activity
20162025
most citedGrover Mixers for QAOA: Shifting Complexity from Mixer Design to State Preparation

110 citations · 344 across the 14 of their papers we have counts for

collaborators

15 papers

cs.CL2025

Quantum Graph Transformer for NLP Sentiment Classification

Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy +1

Quantum machine learning is a promising direction for building more efficient and expressive models, particularly in domains where understanding complex, structured data is critica…

quant-ph2023★ 5 cited

Predicting Expressibility of Parameterized Quantum Circuits using Graph Neural Network

Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy +2

Parameterized Quantum Circuits (PQCs) are essential to quantum machine learning and optimization algorithms. The expressibility of PQCs, which measures their ability to represent a…

quant-ph2022★ 3 cited

Optimized Telecloning Circuits: Theory and Practice of Nine NISQ Clones

Elijah Pelofske, Andreas Bärtschi, Stephan Eidenbenz

Although perfect copying of an unknown quantum state is not possible, approximate cloning is possible in quantum mechanics. Quantum telecloning is a variant of approximate quantum…

quant-ph2022★ 44 cited

Short-Depth Circuits for Dicke State Preparation

Andreas Bärtschi, Stephan Eidenbenz

We present short-depth circuits to deterministically prepare any Dicke state |Dn,k>, which is the equal-amplitude superposition of all n-qubit computational basis states with Hammi…

quant-ph2022★ 6 cited

Quantum Telecloning on NISQ Computers

Elijah Pelofske, Andreas Bärtschi, Bryan Garcia +2

Due to the no-cloning theorem, generating perfect quantum clones of an arbitrary unknown quantum state is not possible, however approximate quantum clones can be constructed. Quant…

quant-ph2022★ 23 cited

Numerical Evidence for Exponential Speed-up of QAOA over Unstructured Search for Approximate Constrained Optimization

John Golden, Andreas Bärtschi, Stephan Eidenbenz +1

Despite much recent work, the true promise and limitations of the Quantum Alternating Operator Ansatz (QAOA) are unclear. A critical question regarding QAOA is to what extent its p…

quant-ph2021★ 27 cited

Sampling on NISQ Devices: "Who's the Fairest One of All?"

Elijah Pelofske, John Golden, Andreas Bärtschi +2

Modern NISQ devices are subject to a variety of biases and sources of noise that degrade the solution quality of computations carried out on these devices. A natural question that…

quant-ph2021★ 23 cited

Threshold-Based Quantum Optimization

John Golden, Andreas Bärtschi, Daniel O'Malley +1

We propose and study Th-QAOA (pronounced Threshold QAOA), a variation of the Quantum Alternating Operator Ansatz (QAOA) that replaces the standard phase separator operator, which e…

quant-ph2021★ 14 cited

Fair Sampling Error Analysis on NISQ Devices

John Golden, Andreas Bärtschi, Daniel O'Malley +1

We study the status of fair sampling on Noisy Intermediate Scale Quantum (NISQ) devices, in particular the IBM Q family of backends. Using the recently introduced Grover Mixer-QAOA…

quant-ph2020★ 110 cited

Grover Mixers for QAOA: Shifting Complexity from Mixer Design to State Preparation

Andreas Bärtschi, Stephan Eidenbenz

We propose GM-QAOA, a variation of the Quantum Alternating Operator Ansatz (QAOA) that uses Grover-like selective phase shift mixing operators. GM-QAOA works on any NP optimization…

quant-ph2019★ 55 cited

The Quantum Alternating Operator Ansatz on Maximum k-Vertex Cover

Jeremy Cook, Stephan Eidenbenz, Andreas Bärtschi

The Quantum Alternating Operator Ansatz is a generalization of the Quantum Approximate Optimization Algorithm (QAOA) designed for finding approximate solutions to combinatorial opt…

cs.GT2017★ 8 cited

Truthful Mechanisms for Delivery with Mobile Agents

Andreas Bärtschi, Daniel Graf, Paolo Penna

We study the game-theoretic task of selecting mobile agents to deliver multiple items on a network. An instance is given by messages (physical objects) which have to be transpo…

cs.DS2016

Energy-efficient Delivery by Heterogeneous Mobile Agents

Andreas Bärtschi, Jérémie Chalopin, Shantanu Das +4

We consider the problem of delivering messages between specified source-target pairs in a weighted undirected graph, by mobile agents initially located at distinct nodes of…

cs.DS2016★ 25 cited

Collaborative Delivery with Energy-Constrained Mobile Robots

Andreas Bärtschi, Jérémie Chalopin, Shantanu Das +5

We consider the problem of collectively delivering some message from a specified source to a designated target location in a graph, using multiple mobile agents. Each agent has a l…

cs.DS2016★ 1 cited

On computing the total displacement number via weighted Motzkin paths

Andreas Bärtschi, Barbara Geissmann, Daniel Graf +3

Counting the number of permutations of a given total displacement is equivalent to counting weighted Motzkin paths of a given area (Guay-Paquet and Petersen, 2014). The former comb…