Robust Bell inequalities from communication com-
plexity
Sophie Laplante
1
, Mathieu Lauri

ere
2
, Alexandre Nolin
1
, J
´
er
´
emie Roland
3
, and Gabriel
Senno
4
1
IRIF, Universit
´
e Paris-Diderot, Paris, France
2
ORFE, Princeton University, Princeton, NJ 08544, USA
3
Universit
´
e Libre de Bruxelles, Brussels, Belgium
4
ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels
(Barcelona), Spain
June 5, 2018
Sophie Laplante: laplante@irif.fr
Mathieu Lauri

ere: lauriere@princeton.edu
Alexandre Nolin: nolin@irif.fr
J
´
er
´
emie Roland: jroland@ulb.ac.be
Gabriel Senno: gabriel.senno@icfo.eu,
A ﬁrst version of this work appeared in [32].
arXiv:1606.09514v3 [quant-ph] 4 Jun 2018
Abstract
The question of how large Bell inequality violations can be, for quantum distributions, has
been the object of much work in the past several years. We say that a Bell inequality is
normalized if its absolute value does not exceed 1 for any classical (i.e. local) distribution.
Upper and (almost) tight lower bounds have been given for the quantum violation of these
Bell inequalities in terms of number of outputs of the distribution, number of inputs, and
the dimension of the shared quantum states. In this work, we revisit normalized Bell
inequalities together with another family: ineﬃciency-resistant Bell inequalities. To be
ineﬃciency-resistant, the Bell value must not exceed 1 for any local distribution, including
those that can abort. This makes the Bell inequality resistant to the detection loophole,
while a normalized Bell inequality is resistant to general local noise. Both these families
of Bell inequalities are closely related to communication complexity lower bounds. We
show how to derive large violations from any gap between classical and quantum commu-
nication complexity, provided the lower bound on classical communication is proven using
these lower bound techniques. This leads to ineﬃciency-resistant violations that can be
exponential in the size of the inputs. Finally, we study resistance to noise and ineﬃciency
for these Bell inequalities.
1 Introduction
The question of achieving large Bell violations has been studied since Bell’s seminal paper
in 1964 [6]. In one line of investigation, proposals have been made to exhibit families
of distributions which admit unbounded violations [33, 39, 40, 43]. In another, various
measures of nonlocality have been studied, such as the amount of communication necessary
and suﬃcient to simulate quantum distributions classically [79, 14, 37, 38, 44, 49, 50],
or the resistance to detection ineﬃciencies and noise. More recently, focus has turned to
giving upper and lower bounds on violations achievable, in terms of various parameters:
number of players, number of inputs, number of outputs, dimension of the quantum state,
and amount of entanglement [14, 22, 23].
Up until quite recently, violations were studied in the case of speciﬁc distributions
(measuring Bell states), or families of distributions. Buhrman et al. [12] gave a construc-
tion that could be applied to several problems which had eﬃcient quantum protocols (in
terms of communication) and for which one could show a trade-oﬀ between communication
and error in the classical setting. This still required an ad hoc analysis of communication
problems. Recently Buhrman et al. [13] proposed the ﬁrst general construction of quantum
states along with Bell inequalities from any communication problem. The quantum states
violate the Bell inequalities when there is a suﬃciently large gap between quantum and
classical communication complexity (a super-quadratic gap is necessary, unless a quantum
protocol without local memory exists).
Table 1 summarizes the best known upper and lower bounds on quantum violations
achievable with normalized Bell inequalities.
Parameter Upper bound
Ad hoc lower
bounds
Best possible
lower bound
from [13]
Number of inputs N 2
c
N [14, 23, 34]
N
log(N)
[22]
c
q
log(N)
Number of outputs K O(K) [22]
K
(log(K))
2
[12] log(K)
Dimension d O(d) [23]
d
(log(d))
2
[12] log log(d)
Table 1: Bounds on quantum violations of bipartite normalized Bell inequalities, in terms of the dimen-
sion d of the local Hilbert space, the number of settings (or inputs) N and the number of outcomes
(or outputs) K per party. In the fourth column, we compare ad hoc results to the recent construc-
tions of [13] (Theorem 2) which gives a lower bound of
c
q
, where c (resp. q) stands for the classical
(resp. quantum) communication complexity of simulating a distribution. We give upper bounds on
their construction in terms of the parameters d, N, K.
1.1 Our results
We revisit the question of achieving large Bell violations by exploiting known connec-
tions with communication complexity. Strong lower bounds in communication complexity,
equivalent to the partition bound, amount to ﬁnding ineﬃciency-resistant Bell inequali-
ties [31]. These are Bell functionals that are bounded above by 1 on all local distributions
that can abort, i.e. local distributions with an additional abort outcome for each party.
In an experimental Bell test, such a constraint would provide resistance to the detection
Accepted in Quantum 2018-05-12, click title to verify 1
loophole, by associating an event where one of the detectors does not click to an abort
outcome.
First, we study the resistance of normalized Bell inequalities to ineﬃciency. We show
that, up to a constant factor in the value of the violation, any normalized Bell inequal-
ity can be made resistant to ineﬃciency while maintaining the normalization property
(Theorem 1).
Second, we show how to derive large Bell violations from any communication problem
for which the partition bound is bounded below and the quantum communication com-
plexity is bounded above. The problems studied in communication complexity are far
beyond the quantum set, but we show how to easily derive a quantum distribution from a
quantum protocol. The Bell value we obtain is 2
c2q
, where c is the partition lower bound
on the classical communication complexity of the problem considered, and q is an upper
bound on its quantum communication complexity (Theorem 3 and Corollary 1). The
quantum distribution has one extra output per player compared to the original distribu-
tion and uses the same amount of entanglement as the quantum protocol plus as many
EPR pairs as needed to teleport the quantum communication in the protocol. Next, we
show that the magnitude of the violations is unaltered in the presence of white noise, i.e.
when the ideal quantum state giving rise to the correlations gets added a maximally mixed
stated with some probability δ (Theorem 4).
