diff --git a/bin/environ.sh b/bin/environ.sh
index 2c72d98f..0ad4b06b 100644
--- a/bin/environ.sh
+++ b/bin/environ.sh
@@ -42,8 +42,12 @@ timeline_groovy_opts=(
   -Djava.awt.headless=true
 )
 
+# run java with more resources, to mitigate large memory residence for long run periods
+timeline_java_opts_highmem=$(echo ${timeline_java_opts[*]} | sed 's;Xmx.*m;Xmx2048m;')
+
 # exports
 export CLASSPATH="$(echo "${java_classpath[*]}" | sed 's; ;:;g')${CLASSPATH:+:${CLASSPATH}}"
 export JYPATH="$(echo "${groovy_classpath[*]}" | sed 's; ;:;g')${JYPATH:+:${JYPATH}}"
 export TIMELINE_JAVA_OPTS="${timeline_java_opts[*]}"
 export TIMELINE_GROOVY_OPTS="${timeline_groovy_opts[*]}"
+export TIMELINE_JAVA_OPTS_HIGHMEM=$timeline_java_opts_highmem
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/fitter/FTOFFitter.groovy b/detectors/src/main/java/org/jlab/clas/timeline/fitter/FTOFFitter.groovy
index e7326b6f..d4138b98 100644
--- a/detectors/src/main/java/org/jlab/clas/timeline/fitter/FTOFFitter.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/fitter/FTOFFitter.groovy
@@ -31,33 +31,33 @@ class FTOFFitter {
     return f1
   }
 
-	static F1D timefit_p2(H1F h1) {
-	    def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -0.5, 0.5);
-        double hAmp  = h1.getBinContent(h1.getMaximumBin());
-        double hMean = h1.getAxis().getBinCenter(h1.getMaximumBin());
-        double hRMS  = 0.3;//h1.getRMS(); //ns
-        double rangeMin = (hMean - 2.5*hRMS);
-        double rangeMax = (hMean + 2.5*hRMS);
-        f1.setRange(rangeMin, rangeMax);
-        f1.setParameter(0, hAmp);
-        f1.setParameter(1, hMean);
-        f1.setParameter(2, hRMS);
-
-		def makefit = {func->
-		  hMean = func.getParameter(1)
-		  hRMS = func.getParameter(2).abs()
-		  func.setRange(hMean-1.5*hRMS,hMean+1.5*hRMS)
-		  MoreFitter.fit(func,h1,"Q")
-		  return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
-		}
-
-		def fits1 = (0..20).collect{makefit(f1)}
-		def bestfit = fits1.sort()[0]
-		f1.setParameters(*bestfit[1])
-		//makefit(f1)
-		return f1
-	}
 
+  static F1D timefit_p2(H1F h1) {
+    def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -0.5, 0.5);
+    double hAmp  = h1.getBinContent(h1.getMaximumBin());
+    double hMean = h1.getAxis().getBinCenter(h1.getMaximumBin());
+    double hRMS  = 0.3;//h1.getRMS(); //ns
+    double rangeMin = (hMean - 2.5*hRMS);
+    double rangeMax = (hMean + 2.5*hRMS);
+    f1.setRange(rangeMin, rangeMax);
+    f1.setParameter(0, hAmp);
+    f1.setParameter(1, hMean);
+    f1.setParameter(2, hRMS);
+
+    def makefit = {func->
+      hMean = func.getParameter(1)
+      hRMS = func.getParameter(2).abs()
+      func.setRange(hMean-1.5*hRMS,hMean+1.5*hRMS)
+      MoreFitter.fit(func,h1,"Q")
+      return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
+    }
+
+    def fits1 = (0..20).collect{makefit(f1)}
+    def bestfit = fits1.sort()[0]
+    f1.setParameters(*bestfit[1])
+    //makefit(f1)
+    return f1
+  }
 
 
   static F1D tdcadcdifffit_p1a(H1F h1) {
@@ -72,7 +72,6 @@ class FTOFFitter {
     f1.setParameter(1, hMean);
     f1.setParameter(2, hRMS);
 
