This document discusses using an exactly solvable hydrodynamic model to study scaling behavior near a phase transition in heavy ion collisions. It proposes using a deformed Gubser solution with azimuthal asymmetries parameterized by dimensionless εn to model initial inhomogeneities. Analytical expressions are derived relating εn, which characterizes the initial geometry, to final state particle distributions like dN/dy and vn. This allows studying how observables change with transport coefficients and other parameters across a phase transition through their scaling behavior.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Solution Manual for Heat Convection second edition by Latif M. Jijiphysicsbook
Solution Manual for Heat Convection
https://unihelp.xyz/solution-manual-for-heat-convection-by-latif-jiji/
****
Solution Manual for Heat Conduction
https://unihelp.xyz/solution-manual-heat-conduction-latif-jiji/
Solution Manual for Heat Convection second edition by Latif M. Jiji
Derivation and solution of the heat equation in 1-DIJESM JOURNAL
Heat flows in the direction of decreasing temperature, that is, from hot to cool. In this paper we derive the heat equation and consider the flow of heat along a metal rod. The rod allows us to consider the temperature, u(x,t), as one dimensional in x but changing in time, t.
Neutral Electronic Excitations: a Many-body approach to the optical absorptio...Claudio Attaccalite
Neutral Electronic Excitations: a Many-body approach to the optical absorption spectra.
Introduction to Bethe-Salpeter equation and linear response theory.
Solution Manual for Heat Convection second edition by Latif M. Jijiphysicsbook
Solution Manual for Heat Convection
https://unihelp.xyz/solution-manual-for-heat-convection-by-latif-jiji/
****
Solution Manual for Heat Conduction
https://unihelp.xyz/solution-manual-heat-conduction-latif-jiji/
Solution Manual for Heat Convection second edition by Latif M. Jiji
Derivation and solution of the heat equation in 1-DIJESM JOURNAL
Heat flows in the direction of decreasing temperature, that is, from hot to cool. In this paper we derive the heat equation and consider the flow of heat along a metal rod. The rod allows us to consider the temperature, u(x,t), as one dimensional in x but changing in time, t.
Neutral Electronic Excitations: a Many-body approach to the optical absorptio...Claudio Attaccalite
Neutral Electronic Excitations: a Many-body approach to the optical absorption spectra.
Introduction to Bethe-Salpeter equation and linear response theory.
Modern Travel and Expense: The Connected Platform [New York]SAP Ariba
Managing employee travel and expenses is no longer just about streamlining processes. With changes in technology and workforce demographics, more and more purchasing power is being pushed directly to employees, decentralizing a once centralized part of the business. As a result, tracking and managing travel and expense is getting harder. An open platform that connects data, applications and people gives organizations and their employees the ability to effortlessly manage travel and expense and provides organizations with total transparency into spending – wherever and whenever it happens.
Will Mayweather-Pacquiao live up to its “Fight of the Century” hype? We used SPECTRUM to measure fan interest compared to last year’s big bouts, as well as marquee events in other pro sports. So far, the welterweight match shows heavyweight buzz.
Taxonomy, ecology, biochemistry and analytical technology of food microorganisms.
Sources of microorganisms in food; distribution, role and significance of microorganisms in foods, intrinsic and extrinsic parameters of foods that affect microbial growth; food spoilage.
Food-borne diseases and fermentations; indices of food sanitary quality and food microbiological standards.
Principles of food preservation: high temperature, low temperature, radiation, pressure, use of additives, drying,
The microbiology of local food stuffs: gari, palm wine, ogi, foofoo etc; microbiology of the dairy industry;
DevOps: Lessons from Manufacturing and Open SourceGordon Haff
Manufacturing has widely adopted standardized and automated processes to create designs, build them, and maintain them through their life cycle. However, many modern manufacturing systems go beyond mechanized workflows to introduce empowered workers, flexible collaboration, and rapid iteration.
Such behaviors also characterize open source software development and are at the heart of DevOps culture, processes, and tooling. In this session, Red Hat’s Gordon Haff will discuss the lessons and processes that DevOps can apply from manufacturing using:
- Container-based platforms designed for modern application development and deployment.
- The ability to design microservices-based applications using modular and reusable parts.
- Iterative development, testing, and deployment using platform-as-a-service and integrated continuous delivery systems.
