49 citations · 68 across the 15 of their papers we have counts for
15 papers
AutoQuREO: A Framework for Automated Quantum Resource Estimation and Optimization
Harshkumar Oza, Aritra Sarkar, Syed Naqi Abbas +4
As quantum computing progresses from proof-of-principle demonstrations toward practical utility, a significant impediment is the need to augment algorithmic feasibility with system…
DeComp2: Description Complexity aware Decomposition
Aritra Sarkar
Quantum compilers optimize execution-only proxies such as gate count, depth, and fidelity, treating the compiled circuit as the unit of cost. This conflates two distinct resources,…
From Characterization To Construction: Generative Quantum Circuit Synthesis from Gate Set Tomography Data
King Yiu Yu, Aritra Sarkar, Erbing Hua +3
High-fidelity circuit execution on noisy intermediate-scale quantum devices is bottlenecked by compilation pipelines that disregard complex, correlated noise. To address this, this…
EQISA: Energy-efficient Quantum Instruction Set Architecture using Sparse Dictionary Learning
Sibasish Mishra, Aritra Sarkar, Sebastian Feld
The scalability of quantum computing in supporting sophisticated algorithms critically depends not only on qubit quality and error handling, but also on the efficiency of classical…
DeQompile: quantum circuit decompilation using genetic programming for explainable quantum architecture search
Shubing Xie, Aritra Sarkar, Sebastian Feld
Demonstrating quantum advantage using conventional quantum algorithms remains challenging on current noisy gate-based quantum computers. Automated quantum circuit synthesis via qua…
CutQAS: Topology-aware quantum circuit cutting via reinforcement learning
Abhishek Sadhu, Aritra Sarkar, Akash Kundu
Simulating molecular systems on quantum processors has the potential to surpass classical methods in computational resource efficiency. The limited qubit connectivity, small proces…
Near-Term Spin-Qubit Architecture Design via Multipartite Maximally-Entangled States
Nikiforos Paraskevopoulos, Matthew Steinberg, Brennan Undseth +4
The design and benchmarking of quantum computer architectures traditionally rely on practical hardware restrictions, such as gate fidelities, control, and cooling. At the theoretic…
EO-GRAPE and EO-DRLPE: Open and Closed Loop Approaches for Energy Efficient Quantum Optimal Control
Sebastiaan Fauquenot, Aritra Sarkar, Sebastian Feld
This research investigates the possibility of using quantum optimal control techniques to co-optimize the energetic cost and the process fidelity of a quantum unitary gate. The ene…
LEGO_HQEC: Automating the Analysis, Construction, and Decoding of Holographic Quantum Codes
Junyu Fan, Matthew Steinberg, Alexander Jahn +3
Quantum error correction (QEC) is a crucial prerequisite for future large-scale quantum computation. Finding and analyzing new QEC codes, along with efficient decoding and fault-to…
ArtA: Automating Design Space Exploration of Spin Qubit Architectures
Nikiforos Paraskevopoulos, David Hamel, Aritra Sarkar +2
In the fast-paced field of quantum computing, identifying the architectural characteristics that will enable quantum processors to achieve high performance across a diverse range o…
YAQQ: Yet Another Quantum Quantizer -- Design Space Exploration of Quantum Gate Sets using Novelty Search
Aritra Sarkar, Akash Kundu, Matthew Steinberg +5
In the standard circuit model of quantum computation, the number and quality of the quantum gates composing the circuit influence the runtime and fidelity of the computation. The f…
KANQAS: Kolmogorov-Arnold Network for Quantum Architecture Search
Akash Kundu, Aritra Sarkar, Abhishek Sadhu
Quantum architecture Search (QAS) is a promising direction for optimization and automated design of quantum circuits towards quantum advantage. Recent techniques in QAS emphasize M…
Transformer Models for Quantum Gate Set Tomography
King Yiu Yu, Aritra Sarkar, Maximilian Rimbach-Russ +2
Quantum computation represents a promising frontier in the domain of high-performance computing, blending quantum information theory with practical applications to overcome the lim…
A quantum information theoretic analysis of reinforcement learning-assisted quantum architecture search
Abhishek Sadhu, Aritra Sarkar, Akash Kundu
In the field of quantum computing, variational quantum algorithms (VQAs) represent a pivotal category of quantum solutions across a broad spectrum of applications. These algorithms…
KetGPT - Dataset Augmentation of Quantum Circuits using Transformers
Boran Apak, Medina Bandic, Aritra Sarkar +1
Quantum algorithms, represented as quantum circuits, can be used as benchmarks for assessing the performance of quantum systems. Existing datasets, widely utilized in the field, su…