77 | Making quantum computing practical: reducing noise and overhead through intelligent circuit cutting

Abstract

Noise in current quantum devices poses a major obstacle to running large and meaningful quantum algorithms. One promising approach to overcome hardware limitations is circuit cutting, where large quantum circuits are decomposed into smaller pieces that can be executed more reliably. However, this comes at a cost: the number of required circuit executions can grow exponentially with the number of cuts, making naïve approaches impractical. In this talk, we explore two complementary directions that make circuit cutting significantly more efficient and practical on today’s quantum hardware. First, we show how combining circuit cutting with operator backpropagation (OBP) can strategically reduce circuit depth, thus controlling the growth in execution overhead. Our approach formulates this as an optimization problem, enabling substantial reductions in resource requirements for common quantum workloads without sacrificing accuracy. Building on this, we examine a key real-world insight: noise in quantum hardware is not uniform. We present a noise-aware framework that uses this structure to guide circuit cutting strategies. By aligning subcircuits with low-noise regions and carefully relaxing device constraints, we show that it is possible to achieve dramatic reductions in execution cost while preserving fidelity, even for larger systems where standard methods break down. Together, these works highlight a broader message: making quantum computing practical is not only about better hardware alone, but also about smarter ways of adapting algorithms to real devices. The talk will introduce the key ideas intuitively, discuss the main techniques, and provide insights into how theory and systems considerations come together in modern quantum computing research.

Speaker Bio

Dr. Ritajit Majumdar is a Research Scientist at IBM Quantum, based at the IBM India Research Lab. He is part of the Quantum Algorithms and Engineering team, where he collaborates with researchers to advance utility-scale applications using IBM Quantum technologies. He, along with some other researchers, demonstrated the first potential quantum advantage candidate from India. He holds a PhD from the Indian Statistical Institute, during which he spent a significant period as a visiting scholar at the IBM T. J. Watson Research Centre in New York with the prestigious Fulbright-Nehru Doctoral Research Fellowship. He is a recipient of the Gold Medal from the University of Calcutta for his Master's degree and was awarded the esteemed DST INSPIRE Fellowship. In addition to his work at IBM, he has contributed to academia as both a full-time and part-time faculty member under the University of Calcutta and the West Bengal University of Technology.