Finally, we provide tools to build Bell inequalities from communication lower bounds
in the literature. Lower bounds used in practice to separate classical from quantum com-
munication complexity are usually achieved using corruption bounds and its variants. In
Theorem 6, we give an explicit construction which translates these bounds into a suitable
Bell functional. Table 2 summarizes the new results or the improvements that we obtain
in this work.
Problem Normalized Bell violations [13]
Ineﬃciency-resistant Bell
violations (this work)
VSP [28, 45]
6
n/
log n
d = 2
Θ(n log n)
, K = 2
Θ(n)
2
Ω(
3
n)O(log n)
d = 2
O(log n)
, K = 3
DISJ [1, 46, 47] N/A
2
Ω(n)O(
n)
d = 2
O(
n)
, K = 3
TRIBES [11, 21] N/A
2
Ω(n)O(
n log
2
n)
d = 2
O(
n log
2
n)
, K = 3
ORT [11, 48] N/A
2
Ω(n)O(
n log n)
d = 2
O(
n log n)
, K = 3
Table 2: Comparison of the Bell violations obtained by the general construction of Buhrman et al. [13]
for normalized Bell violations (second column) and this work, for ineﬃciency-resistant Bell violations
(see Propositions 4, 5, 6, and 7). The parameter n is the size of the input (typically, N = 2
n
.) See
Section 6.2 for the deﬁnitions of the communication problems appearing in this table. The construction
of Buhrman et al. only yields a violation when the gap between classical and quantum complexities is
more than quadratic. In the case where the gap is too small to prove a violation, we indicate this with
“N/A”.
Accepted in Quantum 2018-05-12, click title to verify 2
1.2 Related work
The study of the maximum violation of Bell inequalities began with Tsirelson [51], who
showed that for two-outcome correlation Bell inequalities, the maximum violation is bounded
above by Grothendieck’s constant. Tsirelson also raised the question of whether one can
have unbounded violations of Bell inequalities. More precisely, he asked whether there
exist families of Bell inequalities for which the amount of the violation grows arbitrarily
large.
The ﬁrst answer to this question came from Mermin [39], who gave a family of Bell
inequalities for which a violation exponential in the number of parties is achieved. In the
years that followed, several new constructions appeared for number of parties and number
of inputs [3, 33, 35, 40, 43].
The study of upper bounds on violations of normalized Bell inequalities resumed in [14],
where an upper bound of O(K
2
) (with K the number of outputs per player) and of
2
c
N (with c the communication complexity and N the number of inputs per player)
were proven. In [23] the authors proved a bound of O(d) in terms of the dimension d of
the local Hilbert space, and in [22], the bound in terms of the number of outputs was
improved to O(K). In [22], Bell inequalities are constructed for which a near optimal,
but probabilistic, violation of order Ω(
m/ log m), with N = K = d = m, is proven.
In [12], the same violation, although requiring N = 2
m
inputs, is achieved for a family of
Bell inequalities and quantum distributions built using the quantum advantage in one-way
communication complexity for the Hidden Matching problem (with K = d = m). In the
same paper, a violation of order Ω(m/(log m)
2
), with K = d = m and N = 2
m
/m is
achieved with the Khot-Vishnoi game; later, Junge et al. proved in [25] that N can be
reduced to O(m
8
) . Recently, an asymmetric version of this same game was introduced to
allow one of the parties to only make dichotomic measurements, with a smaller (although
almost optimal for this scenario) violation Ω(
m/(log m)
2
) [42].
For ineﬃciency-resistant Bell inequalities, the bounds in [22] do not apply. In fact,
Laplante et al. proved in [31] a violation exponential in the dimension and the number
of outputs for this type of Bell functionals, achieved by a quantum distribution built, as
in [12], from the Hidden Matching communication complexity problem.
The connection exhibited in [12] between Bell violations and communication complex-
ity is generalized by Buhrman et al. in [13] where a fully general construction is given to
go from a quantum communication protocol for a function f to a Bell inequality and a
quantum distribution violating it when the gap between classical and quantum commu-
nication complexity is larger than quadratic. The downside to this construction is that
the quantum distribution has a double exponential (in the communication) number of
outputs and the protocol to implement it uses an additional double exponential amount
of entanglement. Also, this result does not apply for quantum advantages in a zero-error
setting.
2 Preliminaries
2.1 Quantum nonlocality
Local, quantum, and nonsignaling distributions have been widely studied in quantum
information theory since the seminal paper of Bell [6]. In an experimental setting, two
players share an entangled state and each player is given a measurement to perform.
The outcomes of the measurements are predicted by quantum mechanics and follow some
probability distribution p(a, b|x, y), where a is the outcome of Alice’s measurement x, and
Accepted in Quantum 2018-05-12, click title to verify 3
b is the outcome of Bob’s measurement y.
We consider bipartite distribution families of the form p = (p(·, ·|x, y))
(x,y)∈X×Y
with
inputs (x, y) X × Y determining a probability distribution p(·, ·|x, y) over the outcomes
(a, b) A × B, with the usual positivity and normalization constraints. The set of proba-
bility distribution families is denoted by P. For simplicity, we call simply “distributions”
such probability distribution families. The expression “Alice’s marginal” refers to her
marginal output distribution, that is
P
b
p(·, b|x, y) (and similarly for Bob).
The local deterministic distributions, denoted L
det
, are the ones where Alice outputs
according to a deterministic strategy, i.e., a (deterministic) function of x, and Bob inde-
pendently outputs as a function of y, without communicating. The local distributions L are
obtained by taking distributions over the local deterministic strategies. Operationally, this
corresponds to protocols with shared randomness and no communication. Geometrically,
L is the convex hull of L
det
.
A Bell test [6] consists of estimating all the probabilities p(a, b|x, y) and computing
a Bell functional, or linear function, on these values. The Bell functional B is chosen
together with a threshold τ so that any local classical distribution  satisﬁes the Bell
inequality B() τ, but the chosen distribution p exhibits a Bell violation: B(p) > τ .
