All reports by Author Robin Kothari:

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TR18-156
| 8th September 2018
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Mark Bun, Robin Kothari, Justin Thaler#### Quantum algorithms and approximating polynomials for composed functions with shared inputs

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TR17-169
| 24th October 2017
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Mark Bun, Robin Kothari, Justin Thaler#### The Polynomial Method Strikes Back: Tight Quantum Query Bounds via Dual Polynomials

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TR16-087
| 30th May 2016
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Shalev Ben-David, Robin Kothari#### Randomized query complexity of sabotaged and composed functions

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TR16-072
| 4th May 2016
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Anurag Anshu, Aleksandrs Belovs, Shalev Ben-David, Mika G\"o{\"o}s, Rahul Jain, Robin Kothari, Troy Lee, Miklos Santha#### Separations in communication complexity using cheat sheets and information complexity

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TR15-195
| 3rd December 2015
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Robin Kothari#### Nearly optimal separations between communication (or query) complexity and partitions

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TR15-175
| 5th November 2015
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Scott Aaronson, Shalev Ben-David, Robin Kothari#### Separations in query complexity using cheat sheets

Mark Bun, Robin Kothari, Justin Thaler

We give new quantum algorithms for evaluating composed functions whose inputs may be shared between bottom-level gates. Let $f$ be a Boolean function and consider a function $F$ obtained by applying $f$ to conjunctions of possibly overlapping subsets of $n$ variables. If $f$ has quantum query complexity $Q(f)$, we give ... more >>>

Mark Bun, Robin Kothari, Justin Thaler

The approximate degree of a Boolean function $f$ is the least degree of a real polynomial that approximates $f$ pointwise to error at most $1/3$. The approximate degree of $f$ is known to be a lower bound on the quantum query complexity of $f$ (Beals et al., FOCS 1998 and ... more >>>

Shalev Ben-David, Robin Kothari

We study the composition question for bounded-error randomized query complexity: Is R(f o g) = Omega(R(f) R(g)) for all Boolean functions f and g? We show that inserting a simple Boolean function h, whose query complexity is only Theta(log R(g)), in between f and g allows us to prove R(f ... more >>>

Anurag Anshu, Aleksandrs Belovs, Shalev Ben-David, Mika G\"o{\"o}s, Rahul Jain, Robin Kothari, Troy Lee, Miklos Santha

While exponential separations are known between quantum and randomized communication complexity for partial functions, e.g. Raz [1999], the best known separation between these measures for a total function is quadratic, witnessed by the disjointness function. We give the first super-quadratic separation between quantum and randomized

communication complexity for a ...
more >>>

Robin Kothari

We show a nearly quadratic separation between deterministic communication complexity and the logarithm of the partition number, which is essentially optimal. This improves upon a recent power 1.5 separation of Göös, Pitassi, and Watson (FOCS 2015). In query complexity, we establish a nearly quadratic separation between deterministic (and even randomized) ... more >>>

Scott Aaronson, Shalev Ben-David, Robin Kothari

We show a power 2.5 separation between bounded-error randomized and quantum query complexity for a total Boolean function, refuting the widely believed conjecture that the best such separation could only be quadratic (from Grover's algorithm). We also present a total function with a power 4 separation between quantum query complexity ... more >>>