Quantum state tomography on closed timelike curves using weak measurements

• URL: http://arxiv.org/abs/2407.14577v1
• Date: Fri, 19 Jul 2024 17:43:27 GMT
• Title: Quantum state tomography on closed timelike curves using weak measurements
• Authors: Lachlan G. Bishop, Fabio Costa, Timothy C. Ralph,
• Abstract summary: We show that, for any given combination of chronology-respecting input and unitary interaction, it is always possible to recover the unique state on the P-CTC. We also demonstrate how this state may be derived from analysis of the P-CTC prescription itself.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Any given prescription of quantum time travel necessarily endows a Hilbert space to the chronology-violating (CV) system on the closed timelike curve (CTC). However, under the two foremost models, Deutsch's prescription (D-CTCs) and postselected teleportation (P-CTCs), the CV system is treated very differently: D-CTCs assign a definite form to the state on this system, while P-CTCs do not. To further explore this distinction, we present a methodology by which an operational notion of state may be assigned to their respective CV systems. This is accomplished via a conjunction of state tomography and weak measurements, with the latter being essential in leaving any notions of self-consistency intact. With this technique, we are able to verify the predictions of D-CTCs and, perhaps more significantly, operationally assign a state to the system on the P-CTC. We show that, for any given combination of chronology-respecting input and unitary interaction, it is always possible to recover the unique state on the P-CTC, and we provide a few specific examples in the context of select archetypal temporal paradoxes. We also demonstrate how this state may be derived from analysis of the P-CTC prescription itself, and we explore how it compares to its counterpart in the CV state predicted by D-CTCs.

Related papers

• Self-Organized Time Crystal in Driven-Dissipative Quantum System [0.0]
  Continuous time crystals (CTCs) are characterized by sustained oscillations that break the time translation symmetry. We propose a new kind of CTC realized in a quantum contact model through self-organized bistability. Our results serve as a solid route towards self-protected CTCs in strongly interacting open systems.
  arXiv  Detail & Related papers  (2023-11-15T12:10:32Z)
• Bayes risk CTC: Controllable CTC alignment in Sequence-to-Sequence tasks [63.189632935619535]
  Bayes risk CTC (BRCTC) is proposed to enforce the desired characteristics of the predicted alignment. By using BRCTC with another preference for early emissions, we obtain an improved performance-latency trade-off for online models.
  arXiv  Detail & Related papers  (2022-10-14T03:55:36Z)
• CTC Alignments Improve Autoregressive Translation [145.90587287444976]
  We argue that CTC does in fact make sense for translation if applied in a joint CTC/attention framework. Our proposed joint CTC/attention models outperform pure-attention baselines across six benchmark translation tasks.
  arXiv  Detail & Related papers  (2022-10-11T07:13:50Z)
• Efficient Learning and Decoding of the Continuous-Time Hidden Markov Model for Disease Progression Modeling [119.50438407358862]
  We present the first complete characterization of efficient EM-based learning methods for CT-HMM models. We show that EM-based learning consists of two challenges: the estimation of posterior state probabilities and the computation of end-state conditioned statistics. We demonstrate the use of CT-HMMs with more than 100 states to visualize and predict disease progression using a glaucoma dataset and an Alzheimer's disease dataset.
  arXiv  Detail & Related papers  (2021-10-26T20:06:05Z)
• CTC Variations Through New WFST Topologies [79.94035631317395]
  This paper presents novel Weighted Finite-State Transducer (WFST) topologies to implement Connectionist Temporal Classification (CTC)-like algorithms for automatic speech recognition. Three new CTC variants are proposed: (1) the "compact-CTC", in which direct transitions between units are replaced with epsilon> back-off transitions; (2) the "minimal-CTC", that only adds blank> self-loops when used in WFST-composition; and (3) "selfless-CTC", that disallows self-loop for non-blank units.
  arXiv  Detail & Related papers  (2021-10-06T23:00:15Z)
• Quantum State Discrimination Circuits Inspired by Deutschian Closed Timelike Curves [4.779196219827506]
  A party with access to a Deutschian closed timelike curve (D-CTC) can perfectly distinguish multiple non-orthogonal quantum states. We propose a practical method for discriminating multiple non-orthogonal states, by using a previously known quantum circuit designed to simulate D-CTCs.
  arXiv  Detail & Related papers  (2021-09-23T17:37:50Z)
• Observation of Time-Crystalline Eigenstate Order on a Quantum Processor [80.17270167652622]
  Quantum-body systems display rich phase structure in their low-temperature equilibrium states. We experimentally observe an eigenstate-ordered DTC on superconducting qubits. Results establish a scalable approach to study non-equilibrium phases of matter on current quantum processors.
  arXiv  Detail & Related papers  (2021-07-28T18:00:03Z)
• Time-travelling billiard-ball clocks: a quantum model [0.0]
  General relativity predicts the existence of closed timelike curves (CTCs) A consequence of CTCs is the failure of determinism, even for classical systems. We introduce a new quantum formulation of a classic example, where a billiard ball can travel along two possible trajectories.
  arXiv  Detail & Related papers  (2020-07-24T17:45:35Z)
• CTC-synchronous Training for Monotonic Attention Model [43.0382262234792]
  backward probabilities cannot be leveraged in the alignment process during training due to left-to-right dependency in the decoder. We propose CTC-synchronous training ( CTC-ST), in which MoChA uses CTC alignments to learn optimal monotonic alignments. The entire model is jointly optimized so that the expected boundaries from MoChA are synchronized with the alignments.
  arXiv  Detail & Related papers  (2020-05-10T16:48:23Z)
• Bottom-Up Temporal Action Localization with Mutual Regularization [107.39785866001868]
  State-of-the-art solutions for TAL involve evaluating the frame-level probabilities of three action-indicating phases. We introduce two regularization terms to mutually regularize the learning procedure. Experiments are performed on two popular TAL datasets, THUMOS14 and ActivityNet1.3.
  arXiv  Detail & Related papers  (2020-02-18T03:59:13Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.