Talk given at Physics@FOM Veldhoven 2009. Powerpoint source and high-resolution images available upon request.
Journal reference: Phys. Rev. A 77, 023623 (2008) [arXiv:0711.3425]
The time scale Fibonacci sequences satisfy the Friedmann-Lema\^itre-Robertson-Walker (FLRW) dynamic equation on time scale, which are an exact solution of Einstein's field equations of general relativity for an expanding homogeneous and isotropic universe. We show that the equations of motion correspond to the one-dimensional motion of a particle of position $F(t)$ in an inverted harmonic potential. For the dynamic equations on time scale describing the Fibonacci numbers $F(t)$, we present the Lagrangian and Hamiltonian formalism. Identifying these with the equations that describe factor scales, we conclude that for a certain granulation, for both the continuous and the discrete universe, we have the same dynamics.
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International journal of engineering and mathematical modelling vol2 no3_2015_2IJEMM
Mixed nite element approximation of reaction front propagation model in porous media is presented. The model consists of system of reaction-diffusion equations coupled with the equations of motion under the Darcy law. The existence of solution for the semi-discrete problem is established. The stability of the fully-discrete problem is
analyzed. Optimal error estimates are proved for both semi-discrete and fully-discrete approximate schemes.
This presentation is made to provide the overall conceptual knowledge on Chilton Colburn Analogy. It includes basis, importance, assumption, advantages, limitations and applications in addition to the derivation. Make It Useful!
EXPECTED NUMBER OF LEVEL CROSSINGS OF A RANDOM TRIGONOMETRIC POLYNOMIALJournal For Research
Let EN( T; Φ’ , Φ’’ ) denote the average number of real zeros of the random trigonometric polynomial T=Tn( Φ, É )= . In the interval (Φ’, Φ’’). Assuming that ak(É ) are independent random variables identically distributed according to the normal law and that bk = kp (p ≥ 0) are positive constants, we show that EN( T : 0, 2À ) ~ Outside an exceptional set of measure at most (2/ n ) where β = constant S ~ 1, S’ ~ 1. 1991 Mathematics subject classification (amer. Math. Soc.): 60 B 99.
Low rank tensor approximation of probability density and characteristic funct...Alexander Litvinenko
Very often one has to deal with high-dimensional random variables (RVs). A high-dimensional RV can be described by its probability density (\pdf) and/or by the corresponding probability characteristic functions (\pcf), or by a function representation. Here the interest is mainly to compute characterisations like the entropy, or
relations between two distributions, like their Kullback-Leibler divergence, or more general measures such as $f$-divergences,
among others. These are all computed from the \pdf, which is often not available directly, and it is a computational challenge to even represent it in a numerically feasible fashion in case the dimension $d$ is even moderately large. It is an even stronger numerical challenge to then actually compute said characterisations in the high-dimensional case.
In this regard, in order to achieve a computationally feasible task, we propose to represent the density by a high order tensor product, and approximate this in a low-rank format.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Lateral Ventricles.pdf very easy good diagrams comprehensive
Hydrodynamic scaling and analytically solvable models
1. Hydrodynamic scaling in an exactly solvable model
Based on 1407.5952 with Yoshitaka Hatta,Bowen Xiao, Jorge
Noronha
G.Torrieri
2. What we think we know
High pT distributions determined by tomography in dense matter
Low pT distributions determined by hydrodynamics
Missing: A connection of this to a change in the degrees of freedom (onset
of deconfinement): How do opacity, η/s , EoS etc. change at that point?
Hydrodynamics can be used as a tool to connect statistical physics (more
or less understood) to particle distributions
3. A phase transition and/or a cross-over implies scaling violations
η/s~Nc
2
dip
(crossover)
η/s~0.1
−2
Resonances?
Hagedorn
η λ
2
/s~ ~Ln(T)
At T0 ≃ Tc speed of sound experiences a dip (not to 0,as its a cross-over,but
a dip). Above Tc, η/s ∼ N0
c , below Tc, η/s ∼ N2
c . We should expect...
4. life
phase
Initial
T
Initial µ
Phase 2
Phase 1
Data across
1/2
s , A,Npart
Transition/
threshold
Sdydy
dN dN
<N> (Or , ,...)
