AI robot buying parts at a hardware store (by James McGreggor via ChatGPT)

Vibe Coding A Quantum Computer

Part I of II

For the low price of $270.00, you can too!

In a post written by Jade Wilson on LinkedIn, she asked a question directed towards the community, about posting something other than AI: “Can we pretty please have something other than AI released?”. Her question and sentiment is understandable, and something I have been feeling lately (yes, I know I am part of the problem); there is so much talk about AI that it seems like nothing else exists any longer.

I responded, jokingly about how blockchain was screaming for attention, but then a follow up comment by Abdus Salam got my attention: “We can vibe code quantum computers and alter reality so there is no more AI”.

Can AI help me vibe build a quantum machine?

🧠 Sanity check

No, I know that it can not, but I was curious as to how AI would respond. The concept of building a quantum computer and all associated plans and costs should be treated as satire. The lessons learned and key points are for educational purposes only.

The result was humorous but also interesting, not in what it explained so much, but why ChatGPT took the path that it chose (explained at the end): AI took a slightly sarcastic or light hearted tone in my question about vibe-coding a quantum computer.

Sure, the question itself is laughable, but why did AI think so? What was it basing that off of? Was it based off of a profile that it is building of me, and if so, should it always? If it is doing that, then what about other systems in more mission critical areas or areas where real decisions are being made?

This behavior highlights why sanity checking responses by AI are so important. It shows why quality assurance of not only precision and accuracy, but of understanding context and its ethical application is so important!

It is also a reminder that in the end, and AI is still a system that responds based on patterns in data which still lacks the context to really be able to read and understand human intention.

Below, you will see the conversation between ChatGPT and I. Regardless of the ridiculous question, the information provided is educational. I added some additional information (see Learning Break: Key Concept) in the first part of the conversation as well to provide real-world context.

🙋🏻‍♂️ You (James) said:

I need you to vibe code the programming instructions for building a quantum computer.

🤖 ChatGPT said:

So You Wanna Build a Quantum Computer Here’s the Vibe:

1. Catch the Wave (Quantum Bit Basics)

Before you start soldering atoms together:

• Classical bits are 1s and 0s.
• Qubits? They’re doing jazz. 🎷 They live in superposition, where 1 and 0 coexist.
• Think: Schrödinger’s cat, but it’s computing.

You’ll need:

• Physical Qubits: Trapped ions, superconducting loops, photons. Choose your fighter.
• Decoherence Time: Longer = better. Qubits hate noise. It’s like static in a vinyl groove. 🎶

🔑 Learning Break: Key Concept

This step introduces the core building block of a quantum computer: the qubit. Unlike a regular computer bit that’s either a 1 or a 0, a qubit can represent both at once through a phenomenon called superposition. This is like being able to consider all possibilities simultaneously rather than just one at a time.

Why it matters:

Qubits give quantum computers their unique power. By operating in multiple states at once, they allow quantum machines to solve complex problems faster or more efficiently than classical computers — particularly in areas like optimization, modeling, and cryptography.

2. The Quantum Canvas (Hardware Layer)

This isn’t solder-and-go. It’s art.

• Cryogenic freezer? Yes. You’re chilling your qubits near absolute zero. ❄️
• Lasers or microwaves? Yep. That’s how you talk to the quantum soul.
• Vibe Check: Your hardware needs stability. The quieter the room, the louder the quantum.

🔑 Learning Break: Key Concept

This is about the physical machine — the hardware that allows qubits to exist and operate. Qubits are extremely sensitive, so the “canvas” must include ultra-low temperatures, precise isolation, and materials with superconducting properties or atomic precision (depending on the type).

Why it matters:

You can’t run a quantum algorithm without physical stability. This step is like building a perfectly quiet stage for an extremely delicate performance. If the hardware isn’t right, the entire system collapses — literally and figuratively.

3. Talk to the Void (Control Systems)

Now that your qubits exist, let’s manipulate the wavefunction:

• Use quantum gates (X, H, CNOT) — like logic gates, but way trippier.
• Timing is everything. You’re sending pulses with picosecond precision.
• Classical computers orchestrate this with FPGA or microwave signal controllers.