By normalizing B, we can assume without loss of generality that  satisﬁes B() 1 for
any  L, and B(p) > 1.
In this paper, we will also consider strategies that are allowed to abort the protocol
with some probability. When they abort, they output the symbol ( denotes a new
symbol which is not in A B). We will use the notation L
det
and L
to denote local
strategies that can abort, where is added to the possible outputs for both players.
When  L
det
or L
, (a, b|x, y) is not conditioned on a, b 6= since is a valid output
for such distributions.
The quantum distributions, denoted Q, are the ones that result from applying mea-
surements x, y to their part of a shared bipartite quantum state. Each player outputs his
or her measurement outcome (a for Alice and b for Bob). In communication complexity
terms, these are zero-communication protocols with shared entanglement. If the players
are allowed to abort, then the corresponding set of distributions is denoted Q
.
Boolean (and other) functions can be cast as sampling problems. Consider a boolean
function f : X ×Y {0, 1} (nonboolean functions and relations can be handled similarly).
First, we split the output so that if f(x, y) = 0, Alice and Bob are required to output
the same bit, and if f(x, y) = 1, they output diﬀerent bits. Let us further require Alice’s
marginal distribution to be uniform, likewise for Bob, so that the distribution is well
deﬁned. Call the resulting distribution p
f
, that is, for any a, b {0, 1} and (x, y) X ×Y,
we have p
f
(a, b|x, y) = 1/2 if a b = f(x, y), and p
f
(a, b|x, y) = 0 otherwise, being the
1-bit XOR.
If p
f
were local, f could be computed with one bit of communication using shared
randomness: Alice sends her output to Bob, and Bob XORs it with his output. If p
f
were
quantum, there would be a 1-bit protocol with shared entanglement for f. Interesting
distributions have nontrivial communication complexity and, therefore, they usually lie
well beyond these sets.
Finally, a distribution is nonsignaling if for each player, its marginal output distri-
butions, given by p
A
(a|x, y) =
P
b
p(a, b|x, y), for Alice, and p
B
(b|x, y) =
P
a
p(a, b|x, y),
for Bob, do not depend on the other player’s input. When this is the case, we write the
marginals as p
A
(a|x) and p
B
(b|y). Operationally, this means that each player cannot in-
ﬂuence the statistics of what the other player observes with his own choice of input. We
note with C the set of nonsignaling distributions, also referred to as the causal set, and we
Accepted in Quantum 2018-05-12, click title to verify 4
note C
when we allow aborting. The well-known inclusion relations between these sets
are L Q C P.
For any Boolean function f, the distribution p
f
is nonsignaling since the marginals
are uniform. A fundamental question of quantum mechanics has been to establish ex-
perimentally whether nature is truly nonlocal, as predicted by quantum mechanics, or
whether there is a purely classical (i.e., local) explanation to the phenomena that have
been predicted by quantum theory and observed in the lab.
2.2 Measures of nonlocality
We have described nonlocality as a yes/no property, but some distributions are some-
how more nonlocal than others. To have a robust measure of nonlocality, it should fulﬁll
some common sense properties: for a ﬁxed distribution, the measure should be bounded; it
should also be convex, since sampling from the convex combination of two distributions can
be done by ﬁrst picking randomly one of the two distributions using shared randomness,
and then sampling from that distribution. We also expect such a measure of nonlocality
to have various equivalent formulations. Several measures have been proposed and stud-
ied: resistance to noise [2, 24, 26, 43], resistance to ineﬃciency [31, 35, 36], amount of
communication necessary to reproduce them [9, 14, 37, 44, 49, 50], information-theoretic
measures [10, 16, 17], etc.
In the form studied in this paper, normalized Bell inequalities were ﬁrst studied in [14],
where they appeared as the dual of the linear program for a well-studied lower bound on
communication complexity, known as the nuclear norm ν [34] (the deﬁnition is given in
Section 2.3). There are many equivalent formulations of this bound. For distributions
arising from boolean functions, it has the mathematical properties of a norm, and it is
related to winning probabilities of XOR games. It can also be viewed as a gauge, that is,
a quantity measuring by how much the local set must be expanded in order to contain
the distribution considered. For more general nonsignaling distributions, besides having
a geometrical interpretation in terms of aﬃne combinations of local distributions, it has
also been shown to be equivalent to the amount of local noise that can be tolerated before
the distribution becomes local [23].
A subsequent paper [31] studied equivalent formulations of the partition bound, one of
the strongest lower bounds in communication complexity [20]. This bound also also has
several formulations: the primal formulation can be viewed as resistance to detector inef-
ﬁciency, and the dual formulation is given in terms of ineﬃciency-resistant Bell inequality
violations.
In this paper, we show how to deduce large violations on quantum distributions from
large violations on nonsignaling distributions, provided there are eﬃcient quantum com-
munication protocols for the latter.
2.3 Communication complexity and lower bounds
In classical communication complexity (introduced by [52]), two players each have a share
of the input, and wish to compute a function on the full input. Communication complexity
measures the number of bits they need to exchange to solve this problem in the worst case,
over all inputs of a given size n. In this paper we consider a generalization of this model,
where instead of computing a function, they each produce an output, say a and b, which
should follow, for each (x, y), some prescribed distribution p(a, b|x, y) (which depends on
their inputs x, y). We assume that the order in which the players speak does not depend on
the inputs. This is without loss of generality at a cost of a factor of 2 in the communication.
Accepted in Quantum 2018-05-12, click title to verify 5
We use the following notation for communication complexity of distributions. R
(p)
is the minimum number of bits exchanged in the worst case between players having access
to shared randomness in order to output with the distribution p up to in total variation
distance for all x, y. We call total variation distance between distributions the distance
denoted by |.|
1
, and deﬁned as |p p
0
|
1
= max
x,y
P
a,b
|p(a, b|x, y) p
0
(a, b|x, y)|. We use
Q
to denote quantum communication complexity (see [54]) and Q
when, in addition to
the communication of quantum states, the players are allowed to share entanglement.
