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CFT project genome Slava Rychkov / Paris CERN ENS ERG Trieste 2016 , Critical state mum 12 G vs y This talk D= 3 TIMELINE 1970 's period ancient Grillo Gatto Mack Polyakov Ferrara ; ; , , foundations formal


slide-1
SLIDE 1

CFT

genome

project

Slava Rychkov CERN / ENS Paris ERG 2016 , Trieste
slide-2
SLIDE 2 Critical state mum 12 G vs

y This talk D= 3
slide-3
SLIDE 3 TIMELINE 1970 's ancient period Polyakov ; Ferrara , Gatto , Grillo ; Mack formal foundations 2008 . modern period [ Rattazzi , Rychkov , Tonni , Vichi ] 2014-16 most impressive d=3 results 2016
  • Simons
Collaboration
  • n
the Non . Perturbation Bootstrap
slide-4
SLIDE 4 Why a new approach ? Reas= Practical guy Existing approaches not Vsatisfactoz * RG great

qualitative

, but has limitations as a quantitative tool * Simulations expensive ,
  • ften
inconclusive
slide-5
SLIDE 5 Example I v in

r y Exp : v= 0.67094 ) [ Lipa et al , 2003 ] MCTHT : v= 0.6717 ( i ) [Campos trim ' et al , 2006 ] 85 discrepancy
slide-6
SLIDE 6 EXI Cubic anisotropy in Heisenberg

YID.ge#EEI

? play by

. y d)
  • relevant
? D= 2.991 ( 4) <3 [ Calabrese , Pelissetto , @ 25 level Vicari 2003 ] Other studies [ Tissier et al 2001 ] indicate 1>3
slide-7
SLIDE 7 EXT QED } with Ng massless fermions CFT for NGZNF

't

? [ Gukov 1608 ]
slide-8
SLIDE 8 "RG is a human-made thing. It's a smart way to calculate, but it does not have a breathtaking quality of, say, Dirac equation." [Polyakov] Why a new approach ?

Reas=2

conceptual Critical behavior is universal But : RG introduces nomuniversal structure in the intermediate steps Need a manifestly universal approach to criticality
  • (
F 'T
slide-9
SLIDE 9 Why conformal ? Rotation invariance + Scale invariance } conformal
  • invariance
+ ^

Locality

)

generically

, e.g. in presence
  • f

interactions

( all Known counterexamples are gaussian )
slide-10
SLIDE 10 What is a CFT ?
  • a
list
  • f
local
  • perators
{ Ante ) , Azfu ) , A }fe ) . .
  • }
generally infinite
  • whose
correlates < Aetna ) . . . . > have conformal invariance
slide-11
SLIDE 11

Conformal

transformations x→ Fca ) preserve angles . In Zd z→f(z ) x
  • dim
. In d >2 finite dim . rotations translations D dilatation Kpn stfmqd Koiiwersionofn . transf . inversion
slide-12
SLIDE 12 Local
  • perators
Aik ) characterized by
  • spin
l ( scalar , vector , 2- tensor i under SO (d) ) iii
  • scaling
dimension

*

related to critical exponents

Afp

~

Yndi

E.g.

( Aik

) AJCY

)7~

k¥+1

.
slide-13
SLIDE 13 Monte Carlo Bootstrap 0.51808 0.51810 0.51812 0.51814 0.51816 0.51818 Δσ 1.4125 1.4126 1.4127 1.4128 1.4129 1.4130 Δϵ Ising: Scaling Dimensions 0.518146 0.518148 0.518150 0.518152 1.41260 1.41261 1.41262 1.41263 1.41264 1.41265 magnitude ✏. The result is a new d (∆, ∆✏) = (0.5181489(10), 1.412625(10)), nations of the leading OPE coefficients ( [ Kos , Poland ,

Aqq£f>V

  • Simmons
  • Duffin
, Vichi , 1603.04436 ]

x

t
  • Ds←z
  • rigor
  • userrorba=
  • factor
25-50 better than best MC [ Hasenbusk ] 2010
  • factor
  • 1000
better than best compatible RG Guida , Zinn . Justin 98]
slide-14
SLIDE 14 CFT magic 2- pt is

diagonal

and

fixed

imam

Aicx

)Ajly#E

;

Elie

x-yl2=}

Ie (a) = Known spin
  • dependent
tensor structure Io =L In = fur
  • 2=:k2
. .
slide-15
SLIDE 15

OPT

( Ae 1

OD

Auln ) A 3 ( ns ) . . .