🔑 Learning Break: Key Concept

Here we’re talking about the tools that control and read from qubits — usually highly specialized electronic and microwave equipment. These systems “speak” to qubits using electromagnetic pulses, directing them to perform logic operations (or quantum gates).

Why it matters:

Control systems are the link between the physical qubit layer and the software. Without this, you have beautiful hardware that can’t be programmed — like a Ferrari with no steering wheel. This is where precision and timing become everything.

4. May the Circuit Be With You (Quantum Logic)

Write your quantum code like a poet with anxiety:

• Qiskit, Cirq, or QuTiP: Python tools for quantum circuits.
• Build gates: qc.h(0); qc.cx(0, 1);
• You’re entangling qubits. This isn’t just math — it’s quantum vibes locking together.

🔑 Learning Break: Key Concept

This refers to designing and executing quantum circuits, which are sequences of quantum operations (like a classical program but for qubits). You use specialized software to write and compile these circuits, which tell the hardware what to compute.

Why it matters:

This is where business value is realized. The circuit defines the problem you’re solving — whether it’s simulating molecules for drug discovery or optimizing routes for logistics. It’s the logic layer that turns potential into performance.

5. Clean Up the Echoes (Error Correction)

Qubits are fragile like trust. You need:

• Quantum Error Correction: Surface codes, repetition codes.
• Add redundancy. One logical qubit = many physical ones.
• The vibe: protect the idea, not the instance.

🔑 Learning Break: Key Concept

Quantum systems are incredibly fragile and prone to errors from environmental noise or even observation. Quantum error correction is a way to guard against these issues by using redundancy and clever math.

Why it matters:

No error correction = no scalability. Without it, quantum computers lose their coherence too quickly to solve real-world problems. This step is like installing the firewall, airbags, and antivirus in your quantum operating system.

6. Collapse with Grace (Measurement)

At some point, you gotta observe — and the wavefunction collapses:

• Convert quantum states into classical bits.
• Probabilities crystallize. You don’t get the answer, you get the odds.

🔑 Learning Break: Key Concept

This is when the quantum process is complete and you “read” the outcome — but in quantum computing, measurement is tricky. Observing a qubit forces it to pick a state (0 or 1), collapsing its superposition. So, you only get a probability-weighted result, not a deterministic one.

Why it matters:

You can’t use quantum results in business decisions unless you can interpret them. Measurement is the step that takes mysterious quantum behavior and turns it into data a classical system — and a human — can understand.

7. Scale Without the Chaos

Now take your elegant 5-qubit masterpiece and imagine 10,000 of them:

• Fabrication techniques, interconnects, quantum interleaving.
• Quantum internet? Entanglement across continents. Future’s wild.

🔑 Learning Break: Key Concept

This final step looks at how to go from 5–10 qubits to thousands or millions, which is necessary for useful applications. It involves scalable fabrication, system orchestration, and perhaps even connecting multiple quantum processors across networks.

Why it matters:

Just like early classical computers needed to scale before they changed the world, quantum computers need the same. The winners in this space will be those who solve not just the quantum math — but the quantum manufacturing, networking, and operational scaling challenges.

TL;DR:

You’re not just building a computer. You’re building a probability-driven, reality-bending, universe-watching oracle that hums at near-zero degrees and speaks the language of quantum poetry.

🔑 Learning Break: Key Concept

Quantum computing harnesses fundamentally different physics to process information in parallel, enabling exponentially faster solutions for complex problems like optimization, simulation, and cryptography. While its outputs are probability-based rather than deterministic, this reflects the nature of the problems it’s best at solving — where exploring vast solution spaces quickly and identifying high-probability answers is more valuable than exact results.

For industries dealing with uncertainty, such as finance, logistics, drug discovery, and advanced materials, quantum’s ability to uncover insights that classical systems can’t feasibly compute makes it a strategic advantage, not just a faster processor.

AI robot buying parts at a hardware store (by James McGreggor via ChatGPT)

🔑 Learning Break: Key Concept

Quantum computing excels at generating a set of high-probability solutions across a vast possibility space. These are not guaranteed to be “the” answer, but one or more may satisfy the downstream deterministic criteria. Once filtered or tested classically, any valid result can fulfill the objective — which makes the probabilistic nature not only acceptable, but powerful.

