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Double-jump phase transition for the reverse Littlewood--Offord problem

Lawrence Hollom, Julien Portier, Victor Souza

TL;DR

This work advances the reverse Littlewood–Offord problem in the plane by showing that Erdős’ conjecture fails for odd $n$ via explicit constructions yielding $P( orm{oldsymbol{\sigma}}_2\,m{ obreakf ext{/≤}1)=O(n^{-3/2})$, while an approximate version at radius $1+ ext{δ}$ remains of order $1/n$. It also proves a tight exponential lower bound $P( orm{oldsymbol{\sigma}}_2\\le 1)\ge c(δ)^{n}$ and demonstrates a double-jump phenomenon at $r=1$, alongside refined results on optimal vector configurations (orthogonal, simplicial, mixed) that shape the lower bounds. The paper extends to higher dimensions, providing dimension-specific constructions and showing that simplicial and mixed configurations can outperform orthogonal ones, with parity playing a crucial role in the asymptotics. These results shed light on the intricate geometry of random signed sums, offer new thresholds and constructions, and open several directions for higher-dimensional and quantitative discrepancy questions with potential implications for related probabilistic and geometric problems.

Abstract

Erdős conjectured in 1945 that for any unit vectors $v_1, \dotsc, v_n$ in $\mathbb{R}^2$ and signs $\varepsilon_1, \dotsc, \varepsilon_n$ taken independently and uniformly in $\{-1,1\}$, the random Rademacher sum $σ= \varepsilon_1 v_1 + \dotsb + \varepsilon_n v_n$ satisfies $\|σ\|_2 \leq 1$ with probability $Ω(1/n)$. While this conjecture is false for even $n$, Beck has proved that $\|σ\|_2 \leq \sqrt{2}$ always holds with probability $Ω(1/n)$. Recently, He, Juškevičius, Narayanan, and Spiro conjectured that the Erdős' conjecture holds when $n$ is odd. We disprove this conjecture by exhibiting vectors $v_1, \dotsc, v_n$ for which $\|σ\|_2 \leq 1$ occurs with probability $O(1/n^{3/2})$. On the other hand, an approximated version of their conjecture holds: we show that we always have $\|σ\|_2 \leq 1 + δ$ with probability $Ω_δ(1/n)$, for all $δ> 0$. This shows that when $n$ is odd, the minimum probability that $\|σ\|_2 \leq r$ exhibits a double-jump phase transition at $r = 1$, as we can also show that $\|σ\|_2 \leq 1$ occurs with probability at least $Ω((1/2+μ)^n)$ for some $μ> 0$. Additionally, and using a different construction, we give a negative answer to a question of Beck and two other questions of He, Juškevičius, Narayanan, and Spiro, concerning the optimal constructions minimising the probability that $\|σ\|_2 \leq \sqrt{2}$. We also make some progress on the higher dimensional versions of these questions.

Double-jump phase transition for the reverse Littlewood--Offord problem

TL;DR

This work advances the reverse Littlewood–Offord problem in the plane by showing that Erdős’ conjecture fails for odd via explicit constructions yielding , while an approximate version at radius remains of order . It also proves a tight exponential lower bound and demonstrates a double-jump phenomenon at , alongside refined results on optimal vector configurations (orthogonal, simplicial, mixed) that shape the lower bounds. The paper extends to higher dimensions, providing dimension-specific constructions and showing that simplicial and mixed configurations can outperform orthogonal ones, with parity playing a crucial role in the asymptotics. These results shed light on the intricate geometry of random signed sums, offer new thresholds and constructions, and open several directions for higher-dimensional and quantitative discrepancy questions with potential implications for related probabilistic and geometric problems.

Abstract

Erdős conjectured in 1945 that for any unit vectors in and signs taken independently and uniformly in , the random Rademacher sum satisfies with probability . While this conjecture is false for even , Beck has proved that always holds with probability . Recently, He, Juškevičius, Narayanan, and Spiro conjectured that the Erdős' conjecture holds when is odd. We disprove this conjecture by exhibiting vectors for which occurs with probability . On the other hand, an approximated version of their conjecture holds: we show that we always have with probability , for all . This shows that when is odd, the minimum probability that exhibits a double-jump phase transition at , as we can also show that occurs with probability at least for some . Additionally, and using a different construction, we give a negative answer to a question of Beck and two other questions of He, Juškevičius, Narayanan, and Spiro, concerning the optimal constructions minimising the probability that . We also make some progress on the higher dimensional versions of these questions.

Paper Structure

This paper contains 16 sections, 30 theorems, 186 equations, 3 figures.

Key Result

Theorem 1.2

For any $d \geq 1$, there is a constant $c_d >0$ depending only on $d$ such that the following holds. Let $v_1, \dotsc, v_n$ be vectors in $\mathbb{R}^d$ with $\norm{v_i}_2 \leq 1$ for each $1 \leq i \leq n$. If $\varepsilon_1, \dotsc, \varepsilon_n$ are independent Rademacher random variables, then

Figures (3)

  • Figure 1: On the left, polygon $P$ with each term of the sum $u = v_1 - v_2 + v_3 - \dotsb + v_n$ highlighted. The linear span $U$ of the vector $u$ intersects the boundary of $P$ on $b$ and $-b$. In the middle, the (oblique) projections $\pi_U(\pm a_i)$ into $U$ are shown to pack in the segment $[-b,b]$. On the right, rotate so $U$ aligns with $x$-axis, reflect and relabel vectors so they are on the right half of the plane.
  • Figure 2: The pairings involved in the characterisations of the case $\beta = -1$ (left) and the case $\beta = 1$ (right).
  • Figure 3: The $\normstar{}$-ball of radius $\sqrt{1 - \abs{\beta}}$ centred at $u = (\beta,0)$ is fully contained in the unit $\norm{}_2$-ball centred at the origin.

Theorems & Definitions (71)

  • Conjecture 1.1: Erdős
  • Theorem 1.2: Beck
  • Conjecture 1.3: He, Juškevičius, Narayanan, and Spiro
  • Theorem 1.4
  • Theorem 1.5: Swanepoel
  • Theorem 1.6
  • Theorem 1.7
  • Theorem 1.8
  • Conjecture 1.11: Conjecture 4.3 in He2024-cp
  • Theorem 1.12
  • ...and 61 more