(Intensive quantities)
v2
An change in v2 as the system goes from the viscous hadron gas regime via
a kink in the speed of sound to the sQGP regime.
6. 140
145
150
155
160
165
170
175
180
185
190
1 10 100 1000
T[MeV]
A
p-p C-C Si-Si Pb-Pb
√ sNN = 17.2 GeV
lots of correlated parameters (Qs, η/s, T0(y), µ0(y),freezeout,... ) Need
3D viscous hydro to investigate interplay between: EoS,η/s,τΠ,transverse
initial conditions,longitudinal initial conditions,pre-existing flow,freeze-out
dynamics, jet showers in-medium, fragmentation outside the medium .... .
No jump clearly seen! In which parameters is the phase transition hiding?
7. The problem!
η/s
Equation of state
Rapidity dependence
Initial flow
"With enough
parameters
you can fit..."
vn from ALICE
fits well with a
NAIVE
model with
5 parameters
We understand the equation of state and hopefully the viscosity from first
principles. But initial conditions and their dependence in energy, and
transport coefficients, and jets, and freezeout... Even when you are trying
to fit lots of data simultaneusly, a model with many correlated parameters
can describe nealry any physical system
8. Some people think that this will always be with us
The system we are studying is so complicated that models with lots of
parameters will always be necessary and well never have a “smoking gun”
link between theory and experiment.
Perhaps, but I would not give up just yet!
9. • By decreasing energy
Tinitial,final decreases, µB increases
Lifetime increases Flow etc has more time to develop
Phases change Intensive parameters change (η/s,,opacity, EoS )
Boost-invariance breaks down (regions at different rapidities talk)
• By decreasing system size (pA at high
√
s is an extreme example)
Tfinal increases, Lifetime decreases
Gradients go up , driving up Knudsen number lmfp/R ≃ η/(sTR)
Thermalization/medium “turns off”
• By varying rapidity Initial density decreases (Phase changes? )
(pA also effectively more ”forward” than AA at central rapidity)
All these need to be compared against intensive variable 1
S
dN
dy ?
10. Buckingam’s theorem (How to do hydro, circa 19th century)
Any quantitative law of nature expressible as a formula
f(x1, x2, ..., xn) = 0
can be expressed as a dimensionless formula
F(π1, π2, ..., πn−k) = 0
where
πi = xλi
i , λi = 0
Widely applied within hydrodynamics in the 19th century: Knudsen’s
number, Reynolds number, Rayleigh’s number, etc.
Since we are varying a whole slew of experimental (y, pT , Npart,
√
s, A) And
theoretical (T, µ, η, s, ˆq, τ0, τlife) parameters it would be nice to represent
heavy ion observables this way
11. This is how hydrodynamics
was done in the 19th
century!!!!
The idea:
when you have a pipe
and you make it
twice as big
does your variable
of interest grow asn
2 ? What is n?
12. s,A,Npart,y
dN/dy,<pT>,vn
η/s,Cs,...
Heavy ion−specific
dimensionless
number "O"
life
phase
Initial
T
Initial µ
Phase 2
Phase 1
Data across
1/2
s , A,Npart
Transition/
threshold
Sdydy
dN dN
<N> (Or , ,...)
(Intensive quantities)
<O>
µ,εT,<R>,life,
So, when you double size (or initial temperature, or whatever) how does
vn, pT , ... change? Given enough variable conditions, a scaling dimensionless
number makes it straight-forward to look for scaling violations
13. “And the theorist says.... Consider a spherical elephant in a vacuum”
η/s
Initial flow
14. The shortest course possible on hydro I:Evolution
The 5 energy momentum conservation equations
∂µTµν
= 0
have 10 unknowns. They can be closed by assuming approximate isotropy
Tµν
= (p + ρ)uµ
uν
+ pgµν
+ η∆µναβ∂α
uβ
+ ζ∆µνα
α ∂βuβ
And thermodynamic equations for p, η, ζ in terms ofρ .
Once closed these equations can be integrated from initial conditions
15. The shortest course possible on hydro I:Freezeout
At a critical condition (here critical T ) the fluid has to convert into particles.
