Variational quantum eigensolver for causal loop Feynman diagrams and directed acyclic graphs Giuseppe Clemente1Arianna Crippa1Karl Jansen1Selomit Ram ırez-Uribe2 3 4 Andr es

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Variational quantum eigensolver for causal loop Feynman diagrams and directed acyclic
graphs
Giuseppe Clemente,
1,
Arianna Crippa,
1,
Karl Jansen,
1,
Selomit Ram´ırez-Uribe,
2, 3, 4, §
Andr´es
E. Renter´ıa-Olivo,
2,
Germ´an Rodrigo,
2, ∗∗
German F. R. Sborlini,
5, 6, ††
and Luiz Vale Silva
2, ‡‡
1
Deutsches Elektronen-Synchrotron DESY, Platanenallee 6, 15738 Zeuthen, Germany.
2
Instituto de F´ısica Corpuscular, Universitat de Val`encia – Consejo Superior de Investigaciones Cient´ıficas,
Parc Cient´ıfic, E-46980 Paterna, Valencia, Spain.
3
Facultad de Ciencias F´ısico-Matem´aticas, Universidad Aut´onoma de Sinaloa,
Ciudad Universitaria, CP 80000 Culiac´an, Mexico.
4
Facultad de Ciencias de la Tierra y el Espacio, Universidad Aut´onoma de Sinaloa,
Ciudad Universitaria, CP 80000 Culiac´an, Mexico.
5
Departamento de F´ısica Fundamental e IUFFyM,
Universidad de Salamanca, 37008 Salamanca, Spain.
6
Escuela de Ciencias, Ingenier´ıa y Dise˜no, Universidad Europea de Valencia,
Paseo de la Alameda 7, 46010 Valencia, Spain.
We present a variational quantum eigensolver (VQE) algorithm for the efficient bootstrapping
of the causal representation of multiloop Feynman diagrams in the Loop-Tree Duality (LTD) or,
equivalently, the selection of acyclic configurations in directed graphs. A loop Hamiltonian based on
the adjacency matrix describing a multiloop topology, and whose different energy levels correspond
to the number of cycles, is minimized by VQE to identify the causal or acyclic configurations. The
algorithm has been adapted to select multiple degenerated minima and thus achieves higher detection
rates. A performance comparison with a Grover’s based algorithm is discussed in detail. The VQE
approach requires, in general, fewer qubits and shorter circuits for its implementation, albeit with
lesser success rates.
I. INTRODUCTION
In recent years, there has been a tremendous progress in
achieving highly-precise theoretical predictions for particle
colliders, which has been possible because of the develop-
ment of new techniques in Quantum Field Theories (QFT)
as well as improved (classical) hardware. For instance,
from the theory point of view, the calculation of multi-
loop scattering amplitudes and Feynman integrals was
optimized by applying different sophisticated techniques.
Some of these theoretical advancements include Mellin-
Barnes transformations [
1
5
], algebraic reduction of in-
tegrands [
6
13
], integration-by-parts identities [
14
,
15
],
contour deformation assisted by neural networks [
16
] and
sector decomposition [
17
20
], among several other highly
efficient methods
1
. Special emphasis was recently put
in the development of four dimensional methods [
21
23
],
with the purpose of achieving a seamless combination of
algebraic/analytic strategies and numerical integration
directly in the four physical dimensions of the space-time.
Electronic address: giuseppe.clemente@desy.de
Electronic address: arianna.crippa@desy.de
Electronic address: karl.jansen@desy.de
§Electronic address: selomit@ific.uv.es
Electronic address: andres.renteria@ific.uv.es
∗∗Electronic address: german.rodrigo@csic.es
††Electronic address: german.sborlini@usal.es
‡‡Electronic address: luizva@ific.uv.es
1
For a complete review about currently available technologies for
QFT calculations, see Ref. [21] and references therein.
Overcoming the current precision frontier will certainly
require to push these methods to their limits.
Future collider experiments require challenging theoret-
ical predictions from full calculations at order
n
in the
perturbative expansion (N
n
LO), with
n
3. One fore-
seeable complication is directly related to the appearance
of several scales in multiloop multileg Feynman integrals.
