we have
| (3.6) |
The integrals and can both be evaluated numerically, with the tail bounded analytically for various choices of and . These bounds are somewhat tedious and uninteresting so we do not give all the details. However, we will demonstrate a bound of the tail of with and note that we can bound the others quite similarly.
Lemma 3.4.
If , then
Proof.
We can similarly bound both and for various values of and . However, the integral still has some dependence. Since provides the largest contribution to our eventual error term, we treat it carefully. In the following two lemmas, we provide two different bounds on , the first using the bound in (3.1) and the second using the bound in (3.2).
Lemma 3.5.
If , then
| (3.9) |
where and .
Proof.
We first examine . Pulling out a factor of gives
Since , we see by concavity that . Inserting this bound and expanding the integral gives
We obtain an upper bound on the integrals, and simultaneously remove their -dependence, by extending the integrals to the entire real line. Hence
Rigorously integrating these numerically using SageMath in [1] and bounding the tail (similarly to the proof of Lemma 3.4), we find
Similarly we get a lower bound , and we arrive at the desired conclusion. ∎
Lemma 3.6.
If and , then
| (3.10) |
Proof.
Since , Lemma 3.1 gives
Therefore, we have
Since , we have , and therefore
We also have the upper bound
Inserting both of these bounds gives
Extending the range of integration to the whole real line and expanding gives
The first two integrals we can bound the tails and rigorously integrate using SageMath in the usual way. For the later two integrals, since and are not holomorphic at , we must also analytically bound the integral in a very small neighborhood of the origin before performing numerical integration. Performing the computations in [1], we arrive at
4. Proof of Theorem 1.1
Proof of Theorem 1.1.
With bounds on , we can now directly bound the integral term in (2.1). We apply Lemma 3.2 to (3.1) and (3.2) to arrive at two distinct bounds of . We begin with the bound in (3.1). That is, setting
Lemma 3.2 gives
With these parameters, we numerically bound and in [1] and find
Furthermore, Lemma 3.5 gives
Hence defining
we have
This along with Lemmas 2.1 and 2.2 allows us to write
The two largest terms in this bound are and . As such, we minimize the sum of these terms by choosing
Thus we have
say. Since
is increasing on , we bound the expression trivially for in [1] to find
| (4.1) |
Similarly, we can bound the integral term using the bound given in (3.2). Here we have
With these parameters, we numerically bound and in [1] as follows:
Furthermore, Lemma 3.6 gives
Thus if we define
we have
This along with Lemmas 2.1 and 2.2 allows us to write
The two largest terms in this bound are and . As such, we minimize the sum of these terms by choosing
Thus we have
say. Since
is decreasing on , for we trivially bound this expression in [1] to arrive at
| (4.2) |
Noting that the bound in (4.1) is greater than the bound in (4.2) for all , it follows that for all
Furthermore, we prove computationally in [1] that this bound holds for all . Hence we have the desired bound. ∎
5. Acknowledgments
Both authors are partially supported by the National Science Foundation (DMS-2418328). The second author is also partially supported by the Simons Foundation (MPS-TSM-00007959).
References
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