Blogs

Quantum sensing and imaging have emerged as two of the most experimentally mature branches of quantum technology. Unlike universal quantum computing, which still faces formidable scalability challenges, experimental quantum sensors are already delivering performance beyond classical limits in magnetometry, gravimetry, time-keeping, and biological imaging. These advances are rooted in exploiting uniquely quantum resources like superposition, entanglement, squeezing, and single-photon detection to enhance measurement precision and spatial resolution. This blog provides an experimental perspective on quantum sensing and imaging, highlighting physical platforms, measurement protocols, and real-world applications. 1. Quantum Advantage in Metrology: From SQL to Heisenberg Scaling Classical sensors are fundamentally limited by the Standard Quantum Limit (SQL), where measurement precision scales as    with N  being the number of probe particles (photons or atoms). Quantum...

Quantum computing is often introduced through qubits, superposition, and entanglement, but the true enabler of practical quantum computation lies in quantum software and communication layers. At the heart of this stack sits QASM (Quantum Assembly Language), a low-level, hardware-near language that bridges abstract quantum algorithms and physical quantum processors. Just as classical assembly language connects high-level code to silicon, QASM defines how quantum instructions are communicated, optimized, and executed on real quantum hardware. Why Quantum Software Needs a Specialized Language Quantum algorithms are typically designed using high-level frameworks that resemble classical programming paradigms. However, quantum hardware operates under strict physical constraints: gate fidelities, coherence times, qubit connectivity, and control pulse timing. High-level abstractions alone cannot efficiently communicate these requirements to hardware. This is where QASM becomes essentia...

Quantum computing represents a paradigm shift in how we process information. Instead of relying on classical bits that take values of either 0 or 1, quantum computers use quantum bits (qubits), which exploit the principles of quantum mechanics superposition, entanglement, and interference. These principles enable quantum computers to tackle certain problems far more efficiently than classical machines. At the heart of this power lie quantum algorithms, and one of the most widely used frameworks to design and run them today is Qiskit. This blog introduces the foundations of quantum computing, explores key quantum algorithms, and explains how Qiskit bridges theory and real quantum hardware. Quantum Computing in Brief A qubit can exist in a superposition of |0 ⟩ and |1 ⟩ states, described by a complex probability amplitude. When multiple qubits are combined, the resulting system spans an exponentially large Hilbert space. This allows quantum computers to represent and manipulate i...