To give upper bounds on communication complexity it suﬃces to give a protocol and
analyze its complexity. Proving lower bounds is often a more diﬃcult task, and many tech-
niques have been developed to achieve this. The methods we describe here are complexity
measures which can be applied to any function. To prove a lower bound on communi-
cation, it suﬃces to give a lower bound on one of these complexity measures, which are
bounded above by communication complexity for any function. We describe here most of
the complexity measures relevant to this work.
The nuclear norm ν, given here in its dual formulation and extended to nonsignaling
distributions, is expressed by the following linear program [14, 34]. (There is a quantum
analogue, γ
2
, which is not needed in this work. We refer the interested reader to the
deﬁnition for distributions in [14]).
Deﬁnition 1 ([14, 34]). The nuclear norm ν of a nonsignaling distribution p C is given
by
ν(p) = max
B
B(p)
subject to |B()|≤ 1  L
det
.
With error , ν
(p) = min
p
0
∈C:|p
0
p|
1
ν(p
0
). We call any Bell functional that satisﬁes
the constraint in the above linear program normalized Bell functional.
In this deﬁnition and in the rest of the paper, unless otherwise speciﬁed (in partic-
ular in Lemma 1), B ranges over vectors of real coeﬃcients B
a,b,x,y
and B(p) denotes
P
a,b,x,y
B
a,b,x,y
p(a, b|x, y), where a, b ranges over the nonaborting outputs and x, y ranges
over the inputs. So even when B and p have coeﬃcients on the abort events, we do not
count them. Table 1 summarizes the known upper and lower bounds on ν for various
parameters. The (log of the) nuclear norm is a lower bound on classical communication
complexity.
Proposition 1 ([14, 34]). For any nonsignaling distribution p C, R
(p)+1 log(ν
(p)),
and for any Boolean function f, R
(f) log(ν
(p
f
)).
As lower bounds on communication complexity of Boolean functions go, ν is one of
the weaker bounds, equivalent to the smooth discrepancy [20], and no larger than the
approximate nonnegative rank and the smooth rectangle bounds [29]. More signiﬁcantly
for this work, up to small multiplicative constants, for Boolean functions, (the log of) ν is a
lower bound on quantum communication, so it is useless to establish gaps between classical
and quantum communication complexity. (This limitation, with the upper bound in terms
of the number of outputs on normalized Bell violations, is a consequence of Grothendieck’s
theorem [18].)
The classical and quantum eﬃciency bounds, given here in their dual formulations,
are expressed by the following two convex optimization programs. The classical bound is
a generalization to distributions of the partition bound of communication complexity [20,
31]. This bound is one of the strongest lower bounds known, and can be exponentially
Accepted in Quantum 2018-05-12, click title to verify 6
larger than ν (an example is the Vector in Subspace problem [28]). It is always at least
as large as the relaxed partition bound which is in turn always at least as large as the
smooth rectangle bound [20, 27]. Its weaker variants have been used to show exponential
gaps between classical and quantum communication complexity. The deﬁnition we give
here is a stronger formulation than the one given in [31]. We show they are equivalent in
Appendix E.
Deﬁnition 2 ([31]). The -error eﬃciency bound of a distribution p P is given by
eﬀ
(p) = max
B
β
subject to B(p
0
) β p
0
P s.t. |p
0
p|
1
,
B() 1  L
det
.
We call any Bell functional that satisﬁes the second constraint in the above program
ineﬃciency-resistant Bell functional. The -error quantum eﬃciency bound of a p P is
eﬀ
(p) = max
B
β
subject to B(p
0
) β p
0
P s.t. |p
0
p|
1
,
B(q) 1 q Q
.
We denote eﬀ = eﬀ
0
and eﬀ
= eﬀ
0
the 0-error bounds.
Although it may not be straightforward from the above deﬁnition due to the presence
of absolute values, the program for the classical eﬃciency bound is linear, as a consequence
of L
det
being a polytope (See Appendix E and Ref. [31]).
For any given distribution p, its classical communication complexity is bounded from
below by the (log of the) eﬃciency bound. For randomized communication complexity with
error , the bound is log(eﬀ
) and for quantum communication complexity, the bound is
log(eﬀ
). Note that for any p Q, the quantum communication complexity is 0 and the
eﬀ
bound is 1. For any function f, the eﬃciency bound eﬀ
(p
f
) is equivalent to the
partition bound [20, 31].
Proposition 2 ([31]). For any p P and any 0 < 1/2, R
(p) log(eﬀ
(p)) and
Q
(p)
1
2
log(eﬀ
(p)). For any p C and any 0 1, ν
(p) 2eﬀ
(p).
Theorem 3 in Section 4 below involves upper bounds on the quantum eﬃciency bound.
To give an upper bound on the quantum eﬃciency bound of a distribution p, it is more
convenient to use the primal formulation, and upper bounds can be given by exhibiting
a local (or quantum) distribution with abort which satisﬁes the following two properties:
the probability of aborting should be the same on all inputs x, y, and conditioned on not
aborting, the outputs of the protocol should reproduce the distribution p. The eﬃciency
bound is inverse proportional to the probability of not aborting, so the goal is to abort as
little as possible.
Proposition 3 ([31]). For any distribution p P, eﬀ
(p) = 1
, with η
the optimal
value of the following optimization problem (nonlinear, because Q
is not a polytope).
max
q∈Q
ζ
subject to q(a, b|x, y) = ζp(a, b|x, y) x, y, a, b X×Y×A×B
Moreover, for any 0 1, eﬀ
(p) = min
p
0
∈P:|p
0
p|
1
eﬀ
(p
0
).