Energy-momentum and entropy conservation, plus ”fast” conversion, force
the Cooper-Frye formula
E
dN
d3p
=
1
pT
dN
dpT dydφ
= pµ
dΣµf(pµ
uµ, T)
If Σµ is the locus of constant T , parametrized by t(x, y, z, T) then
dΣµ = ǫµαβγ dΣα
dx
dΣβ
dy
dΣγ
dz
In this formalism
vn = cos(nφ)
dN
dpT dydφ
dφ
16. A ”semi-realistic” but solvable model: A deformed Gubser solution
Gubser flow includes
Viscosity , finite Knudsen number
Transverse flow with ”Conformal” setup
We add
Inhomogeneities parametrized by dimensionless ǫn
Freeze-out isothermal Cooper-Frye
17. The basic idea Conformal invariance of the solution constrains flow to be,
in addition to the usual Bjorken
u⊥
∼
2τx⊥
L2 + τ2 + x2
⊥
, uz ∼
z
t
plugging this into the Relativistic Navier-Stokes equation gives you
something you can solve
ENS = λT4
NS =
1
τ4
λC4
(cosh ρ)8/3
1 +
η0
9λC
(sinh ρ)3
2F1
3
2
,
7
6
,
5
2
; − sinh2
ρ
4
where
sinh ρ = −
L2
− τ2
+ x2
⊥
2Lτ
NB: issues at ρ ≪ −1 (negative temperature!) Physically this reflects
implicit non-causality of NS limit, see 1307.6130 (Noronha et al) to fix this
18. Not (yet!) the real world:
• Strictly conformal EoS (s ∼ T3
, e ∼ T4
) and viscosity (η ∼ s ≡ η0s )
• Azimuthally symmetric
• Transversely much more uniform than your “average” Glauber
• “Small times”, or temperature becomes negative (Israel-Stewart needed).
Temperature becomes negative (i.e., the solution becomes unphysical)
for
τL
L or x⊥
≫
η
sC
3/2
Where C is an overall normalization constant ∼ dN/dy . NB limitation
of the solution ansatz!
19. Azimuthal asymmetries: The Zhukovsky transform
x → x⊥ +
a2
x⊥
cos (nφ) , y → x⊥ −
a2
x⊥
sin (φ)
In two dimensions this is a conformal transformation, so it transforms a
solution into a solution up to a calculable rescaling up to a volume rescaling.
This can be neglected to O a2
/x2
⊥, τa2
/x3
⊥ (Again, early freezeout )
20. To first order in a/L (i.e., ǫn ≪ 1 ) we get
E ≈
λC4
τ4/3
(2L)8/3
(L2 + x2
⊥)8/3
1 −
η0
2λC
L2
+ x2
⊥
2Lτ
2/3 4
× 1 − 4ǫn 1 +
η0
2λC
L2
+ x2
⊥
2Lτ
2/3
2Lx⊥
L2 + x2
⊥
n
cos nφ ,
Deformation breaks down at τ ≃ L
21. this can be solved for an expression of an isothermal surface, ready for
freeze-out
T3
=
C3
(2L)2
τ(L2 + x2
⊥)2
1 −
η0
2λC
L2
+ x2
⊥
2Lτ
2/3 3
×
1 − 3ǫn 1 +
η0
2λC
L2
+ x2
⊥
2Lτ
2/3
2Lx⊥
L2 + x2
⊥
n
cos nφ ≡
C3
B3
(2L)3
,
C: overall multiplicity. B Lifetime of the system
NB: Need B ≫ 1, so lifetime ≪ L, “early” freezeout w.r.t. size. .
22. Now we are set
f(p) =
dN
pT dpT dydφ
= dσµpµ
exp −
uµpµ
T
1 +
Πµν
pµpν
2(e + P)T2
χ(p)
where
χ(p) = 1, πµν
= (gµα
− uµ
uα
) ∂αuν
, σµ = T3
ǫµναβ
dxν
dT
dxα
dT
dxβ
dT
and
dN
dy
= dpT pT dφf(p), pT = dpT p2
T dφf(p), vn = dpT pT dφf(p) cos (2nφ)
we can analytically map
L, T, ǫn,
η
s
, B ⇔
dN
dy
, pT , vn
24. Expanding linearly in ǫn and pT /(TB3
), In(x) ∼ xn
/2n
n!
