Looking for Properties of Low Discrepancy Sequences.

In summary, the conversation discusses the conjecture that <x> denote the fractal part of an irrational number x and whether it is always true for an arbitrary low discrepancy sequence that the limit of the absolute value of <x_n - x_{n-1}> - <x_{n+1} - x_n> equals 0 as n approaches infinity. The difficulty lies in finding a sequence where <x_n - x_{n-1}> alternates between decreasing and increasing. The speaker's goal is to prove this case, but so far a counterexample has been found.
  • #1
mehr1methanol
10
0
Def: A low discrepancy sequence is a uniformly distributed sequence with minimal discrepancy, O(logN/N).

Question: Let [itex]<x>[/itex] denote the fractal part of an irrational number [itex]x[/itex]. Let [itex](<x_n>)[/itex] be an arbitrary low discrepancy sequence. Is it always true that :
[itex] \lim_{n \to +\infty}|<x_n - x_{n-1}> - <x_{n+1} - x_n>| = 0[/itex]

I believe this is an open problem. I'm more than happy to discuss anything that's unclear.

Attempt on the solution:

There are trivial cases such as the followings:

1) [itex](<n\alpha>)[/itex] where [itex]\alpha[/itex]is an irrational number. This is low discrepancy sequence (if you like to see the proof consult me for references). Clearly the conjecture above holds.

2) if I choose the [itex]<x_n>[/itex] such that it's monotonically increasing or monotonically decreasing, then the conjecture above holds because the sequence is also bounded in the unit interval

The difficulty is when if I come up with a sequence [itex](<x_n>)[/itex], where [itex]<x_n - x_{n-1}>[/itex] alternates between decreasing or increasing. In this case it's not clear to me if the conjecture holds. My goal is to rigorously prove the last case. Or are there cases that I'm missing!??
 
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  • #2
mehr1methanol said:
Def: A low discrepancy sequence is a uniformly distributed sequence with minimal discrepancy, O(logN/N).

Question: Let [itex]<x>[/itex] denote the fractal part of an irrational number [itex]x[/itex]. Let [itex](<x_n>)[/itex] be an arbitrary low discrepancy sequence. Is it always true that :
[itex] \lim_{n \to +\infty}|<x_n - x_{n-1}> - <x_{n+1} - x_n>| = 0[/itex]

I believe this is an open problem. I'm more than happy to discuss anything that's unclear.

Attempt on the solution:

There are trivial cases such as the followings:

1) [itex](<n\alpha>)[/itex] where [itex]\alpha[/itex]is an irrational number. This is low discrepancy sequence (if you like to see the proof consult me for references). Clearly the conjecture above holds.

2) if I choose the [itex]<x_n>[/itex] such that it's monotonically increasing or monotonically decreasing, then the conjecture above holds because the sequence is also bounded in the unit interval

The difficulty is when if I come up with a sequence [itex](<x_n>)[/itex], where [itex]<x_n - x_{n-1}>[/itex] alternates between decreasing or increasing. In this case it's not clear to me if the conjecture holds. My goal is to rigorously prove the last case. Or are there cases that I'm missing!??
Wouldn't the sequence [itex](<[n/2]\alpha>)[/itex] where [] denotes integer part be low discrepancy?
 
  • #3
haruspex said:
Wouldn't the sequence [itex](<[n/2]\alpha>)[/itex] where [] denotes integer part be low discrepancy?

Yes for sure!

I actually solved this problem a while ago! It turns out the conjecture doesn't hold and the counterexample is the van der corput sequence.
 
  • #4
I should admit your example is much more clever.
 
  • #5


I would approach this problem by first looking at the existing literature on low discrepancy sequences and their properties. There have been numerous studies and research on this topic, and it is important to review and understand the current state of knowledge before attempting to solve the problem.

After reviewing the literature, I would start by examining the definition of low discrepancy sequences and their properties. It is important to fully understand what constitutes a low discrepancy sequence and how it differs from other types of sequences.

Next, I would analyze the conjecture given in the question and try to understand its implications and potential limitations. It is possible that there are certain assumptions or conditions that need to be met for the conjecture to hold, and it is important to identify these in order to find a solution.

I would also consider different approaches for proving the conjecture. This could involve using mathematical proofs, simulations, or even conducting experiments to gather data and analyze it.

Additionally, I would seek the help of other experts in the field, such as mathematicians or other scientists who have experience with low discrepancy sequences. Collaborating with others can often lead to new insights and ideas for solving a problem.

In conclusion, solving this problem would require a thorough understanding of low discrepancy sequences and their properties, as well as careful analysis and collaboration with others. It may also require innovative thinking and new approaches to proving the conjecture.
 

1. What are low discrepancy sequences?

Low discrepancy sequences are a type of pseudo-random sequence used in numerical analysis and simulation. They are designed to have a more uniform distribution of points, resulting in a low discrepancy between the number of points in each region.

2. Why are low discrepancy sequences important?

Low discrepancy sequences are important because they provide a more accurate representation of a continuous space in numerical analysis and simulation. They also have applications in quasi-Monte Carlo methods, which are used in high-dimensional integration problems.

3. What properties should be considered when looking for low discrepancy sequences?

The most important properties to consider when looking for low discrepancy sequences are their uniformity, randomness, and the rate of convergence to a uniform distribution. Other factors to consider may include the dimensionality, smoothness, and computational efficiency of the sequence.

4. How are low discrepancy sequences generated?

Low discrepancy sequences are typically generated using a deterministic algorithm, such as the Sobol or Halton sequence. These algorithms use number-theoretic techniques to produce a sequence of points that have desirable low discrepancy properties.

5. What are some applications of low discrepancy sequences?

Low discrepancy sequences have applications in numerical integration, optimization, and simulation. They are commonly used in finance, engineering, and scientific computing to improve the accuracy and efficiency of calculations.

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