Non-Markovian jumping process conjecture for the birth Mallows process

From papers

Let n4n\geq 4, and let (Mt)t[0,)({\mathcal{M}}_t)_{t\in[0,\infty)} be the birth Mallows process. If TkT_k are its jump times, its jumping process is (MTk)0k(n2)({\mathcal{M}}_{T_k})_{0\leq k\leq\binom{n}{2}}. Non-Markovian jumping-process conjecture. For every n4n\geq 4, the jumping process of the birth Mallows process is not a Markov chain. The source says that computations for small nn support this claim, but that no formal proof is available.

Progress summary

Open

The conjecture remains unproved: small computations support the claim that the jump sequence is not Markovian in dimensions four and higher.

The conjecture asserts that, for every n4n \ge 4, the sequence of permutations observed at the successive jumps of the birth Mallows process is not a Markov chain. A 2022 paper records the conjecture and explicitly says that no formal proof was available.

Known results

  • Computations for small values of nn support non-Markovianity, but do not establish the conjecture (2022).
  • The birth Mallows process is identified as the unique regular Mallows process that is Markov; this does not settle the Markov property of its embedded jumping process (2022).

Current status (as of August 2026): The conjecture is open for every n4n \ge 4; only computational evidence is recorded, and no formal proof or counterexample has been publicly verified.

Sources
Sources & referencesView supporting material

Primary source

Benoît Corsini, “Continuous-time Mallows processes”, arXiv:2205.04967 (2022).

Solutions 1

Proof

Proof for every n4n\ge4. Write

[j]t=1+t++tj1,Zn(t)=j=2n[j]t,N=(n2).[j]_t=1+t+\cdots+t^{j-1}, \qquad Z_n(t)=\prod_{j=2}^n[j]_t, \qquad N=\binom n2.

By the source's independent inversion-coordinate construction, the birth Mallows process corresponds bijectively to independent unit-birth processes Bj(t)B_j(t) with

Pr(Bj(t)=r)=tr[j]t,0r<j.\Pr(B_j(t)=r)=\frac{t^r}{[j]_t}, \qquad 0\le r<j.

Let H23H_{23} be the history in which the first two global jumps occur in coordinates 2,32,3, and H32H_{32} the reverse history. Both have positive probability and end at the identical state

(B2,B3,B4,,Bn)=(1,1,0,,0).(B_2,B_3,B_4,\ldots,B_n)=(1,1,0,\ldots,0).

If TT denotes the second jump time, independence gives the unnormalized history-time densities

f23(t)=t[2]t[3]t[3]t2j=4n1[j]t,f_{23}(t) = \frac{t}{[2]_t} \frac{[3]'_t}{[3]_t^2} \prod_{j=4}^n\frac1{[j]_t}, f32(t)=t[3]t1[2]t2j=4n1[j]t=t(1+t)Zn(t)=:w(t).f_{32}(t) = \frac{t}{[3]_t} \frac1{[2]_t^2} \prod_{j=4}^n\frac1{[j]_t} = \frac{t}{(1+t)Z_n(t)} =:w(t).

Their ratio is

R(t)=f23(t)f32(t)=(1+t)(1+2t)1+t+t2=2+ϕ(t),ϕ(t)=t11+t+t2.R(t) = \frac{f_{23}(t)}{f_{32}(t)} = \frac{(1+t)(1+2t)}{1+t+t^2} = 2+\phi(t), \qquad \phi(t)=\frac{t-1}{1+t+t^2}.

Palindromicity of ZnZ_n gives

w(1/t)t2=tN3w(t),ϕ(1/t)=tϕ(t).\frac{w(1/t)}{t^2}=t^{N-3}w(t), \qquad \phi(1/t)=-t\phi(t).

Therefore

0w(t)(R(t)2)dt=01w(t)ϕ(t)(1tN2)dt<0.\int_0^\infty w(t)(R(t)-2)\,dt = \int_0^1 w(t)\phi(t)(1-t^{N-2})\,dt <0.

Consequently the normalization ratio

cn=f23f32c_n=\frac{\int f_{23}}{\int f_{32}}

satisfies 1<cn<21<c_n<2. Moreover RR is strictly increasing on (0,1)(0,1), and R(t)2R(t)\ge2 for t1t\ge1. Hence R(t)cnR(t)-c_n changes sign exactly once, from negative to positive. The two conditional time distributions therefore satisfy strict stochastic ordering:

TH23>stTH32.(1)T\mid H_{23}>_{\mathrm{st}}T\mid H_{32}. \tag{1}

Now consider the future embedded-chain event

E={the second jump in coordinate 3 precedes the first jump in coordinate 4}.E= \{ \text{the second jump in coordinate }3 \text{ precedes the first jump in coordinate }4 \}.

Jumps in all other coordinates can be ignored. The two competing birth rates are

a(t)=q3,1(t)=t+21+t+t2,b(t)=q4,0(t)=3t2+2t+1(1+t)(1+t2).a(t)=q_{3,1}(t)=\frac{t+2}{1+t+t^2}, \qquad b(t)=q_{4,0}(t) =\frac{3t^2+2t+1}{(1+t)(1+t^2)}.

A direct calculation yields

(a(t)b(t))=4t6+6t5+15t4+32t3+30t2+18t+3(t2+t+1)2(3t2+2t+1)2<0.\left(\frac{a(t)}{b(t)}\right)' = -\frac{ 4t^6+6t^5+15t^4+32t^3+30t^2+18t+3 }{ (t^2+t+1)^2(3t^2+2t+1)^2 } <0.

Thus h(t)=a(t)/(a(t)+b(t))h(t)=a(t)/(a(t)+b(t)) is strictly decreasing. If τt\tau_t is the first ring of these two clocks after time tt, then

Q(t):=Pr(ET=t,B(T)=(1,1,0,,0))=E[h(τt)].Q(t):=\Pr(E\mid T=t,B(T)=(1,1,0,\ldots,0)) =\mathbb E[h(\tau_t)].

For t<st<s, splitting at ss gives

Q(t)=tsh(u)(a(u)+b(u))etu(a+b)du+ets(a+b)Q(s).Q(t) = \int_t^s h(u)(a(u)+b(u)) e^{-\int_t^u(a+b)} \,du + e^{-\int_t^s(a+b)}Q(s).

Since h(u)>h(s)>Q(s)h(u)>h(s)>Q(s) for t<u<st<u<s, this identity implies Q(t)>Q(s)Q(t)>Q(s). Thus QQ is strictly decreasing.

Applying this to the strict stochastic ordering (1),

Pr(EH23)<Pr(EH32).\boxed{\displaystyle \Pr(E\mid H_{23}) < \Pr(E\mid H_{32}). }

The two histories reach the same state at the same jump index, yet yield different conditional probabilities for a future event determined entirely by the jumping chain. This contradicts the Markov property. Therefore the jumping process is not a Markov chain for every n4n\ge4.

Source: Benoît Corsini, Continuous-time Mallows processes, Conjecture 3, §4.2, https://arxiv.org/abs/2205.04967.

0 endorsements
Shivam Patel ·