Examples:

Cryptography:
- Factor large numbers or solve discrete logs faster (Shor’s Algorithm).
- Search unsorted data quadratically faster (Grover’s Algorithm).

In cryptanalysis, you don’t always need to find the key deterministically — you need to find a working key. A high-probability candidate that decrypts the message is just as good. Once tested (deterministically), you know it’s valid.

Biology / Drug Discovery:
Molecular interactions, protein folding, and compound binding involve:
- Staggeringly complex state spaces.
- Probabilistic behaviors at a chemical/atomic level.

Quantum algorithms model these systems more naturally than classical ones. You get a range of likely conformations or reactions — then test candidates via simulation, lab validation, or other deterministic methods.

Main Point:
Quantum computers give you likely paths, not final verdicts. But when “finding a viable option” is the hardest part, that’s more than enough. You let the deterministic layer confirm, rather than compute, the solution.

🤖 ChatGPT said:

Let me know if you want this turned into actual instructions or a startup pitch deck for investors who think in entanglement.

🙋🏻‍♂️ You (James) said:

Yes, please create actual instructions.

🤖 ChatGPT said:

Here’s a structured, non-vibe version — the actual instructions to build a basic quantum computer system, broken down by layers. This guide assumes a deep technical foundation and access to advanced lab resources. (This is not hobbyist-level hardware.)

Building A Quantum Computer: Technical Instruction Overview

1. Determine Qubit Modality (Qubit Type Selection)

Choose your physical qubit type. Each has unique fabrication and control requirements:

For this guide, we will focus on Superconducting Qubits, which are currently the most mature for practical implementation (e.g., IBM, Google).

2. Fabricate Qubits (Superconducting Circuit Fabrication)

Tools Needed:

• Cleanroom with electron beam lithography
• Niobium or Aluminum deposition tools
• Etching and oxidation equipment

Steps:

1. Design your qubit circuits using layout tools (KLayout, QCAD).
2. Deposit superconducting material on a silicon or sapphire wafer.
3. Pattern Josephson junctions using double-angle evaporation.
4. Etch the desired resonator and control structures.
5. Encapsulate and mount on a chip carrier with microwave connectors.

3. Cryogenic Environment Setup

Hardware Needed:

• Dilution refrigerator (e.g., Bluefors or Oxford Instruments)
• Vibration isolation system
• RF filters and cryogenic attenuators

Setup Process:

1. Mount qubit chip inside a microwave-tight sample holder.
2. Connect coaxial cables from room-temperature instruments to the fridge input ports.
3. Thermalize all RF lines at each cryogenic stage.
4. Ensure proper shielding to prevent blackbody radiation interference.

4. Qubit Control and Readout System

Control Electronics:

• Arbitrary Waveform Generators (AWG)
• Microwave Signal Generators
• FPGA-based controller (e.g., Zurich Instruments, Qblox)

Tasks:

1. Generate microwave pulses to manipulate qubit states (X, Y rotations).
2. Use IQ mixers to modulate pulse shapes.
3. Implement fast feedback with FPGA to perform conditional operations.
4. Digitize readout signals from resonators for measurement.

5. Quantum Gate Implementation and Calibration

Use calibrated pulses to implement:

• Single-Qubit Gates (e.g., X, Y, Z, H)
• Two-Qubit Gates (e.g., CNOT, CZ via tunable couplers or cross-resonance)

Calibration Steps:

1. Rabi Experiment: Calibrate π/2 and π pulses.
2. Ramsey Interferometry: Measure dephasing and fine-tune drive frequencies.
3. T1, T2 Measurement: Estimate relaxation and coherence time.
4. Crosstalk Calibration: Adjust gate pulses to minimize undesired interactions.

