Quantum Computer/Chip Thread

[JaDed]

This thread to discuss advancements in Quantum Computing.

The competitors are below:

1. Majorana 1- the first of its kind and taking a different approach from its rivals, that of Microsoft 1.

2.Willow - Google’s most advanced quantum chip

3. Heron - IBM traditionally the leader but overall has done absolutely nothing with it.

All of these are based upton qubit but internally to maintain such states the tech used is different.
I would really push posters to read on how each company are trying different approaches to solve the problem of states.

for start read below:

Qubit vs bit​

Qubits are represented by a superposition of multiple possible states​

A qubit uses the quantum mechanical phenomena of superposition to achieve a linear combination of two states. A classical binary bit can only represent a single binary value, such as 0 or 1, meaning that it can only be in one of two possible states. A qubit, however, can represent a 0, a 1, or any proportion of 0 and 1 in superposition of both states, with a certain probability of being a 0 and a certain probability of being a 1.

 

[sweep_shot]

A crash course from ChatGPT regarding quantum physics and quantum computing:

Crash Course on Quantum Physics and Quantum Computing​

Let's break this down into digestible segments to give you a solid understanding of both fields.

---

1. Quantum Physics​

Key Concepts:​

Quantum physics deals with the behavior of matter and energy on a very small scale—typically at the level of atoms and subatomic particles.


1.1 Wave-Particle Duality

• Nature of light and particles: At the quantum level, things behave differently than what we experience in everyday life. Particles like electrons and photons (light particles) can act like both particles and waves, a concept known as wave-particle duality.
  
  • Example: Light can travel through space as a wave, but it can also behave like a particle when interacting with matter (e.g., in the photoelectric effect).

1.2 Superposition

• Superposition: A quantum system can exist in multiple states at once. For example, an electron can be in two places simultaneously, until measured, at which point it "collapses" into one state.
  
  • Example: Imagine you flip a coin—it’s either heads or tails. In the quantum world, it’s as if the coin is both heads and tails until you observe it.

1.3 Entanglement

• Quantum Entanglement: When two particles become entangled, the state of one particle instantly affects the state of the other, no matter the distance between them. This "spooky action at a distance" was famously discussed by Einstein.
  
  • Example: If two entangled particles are separated, changing the spin of one will instantly change the spin of the other, even if they are light-years apart.

1.4 Heisenberg Uncertainty Principle

• Uncertainty Principle: You cannot simultaneously know both the position and momentum of a particle with absolute certainty. The more precisely one is measured, the less precisely the other can be known.
  
  • Example: If you know where an electron is, you can’t know its velocity with precision at the same time.

1.5 Quantum Tunneling

• Tunneling: Quantum particles can pass through energy barriers that would be insurmountable in classical physics.
  
  • Example: In the case of radioactive decay, an atom’s nucleus may emit particles by "tunneling" through an energy barrier.

---

2. Quantum Computing​

Quantum computing uses the principles of quantum mechanics to perform computations that would be infeasible for classical computers. Let’s break down the core principles.

Key Concepts:​

2.1 Qubits (Quantum Bits)

• Classical Bits: In classical computing, information is stored as bits, which can be either a 0 or 1.
• Qubits: In quantum computing, the basic unit is the qubit. Unlike classical bits, qubits can represent 0, 1, or both at the same time due to superposition.
  
  • Example: A qubit can exist in a superposition of 0 and 1. This allows quantum computers to process much more information in parallel than classical computers.

2.2 Superposition in Quantum Computing

• A qubit can perform many calculations at once due to its ability to exist in multiple states simultaneously.
  
  • Example: If you have 3 qubits, they can represent 8 different states simultaneously (since each qubit can be 0, 1, or both).

2.3 Entanglement in Quantum Computing

• Entanglement is used in quantum computing to link qubits. When qubits become entangled, the state of one qubit can instantly influence the state of another, regardless of the distance between them. This is used to create faster algorithms.
  
  • Example: Entangled qubits are like two gears that are locked together—changing one will instantly change the other.