Accepted in Quantum 2018-05-12, click title to verify 7
3 Properties of Bell inequalities
Syntactically, there are two diﬀerences between the normalized Bell functionals (Deﬁni-
tion 1) and the ineﬃciency-resistant ones (Deﬁnition 2). The ﬁrst diﬀerence is that the
normalization constraint is relaxed: for ineﬃciency-resistant functionals, the Bell value
for local distributions is, unlike the case for normalized Bell functionals, not bounded in
absolute value; it is only bounded from above. Since this is a maximization problem, this
relaxation allows for larger violations. This diﬀerence alone would not lead to a satis-
factory measure of nonlocality, since one could obtain unbounded violations by shifting
and dilating the Bell functional. The second diﬀerence prevents this. The upper bound is
required to hold for a larger set of local distributions, those that can abort. This is a much
stronger condition. Notice that a local distribution can selectively abort on conﬁgurations
that would otherwise tend to keep the Bell value small, making it harder to satisfy the
constraint.
In this section, we show that normalized Bell violations can be modiﬁed to be resis-
tant to local distributions that abort, while preserving the violation on any nonsignaling
distribution, up to a multiplicative factor of 3 (plus a term independent of the input and
output sizes). This means that we can add the stronger constraint of resistance to local
distributions that abort to Deﬁnition 1, incurring a loss of essentially a factor of 3, and
the only remaining diﬀerence between the resulting linear programs is the relaxation of
the lower bound (dropping the absolute value) for local distributions that abort.
Theorem 1. Let B be a normalized Bell functional on A × B × X × Y and p C
a nonsignaling distribution such that B(p) 1. Then there exists a normalized Bell
functional B
on (A{⊥}) ×(B{⊥}) ×X ×Y with 0 coeﬃcients on the outputs such
that : p C, B
(p)
1
3
B(p)
2
3
, and  L
det
, |B
()| 1.
The formal proof of Theorem 1 is deferred to Appendix A, and we will only give its
high-level structure in this part of the paper. First, we show (see Observation 1) how
to rescale a normalized Bell functional so that it saturates its normalization constraint.
Then, Deﬁnition 3 adds weights to abort events to make the Bell functional resistant to
ineﬃciency. Finally, Lemma 1 removes the weights on the abort events of a Bell functional
while keeping it bounded on the local set with abort, without dramatically changing the
values it takes on the nonsignaling set. Our techniques are similar to the ones used in [36].
4 Exponential violations from communication bounds
Recently, Buhrman et al. gave a general construction to derive normalized Bell inequalities
from any suﬃciently large gap between classical and quantum communication complexity.
Theorem 2 ([13]). For any function f for which there is a quantum protocol using q qubits
of communication but no prior shared entanglement, there exists a quantum distribution
q Q and a normalized Bell functional B such that B(q)
R
1/3
(f)
6
30q
(1 2
q
)
2q
.
Their construction is quite involved, requiring protocols to be memoryless, which they
show how to achieve in general, and uses multiport teleportation to construct a quantum
distribution. The Bell inequality they construct expresses a correctness constraint.
In this section, we show how to obtain large ineﬃciency-resistant Bell violations for
quantum distributions from gaps between quantum communication complexity and the
eﬃciency bound for classical communication complexity. We ﬁrst prove the stronger of
Accepted in Quantum 2018-05-12, click title to verify 8
two statements, which gives violations of
eﬀ
(p)
eﬀ
?
0
(p)
. For any problem for which a classical
lower bound c is given using the eﬃciency or partition bounds or any weaker method
(including the rectangle bound and its variants), and any upper bound q on quantum
communication complexity, it implies a violation of 2
c2q
.
Theorem 3. For any distribution p P and any 0
0
1, if (B, β) is a feasible
solution to the dual of eﬀ
(p) and (ζ, q) is a feasible solution to the primal for eﬀ
?
0
(p),
then there is a quantum distribution q Q such that B(q) ζβ and B() 1,  L
det
,
and in particular, if both are optimal solutions, then B(q)
eﬀ
(p)
eﬀ
?
0
(p)
. The distribution q
has one additional output per player compared to the distribution p.
Proof. Let (B, β) be a feasible solution to the dual of eﬀ
(p), p
0
be such that eﬀ
?
0
(p) =
eﬀ
?
(p
0
) with |p
0
p|
1
0
, and (ζ, q) be a feasible solution to the primal for eﬀ
?
(p
0
).
From the constraints, we have q Q
, q(a, b|x, y) = ζp
0
(a, b|x, y) for all (a, b, x, y)
A × B × X × Y, B() 1 for all  L
det
, and B(p
00
) β for all p
00
s.t. |p
00
p|
1
.
Then B(q) = ζB(p
0
) ζβ. However, q Q
but technically we want a distribution
in Q (not one that aborts). So we add a new (valid) output ‘A’ to the set of outputs
of each player, and they should output ‘A’ instead of aborting whenever q aborts. The
resulting distribution, say q Q (with additional outcomes ‘A’ on both sides), is such that
B(q) = B(q) (since the Bell functional B does not have any weight on or on ‘A’).
Theorem 2 and Theorem 3 are both general constructions, but there are a few signiﬁ-
cant diﬀerences. Firstly, Theorem 3 requires a lower bound on the partition bound in the
numerator, whereas Theorem 2 only requires a lower bound on communication complexity
(which could be exponentially larger). Secondly, Theorem 2 requires a quantum commu-
nication protocol in the denominator, whereas our theorem only requires an upper bound
on the quantum eﬃciency bound (which could be exponentially smaller). Thirdly, our
bound is exponentially larger than Buhrman et al.’s for most problems considered here,
and applies to subquadratic gaps, but their bounds are of the more restricted class of
normalized Bell inequalities. These diﬀerences imply, in principle, diﬀerent applicability
regimes for the two constructions, which we depict in Figure 1.
Theorem 3 gives an explicit Bell functional provided an explicit solution to the eﬃ-
ciency (partition) bound is given and the quantum distribution is obtained from a solution
to the primal of eﬀ
?
