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Exponential Separation between Quantum and Classical Ordered Binary Decision Diagrams, Reordering Method and Hierarchies

机译:量子和经典有序二元决策图之间的指数分离,重排序方法和层次结构

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In this paper, we study quantum OBDD model, it is a restricted version of read-once quantum branching programs, with respect to "width" complexity. It is known that the maximal gap between deterministic and quantum complexities is exponential. But there are few examples of functions with such a gap. We present a method (called "reordering"), which allows us to transform a Boolean function f into a Boolean function f , such that if for f we have some gap between quantum and deterministic OBDD complexities for the natural order over the variables of f , then for any order we have almost the same gap for the function f . Using this transformation, we construct a total function REQ such that the deterministic OBDD complexity of it is at least 2 ( n log n ) , and the quantum OBDD complexity of it is at most O ( n 2 ) . It is the biggest known gap for explicit functions not representable by OBDDs of a linear width. We also prove the quantum OBDD width hierarchy for complexity classes of Boolean functions. Additionally, we show that shifted equality function can also give a good gap between quantum and deterministic OBDD complexities.Moreover, we prove the bounded error probabilistic OBDD width hierarchy for complexity classes of Boolean functions. And using "reordering" method we extend a hierarchy for k-OBDDs of polynomial width, for k = o ( n log 3 n ) . We prove a similar hierarchy for bounded error probabilistic k-OBDDs of polynomial, superpolynomial and subexponential width.
机译:在本文中,我们研究了量子OBDD模型,它是关于“宽度”复杂度的一次读取量子分支程序的受限版本。众所周知,确定性和量子复杂性之间的最大差距是指数的。但是,很少有功能有这样的差距的例子。我们提出了一种方法(称为“重新排序”),该方法允许我们将布尔函数f转换为布尔函数f,这样,对于f,对于f的自然阶,对于f,我们在量子和确定性OBDD复杂度之间有一定的差距,那么对于任何顺序,函数f的间隙几乎相同。使用此变换,我们构造了一个总函数REQ,使得它的确定性OBDD复杂度至少为2(n log n),而其量子OBDD复杂度最多为O(n 2)。对于不能由线性宽度的OBDD表示的显式函数,这是最大的已知间隙。我们还证明了布尔函数的复杂性类别的量子OBDD宽度层次。此外,我们证明了移位等式函数还可以在量子和确定性OBDD复杂度之间提供良好的差距。此外,我们证明了布尔函数的复杂度类别的有界误差概率OBDD宽度层次结构。并使用“重新排序”方法,针对k = o(n log 3 n)扩展了多项式宽度的k-OBDD的层次结构。我们证明了多项式,超多项式和次指数宽度的有界误差概率k-OBDD的相似层次结构。

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