Sonicium Quantum Lab Ltd

Sonicium Quantum Lab Ltd Bangladesh's pioneering quantum computing platform. Join the future of computing in South Asia.

From DNA analysis to cybersecurity, harness the power of quantum algorithms to solve complex problems that classical computers cannot.

18/09/2026

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QUANTUM COMPUTING WORKSHOP IN BANGLADESH  🌐 Quantum Computing in Action: Live Applications & Industry IntegrationSoniciu...
16/09/2026

QUANTUM COMPUTING WORKSHOP IN BANGLADESH

🌐 Quantum Computing in Action: Live Applications & Industry Integration

Sonicium Quantum Lab is hosting a special online Quantum Computing Workshop, where participants will learn from the fundamentals all the way to executing circuits on real quantum hardware.

đŸ”Ŧ What you’ll learn
✅ Quantum Computing Fundamentals
✅ Qubits, Quantum Gates & Circuits
✅ Hands-on Qiskit Programming
✅ Build & Run Quantum Circuits
✅ Execute Circuits on Real Quantum Hardware
✅ Quantum Applications & Industry Integration

📅 Date: Saturday, 19 September 2026
⏰ Time: 10:00 PM — Bangladesh Time
đŸ’ģ Format: Live Online

đŸŽ¯ Who can join
Students â€ĸ Researchers â€ĸ Developers â€ĸ Technology Enthusiasts â€ĸ Entrepreneurs â€ĸ Professionals

No advanced quantum computing background is required.

👤 Special Guest
Hussain Billah
Chairman, Sonicium Quantum Lab Limited

🇧🇩 Start your quantum computing journey from Bangladesh.

📱 Registration
Fill out the form and share your WhatsApp number to receive workshop updates and access details.
👉 https://forms.gle/bJ18pJ2mrqknx7Ds5

Organized by Sonicium Quantum Lab Ltd.
đŸ”Ŧ Exploring the Future of Quantum Computing

Post 4 — Measurement: From Superposition to Usable Random BitsThe final layer of our 5-qubit QRNG circuit is measurement...
05/09/2026

Post 4 — Measurement: From Superposition to Usable Random Bits

The final layer of our 5-qubit QRNG circuit is measurement — the MEA operation applied to all five qubits, q0 through q4. This is the moment where everything built up in the superposition and entanglement layers gets converted into something we can actually use: classical, physical random bits.

Up until measurement, the five qubits exist in a quantum superposition of multiple possible outcomes simultaneously — a state that has no classical analogue. The instant we measure, that superposition "collapses." Each qubit resolves to a definite classical value, 0 or 1, and because of the entanglement we built with the CNOT gates, those outcomes aren't fully independent: q0, q1, and q4 will always agree with each other, and q2 and q3 will always agree with each other, while the pair (q0/q1/q4) and the pair (q2/q3) are independent of one another. Run the circuit many times, and you get a stream of correlated-yet-unpredictable 5-bit strings — raw material for a random number stream.

This is fundamentally different from how a classical computer generates "random" numbers. Standard pseudorandom number generators (PRNGs) use a deterministic mathematical formula and a starting seed value. Give the same seed to the same algorithm twice, and you get the exact same sequence of numbers both times — every time. That's fine for a lot of everyday use cases like shuffling a playlist, but it's a serious weakness anywhere unpredictability actually matters for security: if an attacker can guess or reconstruct your seed, they can predict your "random" output. Quantum measurement doesn't have this problem.

The outcome isn't computed from a formula — it's a physical event whose result is not determined in advance by any prior state, seed, or hidden variable that we know of. That's what "true randomness" means in this context.
This property is exactly why QRNGs matter in the real world. Cryptographic key generation — the foundation of secure communications, banking systems, and digital signatures — depends on unpredictable keys; a compromised RNG can compromise an entire security system, regardless of how strong the encryption algorithm itself is. Scientific simulations that rely on Monte Carlo methods need high-quality randomness to avoid subtle statistical bias creeping into results.

Fair gaming and lottery systems need randomness that can be proven not to favor any outcome. And emerging quantum key distribution (QKD) protocols use exactly this kind of quantum randomness as a core ingredient.
Our 5-qubit circuit is a compact, understandable demonstration of the full pipeline: superposition creates uncertainty, entanglement structures it, and measurement extracts it as usable classical data.

It's a small circuit, but every quantum random number generator — from a research lab bench to a commercial hardware QRNG chip — is built on exactly this same sequence of steps, just scaled up and hardened against physical noise.
In our final post in this series, we'll zoom out and talk about what this project means for Sonicium Quantum Lab and what's coming next.

