• John
  • Felde
  • University of Maryland
  • USA

Latest Posts

  • USA

Latest Posts

  • Flip
  • Tanedo
  • USA

Latest Posts

  • CERN
  • Geneva
  • Switzerland

Latest Posts

  • Aidan
  • Randle-Conde
  • Université Libre de Bruxelles
  • Belgium

Latest Posts

  • Laura
  • Gladstone
  • University of Wisconsin, Madison
  • USA

Latest Posts

  • Richard
  • Ruiz
  • Univ. of Pittsburgh
  • U.S.A.

Latest Posts

  • Seth
  • Zenz
  • Imperial College London
  • UK

Latest Posts

  • Michael
  • DuVernois
  • Wisconsin IceCube Particle Astrophysics Center
  • USA

Latest Posts

  • Jim
  • Rohlf
  • USA

Latest Posts

  • Emily
  • Thompson
  • Switzerland

Latest Posts

  • Ken
  • Bloom
  • USA

Latest Posts

Andrew Adare | USLHC | USA

View Blog | Read Bio

Finding structure in hadronic collisions

When you see event displays from head-on lead-lead collisions like this one,

you might be skeptical that we can learn much of anything about the quark-gluon plasma from such a dense profusion of tracks. And the skepticism is justifiable: getting at the physics of the strong interaction by studying individual events is a hard problem. Fortunately, hundreds or thousands of events like this can be collected each second during the November LHC heavy-ion running period. ALICE recorded tens of millions of collisions last year, and armed with the power of certain statistical techniques, we find patterns that would never clearly emerge from direct examination of individual events.

When the quarks or gluons within nucleons are scattered off one another at high energies, QCD confinement causes the outgoing particles fragment into di-jets, as explained nicely by Brian Dorney in this entry. In proton-proton collisions, the picture is fairly clear: events where a hard scattering occurs tend to show up in the detector with a characteristic back-to-back signature (again from Brian’s entry). Now consider a central (i.e. head-on) collision between two lead nuclei, each with 208 nucleons, at an energy of several TeV. What happens to the di-jets then? Can you just scale up the number of jet fragments from a proton-proton collision by the number of binary \((2 \to 2)\) collisions that occurred?

This in fact serves as our naive baseline expectation for \(R_{AA}\), the quintessential heavy-ion observable. This is the ratio of the yield from nuclear collisions to that from binary-scaled proton-proton collisions. If \(R_{AA} = 1\), either nuclear collisions behave like a superposition of independent hard scatterings, or multiple effects are canceling each other just right to make it look that way.

But since RHIC started up more than ten years ago, we have seen that \(R_{AA}\) is not 1; it’s more like 1/5 for the hadronic fragments we measure at a few GeV/c. That answer hasn’t changed much at the LHC, although we are learning more about what’s happening with the higher-momentum jet fragments. So there’s a big suppression of particles compared to the independent superposition expectation. What does it mean? The conventional interpretation is that the outgoing particles are losing energy in the nuclear material; the jets are being “quenched” like bullets passing through water. See this recent Courier article for a bit more info.

\(R_{AA}\) is an important result, but it can be complicated to interpret because it reflects a combination of several things: there’s the initial hard-scattering cross-section, the interaction between the outgoing partons and the highly dynamic nuclear medium, and the subsequent (or contempoaneous?) jet fragmentation. The theorists have to make assumptions to model the situation, and unfortunately, many different physical pictures lead to equally good matches with the data.

One step towards a more specific measurement is to systematically pair up particles within each event, accumulating over many events a well-populated distribution of angles between their momentum vectors. We correlate a set of “trigger” particles belonging within a specific transverse momentum \((p_T)\) range, say 8-10 GeV, with a set of “associated” or “partner” particles in another \((p_T)\) range.

These two-particle correlation functions contain rich information about the underlying physics, especially when we compare correlations from proton-proton vs. nucleus-nucleus collisions. For example, in p+p collisions, particles clump together azimuthally near 0 and 180 degrees because of di-jets.

In Pb+Pb collisions, we see similar features, depending on the momentum of the particles we look at, but the situation becomes more complicated as we throw new effects into the mix: jet quenching, hydrodynamics, and fluctuations. These are the things that hold keys to the physics we are interested in. In the next post we will explore further how the picture is changed when we correlate particles from Pb+Pb collisions.


5 Responses to “Finding structure in hadronic collisions”

  1. Thanks for the pingback

  2. It seems to me that the collision of iron protons would yeild more of what the lhc is looking for.
    It is logical that the iron proton is far more symetrical than gold, as a field can be spun up and sustained under its own properties. The iron cyrstal is a reflection of the atom, which is a reflection of the neucleus, which a reflection of the particle arrangement. Why does iron sing?

  3. (N+) + (S -) = 0
    E=MC squared
    Number set = decimal
    XYZ 3 axis grid

    (N+) + (S+) = 2 N=S
    E=MC squared Divided by 2 = 1
    Number set = All even positve numbers in base 16. 1=2
    RSTU V 1 axis grid 4 clock points on 1 line V V = velocity/time/energy
    (I dont know what to call it)

    ————– = 1

    What can you engineer with the smallest number of parts? 8

  4. +N + -S = 0
    E = MCsquared = 1
    all positive and negative numbers in the base 10

    N = S
    +N + +S = 2
    E = MCsquared divided by 2 = 1
    All positive even numbers in the base 16 1 = 2


Leave a Reply

Commenting Policy