-
     def makefit = {func->
       hMean = func.getParameter(1)
       hRMS = func.getParameter(2).abs()
@@ -88,6 +87,7 @@ class FTOFFitter {
     return f1
   }
 
+
   static F1D tdcadcdifffit_p1b(H1F h1) {
     def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -1.0, 1.0);
     double hAmp  = h1.getBinContent(h1.getMaximumBin());
@@ -120,19 +120,18 @@ class FTOFFitter {
     def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -1.0, 1.0);
     double hAmp  = h1.getBinContent(h1.getMaximumBin());
     double hMean = h1.getAxis().getBinCenter(h1.getMaximumBin());
-    double hRMS  = h1.getRMS(); //ns
-    double rangeMin = (hMean - 2.5*hRMS);
-    double rangeMax = (hMean + hRMS);
+    double hRMS  = 1.9//h1.getRMS(); //ns
+    double rangeMin = (hMean - 1.5*hRMS);
+    double rangeMax = (hMean + 1.5*hRMS);
     f1.setRange(rangeMin, rangeMax);
     f1.setParameter(0, hAmp);
     f1.setParameter(1, hMean);
     f1.setParameter(2, hRMS);
 
-
     def makefit = {func->
       hMean = func.getParameter(1)
       hRMS = func.getParameter(2).abs()
-      func.setRange(hMean - 1.5*hRMS, hMean + 1.5*hRMS)
+      func.setRange(hMean-1.5*hRMS,hMean+1.5*hRMS)
       MoreFitter.fit(func,h1,"Q")
       return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
     }
@@ -140,7 +139,7 @@ class FTOFFitter {
     def fits1 = (0..20).collect{makefit(f1)}
     def bestfit = fits1.sort()[0]
     f1.setParameters(*bestfit[1])
-    f1.setRange(rangeMin, rangeMax)
+    //makefit(f1)
     return f1
   }
 
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/fitter/MoreFitter.groovy b/detectors/src/main/java/org/jlab/clas/timeline/fitter/MoreFitter.groovy
index ef896f96..fdbd2e06 100644
--- a/detectors/src/main/java/org/jlab/clas/timeline/fitter/MoreFitter.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/fitter/MoreFitter.groovy
@@ -21,42 +21,6 @@ class MoreFitter {
     }
   }
 