2.4 Quantum Gates and Algorithms

• Quantum Gates: Just like classical computers use logical gates (AND, OR, NOT), quantum computers use quantum gates to manipulate qubits. These gates perform operations like flipping the state of qubits or creating entanglements.
• Algorithms: Quantum algorithms take advantage of the unique properties of quantum mechanics to solve problems more efficiently than classical algorithms.
  
  • Example: Shor’s Algorithm is famous for factoring large numbers exponentially faster than classical algorithms, which could potentially break traditional encryption methods.

2.5 Quantum Speedup

• Quantum computers can solve certain problems faster than classical computers due to the parallel processing capability of qubits.
  
  • Example: For problems like searching databases or simulating molecules, a quantum computer might outperform classical systems.

2.6 Quantum Error Correction

• Quantum Computers are Fragile: Qubits are very sensitive to external disturbances (e.g., heat or electromagnetic fields), which can cause errors in calculations. Quantum error correction is a field that seeks to mitigate these errors.
  
  • Example: Quantum computers often need special algorithms to ensure that the results they produce are reliable despite the error-prone nature of qubits.

---

3. Practical Applications of Quantum Computing​

1. Cryptography: Quantum computing could potentially break many of the encryption schemes currently used for secure communication by factoring large numbers much faster than classical computers.
2. Drug Discovery and Materials Science: Quantum computers could model complex molecules and materials, potentially revolutionizing chemistry, drug discovery, and materials science.
3. Optimization Problems: Quantum computing could provide solutions to complex optimization problems, such as improving logistics, financial modeling, or machine learning algorithms.
4. Artificial Intelligence and Machine Learning: Quantum computing could speed up machine learning algorithms, providing more powerful models and faster training.

---

4. Challenges and Limitations​

• Decoherence: Qubits lose their quantum properties when exposed to the environment (decoherence), which is a major challenge in building stable quantum computers.
• Scalability: Current quantum computers have limited qubits. Scaling them up to solve large-scale real-world problems is an ongoing challenge.
• Error Correction: Quantum error correction is still a developing field, and errors due to environmental factors can interfere with the calculations.

---

Key Players in Quantum Computing​

• IBM Quantum: IBM offers access to its quantum computers through the IBM Q Experience.
• Google: Google’s Quantum AI lab works on developing quantum computers that can perform calculations beyond classical capabilities.
• Microsoft: Microsoft is exploring quantum computing with its own approach called the topological qubit.
• Rigetti: A startup building quantum computing hardware and software.

---

How to Get Started​

1. Quantum Physics:
   
   • Read books like “Quantum Mechanics: The Theoretical Minimum” by Leonard Susskind.
   • Watch online lectures (e.g., from MIT OpenCourseWare or YouTube).
   • Use interactive simulators to get hands-on experience.
2. Quantum Computing:
   
   • Learn about quantum computing through resources like IBM's Qiskit tutorials or Google’s Quantum AI blog.
   • Experiment with quantum programming languages like Qiskit, Cirq, or Microsoft's Q#.

---

Final Thoughts​

Quantum physics and quantum computing are still in their infancy, but they are promising areas of research that could drastically change the world in the future. For now, the best approach is to get comfortable with the basic principles and gradually dive deeper into more advanced topics.

 

[sweep_shot]

There is a programming language called "Q#". It is considered as a quantum programming language. @JaDed, do you know anything about it?

Here is the Microsoft's tutorial for Q#: https://learn.microsoft.com/en-us/azure/quantum/qsharp-overview.

 

[IndoorCricket]

There is a programming language called "Q#". It is considered as a quantum programming language. @JaDed, do you know anything about it?

Here is the Microsoft's tutorial for Q#: https://learn.microsoft.com/en-us/azure/quantum/qsharp-overview.

We had a quantum computing chapter in Microsoft in their garage sessions, where there were workshops around QDK and Q#. Never dwelled into. # comes from C# .Net.