Entanglement: Linking Qubits With CNOT GatesAfter the layer of Hadamard gates, our 5-qubit QRNG circuit applies three CN...
04/09/2026

Entanglement: Linking Qubits With CNOT Gates

After the layer of Hadamard gates, our 5-qubit QRNG circuit applies three CNOT (controlled-NOT) gates: q0 controls q1, q2 controls q3, and q1 controls q4.
This is the entanglement layer, and it's where the circuit becomes genuinely quantum in a way that goes beyond what five independent coin flips could give you.
A CNOT gate works on two qubits — a control and a target. If the control qubit is in state |1⟩, the target qubit is flipped; if the control is |0⟩, the target is left alone.

That sounds like ordinary classical logic (it's the same truth table as an XOR), but because our control qubits are in superposition after the Hadamard layer — not simply 0 or 1, but both at once — the CNOT gate doesn't just flip a bit. It creates entanglement: a correlation between qubits that has no classical equivalent.

Look at the first pair: q0 and q1. Before the CNOT, both are in independent 50/50 superpositions. After CNOT(q0→q1), the two qubits become entangled such that when they are eventually measured, their outcomes will always agree — both 0 or both 1 — even though, individually, each still has a 50% chance of being either value.

Neither outcome is decided until measurement, but the two are now linked. The same thing happens between q2 and q3.
Then the circuit does something more interesting: it applies CNOT(q1→q4). Since q1 is already entangled with q0, this gate pulls q4 into that same correlated group.

The result is a three-qubit entangled cluster — q0, q1, and q4 — that will always agree with each other on measurement, structurally similar to what's known in quantum information theory as a GHZ-like state. Meanwhile, q2 and q3 remain a separate, independent entangled pair.
Why build this structure into a random number generator at all, rather than just using five independent H-gate-and-measure qubits? A few reasons.

First, entanglement is a genuinely quantum resource — building circuits that exercise it, even in a randomness-generation context, is valuable for testing and characterizing how well a quantum processor preserves these correlations, which matters far beyond QRNG. Second, structured entanglement patterns like this are the same primitive building blocks used in quantum error correction, quantum key distribution protocols, and more advanced sampling circuits — so a QRNG circuit like this doubles as a compact testbed for verifying that entangling operations behave as expected before they're used in larger algorithms.

In short: the Hadamard layer gives us uncertainty, and the CNOT layer gives that uncertainty structure — linking specific qubits together into correlated groups rather than leaving all five as isolated, unconnected coin flips.

Next up: what actually happens at the MEA (measurement) layer, and how five entangled qubits collapse into the random bits we actually use.

Why Randomness Starts With a Hadamard GateEvery quantum circuit tells a story in layers, and the first layer of our 5-qu...
03/09/2026

Why Randomness Starts With a Hadamard Gate
Every quantum circuit tells a story in layers, and the first layer of our 5-qubit QRNG circuit is the most important one: five Hadamard (H) gates, one applied to each qubit.

Before any gate is applied, every qubit in our circuit starts in a well-defined, classical-like state: |0⟩. In this state, if you were to measure the qubit right now, you would get "0" with 100% certainty. There's nothing random about it yet — it behaves exactly like a classical bit.

The Hadamard gate changes that completely. Applying H to a qubit in the |0⟩ state creates an equal superposition of |0⟩ and |1⟩. In plain terms: the qubit no longer "is" a 0 or a 1. It exists in a combined state where, upon measurement, it has exactly a 50% chance of collapsing to 0 and a 50% chance of collapsing to
1. This is not a probability distribution we've assigned out of ignorance — the outcome genuinely is not determined until the measurement happens.

That's the difference between quantum uncertainty and classical uncertainty, and it's the entire foundation of quantum random number generation.

In our circuit, we apply this Hadamard gate to all five qubits — q0 through q4 — simultaneously, in the very first layer. After this step, we have five qubits, each in an independent 50/50 superposition. If we measured right here, we'd already get five genuinely random classical bits. In fact, a single-qubit QRNG built from just one H gate and one measurement is a perfectly valid (if minimal) random number generator — some early QRNG hardware devices work exactly this way.

So why does our circuit use five qubits and add more gates after this? Because a single H-gate-and-measure circuit, while random, can be sensitive to small hardware biases — imperfections in how a real quantum processor implements the H gate can introduce tiny statistical skews into the output. Scaling up to multiple qubits and adding entangling operations (which we'll cover in our next post) is one way to build in redundancy and structure that can help characterize these effects, especially when circuits like this are eventually run on real quantum hardware rather than a simulator.
For now, the key takeaway is this:

superposition via the Hadamard gate is the seed of quantum randomness. Everything else in the circuit — the entangling CNOT gates and the final measurement — builds on top of the uncertainty this single gate introduces. Without it, there is no randomness to extract at all.