(Proposition 3). Recall that a solution to the primal of eﬀ
?
is pro-
vided by a quantum zero-communication protocol that can abort, which conditioned on
not aborting, outputs following p. We can also start from a quantum protocol, as we
show below. From the quantum protocol, we derive a quantum distribution using stan-
dard techniques.
Corollary 1. For any distribution p P and any 0
0
1 such that R
(p)
log(eﬀ
(p)) c and Q
0
(p) q, there exists an explicit ineﬃciency-resistant B derived
from the eﬃciency lower bound, and an explicit quantum distribution q Q derived from
the quantum protocol such that B(q) 2
c2q
.
Proof. Let (B, β) be an optimal solution to eﬀ
(p) and let c be such that eﬀ
(p) = β 2
c
.
By optimality of B, we have B(p
0
) 2
c
for any p
0
such that |p
0
p|
1
. Since Q
0
(p)
q, there exists a q-qubit quantum protocol (possibly using preshared entaglement) for
some distribution p
0
with |p
0
p|
1
0
. Then, we can use teleportation to obtain
a 2q classical bit, entanglement-assisted protocol for p
0
. We can simulate it without
communication by picking a shared 2q-bit random string and running the protocol but
without sending any messages. If the measurements do not match the string, output a
Accepted in Quantum 2018-05-12, click title to verify 9
R Q
2
eﬀ Q
R Q
eﬀ eﬀ
?
DISJORT
TRIBES
VSP
?
Figure 1: An illustration of the diﬀerent applicability regions of Theorem 2 and Theorem 3. There
are problems in the literature for which both constructions apply, e.g. VSP, and problems for which
only our construction applies, e.g. DISJ, ORT, and TRIBES (see Table 2). Whether there exists
any problem in the region in which R Q
2
but eﬀ eﬀ
(indicated by a question mark in the
picture), for which Theorem 2 applies but our Theorem 3 does not, is, to our current knowledge, an
open question.
new symbol ‘A’ (not in the output set of the quantum protocol and diﬀerent from ). We
obtain a quantum distribution q such that B(q) = B(p
0
)/2
2q
2
c2q
.
Most often, communication lower bounds are not given as eﬃciency or partition bounds,
but rather using variants of the corruption bound. We show in Section 6.1 how to map a
corruption bound to explicit Bell coeﬃcients.
5 Noise-resistant violations from communication bounds
Normalized Bell inequalities are naturally resistant to any constant level of local noise
in the sense that the value of the Bell functional can only decrease by constant additive
and multiplicative terms. Indeed, if the observed distribution is
˜
p = (1 ε)p + ε for
some  L, then B(
˜
p) (1 ε)B(p) ε since | B() |≤ 1. In ineﬃciency-resistant
Bell inequalities, relaxing the absolute value leads to the possibility that B() has a large
negative value for some local . (Indeed, such large negative values are inherent to large
gaps between ν and eﬀ .) If this distribution were used as adversarial noise, the observed
distribution, (1 ε)p + ε, could have a Bell value much smaller than B(p). This makes
ineﬃciency-resistant Bell inequalities susceptible to adversarial local noise.
In Theorem 4 below, whose proof we defer to Appendix B, we show that the quantum
violations arising from our construction in Corollary 1 are resistant to the addition of
white noise. More speciﬁcally, we consider the standard noise model (see e.g., [15, 26, 36])
in which the (ideal) quantum state |ψi gets added a maximally mixed state with some
probability δ,
ρ := (1 δ)|ψihψ| + δ
I
d
.
We show that even in this noisy scenario, the ineﬃciency-resistant Bell functional B
and the quantum distribution q resulting from the construction in Corollary 1 are such
that B(q) 2
c2q
. Intuitively, resistance to this kind of noise follows from: 1) B arising
from a lower bound on bounded-error communication complexity and 2) the teleportation
measurements needed to construct q still giving uniform outcomes when we replace a
maximally entangled with a maximally mixed state.
Accepted in Quantum 2018-05-12, click title to verify 10
Theorem 4. For any p P and any 0
0
1 such that log(eﬀ
(p)) c and
Q
0
(p) q, there exists an explicit ineﬃciency-resistant B, POVMs {E
a|x
}
a∈A∪{S}
over
a Hilbert space H
A
and {E
b|y
}
b∈B∪{S}
over a Hilbert space H
B
and a quantum state |ψi
H
A
H
B
, such that for any 0 δ
0
, we have that
B(q
δ
) 2
c2q
,
with
q
δ
(a, b|x, y) = tr
E
a|x
E
b|y
(1 δ)|ψihψ|+ δ
I
dim(H
A
H
B
)

.
Notice that q has one additional output per player (labelled S) compared to p.
6 Explicit constructions
6.1 From corruption bound to Bell inequality violation
We now explain how to construct an explicit Bell inequality violation from the corruption
bound. The corruption bound, introduced by Yao in [53], is a very useful lower bound
technique. It has been used for instance in [46] to get a tight Ω(n) lower bound on the
randomized communication complexity of Disjointness (whereas the approximate rank,
for example, can only show a lower bound of Θ(
n)). Let us recall that a rectangle R of
X × Y is a subset of that set of the form R
A
× R
B
, where R
A
X and R
B
Y.
Theorem 5 (Corruption bound [4, 30, 53]). Let f be a (possibly partial) Boolean function
on X × Y. Given γ, δ (0, 1), suppose that there is a distribution µ on X × Y such that
for every rectangle R X ×Y
µ(R f
1
(1)) > γµ(R f
1
(0)) δ
Then, for every (0, 1), 2
R
(f)
1
δ
µ(f
1
(0))
γ
.
See, e.g., Lemma 3.5 in [5] for a rigorous treatment. For several problems, such a µ is
already known. In Theorem 6 below, whose proof we defer to Appendix C, we show how
to construct a Bell inequality violation from this type of bound.
