This repo contains my study resources for learning cloud quantum programming.
Shown to the left is a conceptual rendering of a bit vs a qubit, which is a fundamental concept of work in quantum computing. The Repo is a companion to my LI_L course "Cloud Quantum Computing Essentials"
A qubit is a two-state (or two-level) quantum-mechanical system, one of the simplest quantum systems displaying the peculiarity of quantum mechanics. A quantum computer performs quantum computations using the principles of quantum mechanics.
A QPU (quantum processing units) manipulates the quantum states of available qubits in a controlled way to perform computations, such as algorithms. A qubit is a quantum bit of information.
A quantum computer contains QPU processors, some number of qubits and the support mechanisms which allow these items to interact based on quantum instructions or programs.
This Repo is organized by folder as follows:
Conceptual information about quantum languages, libraries, operations, reference programs (Shor's, Grover's, etc...) and notation
Info about quantum runtime environments (and simulators) organized by cloud vendor:
- AWS Braket - Multi-vendor platform with Ocelot chip, Quantum Embark program
- Microsoft Azure Quantum - Logical qubits, Majorana 1, integrated AI+HPC platform
- IBM Quantum - Utility-scale computing, 156-qubit Heron, path to 2029 fault tolerance
- Google Quantum AI - Willow chip with error correction breakthrough
- IonQ - Trapped-ion systems, 99.9% fidelity, path to 2M qubits
- Rigetti - Superconducting multi-chip architecture
Academic research papers of interest including quantum programming algorithms and examples
Code examples, slides and link from a 15-week-long bookclub covering the referenced book on quantum programming
There are a number of quantum computer vendors. These vendors produce hardware (quantum computers) which contains a particular number of qubits and QPUs.
One example is the D-Wave company. Shown to the right are photos from one of D-Wave's quantum computers. This computer contains QPU units, which is hardware with qubits (image taken from D-Wave whitepaper). To run quantum programs on quantum hardware, use quantum languages or libraries.
NOTE: Generally quantum programs are run on quantum simulators prior to being run on quantum hardware due to the cost and time run on live QPUs.
Shown below are screenshots from a couple of quantum programming development environments. This is just a small subset of the available options. Generally these IDEs are either cloud-based (IBM Composer) or downloadable via a SDK (D-Wave).
- The first example (shown below) shows running a quantum program in the IBM Quantum Composer IDE. This example runs the
Grover-examplequantum program. The visual environment includes the composer, which shows quantum operations written in the OPENQASM quantum programming language and a number of other visualization tools.
- The second example (shown below) is from from D-Wave Systems cloud at https://cloud.dwavesys.com/ and is being run using VSCode as an IDE. The sample shows a path optimization solver and is called
pathin the D-Wave examples. The program is written using the D-Wave Python-like quantum programming library. This IDE is a more traditional environment and doesn't include as many visualization tools for the state of the qubits used in computation.
- Yet another example of a quantum program visualization tools is the browser-based
Quantum Playground- http://www.quantumplayground.net/. Shown below is an example of animated output using the H gate example code. This is a particularly good tool for gaining an intuition into key quantum operations and program examples.
- The QuanTime website (partnership with National Q-12 Education Partnership group) aggregates resources and links to materials which are designed to be used by educators - https://q12education.org/quantime
The quantum computing industry achieved major milestones in 2024-2025, marking the transition from research to practical engineering:
- Google Willow: First demonstration of exponential error reduction as qubits scale
- Microsoft: 800x error rate improvement, created 24 entangled logical qubits (world record)
- IBM: Achieved 5,000-gate circuit execution on 156-qubit system
- AWS Ocelot: First AWS quantum chip using cat qubits (90% error correction cost reduction)
- Microsoft Majorana 1: World's first topological quantum processor, designed to scale to 1 million qubits on single chip
- All major cloud providers launched quantum-ready programs (AWS Quantum Embark, Microsoft Quantum Ready, IBM advisory services)
- Focus on hybrid quantum-classical computing integrating AI and HPC
- Industry consensus: Fault-tolerant quantum computing by 2028-2030
Modern cloud quantum systems range from 50-156 physical qubits with several platforms now demonstrating logical qubits with error correction. Key systems include:
- Google Willow: 105 qubits with error correction breakthrough
- IBM Heron: 156 qubits running 5,000-gate circuits
- Microsoft + Atom Computing: 24 logical qubits
- AWS Ocelot: 9 cat qubits (proprietary)
- IonQ Forte Enterprise: 36 algorithmic qubits with 99.9% fidelity
There are a number of quantum computer vendors. These vendors produce hardware (quantum computers) which contains a particular number of qubits and QPUs.