-  static F1D gausFit(H1F h1, String opts) {
-    def f1 = new F1D('fit:'+h1.getName(), '[amp]*gaus(x,[mean],[sigma])', 0,1)
-
-    def scale = Math.max(h1.getBinContent(h1.getMaximumBin())/500, 1)
-    def data = (1..<h1.getDataSize(0)).collectMany{[h1.getDataX(it)]*(h1.getBinContent(it)/scale as int)}
-    int nlen = data.size()
-    if(nlen==0) {
-      f1.setParameters(0,h1.getDataX(0),0)
-      return f1
-    }
-
-    def (q1,q2,q3) = [data[nlen/4 as int], data[nlen/2 as int], data[nlen*3/4 as int]]
-    def (x1,x2) = [1, h1.getDataSize(0)-1].collect{h1.getDataX(it)}
-    def norms = [h1.getBinContent(h1.getMaximumBin())]
-    def mus = [h1.getAxis().getBinCenter(h1.getMaximumBin()), h1.getMean(), q2, h1.getDataX(h1.getDataSize(0)/2 as int)]
-    def sigs = [h1.getRMS()/2, (q3-q1)/1.35]
-
-    def makefit = {amp,mu,sig->
-      f1.setParameters(amp,mu,sig)
-      def rng = [mu-2.5*sig, mu+2.5*sig]
-      f1.setRange(*rng)
-      DataFitter.fit(f1,h1,"Q")
-      (amp,mu,sig) = (0..<f1.getNPars()).collect{f1.getParameter(it)}
-      if(mu<x1 || mu>x2 || sig>(x2-x1)) return null
-      return [f1.getChiSquare(), [amp,mu,sig], rng]
-    }
-
-    def fits = [norms,mus,sigs].combinations().findResults{makefit(it)}
-    fits += fits.findResults{makefit(it[1])}
-
-    def best = fits.min{it[0]} ?: [0, [0,x1,x2-x1], [x1,x2]]
-    f1.setParameters(*best[1])
-    f1.setRange(*best[2])
-    return f1
-  }
-
   static F1D fitgaus(H1F h1) {
     def f1 = new F1D('fit:'+h1.getName(), '[amp]*gaus(x,[mean],[sigma])', 0,1)
     f1.setRange(h1.getDataX(0), h1.getDataX(h1.getDataSize(0)-1))
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/run.groovy b/detectors/src/main/java/org/jlab/clas/timeline/run.groovy
index 12daeb91..ec22078b 100644
--- a/detectors/src/main/java/org/jlab/clas/timeline/run.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/run.groovy
@@ -100,9 +100,6 @@ def engines = [
     new ftof.ftof_tdcadc_p1a(),
     new ftof.ftof_tdcadc_p1b(),
     new ftof.ftof_tdcadc_p2(),
-    // new ftof.ftof_tdcadc_p1a_zoomed(),
-    // new ftof.ftof_tdcadc_p1b_zoomed(),
-    // new ftof.ftof_tdcadc_p2_zoomed(),
     new ftof.ftof_ctof_vtdiff(),
     new dc.dc_residuals_sec(),
     new dc.dc_residuals_sec_sl(),
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/run_rgb.groovy b/detectors/src/main/java/org/jlab/clas/timeline/run_rgb.groovy
index 16dfac0d..0c989730 100644
--- a/detectors/src/main/java/org/jlab/clas/timeline/run_rgb.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/run_rgb.groovy
@@ -103,9 +103,6 @@ def engines = [
     new ftof.ftof_tdcadc_p1a(),
     new ftof.ftof_tdcadc_p1b(),
     new ftof.ftof_tdcadc_p2(),
-    // new ftof.ftof_tdcadc_p1a_zoomed(),
-    // new ftof.ftof_tdcadc_p1b_zoomed(),
-    // new ftof.ftof_tdcadc_p2_zoomed(),
     new ftof.ftof_ctof_vtdiff(),
     new dc.dc_residuals_sec(),
     new dc.dc_residuals_sec_sl(),
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/MYQuery.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/MYQuery.groovy
index 8fdae044..bbca9a93 100755
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/MYQuery.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/MYQuery.groovy
@@ -14,6 +14,7 @@ class MYQuery {
     'd': 'on',          // data update events only
     'p': 'on',          // include prior point
     'm': 'history',     // MYA deployment
+    'l': '',            // limit by binning (downsample)
   ]
 
   // timestamps
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/epics_xy.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/epics_xy.groovy
index b65bacf7..875c6d16 100755
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/epics_xy.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/timeline/epics/epics_xy.groovy
@@ -3,6 +3,7 @@ package org.jlab.clas.timeline.timeline.epics
 import java.text.SimpleDateFormat
 import org.jlab.groot.data.TDirectory
 import org.jlab.groot.data.H1F
+import org.jlab.groot.math.F1D
 import org.jlab.groot.data.GraphErrors
 import org.jlab.clas.timeline.fitter.MoreFitter
 