In our next post, we'll look at the three CNOT gates in the circuit and explain why we chose to link q0→q1, q2→q3, and q1→q4 specifically, rather than leaving all five qubits independent.

Introducing Circuit The 5-Qubit QRNGWe just designed our first publicly shared quantum circuit at Sonicium Quantum Lab —...
03/09/2026

Introducing Circuit

The 5-Qubit QRNG
We just designed our first publicly shared quantum circuit at Sonicium Quantum Lab — a 5-qubit Quantum Random Number Generator (QRNG). This is circuit #1 in a series of 15 circuits we're breaking down publicly, and we wanted to start with one of the most fundamental building blocks in quantum computing: true randomness.
Why start here? Because randomness quietly underpins an enormous amount of the digital world. Every cryptographic key, every secure session, every Monte Carlo simulation, every fair lottery draw depends on numbers that are genuinely unpredictable.

Classical computers cannot produce true randomness — pseudorandom number generators (PRNGs) rely on deterministic algorithms and a seed value, which means that, in principle, if you know the algorithm and the seed, you can predict every number that comes out. That is a real vulnerability in high-stakes applications.

Quantum mechanics gives us something classical computing cannot: randomness that is fundamentally, physically unpredictable — not just computationally hard to predict, but truly probabilistic at the level of nature itself.

Our 5-qubit QRNG circuit, shown above, is a compact demonstration of how this works in practice. It uses five qubits — q0 through q4 — each starting in the |0⟩ state. The circuit has a depth of just 4, meaning only four "layers" of operations are needed to generate high-quality random bits. Despite its simplicity, the circuit combines three core quantum operations that are essential across almost all quantum algorithms: superposition (via Hadamard gates), entanglement (via CNOT gates), and measurement.

Over the next few posts in this series, we'll walk through exactly what each layer of this circuit does — why every qubit starts with a Hadamard gate, why we chose to entangle q0-q1, q2-q3, and then link q1 to q4, and what happens the moment we measure. We'll also explain how this differs from classical randomness and where QRNG circuits like this one are actually used in industry today.

This project has two goals for us at Sonicium Quantum Lab. First, it's educational — we want to make quantum computing concepts accessible to people who are curious but don't have a physics background. Second, it's a demonstration of our lab's capability to design, simulate, and reason about real quantum circuits, as we continue building toward more advanced applications in cryptography, optimization, and scientific computing.

If you're new to quantum computing, this is a great circuit to start with — it's small enough to fully understand qubit by qubit, but it touches every core concept you'll need for more advanced circuits later. Follow along as we go deeper into how it works.

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24/08/2026

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23/08/2026

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āĻ•ā§āϝāĻžāϞāĻŋāĻĢā§‹āĻ°ā§āύāĻŋ⧟āĻžāϰ āĻŦāĻŋāĻ–ā§āϝāĻžāϤ California Institute of Technology—Caltech-āĻ Physics āύāĻŋā§Ÿā§‡ āĻĒ⧜āĻžāĻļā§‹āύāĻž āĻ•āϰ⧇āύ āϰ⧇āĻŦ⧇āĻ•āĻžāĨ¤ āϏ⧇āĻ–āĻžāύ āĻĨ⧇āϕ⧇ āϤāĻŋāύāĻŋ ā§Ē.ā§Ļā§Ļ-āĻāϰ āĻŽāĻ§ā§āϝ⧇ ā§Ē.ā§Ļā§Ļ CGPA āĻ…āĻ°ā§āϜāύ āĻ•āϰ⧇ āĻ¸ā§āύāĻžāϤāĻ• āĻĄāĻŋāĻ—ā§āϰāĻŋ āϏāĻŽā§āĻĒāĻ¨ā§āύ āĻ•āϰ⧇āύāĨ¤ āϛ⧋āϟāĻŦ⧇āϞāĻžāϰ āĻŦāĻŋāϤāĻ°ā§āϕ⧇āϰ āĻŽāĻžā§āϚ āĻĨ⧇āϕ⧇ āĻŦāĻŋāĻļā§āĻŦ⧇āϰ āĻ…āĻ¨ā§āϝāϤāĻŽ āĻ•āĻ āĻŋāύ āĻāĻ•āĻžāĻĄā§‡āĻŽāĻŋāĻ• āĻĒāϰāĻŋāĻŦ⧇āĻļ⧇ āĻāĻŽāύ āĻĢāϞ āϤāĻžāρāϰ āĻŽā§‡āϧāĻž āĻ“ āĻ…āĻ§ā§āϝāĻŦāϏāĻžā§Ÿā§‡āϰāχ āĻĒāϰāĻŋāϚ⧟ āĻŦāĻšāύ āĻ•āϰ⧇āĨ¤

