6 citations · 7 across the 13 of their papers we have counts for
16 papers
No Tile Left Behind: Multiprogramming for Surface-Code Architectures
Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh
Fault-tolerant quantum computing (FTQC) is emerging as the architectural regime in which practical large-scale quantum workloads will execute. In this setting, however, multiprogra…
Rings Around the Ancilla: A Workload-Aware FTQC Architecture
Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh
Obtaining a quantum advantage in practical applications over classical machines requires a fault-tolerant model of computation. However, the resource overhead of developing a fault…
A Graph-Based Forensic Framework for Inferring Hardware Noise of Cloud Quantum Backend
Subrata Das, Archisman Ghosh, Swaroop Ghosh
Cloud quantum platforms give users access to many backends with different qubit technologies, coupling layouts, and noise levels. The execution of a circuit, however, depends on in…
Design Automation in Quantum Error Correction
Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh
Quantum error correction (QEC) underpins practical fault-tolerant quantum computing (FTQC) by addressing the fragility of quantum states and mitigating decoherence-induced errors.…
Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
Archisman Ghosh, Satwik Kundu, Swaroop Ghosh
Quantum Machine Learning (QML) integrates quantum computing with classical machine learning, primarily to solve classification, regression and generative tasks. However, its rapid…
Capturing Quantum Snapshots from a Single Copy via Mid-Circuit Measurement and Dynamic Circuit
Debarshi Kundu, Avimita Chatterjee, Archisman Ghosh +1
We propose Quantum Snapshot with Dynamic Circuit (QSDC), a hardware-agnostic, learning-driven framework for capturing quantum snapshots: non-destructive estimates of quantum states…
Survival of the Optimized: An Evolutionary Approach to T-depth Reduction
Archisman Ghosh, Avimita Chatterjee, Swaroop Ghosh
Quantum Error Correction (QEC) is the cornerstone of practical Fault-Tolerant Quantum Computing (FTQC), but incurs enormous resource overheads. Circuits must decompose into Cliffor…
The Art of Optimizing T-Depth for Quantum Error Correction in Large-Scale Quantum Computing
Avimita Chatterjee, Archisman Ghosh, Swaroop Ghosh
Quantum Error Correction (QEC), combined with magic state distillation, ensures fault tolerance in large-scale quantum computation. To apply QEC, a circuit must first be transforme…
The Q-Spellbook: Crafting Surface Code Layouts and Magic State Protocols for Large-Scale Quantum Computing
Avimita Chatterjee, Archisman Ghosh, Swaroop Ghosh
Quantum error correction is a cornerstone of reliable quantum computing, with surface codes emerging as a prominent method for protecting quantum information. Surface codes are eff…
Forensics of Transpiled Quantum Circuits
Rupshali Roy, Archisman Ghosh, Swaroop Ghosh
Many third-party cloud providers set up quantum hardware as a service that includes a wide range of qubit technologies and architectures to maximize performance at minimal cost. Ho…
Optimizing Quantum Embedding using Genetic Algorithm for QML Applications
Koustubh Phalak, Archisman Ghosh, Swaroop Ghosh
Quantum Embeddings (QE) are essential for loading classical data into quantum systems for Quantum Machine Learning (QML). The performance of QML algorithms depends on the type of Q…
Quantum Prometheus: Defying Overhead with Recycled Ancillas in Quantum Error Correction
Avimita Chatterjee, Archisman Ghosh, Swaroop Ghosh
Quantum error correction (QEC) is crucial for ensuring the reliability of quantum computers. However, implementing QEC often requires a significant number of qubits, leading to sub…
AI-driven Reverse Engineering of QML Models
Archisman Ghosh, Swaroop Ghosh
Quantum machine learning (QML) is a rapidly emerging area of research, driven by the capabilities of Noisy Intermediate-Scale Quantum (NISQ) devices. With the progress in the resea…
The Quantum Imitation Game: Reverse Engineering of Quantum Machine Learning Models
Archisman Ghosh, Swaroop Ghosh
Quantum Machine Learning (QML) amalgamates quantum computing paradigms with machine learning models, providing significant prospects for solving complex problems. However, with the…
Guardians of the Quantum GAN
Archisman Ghosh, Debarshi Kundu, Avimita Chatterjee +1
Quantum Generative Adversarial Networks (qGANs) are at the forefront of image-generating quantum machine learning models. To accommodate the growing demand for Noisy Intermediate-S…
Application of Quantum Tensor Networks for Protein Classification
Debarshi Kundu, Archisman Ghosh, Srinivasan Ekambaram +3
We show that protein sequences can be thought of as sentences in natural language processing and can be parsed using the existing Quantum Natural Language framework into parameteri…