@@ -14,9 +15,49 @@ class epics_xy {
     runlist.push(run)
   }
 
+  static F1D gausFit(H1F h1) { // FIXME: not stable...
+
+    def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -10, 10);
+    double hAmp  = h1.getBinContent(h1.getMaximumBin());
+    double hMean = h1.getAxis().getBinCenter(h1.getMaximumBin());
+    double hRMS  = Math.min(h1.getRMS(),1.0);
+    f1.setRange(hMean-2.0*hRMS, hMean+2.0*hRMS);
+    f1.setParameter(0, hAmp);
+    f1.setParameter(1, hMean);
+    f1.setParameter(2, hRMS);
+
+    def makefit = {func->
+      hMean = func.getParameter(1)
+      hRMS = func.getParameter(2).abs()
+      func.setRange(hMean-2.0*hRMS,hMean+2.0*hRMS)
+      MoreFitter.fit(func,h1,"Q")
+      return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
+    }
+
+    def fits1 = (0..20).collect{makefit(f1)}
+    def bestfit = fits1.sort()[0]
+    f1.setParameters(*bestfit[1])
+    return f1
+
+  }
+
+  static F1D justUseStats(H1F h1) { // no fit, just use mean and RMS from the histogram
+    def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -10, 10);
+    double hAmp  = h1.getBinContent(h1.getMaximumBin());
+    double hMean = h1.getMean()
+    double hRMS  = h1.getRMS()
+    f1.setRange(hMean-2.0*hRMS, hMean+2.0*hRMS);
+    f1.setParameter(0, hAmp);
+    f1.setParameter(1, hMean);
+    f1.setParameter(2, hRMS);
+    return f1
+  }
+
+
   def close() {
 
     def MYQ = new MYQuery()
+    MYQ.querySettings['l'] = "${1000*runlist.size()}" // downsample the payload, since it's too big for a full run period
     def ts = MYQ.getRunTimeStamps(runlist)
 
     def epics = [:].withDefault{[:]}
@@ -69,12 +110,13 @@ class epics_xy {
         hy.fill(it[2], it[0]*it[3]/1000)
       }
 
-      def fx = MoreFitter.gausFit(hx, "Q")
-      def fy = MoreFitter.gausFit(hy, "Q")
+      def fx = justUseStats(hx)
+      def fy = justUseStats(hy)
       grx.addPoint(run, fx.getParameter(1), 0,0)
       gry.addPoint(run, fy.getParameter(1), 0,0)
 
-      [hx,hy,fx,fy].each{out.addDataSet(it)}
+      [hx,hy].each{out.addDataSet(it)}
+      // [fx,fy].each{out.addDataSet(it)}
       println("$run done")
     }
 
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1a.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1a.groovy
index a6c5c698..ab2a7812 100644
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1a.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1a.groovy
@@ -3,6 +3,7 @@ import java.util.concurrent.ConcurrentHashMap
 import org.jlab.groot.data.TDirectory
 import org.jlab.groot.data.GraphErrors
 import org.jlab.clas.timeline.fitter.FTOFFitter
+import org.jlab.clas.timeline.util.HistoUtil
 
 class ftof_tdcadc_p1a {
 
@@ -14,7 +15,7 @@ def processDirectory(dir, run) {
   def sigmalist = []
   def chi2list = []
   def histlist =   (0..<6).collect{
-    def h1 = dir.getObject('/tof/p1a_tdcadc_dt_S'+(it+1))
+    def h1 = HistoUtil.zoomHisto(dir.getObject('/tof/p1a_tdcadc_dt_S'+(it+1)))
     def f1 = FTOFFitter.tdcadcdifffit_p1a(h1)
 