 

[sweep_shot]

We had a quantum computing chapter in Microsoft in their garage sessions, where there were workshops around QDK and Q#. Never dwelled into. # comes from C# .Net.

I see.

I have never heard of Q# or quantum programming language. Learned about it from ChatGPT.

I took C# at college level. That was a few years ago.

 

[JaDed]

There is a programming language called "Q#". It is considered as a quantum programming language. @JaDed, do you know anything about it?

Here is the Microsoft's tutorial for Q#: https://learn.microsoft.com/en-us/azure/quantum/qsharp-overview.

I knew they had quantum computing language, I didn’t know they named it..there is a youtube/media interview when Quantum computing craze started in 2018-21..
Don’t know how significant it is,IBM was the earliest one to invest but Google has achieved Quantum supremacy as per them(google).

 

[sweep_shot]

I knew they had quantum computing language, I didn’t know they named it..there is a youtube/media interview when Quantum computing craze started in 2018-21..
Don’t know how significant it is,IBM was the earliest one to invest but Google has achieved Quantum supremacy as per them(google).

I see.

Python can be used for quantum computing too apparently. See the article below:

Source: https://thequantuminsider.com/2022/07/28/state-of-quantum-computing-programming-languages-in-2022/.

​

===================================

Top 5 Quantum Programming Languages in 2024​

Quantum programming languages are programs that have been designed to run on quantum computers and are very different from classical computing programs. To understand quantum computing languages and work with them effectively a sound knowledge of the principles of quantum mechanics and the underlying mathematics is often essential. As quantum computers work on practical use cases in industry and solve what have been up to now intractable problems for humanity, superseding the work done by classical computers, quantum computing programming languages will become more valuable tools.

Currently, the number of people trained in quantum programming languages is small compared to those with skills in classical programming languages — yet this reality is set to change with the wider adoption of quantum computers.

The intention of this article is to explain clearly but briefly, what a quantum programming language is, what is the difference between quantum/classical programming, and the types of quantum programming languages available.

By its very definition, a quantum programming language is a programming language specifically designed to write programs for quantum computers. More factors to consider when categorizing quantum programming languages from classical programming languages are how they evaluate and qualify quantum algorithms and their execution, as well as their ability to scrutinize the fundamentals of a quantum system, i.e. entanglement, superposition and qubits.

The differences between classical and quantum programming languages come down to the fundamental elements that are the basis of either system. A classical system is “programmed” by a human who utilizes the linear binary elements of ones and zeros which are then processed to get results (information). In a quantum system, however, optimized physical properties of particles are fed into the quantum computer as a matrix so the basic unit of quantum information — known as a qubit — can determine the results.

As already mentioned, the successful implementation of these complex quantum circuits and algorithms requires a high level of physics and maths. Only quantum programming experts — trained to understand the complexities of Quadratic Unconstrained Binary Operation (QUBO) or Quadratic Approximation Optimization Algorithm (QAOA), for example — can provide the experience and knowledge to identify the issues and then process them to get the most out of the quantum computer.

The number of quantum computing languages is growing all the time. Based on an open-source mentality of sharing knowledge and resources, quantum programming languages have been designed to assist quantum algorithms using high-level constructs. Before we go into the specifics of what are the best quantum programming languages in 2024, we shall briefly go over the Quantum Instruction Sets, Quantum Software Development Kits and the types of quantum computing programming languages available.

Quantum Instruction Sets​

These are used to turn complex algorithms into physical instructions that can be performed on quantum processors and vary depending on the qubit modality of the quantum architecture (superconducting/silicon-based/trapped ions etc) of the hardware platform.

Examples of this type include cQASM, Quil, OpenQASM, and Blackbird.

Quantum Software Development Kits​

Quantum software development kits (SDKs) offer various tools to design and exploit quantum programs, while also providing the user with the ability to simulate the quantum programs or prepare them to be run using cloud-based quantum devices.

The Current SDKs with access to quantum processors and/or Quantum Development Kits available are Ocean, Qiskit, ProjectQ, Forest, t|ket>, Strawberry Fields, PennyLane, and Cirq.