These objects are analytically known for specific processes
and kinematic configurations up to two loops with a lim-
ited number of scales and very few examples of three-loop
amplitudes are starting to pop-up [
24
,
25
]. At this point,
it is very unlikely that all the required ingredients will be-
come analytically available and the development of novel
numerical approaches seems unavoidable.
Given present and future needs, a major progress in
solving (at least) two challenges is necessary. On one
side, new computational techniques must be developed,
exploiting the fundamental properties of QFT and the
mathematical concepts behind scattering amplitudes. On
the other side, these new methods must be implemented
in efficient event generators, capable of overcoming the
bottlenecks of the currently available hardware.
Regarding the first challenge, we focus on the Loop-
Tree Duality (LTD) formalism [
26
37
], which exhibits
very attractive mathematical properties and a manifestly
causal physical interpretation. Multiloop scattering am-
plitudes are transformed in LTD into the so-called dual
amplitudes by integrating out one component of each of
the loop momenta through the Cauchy’s residue theorem.
In this way, physical observables are expressed in terms
of Euclidean integrals that combine loop and tree-level
contributions (as well as renormalization counter-terms)
arXiv:2210.13240v3 [hep-ph] 14 Nov 2023
2
to achieve a fully local cancellation of singularities [
38
44
].
Besides the possibility of a local regularization, including
the simultaneous cancellation of infrared and ultraviolet
singularities, the LTD formalism fully exploits causal-
ity in QFT. A recent reformulation [
45
57
] showed that
multiloop scattering amplitudes and Feynman integrals
can be represented in terms of a subset of cut diagrams
that generalize the well-known Cutkosky’s rules [
58
]. In
particular, a manifestly causal representation can be di-
rectly obtained by decomposing the original Feynman
diagrams into binary connected partitions in the equiva-
lence class of topologies defined by collapsing propagators
into edges (or multi-edges) [
51
,
59
]. As a result, a well
defined geometrical algorithm is available and a strong
connection between causality and directed acyclic graphs
can be established [60].
The other challenge is related to an efficient calcula-
tion of Feynman integrals, overcoming current hardware
limitations. In this direction, the development of novel
strategies for classically hard problems based on quantum
algorithms (QAs) is gaining momentum across different
areas. For instance, there are several ideas that exploit
the potential speed-up of quantum computers, such as
database querying through Grover’s algorithm [
61
], the
famous Shor’s algorithm for factorization of large inte-
gers [
62
] or Hamiltonian minimization through quantum
annealing [
63
]. In the context of particle physics, QAs are
often applied to solve problems related to lattice gauge
theories [
64
69
]. Recent applications for high-energy col-
liders include jet identification and clustering [
70
76
],
determination of parton densities (PDFs) [
77
], simulation
of parton showers [
78
,
79
], anomaly detection [
80
], and
integration of elementary particle processes [
81
]. This list
is rapidly growing, since QAs are suitable for several uses,
especially those involving minimization problems.
With this panorama in mind, the purpose of this article
is to explore the application of QAs for unveiling the
causal structure of multiloop scattering amplitudes and
Feynman integrals, or equivalently acyclic configurations
of directed graphs. Our strategy consists in exploiting
the properties of the adjacency matrix in graph theory
to build a Hamiltonian which weights the cost of differ-
ent momentum flow configurations. Explicitly, causal
configurations are those with minimum energy, so we se-
lect them by identifying the minima of the Hamiltonian.
This identification is implemented through a Variational
Quantum Eigensolver (VQE) [
82
84
], namely a hybrid
quantum-classical algorithm that seeks the ground state
of a given operator.
The classical problem of identifying or counting directed
acyclic graphs is #P-hard, see Ref. [
85
]. Explicitly, given
a graph
G
= (
V, E
) with
V
vertices and
E
edges, there
are 2
|E|
possible directed graphs that must be checked
for cycles. Efficient classical algorithms have been pro-
posed in the literature: e.g., Ref. [
86
] gives an example
of a Fixed Parameter Tractable algorithm, whose scaling
depends on a single structural parameter of the graph,
see also references therein. This algorithm consists of a
Binary Decision Diagram algorithm [
87
], which performs
asymptotically in
O
(2
p2
w/4
) running time per solution,
with the path-width
pw
always smaller than the input size
of the graph, becoming closer to it for dense graphs (i.e.,
maximally connected graphs). Instead, the motivation of
our paper is to encode the complexity of the graph by
means of a Hamiltonian, i.e. a cost function to be mini-
mized in order to find the directed acyclic configurations.