     funclist.add(f1)
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1a_zoomed.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1a_zoomed.groovy
deleted file mode 100644
index 9163bc41..00000000
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1a_zoomed.groovy
+++ /dev/null
@@ -1,80 +0,0 @@
-package org.jlab.clas.timeline.timeline.ftof
-import java.util.concurrent.ConcurrentHashMap
-import org.jlab.groot.data.TDirectory
-import org.jlab.groot.data.GraphErrors
-import org.jlab.clas.timeline.fitter.FTOFFitter
-import org.jlab.groot.data.H1F
-
-class ftof_tdcadc_p1a_zoomed {
-
-def data = new ConcurrentHashMap()
-
-def processDirectory(dir, run) {
-  def funclist = []
-  def meanlist = []
-  def sigmalist = []
-  def chi2list = []
-  def histlist =   (0..<6).collect{
-    def h1 = dir.getObject('/tof/p1a_tdcadc_dt_S'+(it+1))
-    def f1 = FTOFFitter.tdcadcdifffit_p1a(h1)
-    def peak = f1.getParameter(1)
-    def sigma = f1.getParameter(2).abs()
-    def minH = h1.getAxis().min()
-    def maxH = h1.getAxis().max()
-    if (peak>minH && peak<maxH){
-        minH = peak - 2.5*sigma
-        maxH = peak + 2.5*sigma
-        def minBin = h1.getAxis().getBin(minH)
-        def maxBin = h1.getAxis().getBin(maxH)
-        minH = h1.getAxis().getBinCenter(minBin) - h1.getAxis().getBinWidth(0)*0.5
-        maxH = h1.getAxis().getBinCenter(maxBin) + h1.getAxis().getBinWidth(0)*0.5
-        def h2 = new H1F("new_" + h1.getName(), "new_" + h1.getTitle(), maxBin-minBin+1, minH, maxH)
-        (minBin..maxBin).each{
-                h2.setBinContent(it-minBin, h1.getBinContent(it))
-        }   
-        println(h1.getAxis().getBinCenter(h1.getMaximumBin()))
-        println(h2.getAxis().getBinCenter(h2.getMaximumBin()))
-        h1 = h2
-        f1 = FTOFFitter.tdcadcdifffit_p1a(h1)
-    }   
-
-
-    funclist.add(f1)
-    meanlist.add(f1.getParameter(1))
-    sigmalist.add(f1.getParameter(2).abs())
-    chi2list.add(f1.getChiSquare())
-    return h1
-  }
-  data[run] = [run:run, hlist:histlist, flist:funclist, mean:meanlist, sigma:sigmalist, clist:chi2list]
-}
-
-
-
-def close() {
-
-  ['mean', 'sigma'].each{ name ->
-    TDirectory out = new TDirectory()
-    out.mkdir('/timelines')
-    (0..<6).each{ sec->
-      def grtl = new GraphErrors('sec'+(sec+1))
-    grtl.setTitle("p1a t_tdc-t_fadc (" + name +")")
-    grtl.setTitleY("p1a t_tdc-t_fadc (" + name +") (ns)")
-    grtl.setTitleX("run number")
-
-      data.sort{it.key}.each{run,it->
-        if (sec==0){
-          out.mkdir('/'+it.run)
-        }
-        out.cd('/'+it.run)
-        out.addDataSet(it.hlist[sec])
-        out.addDataSet(it.flist[sec])
-        grtl.addPoint(it.run, it[name][sec], 0, 0)
-      }
-      out.cd('/timelines')
-      out.addDataSet(grtl)
-    }
-
-    out.writeFile('ftof_tdcadc_time_p1a_zoomed_' + name + '.hipo')
-  }
-}
-}
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1b.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1b.groovy
index 007ec9d1..7df8f3c3 100644
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1b.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1b.groovy
@@ -3,6 +3,7 @@ import java.util.concurrent.ConcurrentHashMap
 import org.jlab.groot.data.TDirectory
 import org.jlab.groot.data.GraphErrors
 import org.jlab.clas.timeline.fitter.FTOFFitter
+import org.jlab.clas.timeline.util.HistoUtil
 
 class ftof_tdcadc_p1b {
 
@@ -14,7 +15,7 @@ def processDirectory(dir, run) {
   def sigmalist = []
   def chi2list = []
   def histlist =   (0..<6).collect{
-    def h1 = dir.getObject('/tof/p1b_tdcadc_dt_S'+(it+1))
+    def h1 = HistoUtil.zoomHisto(dir.getObject('/tof/p1b_tdcadc_dt_S'+(it+1)))
     def f1 = FTOFFitter.tdcadcdifffit_p1b(h1)
 