One example is the D-Wave company. Shown to the right are photos from one of D-Wave's quantum computers. This computer contains QPU units, which is hardware with qubits (image taken from D-Wave whitepaper).
To run quantum programs on quantum hardware, use quantum languages or libraries.
NOTE: Generally quantum programs are run on quantum simulators prior to being run on quantum hardware due to the cost and time run on live QPUs.
Shown below are screenshots from a couple of quantum programming development environments. This is just a small subset of the available options. Generally these IDEs are either cloud-based (IBM Composer) or downloadable via a SDK (D-Wave).
The first example (shown below) shows running a quantum program in the IBM Quantum Composer IDE. This example runs the Grover-example quantum program. The visual environment includes the composer, which shows quantum operations written in the OPENQASM quantum programming language and a number of other visualization tools.
The second example (shown below) is from from D-Wave Systems cloud at https://cloud.dwavesys.com/ and is being run using VSCode as an IDE. The sample shows a path optimization solver and is called path in the D-Wave examples. The program is written using the D-Wave Python-like quantum programming library. This IDE is a more traditional environment and doesn't include as many visualization tools for the state of the qubits used in computation.
Yet another example of a quantum program visualization tools is the browser-based Quantum Playground - http://www.quantumplayground.net/. Shown below is an example of animated output using the H gate example code. This is a particularly good tool for gaining an intuition into key quantum operations and program examples.
The QuanTime website (partnership with National Q-12 Education Partnership group) aggregates resources and links to materials which are designed to be used by educators - https://q12education.org/quantime
For Hardware Diversity: AWS Braket (access to IonQ, Rigetti, IQM, D-Wave, and more)
For Logical Qubits: Microsoft Azure Quantum (24 entangled logical qubits, topological qubits)
For Utility-Scale Computing: IBM Quantum (5,000-gate circuits, 156 qubits)
For Open Source: IBM Quantum (Qiskit framework)
For Highest Fidelity: IonQ via AWS/Azure (99.9% two-qubit gate fidelity)
-
Courses:
- LinkedIn Learning: Cloud Quantum Computing Essentials
- IBM Qiskit Textbook
- AWS Braket Digital Learning Plan (free credentials)
- Microsoft Learn: Quantum Computing Fundamentals
-
Hands-On Practice:
- IBM Quantum (free access to quantum computers)
- AWS Braket (free simulator time)
- Azure Quantum ($500 free credits)
- Annual quantum coding challenges
-
Community:
- Quantum Computing Stack Exchange
- IBM Quantum Network
- Cloud provider quantum communities
Based on 2024-2025 announcements, the industry is converging on this timeline:
| Period | Expected Progress |
|---|---|
| 2025 | 100-500 physical qubits, maturing logical qubit technology |
| 2026-2027 | 500-5,000 physical qubits, 10-100 logical qubits |
| 2028-2029 | 1,000-20,000 physical qubits, 100-1,000 logical qubits |
| 2030+ | Fault-tolerant quantum computers, quantum advantage at scale |
- Superconducting (IBM, Google, AWS, Rigetti): Fast gates, cryogenic cooling required
- Trapped Ion (IonQ, Quantinuum): High fidelity, all-to-all connectivity
- Neutral Atom (Atom Computing, Pasqal): Scalability, reconfigurable
- Topological (Microsoft Majorana 1): Hardware-protected error resistance
- Photonic (Xanadu): Room temperature operation
- Quantum Annealing (D-Wave): Optimization problems
- Qiskit (IBM): Most popular, open-source
- Q# (Microsoft): Enterprise-focused, integrated with .NET
- Cirq (Google): Research-oriented
- Amazon Braket SDK: Multi-platform access
- PennyLane: Quantum machine learning
- Google Willow Quantum Chip
- AWS Ocelot Chip
- Microsoft Majorana 1
- IBM Quantum Roadmap
- Microsoft 24 Logical Qubits
Explore the cloud-vendors directory for detailed information about each platform, including:
- Getting started guides
- Code examples
- Hardware specifications
- Pricing information
- Recent updates and announcements