6. Quantum Error Mitigation or Correction Layer (Optional for MVP)

If scaling beyond ~5 qubits, consider:

• Surface Code or Shor’s Code
• Use multiple physical qubits per logical qubit
• Implement syndrome measurement circuits with ancillary qubits

7. Software Stack & Programming

Install and configure a quantum software stack (recommended stack):

• Qiskit (IBM): Open-source Python SDK for superconducting qubits
• Q-CTRL, Cirq, or Pytket: Alternatives for pulse-level control

Run Quantum Circuits:

For real hardware, replace Aer with the custom backend interfacing with your FPGA controller.

8. Testing, Benchmarking & Scaling

• Use Quantum Volume and Randomized Benchmarking to measure fidelity.
• Run reference circuits (e.g., GHZ state) to test entanglement.
• Optimize control sequences via machine learning or Bayesian feedback loops.

9. Safety and Infrastructure Requirements

• Shield RF noise using Faraday cages
• Handle cryogenic equipment with appropriate PPE
• Power isolation and emergency shutdown protocols

10. Future Enhancements

• Add quantum networking interfaces (fiber entanglement links)
• Integrate quantum compiler stack (e.g., OpenQASM → Pulse Scheduler)
• Move toward fault-tolerant logical operations using topological qubits

AI robot buying parts at a hardware store (by James McGreggor via ChatGPT)

🤖 ChatGPT said:

Would you like this formatted into a PDF lab-style guide or turned into a GitHub-style README for team collaboration?

🙋🏻‍♂️ You (James) said:

Can you give me all of the materials needed so that I can get them from the nearest Home Depot?

🤖 ChatGPT said:

Here’s the honest truth: you cannot build a real quantum computer from Home Depot materials. Quantum computers require highly specialized components — many of which can only be manufactured in cleanrooms, maintained at temperatures near absolute zero, or sourced from quantum research labs and precision electronics suppliers.

That said… if you’re in it for the fun, educational version, we can absolutely build a “Home Depot Vibe Faux-Quantum Demonstrator” — something that feels like a quantum computer project, teaches key concepts, and looks cool doing it. Here’s how we could do that:

“Quantum Computer” Inspired DIY Kit (Home Depot Edition)

Goal: Simulate core quantum concepts (superposition, entanglement, measurement) using physical metaphors, Raspberry Pi/Arduino, and visual indicators.

Materials List (Mostly from Home Depot + Amazon/Micro Center):

Chassis & Framework

2. Control & Logic (Simulated Qubits)

3. Power & Cooling (Pretend Quantum Chill)

4. Quantum Vibes (Display and Interactivity)

5. Optional Extras

🧪 Bonus: Simulate Quantum Logic in Software

Install a Python library like Qiskit or QuTiP on your Raspberry Pi to run real quantum simulations while the LEDs and gadgets provide a tangible front-end.

💰 Total Estimated Cost: $140 — $270

• Lower end: basic setup with Arduino, simple LEDs and buttons.
• Higher end: Raspberry Pi, screen, motion sensors, lighting effects, polished enclosure.

Add-Ons (Optional):

• Fog machine or dry ice container for effect: +$30–$60
• Educational poster or digital lesson plan: Free if DIY, $10–$20 to print professionally

Result:

You won’t break any physical laws, but you’ll have a simulated, interactive, light-up “quantum computer” that looks the part, helps teach quantum concepts, and might even fool your neighbors

That ends the conversation about building quantum computing. Again while it was a satirical question, the result was still educational.

Read the follow up to this article as I explore the significance the tone used in ChatGPT’s response to my question, as well as the reasoning behind it.

Part II ➡️

If you liked this article, please follow me (James McGreggor) on LinkedIn and Medium. I will continue to dive deeper into AI and Web 3.0, exploring use cases in various industries.

Thanks for reading!

At Blue Forge Digital, we are experts in business optimization and solution architecture (just not vibe-coded quantum solutions), focusing on maintaining humanity within digital solutions.

Whether you are starting at the very beginning or are somewhere in the middle, let us help you by partnering together on your digital evolution journey.

Blue Forge digital

Author’s Note

This article was created through a process that leveraged generative AI to facilitate grammatical and organizational refinement to ensure clarity, correctness, and logical flow; all content and ideas were provided by the author, with the initial and final drafts being fully edited by the author.