Since VQE is expected to offer a speed-up in minimiza-
tion problems compared to purely classical algorithms,
we explore up to what extent this speed-up remains in
the detection of directed acyclic graphs.
The outline of this paper is the following. In Sec. II,
we present a brief introduction to LTD, and we offer a de-
scription of its manifestly causal representation. Then, in
Sec. III, we discuss the geometrical aspects of the causal
configurations, presenting explicit examples in App. A.
After that, we introduce the Hamiltonian approach in
Sec. IV, putting special emphasis in the connection with
the adjacency matrix of directed acyclic graphs. We of-
fer a definition of the loop Hamiltonian and its classical
reconstruction algorithm in Secs. IV A and IV B, respec-
tively. We discuss subtleties of the encoding of vertex
registers in App. B. Then, we discuss the implementation
of the VQE in Sec. V, presenting an explicit example
for a representative two-loop topology in Sec. V A. The
full list of Hamiltonians for the topologies studied in this
article is given in App. C. Right after in Sec. V B, we
discuss an improved strategy based on multiple runs of
the VQE to collect, step by step, all the possible causal
solutions. In Sec. VI, we carefully compare the VQE
approach with the Grover’s based algorithm described in
Ref. [
60
], paying attention to the resources required for
a successful implementation in (real) quantum devices.
Finally, conclusions and further research directions are
presented in Sec. VII.
II. LOOP-TREE DUALITY AND CAUSALITY
To reach highly precise theoretical predictions, it is
necessary to deal with multiloop scattering amplitudes
and the corresponding Feynman integrals. In the Feyn-
man representation, the most general
L
-loop scattering
amplitude with Pexternal particles is given by
A(L)
F=Z1...ℓL
N{s}L,{pj}Pn
Y
i=1
GF(qi),(1)
where
qi
with
i∈ {
1
, . . . , n}
are the momenta flowing
through each Feynman propagator,
GF
(
qi
) = (
q2
im2
i
+
ı
0)
1
, and
N
represents a numerator, whose specific form
depends on the topologies of the different diagrams, the
interaction vertices and the nature of the particles that
propagate inside the loops. Regarding the momenta of
the internal particles, they are linear combinations of
the primitive loop momenta associated to the integra-
tion variables in the loop,
s
with
s∈ {
1
, . . . , L}
), and
3
the external momenta,
pj
with
j∈ {
1
, . . . , P }
. Given a
Feynman diagram, we can group the different internal
momenta into sets: two lines are said to belong to the
same set if their propagators involve the same linear com-
bination of primitive loop momenta [
46
]. This is useful for
achieving an efficient classification of diagrams according
to their causal structure [4749].
The denominator of Eq. (1) characterizes the singular
structure of the scattering amplitude, and singularities
provide important information to simplify loop calcula-
tions. In this direction, the Loop-Tree Duality (LTD)
[
26
,
27
] makes use of Cauchy’s residue theorem (CRT) to
reduce the dimensionality of the integration domain, en-
abling the possibility of transforming it into an Euclidean
space. By means of an iterated application of CRT, we
can get rid of one integration variable per loop: this is
equivalent to say that the LTD representation of a
L
-loop
amplitude is obtained by cutting (or setting on-shell)
L
internal lines. The effect of cutting a line is the modifica-
tion of the infinitesimal complex prescription, leading to
the so-called dual propagators [
26
,
27
]. It is important to
highlight that this modified prescription plays a crucial
role to preserve causality, as we will discuss later.
The traditional formulation of LTD leads to the so-
called dual representation, in which there is one contribu-
tion for each possible connected tree obtained by setting
on-shell
L
internal propagators. If we study the structure
of the denominators of each dual term, we immediately
realize the presence of divergences that do not correspond
to any physical configuration. These unphysical singu-
larities are spurious, and they vanish when we add all
the dual contributions together. This is the so called
manifestly causal representation within LTD [46,88].