     funclist.add(f1)
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1b_zoomed.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1b_zoomed.groovy
deleted file mode 100644
index c57d2fcf..00000000
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p1b_zoomed.groovy
+++ /dev/null
@@ -1,80 +0,0 @@
-package org.jlab.clas.timeline.timeline.ftof
-import java.util.concurrent.ConcurrentHashMap
-import org.jlab.groot.data.TDirectory
-import org.jlab.groot.data.GraphErrors
-import org.jlab.clas.timeline.fitter.FTOFFitter
-import org.jlab.groot.data.H1F
-
-class ftof_tdcadc_p1b_zoomed {
-
-def data = new ConcurrentHashMap()
-
-def processDirectory(dir, run) {
-  def funclist = []
-  def meanlist = []
-  def sigmalist = []
-  def chi2list = []
-  def histlist =   (0..<6).collect{
-    def h1 = dir.getObject('/tof/p1b_tdcadc_dt_S'+(it+1))
-    def f1 = FTOFFitter.tdcadcdifffit_p1b(h1)
-    def peak = f1.getParameter(1)
-    def sigma = f1.getParameter(2).abs()
-    def minH = h1.getAxis().min()
-    def maxH = h1.getAxis().max()
-    if (peak>minH && peak<maxH){
-        minH = peak - 2.5*sigma
-        maxH = peak + 2.5*sigma
-        def minBin = h1.getAxis().getBin(minH)
-        def maxBin = h1.getAxis().getBin(maxH)
-        minH = h1.getAxis().getBinCenter(minBin) - h1.getAxis().getBinWidth(0)*0.5
-        maxH = h1.getAxis().getBinCenter(maxBin) + h1.getAxis().getBinWidth(0)*0.5
-        def h2 = new H1F("new_" + h1.getName(), "new_" + h1.getTitle(), maxBin-minBin+1, minH, maxH)
-        (minBin..maxBin).each{
-                h2.setBinContent(it-minBin, h1.getBinContent(it))
-        }   
-        println(h1.getAxis().getBinCenter(h1.getMaximumBin()))
-        println(h2.getAxis().getBinCenter(h2.getMaximumBin()))
-        h1 = h2
-        f1 = FTOFFitter.tdcadcdifffit_p1a(h1)
-    }   
-
-
-    funclist.add(f1)
-    meanlist.add(f1.getParameter(1))
-    sigmalist.add(f1.getParameter(2).abs())
-    chi2list.add(f1.getChiSquare())
-    return h1
-  }
-  data[run] = [run:run, hlist:histlist, flist:funclist, mean:meanlist, sigma:sigmalist, clist:chi2list]
-}
-
-
-
-def close() {
-
-  ['mean', 'sigma'].each{ name ->
-    TDirectory out = new TDirectory()
-    out.mkdir('/timelines')
-    (0..<6).each{ sec->
-      def grtl = new GraphErrors('sec'+(sec+1))
-    grtl.setTitle("p1b t_tdc-t_fadc (" + name +")")
-    grtl.setTitleY("p1b t_tdc-t_fadc (" + name +") (ns)")
-    grtl.setTitleX("run number")
-
-      data.sort{it.key}.each{run,it->
-        if (sec==0){
-          out.mkdir('/'+it.run)
-        }
-        out.cd('/'+it.run)
-        out.addDataSet(it.hlist[sec])
-        out.addDataSet(it.flist[sec])
-        grtl.addPoint(it.run, it[name][sec], 0, 0)
-      }
-      out.cd('/timelines')
-      out.addDataSet(grtl)
-    }
-
-    out.writeFile('ftof_tdcadc_time_p1b_zoomed_' + name + '.hipo')
-  }
-}
-}
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p2.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p2.groovy
index 8ad98aa0..0d52cae1 100644
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p2.groovy
+++ b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p2.groovy
@@ -3,6 +3,7 @@ import java.util.concurrent.ConcurrentHashMap
 import org.jlab.groot.data.TDirectory
 import org.jlab.groot.data.GraphErrors
 import org.jlab.clas.timeline.fitter.FTOFFitter
+import org.jlab.clas.timeline.util.HistoUtil
 