Theorem 6. Let f be a (possibly partial) Boolean function on X × Y, where X, Y
{0, 1}
n
. Fix z {0, 1}. Let µ be an input distribution, and (U
i
)
iI
(resp. (V
j
)
jJ
) be a
family of pairwise nonoverlapping subsets of f
1
(¯z) (resp. of f
1
(z)). Assume that there
exists g : (0, +) such that, for any rectangle R X ×Y
X
iI
u
i
µ(R U
i
)
X
jJ
v
j
µ(R V
j
) g(n). (1)
Then, the Bell functional B given by the following coeﬃcients: for all a, b, x, y {0, 1} ×
{0, 1} × X ×Y,
B
a,b,x,y
=
1/2(u
i
g(n)
1
µ(x, y)) if (x, y) U
i
and a b = z,
1/2(v
j
g(n)
1
µ(x, y)) if (x, y) V
j
and a b = z,
0 otherwise.
(2)
satisﬁes
B() 1,  L
det
, (3)
B(p
f
) =
1
2 · g(n)
X
j
v
j
µ(V
j
) (4)
Accepted in Quantum 2018-05-12, click title to verify 11
and for any p
0
P such that |p
0
p
f
|
1
:
B(p
0
)
1
2 · g(n)
X
j
v
j
µ(V
j
)
X
j
|v
j
|µ(V
j
) +
X
i
|u
i
|µ(U
i
)
. (5)
For many other problems in the literature, such as Vector in Subspace and Tribes,
stronger variants of the corruption bound are needed to obtain good lower bounds. These
stronger variants have been shown to be no stronger than the partition bound (more
speciﬁcally, the relaxed partition bound) [27]. The generalization in Theorem 6 of the
hypothesis of Theorem 5, which the reader might have noticed, allow us to construct
explicit Bell functionals also for these problems.
6.2 Some speciﬁc examples
Using Corollary 1 and the construction to go from a corruption bound (or its variants)
to a Bell inequality (Theorem 6), we give explicit Bell inequalities and violations for
several problems studied in the literature. Since our techniques also apply to small gaps,
we include problems for which the gap between classical and quantum communication
complexity is polynomial.
Vector in Subspace In the Vector in Subspace Problem VSP
0,n
, Alice is given an n/2
dimensional subspace of an n dimensional space over R, and Bob is given a vector. This
is a partial function, and the promise is that either Bob’s vector lies in the subspace, in
which case the function evaluates to 1, or it lies in the orthogonal subspace, in which case
the function evaluates to 0. Note that the input set of VSP
0,n
is continuous, but it can be
discretized by rounding, which leads to the problem
g
VSP
θ,n
(see [28] for details). Klartag
and Regev [28] show that the VSP can be solved with an O(log n) quantum protocol, but
the randomized communication complexity of this problem is Ω(n
1/3
). As shown in [27],
this is also a lower bound on the relaxed partition bound. Hence Corollary 1 yields the
following.
Proposition 4. There exists a Bell inequality B and a quantum distribution q
V SP
Q
such that B (q
V SP
) 2
Ω(n
1/3
)O(log n)
and for all  L
det
, B() 1.
Note that the result of [28] (Lemma 4.3) is not of the form needed to apply Theorem 6.
It is yet possible to obtain an explicit Bell functional following the proof of Lemma 5.1
in [27].
Disjointness In the Disjointness problem, the players receive two sets and have to de-
termine whether they are disjoint or not. More formally, the Disjointness predicate is
deﬁned over X = Y = P([n]) by DISJ
n
(x, y) = 1 iﬀ x and y are disjoint. It is also
convenient to see this predicate as deﬁned over length n inputs, where DISJ
n
(x, y) = 1
for x, y {0, 1}
n
if and only if |{i : x
i
= 1 = y
i
}| = 0. The communication complexity
for DISJ
n
is Ω(n) using a corruption bound [46] and there is a quantum protocol using
O(
n) communication [1]. Combining these results with ours, we obtain the following.
Proposition 5. There is a quantum distribution q
DISJ
Q and an explicit Bell inequal-
ity B satisfying: B(q
DISJ
) = 2
Ω(n)O(
n)
, and for all  L
det
, B() 1.
The proof is deferred to the Appendix (see Section D.1).
Accepted in Quantum 2018-05-12, click title to verify 12
Tribes. Let r 2, n = (2r + 1)
2
. Let TRIBES
n
: {0, 1}
n
× {0, 1}
n
{0, 1} be deﬁned
as: TRIBES
n
(x, y) :=
n
V
i=1
n
W
j=1
(x
(i1)
n+j
y
(i1)
n+j
)
!
. The Tribes function has an
Ω(n) classical lower bound [19] using the smooth rectangle bound and a O(
n(log n)
2
)
quantum protocol [11]. Combining these results with ours, we obtain the following.
Proposition 6. There is a quantum distribution q
TRIBES
Q and an explicit Bell in-
equality B satisfying: B(q
TRIBES
) = 2
Ω(n)O(
n(log n)
2
)
, and for all  L
det
, B() 1.
The proof is deferred to the Appendix (see Section D.2).
Gap Orthogonality. The Gap Orthogonality (ORT) problem was introduced by Sher-
stov as an intermediate step to prove a lower bound for the Gap Hamming Distance (GHD)
problem [48]. We derive an explicit Bell inequality for ORT from Sherstov’s lower bound
of Ω(n), shown in [27] to be a relaxed partition bound. (Applying Corollary 1 also gives
a (nonexplicit) violation for GHD.) The quantum upper bound is O(
n log n) by the
general result of [11]. In the ORT problem, the players receive vectors and need to tell
whether they are nearly orthogonal or far from orthogonal. More formally, we consider the
input space {−1, +1}
n
(to stick to the usual notations for this problem), and we denote
, ·i the scalar product on {−1, +1}
n
. Let ORT
n
: {−1, +1}
n
× {−1, +1}
n
{−1, +1}
be the partial function deﬁned as in [48] by: ORT
n
(x, y) = 1 if |hx, yi|
n, and
ORT
n
(x, y) = +1 if |hx, yi| 2
n. Combining the results mentioned above with ours, we
obtain the following.