Before moving on, let us recall one crucial fact about the
Feynman propagators. If we define the positive on-shell
energy
q(+)
i,0=qqi2+m2
iı0,(2)
then the propagator can be written as
GF(qi) = 1
qi,0q(+)
i,0
×1
qi,0+q(+)
i,0
.(3)
This decomposition suggests that each Feynman propa-
gator encodes a quantum superposition of two on-shell
modes, with positive and negative energy respectively.
The so-called causal representations are obtained by con-
sistently aligning these modes. Furthermore, this super-
position also motivates the identification of each internal
propagator with a qubit, as we will explain later.
As carefully discussed in Refs. [
46
,
89
], the calculation
of the nested residues within the LTD formalism leads to
a manifestly causal representation of multiloop multileg
scattering amplitudes. Thus, it can be shown that Eq. (1)
is equivalent to
A(L)
D=Z
1...
L
1
xnX
σΣ
Nσ
nL
Y
i=1
1
λhσ(i)
σ(i)
+(λ+
pλ
p),(4)
with xn=Qn2q(+)
i,0,hσ(i)=±1, and
Z
s
=µ4dZdd1s
(2π)d1,(5)
the integration measure in the loop three-momentum
space. It turns out that Eq. (4) only involves denom-
inators with on-shell energies, added together in same-
sign combinations within the so-called causal propagators,
1hσ(i)
σ(i), with
λhσ(i)
σ(i)λ±
p=X
ip
q(+)
i,0±kp,0,(6)
where
σ
(
i
) includes information about the partition
p
of
the set of on-shell energies and the corresponding orienta-
tion of the energy components of the external momenta,
kp,0
. Each causal propagator is in a one-to-one corre-
spondence with any possible threshold singularity of the
amplitude
A(L)
F
, which contains overlapped thresholds.
These are known as entangled causal thresholds:
σ
(
i
)
indicates the set of causal propagators that can be simul-
taneously entangled. The set Σ in Eq. (4) contains all
the combinations of allowed causal entangled thresholds,
which involves overlapped cuts with aligned momenta
flow.
An important advantage of the representation shown in
Eq. (4) is the absence of spurious nonphysical singularities.
In fact, since causal propagators involve same-sign com-
binations of positive on-shell energies, the only possible
singularities are related to IR/UV and physical thresholds.
More details about the manifestly causal LTD representa-
tion and its benefits can be found in Refs. [
47
,
48
,
50
,
51
].
III. GEOMETRIC INTERPRETATION OF
CAUSAL FLOWS
In order to identify the causal configurations of a multi-
loop Feynman diagram in a quantum device, it is necessary
to translate the problem into a suitable language. The
geometrical formulation of the manifestly causal LTD
representations [
51
] provides a clear and intuitive inter-
pretation. In the following, we briefly describe the most
relevant features of this formalism, recalling some basic
concepts and definitions as presented in Refs. [
51
,
59
,
60
].
Any scattering amplitude can be represented starting
from Feynman diagrams built from interaction vertices
and internal lines (or propagators) connecting those ver-
tices. Regarding causality, those lines that connect the
same vertices can be merged into a single edge, leading
to reduced Feynman graphs because the only allowed con-
4
figurations which are causal are those in which all the
momentum flows of these propagators are aligned in the
same direction. Then, reduced graphs are built from ver-
tices and edges, as described in Refs. [
50
52
], and their
causal structure turns out to be equivalent to that of the
dual representation of the original Feynman diagrams [
49
].
The number of loop integration variables in the LTD rep-
resentation given by Eq. (4) is directly related to the
topological independent loops present at the level of the
Feynman diagram. However, the reduced Feynman graph
has a fewer number of graphical loops, also called eloops,
since bunches of propagators connecting the same vertices
were collapsed to a single edge. Furthermore, it turns
out that vertices, edges and eloops are the only required
ingredients to obtain the causal representation of any
multiloop scattering amplitude [50,51].
Specifically, given a reduced Feynman graph, the asso-
ciated causal propagators 1
±
p
correspond to the set of
connected binary partitions of vertices. Also, they can be
graphically interpreted as lines cutting the diagrams into
two disconnected pieces, in a full analogy with Cutkosky’s
formulation [
58
]. Then, the representation in Eq. (4) can
be constructed from all the possible causal compatible
combinations of
k
causal propagators, the so-called causal
entangled thresholds. The number
k
is known as the order
of the diagram and defined as
k
=
V
1 [
46
,
50
,
51
]. It
naturally induces a topological classification of families
of Feynman diagrams, or equivalently, reduced Feynman
graphs. The family with
k
= 1 is known as Maximal
Loop Topology (MLT) [
46
] and only involves two vertices;
a Next-to-Maximal Loop Topology (NMLT) has three
vertices, and so on.
