In this paper, we propose the concept of symplectic computers, which have the potential to be more powerful than quantum computers. Unlike quantum computing, which consists of a sequence of unitary transformations (gates) and projectors (measurements), symplectic computation involves a sequence of symplectic transformations and measurements. The proposal to explore symplectic computers is based on the following quantum-symplectic duality. The Schrödinger equation in its standard complex form describes the unitary evolution of a quantum system, while its real form describes the symplectic evolution of a classical mechanical system. This quantum-symplectic duality can be leveraged to enhance the capabilities of quantum and symplectic computers. In this symplectic approach, the role of a quantum bit (qubit) is taken by a symplectic bit (symbit).
In this paper, we propose the concept of symplectic computers, which have the potential to be more powerful than quantum computers. Unlike quantum computing, which consists of a sequence of unitary transformations (gates) and projectors (measurements), symplectic computation involves a sequence of symplectic transformations and measurements. The proposal to explore symplectic computers is based on the following quantum-symplectic duality. The Schrödinger equation in its standard complex form describes the unitary evolution of a quantum system, while its real form describes the symplectic evolution of a classical mechanical system. This quantum-symplectic duality can be leveraged to enhance the capabilities of quantum and symplectic computers. In this symplectic approach, the role of a quantum bit (qubit) is taken by a symplectic bit (symbit).
This anatomical review critically dissects Igor Volovich's (2024) proposal for symplectic computers, a conceptual framework grounded in the quantum-symplectic duality. By reformulating the Schrödinger equation in real variables, Volovich reveals that unitary quantum evolution is embedded within the larger symplectic group Sp(2N, ℝ). The review evaluates the paper's mathematical structure, the introduction of symplectic bits (symbits), and the canonical embedding map γ : U(N) → Sp(2N, ℝ). While acknowledging the elegance of the duality, the analysis identifies significant gaps in the formal definition of a computational model, the absence of complexity-theoretic grounding for claimed superiority, and ambiguities in scaling from single symbits to multi-symbit registers. Comparative analysis situates the work within emerging geometric approaches to quantum and classical computation. Profound epistemological questions arise concerning the privileging of complex Hilbert spaces, alongside ontological implications for the quantum-classical boundary. This Volume I initiates a multi-volume research program aimed at rigorous formalization and exploration of symplectic computation as a potential post-quantum paradigm. K S C Also available on Academia.edu: https://www.academia.edu/attachments/133164750/download_file?s=portfolio
Quantum computing stands as a pioneering field within computer science, leveraging the enigmatic principles of quantum mechanics to execute intricate calculations. At its heart lies the qubit, the elemental building block of quantum information, which resides in a state of superposition, representing both 0 and 1 concurrently. Quantum computers, constructed from assemblies of qubits, inhabit an expansive and intricate 2^n-dimensional complex Hilbert space, with their evolution governed by the Schrödinger equation. The process of quantum computation can be distilled into three key stages:1) Initialization of the input state: Initiating the quantum process; 2)Application of unitary transformations: Executing the desired transformations on the input state; 3) Measurement of the output state. Quantum computers serve as universal machines, capable of decomposing any unitary transformation into a sequence of fundamental gates. This chapter will reveal the importance of quantum mechanics, quantum computation and its applications.
Today's computers work on bits that exist as either 0 or 1. Quantum computers aren't limited to two states; they encode information as quantum bits, or qubits, which can exist in superposition. Qubits represent atoms, ions, photons or electrons and their respective control devices that are working together to act as computer memory and a processor. Because a quantum computer can contain these multiple states simultaneously, it has the potential to be millions of times more powerful than today's most powerful supercomputers. A processor that can use registers of qubits will be able to perform calculations using all the possible values of the input registers simultaneously. This superposition causes a phenomenon called quantum parallelism, and is the motivating force behind the research being carried out in quantum computing. Due to technical obstacles, till date, a quantum computer has not yet been realized. But the concepts and ideas of quantum computing has been demonstrated using various methods like NMR, Ion Trap, Quantum Dot, Optical Methods, etc. A quantum computer manipulates qubits by executing a series of quantum gates, each a unitary transformation acting on a single qubit or pair of qubits. In applying these gates in succession, a quantum computer can perform a complicated unitary transformation to a set of qubits in some initial state. The qubits can then be measured, with this measurement serving as the final computational result. Research must devise a way to maintain decoherence and other potential sources of error at an acceptable level. Probably the most important idea in this field is the application of error correction in phase coherence as a means to extract information and reduce error in a quantum system without actually measuring that system. Thereby, quantum computers will emerge as the superior computational devices and perhaps one day make today's modern computer obsolete.