>

=

¥fnak

[Art

) + # nmfu Arlo )

¥+12

.

Dv¥=

amnu you Arlo )

/

fixedif

"!¥rmd

symmetry OPE coefficient
slide-16
SLIDE 16 OPE : n
  • pt
functions

tu

pt functions t 2
  • pit
  • '
functions ( fixed )
If we know all

(

Ii , li ) , Cijk can compute au

}F'jaµdr*#

slide-17
SLIDE 17 From CFT

point

  • f
view , Cojk are

just

as fundamental as Di . While in RG they are rarely discussed ( and hard to compute ) Bootstrap for 3d Ising : C ogq = 1.0518537141 ) affirm , ... ,

µ¥Eee

( qqq I f. 53243549 ) Ceee=k [ Kos , Poland , Simmons . D
slide-18
SLIDE 18 OPE

convergence

ii

"
  • ne

:o)

Thm : 1 . OPE converges
  • 2.
Error from
  • mitting
Dade
  • ps
is

<~(Yf)D*

[ Pappadopulo , Ryehbov, Espn , Ruttazti , 2012 ]
slide-19
SLIDE 19 OPE convergence = low
  • energy

/

high . energy decoupling low energy ←> low D high energy a high D
slide-20
SLIDE 20 Not

every

set
  • f
Cftdata

( Di

.li )

,

Cijk

define

a consistent CFT
slide-21
SLIDE 21 OPE associating .

(

Ai Aj

)

An

=

AICAJAK

) WW 4 consistency condition
  • n
CFT data
slide-22
SLIDE 22 Bootstrap eqn for 4pt
  • fu
. Al Ay 1 y
  • @

Zo¥Te{

= -2¥ " Crossing "

=

Az As z 3 NB : Not Feynman diagrams Roughly

?

Gzkc }yk( . . . ) =

[

CMKCZ }k( . " ) If imposed for all 4ft fns equivalent to OPE associatively
slide-23
SLIDE 23
  • Bootstrap
egns first formulated in 70 's . Non
  • pertrbative
, manifestly universal , mathematically well
  • def 'd
( convergent )
  • N
eafns for a unknowns
  • [ Belavin
, Polyakov , Zamolodohikov 1 83 ] : In D= 2 in some cases finitely many variables ( minimal models ) can solve analytically
  • 2008
  • progress
in d >z

numerical

techniques
slide-24
SLIDE 24 What we can do .) construct approximate solutions to the bootstrap eqns arbitrary requested accuracy , say 10-100
  • )
prove , numerically but rigorously , that sometimes solution does not exist rule
  • ut
chunks
  • f
CFT parameter space
slide-25
SLIDE 25 Bootstrap

analysis

  • f
3d Ising CFT

÷

2 global symmetry
  • ne
relevant zz
  • dd
  • 6
C y )
  • ne
relevant zz
  • even
  • Ee
( qy
  • robust
experimental fact first A priori , it makes sense

tovctassify

C FT with small number
  • f
relevant
  • ps
.

÷

slide-26
SLIDE 26 a irrel . ( 44 6×5=1 + { + E ' + . . . 1l=o )

+Tµ+

In 't ... e=z + l=9 , 6 , . . . E x { = same
  • ps
( but different OPE ueffs ) girrel . ( ys) Ox E = 5 + 5 ' + . . .

l÷0

+ l
  • 4,2
, 3,9 , .
  • .
slide-27
SLIDE 27 OPE weffs . are symmetric ; 5×5 Core
  • E
" { x 5 > C
  • er
' J Ward

identity

fixes OPE weffoftuv : 0×0 > Coot

In

Coot

=

Ct central charge
slide-28
SLIDE 28

Unitarily

(

reflection positivity ) ⇒

Cijnek

Di 7

Dmiulli

)