Caltech-āĻāϰ āĻĒāϰ āϤāĻžāρāϰ āĻ—āĻ¨ā§āϤāĻŦā§āϝ āĻšā§Ÿ BostonāĨ¤ āϤāĻžāρāϰ āύāĻŋāĻœā§‡āϰ āĻ­āĻžāώāĻžā§Ÿ, Pasadena-āĻāϰ āĻĒāϰ āϤāĻŋāύāĻŋ āϝāĻžāύ ‘snowy Boston’-āĻāĨ¤ āϏ⧇āĻ–āĻžāύ⧇ Harvard University-āϤ⧇ Physics-āĻ āĻĒāĻŋāĻāχāϚāĻĄāĻŋ āĻ•āϰ⧇āύāĨ¤ āϤāĻžāρāϰ āĻ—āĻŦ⧇āώāĻŖāĻžāϰ āĻŦāĻŋāώ⧟ āĻ›āĻŋāϞ āĻŦā§āĻ˛ā§āϝāĻžāĻ• āĻšā§‹āĻ˛â€”āĻŦāĻŋāĻļ⧇āώ āĻ•āϰ⧇ āĻŦā§āĻ˛ā§āϝāĻžāĻ• āĻšā§‹āϞ⧇āϰ spin āĻŦāĻž āĻ˜ā§‚āĻ°ā§āĻŖāύ āύāĻŋā§Ÿā§‡āĨ¤

āĻĒāĻĻāĻžāĻ°ā§āĻĨāĻŦāĻŋāĻĻā§āϝāĻž āĻ“ āĻ…ā§āϝāĻžāĻ¸ā§āĻŸā§āϰ⧋āĻĢāĻŋāϜāĻŋāĻ•ā§āϏ⧇ āĻāχ āĻĻā§€āĻ°ā§āϘ āĻĒāĻĨ āĻĒ⧇āϰāĻŋā§Ÿā§‡ āϰ⧇āĻŦ⧇āĻ•āĻž āĻĒāϰ⧇ āĻ—āĻŦ⧇āώāĻŖāĻžāϰ āĻ•ā§āώ⧇āĻ¤ā§āϰ āĻŦāĻĻāϞ⧇ āĻĢ⧇āϞ⧇āύāĨ¤ āĻāĻŦāĻžāϰ āϤāĻžāρāϰ āφāĻ—ā§āϰāĻšā§‡āϰ āϕ⧇āĻ¨ā§āĻĻā§āϰ āĻšā§Ÿā§‡ āĻ“āϠ⧇ āĻŽāĻžāύ⧁āώ⧇āϰ āĻŽāĻ¸ā§āϤāĻŋāĻˇā§āĻ• āĻ“ āĻœā§‡āύ⧇āϟāĻŋāĻ•ā§āϏāĨ¤ āĻŦāĻ°ā§āϤāĻŽāĻžāύ⧇ āϤāĻŋāύāĻŋ āϝ⧁āĻ•ā§āϤāϰāĻžāĻˇā§āĻŸā§āϰ⧇āϰ National Institute of Mental Health (NIMH)-āĻ Research Fellow āĻšāĻŋāϏ⧇āĻŦ⧇ āĻ•āĻžāϜ āĻ•āϰāϛ⧇āύāĨ¤ āϤāĻžāρāϰ āĻ—āĻŦ⧇āώāĻŖāĻž āĻŽā§‚āϞāϤ neuroscience āĻ“ human genetics-āĻāϰ āϏāĻ‚āϝ⧋āĻ—āĻ¸ā§āĻĨāϞ⧇, āϝ⧇āĻ–āĻžāύ⧇ āĻŽāĻžāύ⧁āώ⧇āϰ āĻŽāĻ¸ā§āϤāĻŋāĻˇā§āϕ⧇āϰ āĻ—āĻ āύ āĻ“ āϜāĻŋāύāĻ—āϤ āĻŦ⧈āĻļāĻŋāĻˇā§āĻŸā§āϝ⧇āϰ āϏāĻŽā§āĻĒāĻ°ā§āĻ• āύāĻŋā§Ÿā§‡ āĻ•āĻžāϜ āĻ•āϰāϛ⧇āύāĨ¤