t io at u mp o cC Building directly on the quantum-symplectic duality introduced in Volume I, this paper develops the formal circuit ti lec model for symplectic computation. We define an n-symbit register as the 2n-dimensional real symplectic vector mp y | S space (ℝ^{2n}, ω) equipped with the standard symplectic form. Computation proceeds via sequences N of local CC S symplectic gates drawn from Sp(4, ℝ) (two-symbit) or Sp(2k, ℝ) (k-symbit interactions), Kfollowed by measurements. We construct minimal universal gate sets capable of approximating arbitrary elements of Sp(2n, ℝ) to arbitrary precision. Central results concern complexity: because the state space dimension grows only linearly with the number of symbits, any symplectic circuit can be simulated classically in polynomial time by maintaining and updating a 2n-dimensional real vector under local matrix multiplications. Consequently, we prove that the deterministic class SymP coincides with P, and the bounded-error class BSymP coincides with BPP. This establishes that symplectic circuits do not yield exponential speed-ups for decision problems in the manner of quantum circuits. Their potential advantage instead resides in analog precision, natural simulation of classical Hamiltonian dynamics, hybrid quantum-symplectic architectures, and physical implementations where symplectic structure is native. Also available on Academia.edu: https://www.academia.edu/attachments/133167878/download_file?s=portfolio
Summary form only given, as follows. Gives a system theoretic approach to the concept of quantum computing. A quantum computer is envisaged to be a system of quantum circuits, acting on a state space, which is a finite-say 2/sup n/-dimensional-complex Hilbert space. The circuitry is a sequence of unitary transforms U/sub t/ /spl epsiv/ SU(2/sup n/) followed by a measurement. These transforms, so-called quantum gates, are controlled by a classical computer, usually especially electromagnetic fields. The state space of a quantum computer has the structure of a Hermitian vector space. Thus it allows "simultaneous" superposition of orthogonal basis states (corresponding to classical states) with the possibility of constructive and destructive interference between different paths of computation. This principle allows the usage of so-called entangled states by preparing the superposition of special "bent" configurations of basis vectors in the product Hilbert space, e.g., as they are known from error control and cryptography. This latter "entanglement" not only promises to make a quantum computer much more powerful than a probabilistic one, but it also allows a method of parallelism. The reason for this lies not only in the fact that the 2/sup n/ dimensional Hilbert space is the n-fold tensor product of 2-dimensional spaces as it is given by spin-1/2-particles, like photons, representing a quantum bit. First of all, we shall address the fact that the power of quantum computing lies in the properties of entangled states as opposed to those of separable states which essentially would resemble classical circuits without giving the feature of exponential speed-up. We shall briefly describe possible physical realisations of quantum (optic, electronic, magnetic,...) devices allowing the engineering of Hamiltonians needed for quantum systems. Basic quantum gates, especially the quantum Horner-Toffoli gate will be discussed to display the principles and methodology for designing quantum circuits. An outlook towards the possible availability of nano- and mesoscopic technologies supporting this new architecture in future generations concludes based on a speculative worst/best case forecast of possible applications, e.g., in public key and conventional cryptography.
Quantum mechanics possesses peculiar properties that is hard to comprehend with mundane experience. Exploiting the quantum properties of quantum systems, quantum computer can provide more computing power than classical computer. Duality quantum computer, or duality computer for short, is a new type of quantum computer that exploits the particle wave duality of quantum mechanics. In a duality computer, the computing gates, or generalized quantum gates, need not be unitary. Thus duality computer provides a novel paradigm for quantum computing, and may bring new computing power. In addition, it provides flexibility in computing gates design that is familiar to computer scientists. Here we review the basic concepts of duality quantum computing and give some examples.