 class ftof_tdcadc_p2 {
 
@@ -14,7 +15,7 @@ def processDirectory(dir, run) {
   def sigmalist = []
   def chi2list = []
   def histlist =   (0..<6).collect{
-    def h1 = dir.getObject('/tof/p2_tdcadc_dt_S'+(it+1))
+    def h1 = HistoUtil.zoomHisto(dir.getObject('/tof/p2_tdcadc_dt_S'+(it+1)))
     def f1 = FTOFFitter.tdcadcdifffit_p2(h1)
 
     funclist.add(f1)
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p2_zoomed.groovy b/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p2_zoomed.groovy
deleted file mode 100644
index 3b90d321..00000000
--- a/detectors/src/main/java/org/jlab/clas/timeline/timeline/ftof/ftof_tdcadc_p2_zoomed.groovy
+++ /dev/null
@@ -1,84 +0,0 @@
-package org.jlab.clas.timeline.timeline.ftof
-import java.util.concurrent.ConcurrentHashMap
-import org.jlab.groot.data.TDirectory
-import org.jlab.groot.data.GraphErrors
-import org.jlab.clas.timeline.fitter.FTOFFitter
-import org.jlab.groot.data.H1F
-
-class ftof_tdcadc_p2_zoomed {
-
-def data = new ConcurrentHashMap()
-
-def processDirectory(dir, run) {
-  def funclist = []
-  def meanlist = []
-  def sigmalist = []
-  def chi2list = []
-  def histlist =   (0..<6).collect{
-    def h1 = dir.getObject('/tof/p2_tdcadc_dt_S'+(it+1))
-    def f1 = FTOFFitter.tdcadcdifffit_p2(h1)
-    def peak = f1.getParameter(1)
-    def sigma = f1.getParameter(2).abs()
-    def minX = h1.getAxis().min()
-    def maxX = h1.getAxis().max()
-    if (peak>minX && peak<maxX){
-        def minH = peak - 2.5*sigma
-        def maxH = peak + 2.5*sigma
-        if(minH<minX || maxH>maxX || maxH<minH) {
-          minH = h1.getAxis().getBinCenter(h1.getMaximumBin()) - 2.5*h1.getRMS().abs()
-          maxH = h1.getAxis().getBinCenter(h1.getMaximumBin()) + 2.5*h1.getRMS().abs()
-        }
-        def minBin = h1.getAxis().getBin(minH)
-        def maxBin = h1.getAxis().getBin(maxH)
-        minH = h1.getAxis().getBinCenter(minBin) - h1.getAxis().getBinWidth(0)*0.5
-        maxH = h1.getAxis().getBinCenter(maxBin) + h1.getAxis().getBinWidth(0)*0.5
-        def h2 = new H1F("new_" + h1.getName(), "new_" + h1.getTitle(), maxBin-minBin+1, minH, maxH)
-        (minBin..maxBin).each{
-                h2.setBinContent(it-minBin, h1.getBinContent(it))
-        }   
-        println([minBin, maxBin, minH, maxH])
-        println(h1.getAxis().getBinCenter(h1.getMaximumBin()))
-        println(h2.getAxis().getBinCenter(h2.getMaximumBin()))
-        h1 = h2
-        f1 = FTOFFitter.tdcadcdifffit_p1a(h1)
-    }   
-
-    funclist.add(f1)
-    meanlist.add(f1.getParameter(1))
-    sigmalist.add(f1.getParameter(2).abs())
-    chi2list.add(f1.getChiSquare())
-    return h1
-  }
-  data[run] = [run:run, hlist:histlist, flist:funclist, mean:meanlist, sigma:sigmalist, clist:chi2list]
-}
-
-
-
-def close() {
-
-  ['mean', 'sigma'].each{ name ->
-    TDirectory out = new TDirectory()
-    out.mkdir('/timelines')
-    (0..<6).each{ sec->
-      def grtl = new GraphErrors('sec'+(sec+1))
-    grtl.setTitle("p2 t_tdc-t_fadc (" + name +")")
-    grtl.setTitleY("p2 t_tdc-t_fadc (" + name +") (ns)")