J0
1 = 4πmT K1(mT /T )16L3
B3 1 −
κx2
⊥max
64L2 6 +
m2
T
2T 2
K3−K1
K1
−
p2
T
T 2 ,
J0
2 = 4πK0(mT /T )
215L3p2
T
T B9
1
21 − κ
640 12 +
m2
T
T 2
K2−K0
K0
−
p2
T
T 2 ,
δJ1 = 4π
mT
T K1(mT /T )Γ(3n)
Γ(4n)
9·26nL3pn
T
B3(n+1)T n−1
×(n−1) 2(3n+2)
4n+1 − nκ
8(3n−1) 6n + 6 +
m2
T
2T 2
K3−K1
K1
−
p2
T
T 2
δJ2 = 4πK0(mT /T )Γ(3n)
Γ(4n)
9·26nL3pn
T
B3(n+1)T n−1
×2n 6n2−6n−5
4n+1 − (6n2−10n+1)κ
48(3n−1) 6n +
m2
T
T 2
K2−K0
K0
−
p2
T
T 2 ,
δJ3 = 4πK0(mT /T )Γ(3n)
Γ(4n)
9·26nL3pn
T
B3(n+1)T n−1
×2n 1 − (4n−1)κ
48(3n−1) 6n +
m2
T
T 2
K2−K0
K0
−
p2
T
T 2 ,
25. Low pT vn pT /(TB3
) ≪ 1 , but B ≫ 1
vn(pT )
ǫn
=
9(n − 1)
32
Γ(3n)
Γ(4n)
64pT
B3T
n
2(3n + 2)
4n + 1
−
nκ
8(3n − 1)
6n + 9 +
2mT
T
−
p2
T
T2
The v2 and “Knudsen number” for this solution:
vn
ǫ
∼ O
pT
T
n
(1 − K) , K ∼
η
s
L
τ
2/3
A bit different from Gomebaud et al, Lacey et al vn
n ∼ n
T R Sensitivity
to form of solution , Interplay of L, τ
NB: vn(pT ) ∼ pn
T phenomenologically important general prediction
(Depends on azimuthal integral, independent of approxuimations!
26. vn ∼ pn
T : A robust prediction
All it requires is that
vn ∼ dφ cos φ (1 − tf cos(φ) exp [γ (E − vT (φ)pT )]) ∼ In O
pT
T
∼
pT
T
n
This is much more robust than the assumptions of Gubser flow
27. A large momentum region, pT ≫ TB3
is also possible,
In(z) ≈
ez
√
2πz
∼ exp
pT
T
2x⊥(2L)5
B3(x2
⊥ + L2)3
(1 − α) .
The x⊥-integral can be evaluated by doing the saddle point at x∗
⊥ = L/
√
5.
The result is
vn(pT ) ≈
ǫn
2
pT
T
δu∗
⊥0 = ǫn
500pT
27TB3
√
5
3
n−1
n − 1 −
27κ
200
n .
but jet contamination likely. Experimental opportunity to see how scaling
ofvn(pT ) changes with n, pT
∼ pn
T @low pT , ∼ pT @High pT . NB: High, low w.r.t. T×Size/Lifetime≫ 1
28. The role of bulk viscosity
Plugging in the 14-moment correction of the distribution function
δfbulk
feq
=
12T2
m2
12 +
8
T
uµpµ
+
1
T2
(uµpµ
)2 ∇µuµ
T
ζ
S
,
and assuming early time ∂µuµ
∼ 1/τ , we carry these terms to be
δvbulk
n ≈
81
128
128
B3
n
n2
(n − 1)Γ(3n)
Γ(4n)
Γ2 n
2
(3n + 2)2
4(4n + 1)
x2
max
L2
−
3n
3n − 1
B2
ζ
CS
ǫn ,
Shear and bulk viscosity compete with terms which may be of opposite sign
and non-trivial contribution, Confirming the numerical work of Noronha-
Hostler et al
vn
videal
n
− 1 ∼ ±n2 T2
m2
κbulk
,
29. Now we fix K, C, B in terms of bulk obvservables
These are dominated by soft regions, so can calculate
dN
dY
=
1
(2π)2
dpT pT (J0
1 + J0
2 ) ≈
4C3
π
pT ≡
dN
dY
−1
pT dpT
dN
dY dpT
≈
3πT
4
=
3πCB
8L
Therefore
C ∼
dN
dY
1/3
,
1
B3
∼
1
pT
3L3
dN
dY
.