Quantum Programming Languages​

Quantum Programming Languages can be divided into two language categories: Imperative and Functional. Imperative programming is when the software utilizes statements that change a program’s state, while Functional programming is constructed by applying and composing functions.

Examples of Imperative quantum programming languages accessible in 2024 include QCL, Quantum pseudocode, Q#, Q|SI>, Q language, qGCL, QMASM, Scaffold, and finally, Silq, developed at ETH Zürich.

Functional variations comprise languages such as QFC, QPL, QML, LIQUi|>, Quantum lambda calculi, Quipper, and funQ.

Now that we have presented the different types of quantum programming languages available with examples of individual quantum programming languages in those categories, we will now go through which are the “best” quantum computing programming languages in 2024.

With all “Best Lists”, this is mightily subjective, but The Quantum Insider’s decision as to which are the best quantum programming languages in 2024 is simply because the ones we are about to mention are used by the top quantum experts on the planet, both in academia and in industry. Go to any YouTube video, blog tutorial or book on Amazon and you will see the same programs pop up time and time again.

It’s not our decision, but the wider community’s objective view.

1. Python (Actual Quantum Programming Language)​

When it comes to an actual programming language to help you get into quantum computing as quickly and as stress-free as possible, Python could be the answer. First developed more than thirty years ago by the Python Software Foundation, Python is a good programming language as many packages like QuTip etc are available for it, which allows working with quantum systems even easier. Probably the easiest case for using this is that it’s easy to learn and a lot of the quantum frameworks have been designed with this language specifically in mind.

Now let’s get into the individual open-source suites and development kits.

2. Qiskit (Open-source Programming Tool)​

Qiskit was IBM’s gift to the quantum programming world in 2017. An open-source Software Development Kit for working with quantum computers at the level of circuits, pulses, and algorithms, Qiskit was developed by IBM Research and the wider Qiskit community and provides tools for creating and manipulating quantum programs and running them on prototype quantum devices on IBM Quantum Experience or on simulators on a local computer.

3. Ocean™ (Quantum Computing Programming Suite)​

Ocean™ software is a suite of open-source Python tools accessible via the Ocean Software Development Kit on both the D-Wave GitHub repository and within the Leap quantum cloud service. D-Wave, a pioneer in the quantum computing industry, designed Ocean to allow developers to experiment with and leverage the power of D-Wave’s Advantage quantum computer to solve complex problems.

4. Q# (Quantum Computing Programming Algorithm)​

Next up is Q# — the # is pronounced ‘sharp’ — by Microsoft. Used in conjunction with the Quantum Development Kit, Q# first appeared in 2017 and is a domain-specific programming language used for expressing quantum algorithms. One advantage of this quantum programming language is it supports general classical flow control during the execution of an algorithm. In particular, classical flow control is based on quantum measurement outcomes, which makes it much easier to write things that depend on intermediate measurements.

5. Cirq (Google AI Programming Language)​

Developed by the team at Google Quantum AI announced (public alpha) at the International Workshop on Quantum Software and Quantum Machine Learning in the summer of 2018, Cirq is an open-source framework for noisy intermediate scale quantum (NISQ) computers. The package comes with built-in simulators, both for wave functions and for density matrices, which can deal with noisy quantum channels using Monte Carlo or full-density matrix simulations. Cirq also works with a wavefunction simulator, qsim.

There are so many toolboxes and packages that are equally as good, but we simply have no time to mention them all.
As neither we nor our readers are Nostradamus, this question seems like it’s impossible to answer. However, in a very insightful Forbes article, What To Expect From Quantum Computing In The Next Two Years, published in December 2021 and written by Dr. Yehuda Naveh, co-founder and CTO of Classiq, a Tel Aviv, Israel-based quantum startup that provides a quantum algorithm design software platform for the automated synthesis of quantum circuits, Naveh believes the “demand for quantum talent and better software platforms will soar.”