-    grtl.setTitleX("run number")
-
-      data.sort{it.key}.each{run,it->
-        if (sec==0){
-          out.mkdir('/'+it.run)
-        }
-        out.cd('/'+it.run)
-        out.addDataSet(it.hlist[sec])
-        out.addDataSet(it.flist[sec])
-        grtl.addPoint(it.run, it[name][sec], 0, 0)
-      }
-      out.cd('/timelines')
-      out.addDataSet(grtl)
-    }
-
-    out.writeFile('ftof_tdcadc_time_p2_zoomed_' + name + '.hipo')
-  }
-}
-}
diff --git a/detectors/src/main/java/org/jlab/clas/timeline/util/HistoUtil.groovy b/detectors/src/main/java/org/jlab/clas/timeline/util/HistoUtil.groovy
new file mode 100644
index 00000000..bf77c728
--- /dev/null
+++ b/detectors/src/main/java/org/jlab/clas/timeline/util/HistoUtil.groovy
@@ -0,0 +1,60 @@
+package org.jlab.clas.timeline.util
+import org.jlab.groot.data.H1F
+
+class HistoUtil {
+
+  /// zoom on the range of filled bins of a histogram
+  /// @param histIn the input histogram
+  /// @param threshold the fraction of the max bin to assume valid data (useful for ignoring long tails)
+  /// @param nBufferBins how many extra bins on each side of the zoomed range
+  static def zoomHisto(H1F histIn, double threshold=0.0, int nBufferBins=3) {
+
+    // read input histogram
+    def nBinsIn = histIn.getXaxis().getNBins()
+    def xData   = (0..<nBinsIn).collect{ histIn.getBinContent(it) }
+    def rangeIn = [ histIn.getXaxis().min(), histIn.getXaxis().max() ]
+    def widthIn = (rangeIn[1]-rangeIn[0]) / nBinsIn
+
+    // check arguments
+    if(threshold<0 || threshold>1 || nBufferBins<0) {
+      throw new Exception("bad arguments for zoomHisto")
+    }
+
+    // find the data range
+    def minVal = xData.max() * threshold
+    def dataBinRange = [
+      [ xData.findIndexOf{ it > minVal } - nBufferBins, 0 ].max(),
+      [ nBinsIn - xData.reverse().findIndexOf{ it > minVal } + nBufferBins, nBinsIn-1].min()
+    ]
+    def rangeOut = dataBinRange.collect{ histIn.getXaxis().getBinCenter(it) }
+    rangeOut[0] -= widthIn / 2
+    rangeOut[1] += widthIn / 2
+    def nBinsOut = dataBinRange[1] - dataBinRange[0] + 1
+    def widthOut = (rangeOut[1]-rangeOut[0]) / nBinsOut
+
+    // print some information, for debugging
+    def printDebug = {
+      System.err.println """
+      histoZoom of histogram '${histIn.getName()}':
+        nBins: ${nBinsIn} -> ${nBinsOut}
+        xMin:  ${rangeIn[0]} -> ${rangeOut[0]}
+        xMax:  ${rangeIn[1]} -> ${rangeOut[1]}
+        binWidth: ${widthIn} -> ${widthOut}
+      """
+    }
+    // printDebug()
+
+    // check that the bin width is correct
+    if((widthIn-widthOut).abs()>0.0001) {
+      printDebug()
+      throw new Exception("bin widths don't match")
+    }
+
+    // define and fill the output, zoomed histogram
+    def histOut = new H1F(histIn.getName(), histIn.getTitle(), nBinsOut, rangeOut[0], rangeOut[1])
+    histOut.setTitleX(histIn.getTitleX())
+    histOut.setTitleY(histIn.getTitleY())
+    nBinsIn.times{ histOut.fill(histIn.getXaxis().getBinCenter(it), histIn.getBinContent(it)) }
+    return histOut
+  }
+}