From f4046b1106937531cf2b034f550f311087b4ff82 Mon Sep 17 00:00:00 2001
From: Jaron Kent-Dobias <jaron@kent-dobias.com>
Date: Wed, 24 Mar 2021 16:00:04 +0100
Subject: Paragraph massaging.

---
 bezout.tex | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

(limited to 'bezout.tex')

diff --git a/bezout.tex b/bezout.tex
index ca0475c..151ea2a 100644
--- a/bezout.tex
+++ b/bezout.tex
@@ -88,17 +88,17 @@ sign problem \cite{Cristoforetti_2012_New, Tanizaki_2017_Gradient,
 Scorzato_2016_The}.  In order to do this correctly, features of landscape of
 the action in complex space---such as the relative position of saddles and the
 existence of Stokes lines joining them---must be understood.  This is typically
-done for simple actions with few critical points, or with a target
-phenomenology that possesses symmetries that restrict the set of critical
+done for simple actions with few critical points, or for a target
+phenomenology with symmetries that restrict the set of critical
 points to few candidates. Given the recent proliferation of `glassiness' in
 condensed matter and high energy physics, it is inevitable that someone will
-study a complex landscape with these methods, and will find old heuristic
-approaches unsuitable. Such landscapes may in general not be random: here we
+want to apply these methods to a system with a complex landscape, and will find
+they cannot use approaches that rely on such assumptions. Their landscape may not be random: here we
 follow the standard strategy of computer science by understanding the generic
 features of random instances of a simple case, expecting that this sheds light
-on practical, nonrandom problems. While in this paper we do not address
-analytic continuation of configuration space integrals, understanding the
-distribution and spectra of critical points is an essential first step.
+on practical, nonrandom problems. While in this paper we do not yet address
+analytic continuation of integrals, understanding the distribution and spectra
+of critical points is an essential first step.
 
 Returning to our problem, the spherical constraint is enforced using the method
 of Lagrange multipliers: introducing $\epsilon\in\mathbb C$, our constrained
-- 
cgit v1.2.3-54-g00ecf