Proposition 7. There is a quantum distribution q
ORT
Q and an explicit Bell inequality
B satisfying: B(q
ORT
) = 2
Ω(n)O(
n log n)
, and for all  L
det
, B(`) 1.
The proof is deferred to the Appendix (see Section D.3).
7 Discussion
We have given three main results. First, we showed that normalized Bell inequalities
can be modiﬁed to be bounded in absolute value on the larger set of local distributions
that can abort without signiﬁcantly changing the value of the violations achievable with
nonsignaling distributions. Then, we showed how to derive large ineﬃciency-resistant Bell
violations from any gap between the partition bound and the quantum communication
complexity of some given distribution p. The distributions q achieving the large violations
are relatively simple (only 3 outputs for boolean distributions p) and are resistant to the
addition of white noise to the ideal entangled state giving rise to them. Finally, we
showed how to construct explicit Bell inequalities when the separation between classical
and quantum communication complexity is proven via the corruption bound.
From a practical standpoint, the speciﬁc Bell violations we have studied are prob-
ably not feasible to implement, because the parameters needed are still impractical or
the quantum states are infeasible to implement. However, our results suggest that we
could consider functions with small gaps in communication complexity, in order to ﬁnd
practical Bell inequalities that are robust against uniform noise and detector ineﬃciency.
As an example, let us show how we could design a Bell test from a gap in communica-
tion complexity using our techniques. Consider a boolean function f with a communi-
cation complexity lower bound R
(p
f
) log(eﬀ
(p
f
)) c(n), and accepting a quan-
tum protocol using at most q(n) qubits of communication with error at most
0
< ,
Accepted in Quantum 2018-05-12, click title to verify 13
where n is the size of the inputs. The construction from Theorem 4 then leads to a
Bell inequality B, a quantum state |ψi H
A
H
B
and POVMs {E
a|x
} and {E
b|y
}
over H
A
and H
B
respectively, such that, for any δ
0
, B(q
δ
) 2
c(n)2q(n)
for
q
δ
(a, b|x, y) = tr
h
E
a|x
E
b|y
(1 δ)|ψihψ|+ δ
I
dim(H
A
⊗H
B
)
i
. More precisely, |ψi is ob-
tained by preparing q(n) EPR pairs shared between Alice and Bob, and the POVMs {E
a|x
}
and {E
b|y
} arise from the players performing the local unitaries described by the quantum
protocol together with a total of q(n) local Bell measurements (each qubit communicated
by Alice to Bob in the quantum communication protocol for p
f
will turn into a Bell mea-
surement on Alice’s side, and vice versa on Bob’s side) and a ﬁnal measurement on both
sides to obtain outcomes (a, b) in p
f
. Practically, these measurements will not always be
successful due to the imperfect eﬃciency of the detectors. Suppose that the eﬃciency for
each Bell measurement is η
0
, and that the overall eﬃciency for the ﬁnal measurements is at
least η
2q(n)
0
(these ﬁnal measurements involve 2q(n) qubits, which justiﬁes such an expected
scaling). Therefore, factoring in this eﬃciency and assuming that the noise aﬀecting the
experiment is δ <
0
, the observed Bell value will be
˜
B(q
0
) 2
c(n)2q(n)
η
2q(n)
0
, hence
we still observe a Bell violation (a value
˜
B(q
0
) > 1) as long as n is chosen high enough (or
the detector eﬃciencies are large enough) to have η
0
> 2
(
c(n)
2q(n)
1)
.
The preceding analysis, although accounting for detectors whose eﬃciency decreases
exponentially with the number of EPR measurements q(n), assumes that the (uniform)
δ-noise aﬀects the quantum state both globally and independently of n. This is a quite
standard noise model, used in various studies of Bell inequalities such as [15, 26, 36]. In
a practical scenario, one might nevertheless want to consider an arguably more realistic
noise model where the error increases with the dimension of the global quantum state (this
would happen for example in the case of noisy teleportation, where each individual EPR
pair gets added a maximally mixed state). As is, our construction is not resistant to such
a noise model as it is based on a classical lower bound for bounded-error communication
complexity, which can therefore only tolerate bounded noise. One way around this issue
would be to turn the bounded-error classical lower bound into a bound valid for low
success probabilities using standard ampliﬁcation techniques (see, e.g. [30]). Another
possible solution would be to reduce the noise in the quantum protocol by using quantum
error correction (see, e.g. [41]). We leave these ideas for future work.
Lastly, we comment on upper bounds for the violation of ineﬃciency-resistant Bell
inequalities. First, since (the log of) the eﬃciency bound is a lower bound on commu-
nication complexity, these violations are bounded above by the number of inputs per
side. Next, for dimension d and number of outcomes K, we obtain the upper bound
eﬀ
(q) 2
O((
Kd
)
2
log
2
(K))
for quantum distributions, by combining known bounds. In-
deed, we know that R
(p) O((
Kν(p)
)
2
log
2
(K)) for any p C (see [14]). Combining
this with the bounds eﬀ
(p) 2
R
(p)
(Proposition 2), and ν(q) O(d) for any q Q
(see [23]), gives the desired upper bound. Hence unbounded violations are possible for
K = 3 outputs per side.
Acknowledgments
We would like to acknowledge the following sources of funding for this work: the Euro-
pean Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no.
600700 (QALGO), the Argentinian ANPCyT (PICT-2014-3711), the Laboratoire Inter-
national Associ´ee INFINIS, the Belgian ARC project COPHYMA and the Belgian Fonds
de la Recherche Scientiﬁque - FNRS under grant no. F.4515.16 (QUICTIME), and the
Accepted in Quantum 2018-05-12, click title to verify 14
French ANR Blanc grant RDAM ANR-12-BS02-005.
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