30. As for azimuthal coefficients, these are
vn(pT )
ǫn
1/n
∼
pT
A
3/2
⊥ pT
4
dN
dY
(1−nκ) ,
vn
ǫn
1/n
∼
1
A
3/2
⊥ pT
3
dN
dY
(1−nκ) ,
Note that vn ∼ pn
T robust against assumptions we made, should survive for
realistic scenarios where the “knudsen number” is
κ ∼
B2
C
η
S
∼
A⊥ pT
2
dN/dY
η
S
, , A⊥ ∼ L2
, A
3/2
⊥ ∼ Npart
NB: this is a bit different from Bhalerao et al , as well as GT,1310.3529
v2
ǫ2
∼ f(τ) (const. − O (κ))
31. Plugging in some more empirical formulae
dN
dY
∼ Npart(
√
s)γ
, pT ∼ F
1
N
2/3
part
dN
dY
∼ F N
1/3
part(
√
s)γ
,
where γ ≈ 0.15 in AA collisions and γ ≈ 0.1 in pA and pp collisions, and
F is a rising function of its argument, we get
vn
ǫn
1/n
∼ (
√
s)γ
G N
1/3
part(
√
s)γ
(1−nκ) , κ ∼ H N
1/3
part(
√
s)γ η
S
,
where G(x) = F−3
(x) and H(x) = F2
(x)/x.
32. Flow... the experimental situation
0 10 20 30 40 50 60
pT
-0.5
0
0.5
1
1.5
2
2.5
3
v2
(pT
)/<v2
>
0-10%
10-20%
20-30%
30-40%
40-50%
0 5 10 15 20
pT
(GeV)
-2
0
2
4
6
v2
(pT
)/<v2
>
CMS 0-5%
60-70%
PHENIX 0-10%
50-60%
BRAHMS,NPA 830, 43C (2009)
pT
CMS
1204.1850
CMS
1204.1409
PHENIX PRL98, 162301 (2007)
PHENIX
PRL98:162301,2007
CMS
PRL109 (2012) 022301
NPA830 (2009)
PHOBOS
STAR 1206.5528
Here is what we know experimentally
v2 ≃ ǫ(b, A)F(pT ), v2 ≃ dpT F(pT )f pT , pT y,A,b,
√
s
F(pT ) universal for all energies , f(pT ) tracks mean momentum, ∼ 1
S
dN
dy
This is an experimental statement, as good as the error bars. Very different
from our scaling!
33. knew
this:
for years
and we
Wrong power w.r.t.
vn(pT )
ǫn
1/n
∼
pT
A
3/2
⊥ pT
4
dN
dY
(1−nκ) ,
vn
ǫn
1/n
∼
1
A
3/2
⊥ pT
3
dN
dY
(1−nκ) ,
but since κ ∼ 1
A⊥
dN
dy , it is enough to “naively extrapolate” from B2
∼ O (1)
to B2
∼ O (L/τ). Extra A1/2
power enough for scaling but Need Realistic
hydrodynamics to test this extrapolation
35. LHC vn(pT ) data allows us to test vn ∼ pn
T
a robust prediction, based on In ≃ (z/2)n
/n! , independent of lifetime.
Not bad, not ideal! Can experimentalists constrain this further?
0 1 2 3 4
pT
(GeV)
0
0,5
1
1,5
2
Ratio
v3
(pT
)/v2
(pT
)
v4
(pT
)/v2
(pT
)
v5
(pT
)/v2
(pT
)
0 1 2 3 4
pT
(GeV)
0
0,1
0,2
0,3
0,4
0,5
Ratio
v3
(pT
)/v2
(pT
)
v4
(pT
)/v2
(pT
)
v5
(pT
)/v2
(pT
)
0 1 2 3 4
pT
(GeV)
0
0,5
1
1,5
2
Ratio
v3
(pT
)/v2
(pT
)
v4
(pT
)/v2
(pT
)
v5
(pT
)/v2
(pT
)
Data from ALICE
1105.3865
36. PRL107 032301 (2011)
vn from ALICE
eccentricities from Glauber
model
vn actually fit quite well with Glauber model ǫn , but see my intro... this is
not how one checks this model is realistic
37. What we learned
• A simplified exactly solvable model incorporating vn yields some very
simple scaling patters
– vn(pT ) ∼ pn
T
– vn ∼ A
−3/2
⊥ for early freezeout
– vn(pT ) ∼ pT
−1 dN
dy
– Given a constant η/s , κ ∼ A⊥ pT
2
(dN
dy )−1
– ...
