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Not all contracts are good, but all good contracts can be expressed as a finite-state transition system ("State-Transition Contracts"). Contracts that can be represented as State-Transition Contracts discretize fat-tailed risk to…

Formal Languages and Automata Theory · Computer Science 2023-02-02 J. Nathaniel Holmes , Homayoon Beigi

We give new bounds on the circuit complexity of the quantum Fourier transform (QFT). We give an upper bound of O(log n + log log (1/epsilon)) on the circuit depth for computing an approximation of the QFT with respect to the modulus 2^n…

Quantum Physics · Physics 2007-05-23 Richard Cleve , John Watrous

Finite-state transducers give efficient representations of many Natural Language phenomena. They allow to account for complex lexicon restrictions encountered, without involving the use of a large set of complex rules difficult to analyze.…

cmp-lg · Computer Science 2008-02-03 Mehryar Mohri

Pebble transducers are nested two-way transducers which can drop marks (named "pebbles") on their input word. Blind transducers have been introduced by Nguy\^en et al. as a subclass of pebble transducers, which can nest two-way transducers…

Formal Languages and Automata Theory · Computer Science 2022-10-03 Gaëtan Douéneau-Tabot

When designing quantum circuits for a given unitary, it can be much cheaper to achieve a good approximation on most inputs than on all inputs. In this work we formalize this idea, and propose that such "optimistic quantum circuits" are…

We describe the low-temperature optical conductivity as a function of frequency for a quantum-mechanical system of electrons that hop along a polymer chain. To this end, we invoke the Su-Schrieffer-Heeger \emph{tight-binding} Hamiltonian…

Mathematical Physics · Physics 2022-09-28 Dionisios Margetis , Alexander B. Watson , Mitchell Luskin

Modern large language models (LLMs) excel at tasks that require storing and retrieving knowledge, such as factual recall and question answering. Transformers are central to this capability because they can encode information during training…

Machine Learning · Statistics 2026-03-18 Nuri Mert Vural , Alberto Bietti , Mahdi Soltanolkotabi , Denny Wu

We present a transductive learning algorithm that takes as input training examples from a distribution $P$ and arbitrary (unlabeled) test examples, possibly chosen by an adversary. This is unlike prior work that assumes that test examples…

Machine Learning · Computer Science 2020-10-01 Shafi Goldwasser , Adam Tauman Kalai , Yael Tauman Kalai , Omar Montasser

We prove that transformers can exactly interpolate datasets of finite input sequences in $\mathbb{R}^d$, $d\geq 2$, with corresponding output sequences of smaller or equal length. Specifically, given $N$ sequences of arbitrary but finite…

Machine Learning · Computer Science 2026-05-14 Albert Alcalde , Giovanni Fantuzzi , Enrique Zuazua

Force detectors rely on resonators to transduce forces into a readable signal. Usually these resonators operate in the linear regime and their signal appears amidst a competing background comprising thermal or quantum fluctuations as well…

Mesoscale and Nanoscale Physics · Physics 2018-07-04 A. Eichler , T. L. Heugel , A. Leuch , C. L. Degen , R. Chitra , O. Zilberberg

As a generalization of the sum of digits function and other digital sequences, sequences defined as the sum of the output of a transducer are asymptotically analyzed. The input of the transducer is a random integer in $[0, N)$. Analogues in…

Combinatorics · Mathematics 2015-09-16 Clemens Heuberger , Sara Kropf , Helmut Prodinger

Decision trees are one of the most fundamental computational models for computing Boolean functions $f : \{0, 1\}^n \mapsto \{0, 1\}$. It is well-known that the depth and size of decision trees are closely related to time and number of…

Computational Complexity · Computer Science 2025-01-03 Deepu Benson , Balagopal Komarath , Jayalal Sarma , Nalli Sai Soumya

We continue the study of the approximate $k$-wise independence of random reversible circuits as permutations of $\{\pm1\}^n$. Our main result is the first construction of a natural class of random reversible circuits with a sublinear-in-$n$…

Computational Complexity · Computer Science 2025-02-13 William Gay , William He , Nicholas Kocurek

A notorious open question in circuit complexity is whether Boolean operations of arbitrary arity can efficiently be expressed using modular counting gates only. H{\aa}stad's celebrated switching lemma yields exponential lower bounds for the…

Computational Complexity · Computer Science 2026-04-07 Benedikt Pago

We establish new separations between the power of monotone and general (non-monotone) Boolean circuits: - For every $k \geq 1$, there is a monotone function in ${\sf AC^0}$ that requires monotone circuits of depth $\Omega(\log^k n)$. This…

Computational Complexity · Computer Science 2023-05-12 Bruno P. Cavalar , Igor C. Oliveira

Superconducting circuits consisting of a few low-anharmonic transmons coupled to readout and bus resonators can perform basic quantum computations. Since the number of qubits in such circuits is limited to not more than a few tens, the…

Mesoscale and Nanoscale Physics · Physics 2019-07-18 Mohammad H. Ansari

This paper presents an efficient algorithm for the incremental construction of a minimal acyclic sequential transducer (ST) for a dictionary consisting of a list of input and output strings. The algorithm generalises a known method of…

Computation and Language · Computer Science 2007-05-23 Wojciech Skut

A model of computation that is widely used in the formal analysis of reactive systems is symbolic algorithms. In this model the access to the input graph is restricted to consist of symbolic operations, which are expensive in comparison to…

Data Structures and Algorithms · Computer Science 2017-11-28 Krishnendu Chatterjee , Wolfgang Dvořák , Monika Henzinger , Veronika Loitzenbauer

Large Transformer models routinely achieve state-of-the-art results on a number of tasks but training these models can be prohibitively costly, especially on long sequences. We introduce two techniques to improve the efficiency of…

Machine Learning · Computer Science 2020-02-19 Nikita Kitaev , Łukasz Kaiser , Anselm Levskaya

Proving complexity lower bounds remains a challenging task: we only know how to prove conditional uniform lower bounds and nonuniform lower bounds in restricted circuit models. Williams (STOC 2010) showed how to derive nonuniform lower…

Computational Complexity · Computer Science 2026-03-10 Nikolai Chukhin , Alexander S. Kulikov , Ivan Mihajlin , Arina Smirnova