Taking the view of this expert in the field, we can expect, as Naveh puts it:

“[The] rise of software platforms that make quantum more accessible to people who know how to program but are not — at least not yet — quantum computing experts […]. Like common machine learning platforms, they shield users from the complexity under the hood. These quantum design platforms could help.”

There is little doubt that, in the coming years, we will witness more use cases of quantum computing’s efficacy over classical machines. We expect, then, quantum programming languages, Quantum Software Development Kits, and coding platforms to be more understood and accessible through educational courses and accredited certification, leading to an industry where the recruitment of software specialists and connected professions will not be a difficult task.

 

[JaDed]

The challenges faced by quantum computing currently is the limitations it has in qubit stability and error correction, due to which the way to understand quantum language makes it very difficult.

 

[Kroll]

Think the banks and other fintechs will be crapping it over the potential to break ciphers such as RSA-256. But I think this is still some time away.

 

[DeadlyVenom]

@Devadwal had this computer in 2007, init @RedwoodOriginal

 

[Devadwal]

@Devadwal had this computer in 2007, init @RedwoodOriginal

I had the tv which expert hiding behind wimbledon would have not. He didn't even born when Pakistan oast time drawn a test in Australia.

 

[JaDed]

Think the banks and other fintechs will be crapping it over the potential to break ciphers such as RSA-256. But I think this is still some time away.

Funny you said that, just this month EU announced a plan to start “quantum” securing Energy ,Finance, telecommunication from 2026 and finish it by 2030..

Still unclear on the algorithms that will be used though.
Chinese have already cracked 22 bit key RSA so for now 2048 is safe

 

[RedwoodOriginal]

@Devadwal had this computer in 2007, init @RedwoodOriginal

...and a portal to the fourth dimension

 

[sweep_shot]

A nice introductory video on quantum computing.

 

[sweep_shot]

A nice introductory video on quantum computing.

Here is the ChatGPT's summary of the video (the summary doesn't cover everything but gives a general idea):

==========================

The video titled "The Map of Quantum Computing - Quantum Computing Explained" provides a comprehensive overview of quantum computing, breaking down its complexities into understandable segments. Here's a concise summary of the key points covered:

---

Understanding Quantum Computing​

• Classical vs. Quantum Computing: Traditional computers use bits (0s and 1s) to process information. Quantum computers utilize qubits, which can exist in multiple states simultaneously, thanks to quantum phenomena like superposition and entanglement.
• Qubits: The fundamental units of quantum computing, qubits can represent both 0 and 1 at the same time, allowing quantum computers to process a vast amount of information concurrently.

---

Key Concepts in Quantum Computing​

• Superposition: This principle allows qubits to be in a combination of states, enabling quantum computers to explore many possibilities simultaneously.
• Entanglement: A phenomenon where qubits become interconnected, such that the state of one qubit instantly influences the state of another, regardless of the distance between them.
• Quantum Gates: Operations that manipulate qubits, similar to classical logic gates but with the added complexity of quantum mechanics.

---

Applications of Quantum Computing​

• Cryptography: Quantum computers have the potential to break traditional encryption methods, leading to the development of quantum-resistant algorithms.
• Optimization Problems: They can solve complex optimization problems in various fields, including logistics, finance, and manufacturing.
• Drug Discovery: Quantum simulations can model molecular structures, accelerating the process of discovering new pharmaceuticals.

---

Challenges in Quantum Computing​

• Decoherence: Quantum states are delicate and can be easily disturbed by their environment, leading to loss of information.
• Error Rates: Current quantum computers have higher error rates compared to classical systems, necessitating advanced error correction techniques.
• Scalability: Building large-scale quantum computers requires overcoming significant technical hurdles, including maintaining qubit coherence and minimizing errors.

---

The Future of Quantum Computing​

• Quantum Supremacy: The point at which quantum computers can solve problems that are practically unsolvable by classical computers.
• Hybrid Systems: Integrating quantum processors with classical systems to leverage the strengths of both.
• Global Collaboration: Countries and organizations worldwide are investing in quantum research, aiming to lead in this transformative technology.