āĻ…āĻ°ā§āĻĨāĻžā§Ž āϰ⧇āĻŦ⧇āĻ•āĻž āĻļāĻžāĻĢāĻŋāϰ āĻĒāĻĨāϚāϞāĻžā§Ÿ āĻāϕ⧇āϰ āĻĒāϰ āĻāĻ• āĻāϏ⧇āϛ⧇ āĻ­āĻŋāĻ¨ā§āύ āĻ­āĻŋāĻ¨ā§āύ āϜāĻ—āĻ¤â€”āĻŦāĻžāĻ‚āϞāĻžāĻĻ⧇āĻļ⧇āϰ āĻŦāĻŋāϤāĻ°ā§āϕ⧇āϰ āĻŽāĻžā§āϚ, Physics-āĻ āĻ…āϏāĻžāϧāĻžāϰāĻŖ āĻāĻ•āĻžāĻĄā§‡āĻŽāĻŋāĻ• āĻĢāϞ, Caltech, Harvard-āĻ āĻŦā§āĻ˛ā§āϝāĻžāĻ• āĻšā§‹āϞ āύāĻŋā§Ÿā§‡ āĻĒāĻŋāĻāχāϚāĻĄāĻŋ, āφāϰ āĻāĻ–āύ āĻŽāĻžāύ⧁āώ⧇āϰ āĻŽāĻ¸ā§āϤāĻŋāĻˇā§āĻ• āĻ“ āϜāĻŋāύ āύāĻŋā§Ÿā§‡ āĻ—āĻŦ⧇āώāĻŖāĻžāĨ¤

āϤāĻžāρāϰ āĻ—āĻ˛ā§āĻĒ⧇āϰ āϏāĻŦāĻšā§‡ā§Ÿā§‡ āĻ…āύ⧁āĻĒā§āϰ⧇āϰāĻŖāĻžāϰ āϜāĻžā§ŸāĻ—āĻžāϟāĻŋ āϏāĻŽā§āĻ­āĻŦāϤ āĻāĻ–āĻžāύ⧇āĻ‡â€”āĻāĻ•āϟāĻŋ āĻ•ā§āώ⧇āĻ¤ā§āϰ⧇āϰ āĻ—āĻŖā§āĻĄāĻŋāϤ⧇ āύāĻŋāĻœā§‡āϕ⧇ āφāϟāϕ⧇ āύāĻž āϰ⧇āϖ⧇ āϤāĻŋāύāĻŋ āĻŦāĻžāϰāĻŦāĻžāϰ āύāϤ⧁āύ āĻœā§āĻžāĻžāύ⧇āϰ āϜāĻ—āϤ⧇ āĻĒā§āϰāĻŦ⧇āĻļ āĻ•āϰ⧇āϛ⧇āύāĨ¤ āϛ⧋āϟāĻŦ⧇āϞāĻžāϰ āϏ⧇āχ āĻŦāĻŋāϤāĻžāĻ°ā§āĻ•āĻŋāĻ• āϰ⧇āĻŦ⧇āĻ•āĻž āĻļāĻžāĻĢāĻŋ āφāϜ āϝ⧁āĻ•ā§āϤāϰāĻžāĻˇā§āĻŸā§āϰ⧇āϰ āĻ…āĻ¨ā§āϝāϤāĻŽ āϗ⧁āϰ⧁āĻ¤ā§āĻŦāĻĒā§‚āĻ°ā§āĻŖ āĻŽāĻžāύāϏāĻŋāĻ• āĻ¸ā§āĻŦāĻžāĻ¸ā§āĻĨā§āϝ āĻ—āĻŦ⧇āώāĻŖāĻž āĻĒā§āϰāϤāĻŋāĻˇā§āĻ āĻžāύ⧇ āĻŽāĻžāύāĻŦāĻŽāĻ¸ā§āϤāĻŋāĻˇā§āϕ⧇āϰ āϜāϟāĻŋāϞāϤāĻž āĻŦā§‹āĻāĻžāϰ āĻ•āĻžāĻœā§‡ āϝ⧁āĻ•ā§āϤāĨ¤ āĻŦāĻŋāĻœā§āĻžāĻžāύ⧇āϰ āĻŦāĻŋāώ⧟ āĻŦāĻĻāϞ⧇āϛ⧇, āĻ•āĻŋāĻ¨ā§āϤ⧁ āĻ…āϜāĻžāύāĻžāϕ⧇ āϜāĻžāύāĻžāϰ āĻ•ā§ŒāϤ⧂āĻšāϞāϟāĻŋ āĻ°ā§Ÿā§‡ āϗ⧇āϛ⧇ āĻāĻ•āχāĨ¤

21/08/2026

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