Quantum computers (v1.0)
Collected from many sources especially IBM's website (the leader). Perhaps it provides a starting point for some investment research on your part? This is not to be considered professional financial advice from me. Please consult a financial planner for advice that suits you.
Quantum mechanics is the most fundamental part of physics and is only demonstrated in experiments with no underlying theory that explains why it is the way it is. But there has been no measurement to date that violates quantum mechanics!! It is absolutely true!!
Quantum mechanics describes observed behavior of the very small and its effects diminishes very rapidly as the size increases. For everyday objects, its effects are practically zero.
There are two concepts that are very weird.
The first is superposition. This states that there exists only a probability wave of the state (example position or velocity or spin) of the particle. In other words, it could be in multiple states simultaneously. This probability wave over time and space is called the Schrodinger wave equation (which is a complex waveform with real and imaginary parts!!). But once the state of the particle is actually observed by measurement, the wave collapses everywhere simultaneously down the wave, and it takes a discrete state (example up spin)!!
The second is entanglement. This states that if two particles are coaxed to get entangled, then their states are coupled. If you observe the state of one, the state of the other is instantly set even if they are on different ends of the universe!!
Not sure how physicists rationalize these two phenomena with relativity that says not even information can travel faster than the speed of light!!
When scientists and engineers encounter difficult problems, they turn to supercomputers. These are very large classical computers, often with thousands of classical CPU and GPU cores capable of running very large calculations and advanced artificial intelligence. However, even supercomputers are binary code-based machines reliant on 20th-century transistor technology. They struggle to solve certain kinds of problems.
If a supercomputer gets stumped, that's probably because the big classical machine was asked to solve a problem with a high degree of complexity. When classical computers fail, it's often due to complexity.
Complex problems are problems with lots of variables interacting in complicated ways. Modeling the behavior of individual atoms in a molecule is a complex problem, because of all the different electrons interacting with one another. Identifying subtle patterns of fraud in financial transactions or new physics in a supercollider are also complex problems. There are some complex problems that we do not know how to solve with classical computers at any scale. But for a certain class of these problems, quantum computers may one day be able to solve them rapidly. Quantum algorithms take a new approach to these sorts of complex problems — creating multidimensional computational spaces. This turns out to be a much more efficient way of solving complex problems like chemical simulations.
Quantum computers leverage quantum superposition and entanglement to create extremely fast (but today very expensive, large) computers. The fundamental unit is a qubit which can take values of 0, 1 and also BOTH!! It can be in a superposition state, which represents a combination of all possible configurations of the qubit. Two qubits can be made to be entangled. Entanglement multiplies the computational power. Qubits by themselves are not that useful, but what makes them extremely powerful for computation is superposition and entanglement.
In an environment of entangled qubits placed into a state of superposition, there are many waves of probabilities interacting. These are the probabilities of the outcomes of a measurement of the system. These waves can build on each other when many of them peak at a particular outcome or cancel each other out when peaks and troughs interact. These are both forms of interference.
A computation on a quantum computer works by preparing a superposition of all possible computational states on entangled qubits. A quantum circuit, prepared by the user, uses interference selectively on the components of the superposition according to an algorithm. Many possible outcomes are cancelled out through interference, while others are amplified. The amplified outcomes are the solutions to the computation. When the measurement is taken, the qubits fall out of their quantum state. This is run multiple times from scratch to get the net result distribution for the qubits.
Comparing conventional computers with quantum computers is like comparing apples and oranges, but we can talk more broadly in terms of computational power or problem-solving ability for the class of problems of interest to compare. The computer power of a quantum computer increases exponentially with qubits. A 30-qubit-quantum computer would equal the computational power of a conventional computer that could run teraflops (trillions of floating-point operations per second). At 100 qubits quantum computer processor would, theoretically, be more powerful computationally than all the supercomputers on the planet combined. With 300 qubits—that's more possibilities than there are particles in the universe. A quantum computer with a thousand qubits would be able to process 10 ** 301 states simultaneously!!! That's a 1 with 301 zeros after it. Late last year, IBM took the record for the largest quantum computing system with a processor that contained 433 qubits. IBM's goal is a 100,000-qubit quantum computer over the next decade!!!
What if a 100,000-qubit quantum computer is coupled with AI machine learning? Would we have duplicated the computational power/knowledge potential of the universe's creator? I don't know.
The biggest challenge is decoherence. Qubits are extremely sensitive to their environment, and even small disturbances can cause them to lose their quantum properties, a phenomenon known as decoherence. The struggle to master decoherence may require new materials, new computational techniques and deep exploration of various quantum approaches. It’s not just the hardware that’s challenging for quantum computing. Quantum algorithms are also much more complex than classical algorithms and require developers to approach computational problems in original ways. Quantum computers are also extremely sensitive to noise and errors caused by interactions with their environment. This can cause errors to accumulate and degrade the quality of computation. Developing reliable error correction techniques is therefore essential for building practical quantum computers. Scaling up quantum computers to hundreds or thousands of qubits while maintaining high levels of coherence and low error rates remains a major challenge. A recent breakthrough though demonstrated vastly increased reliability for quantum computers. See article: Error-corrected qubits 800 times more reliable after breakthrough, paving the way for 'next level' of quantum computing (msn.com)
This reminds me of analog computers I used at college. You create a circuit of resistors, capacitors, inductors. You feed in a voltage input. The output voltage of the circuit is the solution to a differential equation. You actually solve differential equations you want to solve by putting together an appropriate circuit and measure the output voltage. You leverage the physical properties of components to solve the differential equation you want to solve. This is similar. You leverage the natural behavior of interacting quantum wave functions of entangled superpositioned qubits in a user defined "circuit" to shape the waves to solve complex problems.
Future quantum computers could open hitherto unfathomable frontiers in mathematics, chemistry, physics, life sciences, linear systems, materials, financial modeling, optimizations, AI and machine learning, unstructured search, factoring and encryption, simulation, and helping to solve existential challenges like climate change and food security. But any disrupter comes with risks, and quantum computers have become a national-security migraine. Its problem-solving capacity will soon render all existing cryptography obsolete, jeopardizing communications, financial transactions, and even military defenses.
Some of the main businesses leading the way in quantum computing include Google, IBM,
For more advanced programming, need to know Hilbert spaces. Almost everyone in quantum mechanics operates in Hilbert space. This is a complex abstract vector space (complex as in having a real and imaginary part) that can have infinite dimension or finite dimension. It is way beyond me!!
Quantum Mechanics, Hilbert Space and Qubits | by Bijula Ratheesh | Analytics Vidhya | Medium
A deep dive into quantum logic and Hilbert spaces for mathematicians.
To better understand the role of quantum entanglement in quantum computing, read below (need to create account).
Entanglement and its role in quantum computing | by Madali Nabil | Medium
Comments
They bring back to my mind analog computers which were super great at solving integration and differentiation in calculus.
This is another specialty computer for specialized purpose that is extremely good at some things.