( unitarily bounds ) E.g. beat

De > . > ltd
  • 2
Applies to most interesting models
slide-29
SLIDE 29

Workflow

al ; determine dim 's
  • f
a few low
  • lying
  • perators
& their relative OPE coeffs ( low CFT data ) E.g. 5 , E , 5 ' , E ' for the 3d

Isiy

slide-30
SLIDE 30 / . Pick a few Ypt functions involving
  • ps
.
  • f
interest as Jemal
  • r
internal ( exchanged ) E.g. for 3d Ising can look at cross >
  • r
{ cross > < rE{o> CEEEE > } The more the better
slide-31
SLIDE 31 2. Consider OPE expansion
  • f
these 4pt functions :

? >€=

low + high 3 . For low CFT data fixed , can we find high
  • perators
( and their OPE wefts ) so that conf . bootstrap egs for selected Gpt fus are satisfied ?
slide-32
SLIDE 32 Monte Carlo Bootstrap 0.51808 0.51810 0.51812 0.51814 0.51816 0.51818 Δσ 1.4125 1.4126 1.4127 1.4128 1.4129 1.4130 Δϵ Ising: Scaling Dimensions 0.518146 0.518148 0.518150 0.518152 1.41260 1.41261 1.41262 1.41263 1.41264 1.41265 magnitude ✏. The result is a new d (∆, ∆✏) = (0.5181489(10), 1.412625(10)), nations of the leading OPE coefficients ( for every point
  • utside
shaded region , we can show that there is no solution
slide-33
SLIDE 33 IS this

surprising

?
  • Exclusions
follow from positivity . Once low
  • ops
violate crossing by a " positive " amount , high
  • ps
cannot undo this Role
  • f
algorithm
  • identify
" positive " directions Linear programming Semi
  • definite
programming
slide-34
SLIDE 34 BUT : surprising that get very strong constraints from just a handful
  • f
Gpt functions . Why ?
  • pen
problem .
slide-35
SLIDE 35 Monte Carlo Bootstrap 0.51808 0.51810 0.51812 0.51814 0.51816 0.51818 Δσ 1.4125 1.4126 1.4127 1.4128 1.4129 1.4130 Δϵ Ising: Scaling Dimensions 0.518146 0.518148 0.518150 0.518152 1.41260 1.41261 1.41262 1.41263 1.41264 1.41265 magnitude ✏. The result is a new d (∆, ∆✏) = (0.5181489(10), 1.412625(10)), nations of the leading OPE coefficients ( and

just

;bbi°n

we can find it ( same

algorithm)

slide-36
SLIDE 36

%

ceeazdsiyeinmeenaaatt

¥

leading irrelevant Zz .
  • dd
uncertainties
  • n
dims . & OPE weffs from varying in the allowed region [ of . Komargodski , Simmons
  • Duffin
2016 ]
slide-37
SLIDE 37 Precision improvement
  • ur
results get more precise with time . WHY ? physical 1 . We add

morehtwnstraiuts

. E.g. three Ypt functions instead
  • f
  • ne
, etc. 2 . Even for a single 4pt function , conformal bootstrap is a funclionalequation ( has to be satisfied for any xe ,xz,x3 , >cs ) so many constraints ,
  • f
which we use larger and larger subsets
slide-38
SLIDE 38 So ,

Ising

  • 3
is in good shape What next ? Same method can be

applied

to
  • ther
universality classes with a small number
  • f
relevant
  • ps
. a 01N ) * Gross
  • Neveu
(
  • i
This work has already started
slide-39
SLIDE 39 Dopa OCN)ar=iphg

Bi

shot [ Kos , Poland , Simmons . Duffin , Vichi , 2015 ]
slide-40
SLIDE 40 0 ( 2) : 86 V discrepancy
  • ¢2←>VBtd
H [ Campostrineeal ] t f. Lthspipaetoy

eaD¢

rigorous bootstrap islands [ Kos , Poland , Simmons
  • Duffin
, Vichi , 2016 ]
slide-41
SLIDE 41

CFTgenomef.ro#

Determine CFT data
  • f
low
  • D
  • perators
  • f
all consistent CFTS with a small number
  • f
relevant
  • ps
. Expect a revolution in 3d critical phenomena within next 5 years