• These scaling patters Can be compared to experiment! provided different
system sizes, energies, rapidities compared! . This way no free
parameters!
What else can we do?
38. More detailed correlations... Mixing between ǫn and ǫ2n
Lets put in two eccentricities
v2n(pT ) ≈
pT
2TB3
10
3
3 √
5
3
2n−1
(2n−1)ǫ2n+
1
2
pT
2TB3
2 10
3
6 √
5
3
2n−2
(n−1)2
For integrated v2 it becomes
v2n → v2n
ǫ2n + O(n2
ǫ2
n)
ǫ2n
Can be tested by finding v3 in terms of centrality
39. More generally
v2n(pT ) ≈
pT
2TB3
10
3
3 √
5
3
2n−1
(2n−1)ǫ2n+
1
2
pT
2TB3
2 10
3
6 √
5
3
2n−2
(n−1)2
together with the definition of the two-particle correlation function
dN
dpT 1dpT 2d(φ1 − φ2)
∼
n
vn (pT 1) vn (pT 2) cos (n (φ1 − φ2))
Predicts a systematic rotation of the reaction plane that can be compared
with data
40. A hydrodynamic outlook
Calculate the same things we had with realistic hydro simulations
• Long life
• Realistic transverse initial conditions
dN/dy
pT
vn
=
... ... ...
... ... ...
... ... ...
η/s,cs,τπ,...
×
Tinitial
L
ǫn
→Npart,A,
√
s
Finding a scaling variable ≡ finding a basis to diagonalize this
41. Should hydrodynamic scaling persist in tomographic regime? NO!
Take, as an initial condition, an elliptical distribution of opaque matter at
a given ǫn , run jets through it and calculate vn . Now increase R while
mantaining ǫn constant.
vn
ǫn tomo
→
Surface
V olume
→ 0,
vn
ǫn hydro
→ constant
Role of “size” totally different in tomo vs hydro regime .
Probe by comparing vn in Cu-Cu vs Au-Au, Pb-Pb vs Ar-Ar collisions of
Same multiplicity!
42. Can we investigate this both quantitatively and generally?
When we study a jet traversing in the medium, we assume
• Fragments outside the medium phadron
T ∼ f(pparton
T )
• Comes from a high-energy parton, T/pT ≪ 1
• Travels in an extended hot medium, (Tτ)−1
≪ 1
When we expand any jet energy loss model, f (pT /T, Tτ) around
T/pT , (Tτ)−1
43. The ABC-model!
dE
dx
= κpa
Tb
τc
+ O
T
pT
,
1
Tτ
A phenomenological way of keeping track of every jet energy loss model:
c = 0 Bethe Heitler
c = 1 LPM
c > 2 AdS/CFT “falling string”
Conformal invariance, weakly or strongly coupled, implies a + b − c = 2
44. Embed ABC model in Gubser solution
And calculate v2(pT ≫ ΛQCD) as a function of pT , L, T .
0 10 20 30 40 50 60
pT
-0.5
0
0.5
1
1.5
2
2.5
3
v2
(pT
)/<v2
>
0-10%
10-20%
20-30%
30-40%
40-50%
0 5 10 15 20
pT
(GeV)
-2
0
2
4
6
v2
(pT
)/<v2
>
CMS 0-5%
60-70%
PHENIX 0-10%
50-60%
CMS
1204.1850
CMS
1204.1409
PHENIX PRL98, 162301 (2007)
v2 at low and high pT look remarkably similar.
45. Conclusions: heavy ions beyond fitting
Choose observable O and your favorite theory, try to determine a, b, c, ...
O ≃ La dN
dy
b
ǫc
n...
compare a,b,c with all experimental data
We did this with a highly simplified analytically solvable hydro model .
Calculations fro ”real” hydro and tomography also possible.