It was shown that causal entangled thresholds can be
identified by imposing geometrical selection rules. These
rules are deeply connected to the algebraic formulation
presented in Refs. [50,90], and they establish that:
1.
When considering all the
k
causal thresholds that
can be simultaneously entangled, all the edges can
be set on shell simultaneously. This is equivalent to
impose that the causal entangled thresholds depends
on the on-shell energies q(+)
i,0of all the edges.
2.
Two different causal propagator
λi
and
λj
can be
simultaneously entangled if they do not cross each
other. In other words, this means that the asso-
ciated partition of vertices do not intersect or are
totally included one in the other.
3.
The momentum of the edges that crosses a given
binary partition of vertices must be consistently
aligned, i.e., momentum must flow from one parti-
tion to a different one.
A careful explanation of these causal rules and their geo-
metric interpretation was presented in Ref. [
51
], including
pedagogical examples and practical cases of use. By im-
posing these three rules on the set of all the possible
combinations of
k
thresholds, we construct Σ, namely the
set of all causal entangled thresholds leading to Eq. (4).
Furthermore, as previously shown in Ref. [
60
], the third
condition is equivalent to ordering the internal edges in
such a way that the reduced Feynman diagram is a di-
rected acyclic graph. This means that there cannot be
closed cycles, allowing the information to propagate con-
sistently from one partition of the diagram to the other;
this condition is necessary for having a causal-compatible
partition. For this reason, given a reduced Feynman
graph, it is crucial to efficiently detect all the associated
directed acyclic graphs, since they are a vital ingredient to
reconstruct the LTD causal representation. To clarify this
discussion, we present an explicit application example in
App. A.
IV. HAMILTONIAN FORMALISM FOR
CAUSAL-FLOW IDENTIFICATION
The first proof-of-concept of a quantum algorithm for
Feynman loop integrals was presented in Ref. [
60
], man-
aging to successfully unfold the causal configurations of
multiloop Feynman diagrams. The implementation fol-
lows a modified Grover’s quantum algorithm to identify
the presence of directed acyclic configurations, represent-
ing the causal solutions, over different subloops of the
multiloop topologies.
The aim of this Section is to define a Hamiltonian
whose ground state corresponds to a superposition of
all the acyclic configurations of a given multiloop Feyn-
man diagram2. We first discuss the construction of such
Hamiltonian based on direct inspection of the multiloop
topology, and then we discuss a more general approach
based on the adjacency matrix of a graph, an object that
concentrates all the information regarding the orientation
of edges and the vertices that they connect within a re-
duced Feynman graph (as defined in Sec. III). We also
give a more formal presentation, relying on concepts and
notations from graph theory.
A. Cycle detection via Hamiltonian optimization
Let us consider a generic undirected graph
G
= (
V, E
),
with
V
a set of distinct vertices and
EV×V
a set of
edges (also known as links). Given the graph
G
, one can
build a set
DG
of 2
|E|
possible directed graphs where we
associate a specific direction to each link. We will denote
the subset of directed acyclic graphs as e
DG⊂ DG.
In order to formulate this problem as a Hamiltonian
optimization, we first fix the encoding for all the possible
(classical) solutions as elements of the computational basis
2
To avoid any possible confusion, we would like to emphasize that
this is not the Hamiltonian of the theory from which the Feynman
rules are extracted, but rather a function whose minimization
sets by construction the causal orientations of the diagram.
摘要:

VariationalquantumeigensolverforcausalloopFeynmandiagramsanddirectedacyclicgraphsGiuseppeClemente,1,∗AriannaCrippa,1,†KarlJansen,1,‡SelomitRam´ırez-Uribe,2,3,4,§Andr´esE.Renter´ıa-Olivo,2,¶Germ´anRodrigo,2,∗∗GermanF.R.Sborlini,5,6,††andLuizValeSilva2,‡‡1DeutschesElektronen-SynchrotronDESY,Platanenal...

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